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#
Projet
Open
Access
Compliance
Check
Tool
(
OACCT
)
Projet
P5
de
la
biblioth
è
que
de
l
'
EPFL
en
collaboration
avec
les
biblioth
è
ques
des
Universit
é
s
de
Gen
è
ve
,
Lausanne
et
Berne
:
https
:
//www.swissuniversities.ch/themen/digitalisierung/p-5-wissenschaftliche-information/projekte/swiss-mooc-service-1-1-1-1
Ce
notebook
permet
d
'
extraire
les
donn
é
es
de
Sherpa
/
Romeo
obtenues
par
API
et
les
traiter
pour
les
rendre
exploitables
dans
l
'
application
OACCT
.
Auteur
:
**
Pablo
Iriarte
**,
Universit
é
de
Gen
è
ve
(
pablo
.
iriarte
@
unige
.
ch
)
Date
de
derni
è
re
mise
à
jour
:
16.07.2021
##
Donn
é
es
de
Sherpa
/
Romeo
###
Exemple
https
:
//v2.sherpa.ac.uk/cgi/retrieve_by_id?item-type=publication&api-key=EEE6F146-678E-11EB-9C3A-202F3DE2659A&format=Json&identifier=17601
```
python
import
pandas
as
pd
import
csv
import
json
import
numpy
as
np
import
os
#
afficher
toutes
les
colonnes
pd
.
set_option
(
'
display
.
max_columns
'
,
None
)
```
##
Table
publisher_sherpa
```
python
#
creation
du
DF
col_names
=
[
'
journal
'
,
'
publisher_id
'
,
'
name
'
,
'
country
'
,
'
type
'
,
'
url
'
]
publisher_sherpa
=
pd
.
DataFrame
(
columns
=
col_names
)
publisher_sherpa
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
journal
</
th
>
<
th
>
publisher_id
</
th
>
<
th
>
name
</
th
>
<
th
>
country
</
th
>
<
th
>
type
</
th
>
<
th
>
url
</
th
>
</
tr
>
</
thead
>
<
tbody
>
</
tbody
>
</
table
>
</
div
>
##
Table
sherpa
match
issn
```
python
#
creation
du
DF
col_names
=
[
'
issn
'
,
'
sherpa_match
'
,
]
sherpa_match_issn
=
pd
.
DataFrame
(
columns
=
col_names
)
sherpa_match_issn
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
issn
</
th
>
<
th
>
sherpa_match
</
th
>
</
tr
>
</
thead
>
<
tbody
>
</
tbody
>
</
table
>
</
div
>
##
Table
sherpa
issns
```
python
#
creation
du
DF
col_names
=
[
'
issn
'
,
'
type
'
,
]
sherpa_issn
=
pd
.
DataFrame
(
columns
=
col_names
)
sherpa_issn
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
issn
</
th
>
<
th
>
type
</
th
>
</
tr
>
</
thead
>
<
tbody
>
</
tbody
>
</
table
>
</
div
>
##
Table
sherpa
journals
```
python
#
creation
du
DF
col_names
=
[
'
journal
'
,
'
title
'
,
'
url
'
,
]
sherpa_journal
=
pd
.
DataFrame
(
columns
=
col_names
)
sherpa_journal
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
journal
</
th
>
<
th
>
title
</
th
>
<
th
>
url
</
th
>
</
tr
>
</
thead
>
<
tbody
>
</
tbody
>
</
table
>
</
div
>
##
Import
table
Journals
et
ISSN
```
python
journal
=
pd
.
read_csv
(
'
sample
/
journals_publishers_brut
.
tsv
'
,
encoding
=
'
utf
-
8
'
,
header
=
0
,
sep
=
'\t'
)
journal
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
id
</
th
>
<
th
>
issn
</
th
>
<
th
>
issnl
</
th
>
<
th
>
title
</
th
>
<
th
>
starting_year
</
th
>
<
th
>
end_year
</
th
>
<
th
>
url
</
th
>
<
th
>
name_short_iso_4
</
th
>
<
th
>
language
</
th
>
<
th
>
country
</
th
>
<
th
>
doaj_title
</
th
>
<
th
>
doaj_seal
</
th
>
<
th
>
APC
</
th
>
<
th
>
doaj_status
</
th
>
<
th
>
lockss_title
</
th
>
<
th
>
lockss
</
th
>
<
th
>
portico_status
</
th
>
<
th
>
portico
</
th
>
<
th
>
nlch_title
</
th
>
<
th
>
nlch
</
th
>
<
th
>
qoam_av_score
</
th
>
<
th
>
doublon_issnl
</
th
>
<
th
>
oa_status
</
th
>
<
th
>
publisher
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
1660
-
9379
</
td
>
<
td
>
1660
-
9379
</
td
>
<
td
>
Revue
m
é
dicale
suisse
</
td
>
<
td
>
2005
</
td
>
<
td
>
9999
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Rev
.
m
é
d
.
suisse
</
td
>
<
td
>
138
</
td
>
<
td
>
215
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
2
</
td
>
<
td
>
0031
-
9007
</
td
>
<
td
>
0031
-
9007
</
td
>
<
td
>
Physical
review
letters
(
Print
)</
td
>
<
td
>
1958
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//prl.aps.org/</td>
<
td
>
Phys
.
rev
.
lett
.
(
Print
)</
td
>
<
td
>
124
</
td
>
<
td
>
236
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
preserved
</
td
>
<
td
>
1.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1.0
</
td
>
<
td
>
1
</
td
>
<
td
>
2
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
3
</
td
>
<
td
>
1932
-
6203
</
td
>
<
td
>
1932
-
6203
</
td
>
<
td
>
PloS
one
</
td
>
<
td
>
2006
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.plosone.org/</td>
<
td
>
NaN
</
td
>
<
td
>
124
</
td
>
<
td
>
236
</
td
>
<
td
>
PLoS
ONE
</
td
>
<
td
>
1.0
</
td
>
<
td
>
Yes
</
td
>
<
td
>
1.0
</
td
>
<
td
>
PLoS
One
</
td
>
<
td
>
1.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
4.035714
</
td
>
<
td
>
NaN
</
td
>
<
td
>
5
</
td
>
<
td
>
3
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
4
</
td
>
<
td
>
2174
-
8454
</
td
>
<
td
>
2174
-
8454
</
td
>
<
td
>
EU
-
top
í
as
</
td
>
<
td
>
2011
</
td
>
<
td
>
9999
</
td
>
<
td
>
NaN
</
td
>
<
td
>
EU
-
top
í
as
</
td
>
<
td
>
124
,
138
,
402
,
292
</
td
>
<
td
>
209
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1
</
td
>
<
td
>
4
,
5
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
5
</
td
>
<
td
>
1098
-
0121
</
td
>
<
td
>
1098
-
0121
</
td
>
<
td
>
Physical
review
.
B
,
Condensed
matter
and
mater
...</
td
>
<
td
>
1998
</
td
>
<
td
>
2015
</
td
>
<
td
>
http
:
//ojps.aip.org/prbo/</td>
<
td
>
Phys
.
rev
.,
B
,
Condens
.
matter
mater
.
phys
.</
td
>
<
td
>
124
</
td
>
<
td
>
236
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
preserved
</
td
>
<
td
>
1.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1.0
</
td
>
<
td
>
1
</
td
>
<
td
>
6
</
td
>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
906
</
td
>
<
td
>
997
</
td
>
<
td
>
0964
-
1726
</
td
>
<
td
>
0964
-
1726
</
td
>
<
td
>
Smart
materials
and
structures
(
Print
)</
td
>
<
td
>
1992
</
td
>
<
td
>
9999
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Smart
mater
.
struct
.
(
Print
)</
td
>
<
td
>
124
</
td
>
<
td
>
234
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
preserved
</
td
>
<
td
>
1.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1
</
td
>
<
td
>
47
</
td
>
</
tr
>
<
tr
>
<
td
>
907
</
td
>
<
td
>
998
</
td
>
<
td
>
0022
-
3468
</
td
>
<
td
>
0022
-
3468
</
td
>
<
td
>
Journal
of
pediatric
surgery
(
Print
)</
td
>
<
td
>
1966
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.jpedsurg.org</td>
<
td
>
J
.
pediatr
.
surg
.
(
Print
)</
td
>
<
td
>
124
</
td
>
<
td
>
236
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
preserved
</
td
>
<
td
>
1.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1
</
td
>
<
td
>
75
</
td
>
</
tr
>
<
tr
>
<
td
>
908
</
td
>
<
td
>
999
</
td
>
<
td
>
1432
-
2064
</
td
>
<
td
>
0178
-
8051
</
td
>
<
td
>
Probability
theory
and
related
fields
(
Internet
)</
td
>
<
td
>
uuuu
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.springerlink.com/content/100451</td>
<
td
>
Probab
.
theory
relat
.
fields
(
Internet
)</
td
>
<
td
>
124
</
td
>
<
td
>
83
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
Probability
Theory
and
Related
Fields
</
td
>
<
td
>
1.0
</
td
>
<
td
>
preserved
</
td
>
<
td
>
1.0
</
td
>
<
td
>
Probability
Theory
and
Related
Fields
</
td
>
<
td
>
1.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1
</
td
>
<
td
>
8
</
td
>
</
tr
>
<
tr
>
<
td
>
909
</
td
>
<
td
>
1000
</
td
>
<
td
>
0960
-
1481
</
td
>
<
td
>
0960
-
1481
</
td
>
<
td
>
Renewable
energy
</
td
>
<
td
>
1991
</
td
>
<
td
>
9999
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Renew
.
energy
</
td
>
<
td
>
124
</
td
>
<
td
>
234
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
preserved
</
td
>
<
td
>
1.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1
</
td
>
<
td
>
119
</
td
>
</
tr
>
<
tr
>
<
td
>
910
</
td
>
<
td
>
1001
</
td
>
<
td
>
0161
-
7567
</
td
>
<
td
>
0161
-
7567
</
td
>
<
td
>
Journal
of
applied
physiology
:
respiratory
,
en
...</
td
>
<
td
>
1977
</
td
>
<
td
>
1984
</
td
>
<
td
>
https
:
//www.physiology.org/journal/jappl</td>
<
td
>
J
.
appl
.
physiol
.:
respir
.,
environ
.
exercise
...</
td
>
<
td
>
124
</
td
>
<
td
>
236
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1
</
td
>
<
td
>
217
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
911
rows
×
24
columns
</
p
>
</
div
>
```
python
issn
=
pd
.
read_csv
(
'
sample
/
issn_brut
.
tsv
'
,
encoding
=
'
utf
-
8
'
,
header
=
0
,
sep
=
'\t'
)
issn
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
issn
</
th
>
<
th
>
issnl
</
th
>
<
th
>
journal
</
th
>
<
th
>
format
</
th
>
<
th
>
issn_type
</
th
>
<
th
>
id
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
0001
-
2815
</
td
>
<
td
>
0001
-
2815
</
td
>
<
td
>
532
</
td
>
<
td
>
PRINT
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
1399
-
0039
</
td
>
<
td
>
0001
-
2815
</
td
>
<
td
>
532
</
td
>
<
td
>
NaN
</
td
>
<
td
>
3
</
td
>
<
td
>
2
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
0001
-
4842
</
td
>
<
td
>
0001
-
4842
</
td
>
<
td
>
498
</
td
>
<
td
>
PRINT
</
td
>
<
td
>
1
</
td
>
<
td
>
3
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
1520
-
4898
</
td
>
<
td
>
0001
-
4842
</
td
>
<
td
>
498
</
td
>
<
td
>
NaN
</
td
>
<
td
>
3
</
td
>
<
td
>
4
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
0001
-
4966
</
td
>
<
td
>
0001
-
4966
</
td
>
<
td
>
789
</
td
>
<
td
>
PRINT
</
td
>
<
td
>
1
</
td
>
<
td
>
5
</
td
>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
1755
</
td
>
<
td
>
2470
-
0045
</
td
>
<
td
>
2470
-
0045
</
td
>
<
td
>
533
</
td
>
<
td
>
OTHER
</
td
>
<
td
>
3
</
td
>
<
td
>
1756
</
td
>
</
tr
>
<
tr
>
<
td
>
1756
</
td
>
<
td
>
2470
-
0053
</
td
>
<
td
>
2470
-
0045
</
td
>
<
td
>
533
</
td
>
<
td
>
NaN
</
td
>
<
td
>
3
</
td
>
<
td
>
1757
</
td
>
</
tr
>
<
tr
>
<
td
>
1757
</
td
>
<
td
>
2475
-
9953
</
td
>
<
td
>
2475
-
9953
</
td
>
<
td
>
608
</
td
>
<
td
>
ELECTRONIC
</
td
>
<
td
>
2
</
td
>
<
td
>
1758
</
td
>
</
tr
>
<
tr
>
<
td
>
1758
</
td
>
<
td
>
2504
-
4427
</
td
>
<
td
>
2504
-
4427
</
td
>
<
td
>
994
</
td
>
<
td
>
PRINT
</
td
>
<
td
>
1
</
td
>
<
td
>
1759
</
td
>
</
tr
>
<
tr
>
<
td
>
1759
</
td
>
<
td
>
2504
-
4435
</
td
>
<
td
>
2504
-
4427
</
td
>
<
td
>
994
</
td
>
<
td
>
NaN
</
td
>
<
td
>
3
</
td
>
<
td
>
1760
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
1760
rows
×
6
columns
</
p
>
</
div
>
```
python
issn_ids
=
pd
.
read_csv
(
'
sample
/
issn_ids
.
tsv
'
,
encoding
=
'
utf
-
8
'
,
header
=
0
,
sep
=
'\t'
)
issn_ids
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
id
</
th
>
<
th
>
issn
</
th
>
<
th
>
issnl
</
th
>
<
th
>
journal
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0001
-
2815
</
td
>
<
td
>
0001
-
2815
</
td
>
<
td
>
532
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
2
</
td
>
<
td
>
1399
-
0039
</
td
>
<
td
>
0001
-
2815
</
td
>
<
td
>
532
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
3
</
td
>
<
td
>
0001
-
4842
</
td
>
<
td
>
0001
-
4842
</
td
>
<
td
>
498
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
4
</
td
>
<
td
>
1520
-
4898
</
td
>
<
td
>
0001
-
4842
</
td
>
<
td
>
498
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
5
</
td
>
<
td
>
0001
-
4966
</
td
>
<
td
>
0001
-
4966
</
td
>
<
td
>
789
</
td
>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
1755
</
td
>
<
td
>
1756
</
td
>
<
td
>
2470
-
0045
</
td
>
<
td
>
2470
-
0045
</
td
>
<
td
>
533
</
td
>
</
tr
>
<
tr
>
<
td
>
1756
</
td
>
<
td
>
1757
</
td
>
<
td
>
2470
-
0053
</
td
>
<
td
>
2470
-
0045
</
td
>
<
td
>
533
</
td
>
</
tr
>
<
tr
>
<
td
>
1757
</
td
>
<
td
>
1758
</
td
>
<
td
>
2475
-
9953
</
td
>
<
td
>
2475
-
9953
</
td
>
<
td
>
608
</
td
>
</
tr
>
<
tr
>
<
td
>
1758
</
td
>
<
td
>
1759
</
td
>
<
td
>
2504
-
4427
</
td
>
<
td
>
2504
-
4427
</
td
>
<
td
>
994
</
td
>
</
tr
>
<
tr
>
<
td
>
1759
</
td
>
<
td
>
1760
</
td
>
<
td
>
2504
-
4435
</
td
>
<
td
>
2504
-
4427
</
td
>
<
td
>
994
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
1760
rows
×
4
columns
</
p
>
</
div
>
##
Extraction
de
Sherpa
Romeo
```
python
#
extraction
des
informations
à
partir
des
donn
é
es
Sherpa
/
Romeo
for
index
,
row
in
issn
.
iterrows
():
journal_id
=
row
[
'
journal
'
]
journal_issn
=
row
[
'
issn
'
]
#
if
(((
index
/
10
)
-
int
(
index
/
10
))
==
0
)
:
#
print
(
index
)
#
initialisation
des
variables
à
extraire
publisher_id
=
np
.
nan
publisher_name
=
''
publisher_country
=
''
publisher_type
=
''
publisher_url
=
''
#
boucle
des
fichiers
json
#
test
d
'
existance
du
fichier
#
print
(
row
[
'
issn
'
])
if
os
.
path
.
exists
(
'
sherpa
/
data
/
'
+
journal_issn
+
'
.
json
'
):
with
open
(
'
sherpa
/
data
/
'
+
journal_issn
+
'
.
json
'
,
'r'
,
encoding
=
'
utf
-
8
'
)
as
f
:
data
=
json
.
load
(
f
)
if
(
len
(
data
[
'
items
'
])
>
0
):
publisher_id
=
data
[
'
items
'
][
0
][
'
publishers
'
][
0
][
'
publisher
'
][
'
id
'
]
if
(
'
country
'
in
data
[
'
items
'
][
0
][
'
publishers
'
][
0
][
'
publisher
'
]):
publisher_country
=
data
[
'
items
'
][
0
][
'
publishers
'
][
0
][
'
publisher
'
][
'
country
'
]
if
(
'
relationship_type
'
in
data
[
'
items
'
][
0
][
'
publishers
'
][
0
]):
publisher_type
=
data
[
'
items
'
][
0
][
'
publishers
'
][
0
][
'
relationship_type
'
]
if
(
'
url
'
in
data
[
'
items
'
][
0
][
'
publishers
'
][
0
][
'
publisher
'
]):
publisher_url
=
data
[
'
items
'
][
0
][
'
publishers
'
][
0
][
'
publisher
'
][
'
url
'
]
if
(
'
name
'
in
data
[
'
items
'
][
0
][
'
publishers
'
][
0
][
'
publisher
'
][
'
name
'
][
0
]):
publisher_name
=
data
[
'
items
'
][
0
][
'
publishers
'
][
0
][
'
publisher
'
][
'
name
'
][
0
][
'
name
'
]
sherpa_match
=
'
OK
'
publisher_sherpa
=
publisher_sherpa
.
append
({
'
journal
'
:
journal_id
,
'
publisher_id
'
:
publisher_id
,
'
name
'
:
publisher_name
,
'
country
'
:
publisher_country
,
'
type
'
:
publisher_type
,
'
url
'
:
publisher_url
},
ignore_index
=
True
)
else
:
print
(
row
[
'
issn
'
]
+
'
-
trouv
é
mais
vide
'
)
sherpa_match
=
'
empty
'
else
:
print
(
row
[
'
issn
'
]
+
'
-
pas
trouv
é'
)
sherpa_match
=
'
missing
'
sherpa_match_issn
=
sherpa_match_issn
.
append
({
'
issn
'
:
row
[
'
issn
'
],
'
sherpa_match
'
:
sherpa_match
},
ignore_index
=
True
)
```
1399
-
0039
-
pas
trouv
é
1520
-
8524
-
trouv
é
mais
vide
1520
-
9024
-
pas
trouv
é
1468
-
2834
-
pas
trouv
é
1551
-
2916
-
pas
trouv
é
1943
-
2984
-
pas
trouv
é
1555
-
7162
-
trouv
é
mais
vide
2163
-
5773
-
pas
trouv
é
1873
-
4324
-
trouv
é
mais
vide
1526
-
7598
-
pas
trouv
é
1673
-
3134
-
pas
trouv
é
1777
-
5884
-
pas
trouv
é
1528
-
1140
-
pas
trouv
é
1468
-
2060
-
pas
trouv
é
1552
-
6259
-
pas
trouv
é
0003
-
6935
-
trouv
é
mais
vide
1520
-
8842
-
pas
trouv
é
0003
-
9926
-
trouv
é
mais
vide
1538
-
3679
-
pas
trouv
é
0003
-
9942
-
trouv
é
mais
vide
1538
-
3687
-
pas
trouv
é
1529
-
0131
-
pas
trouv
é
1090
-
2104
-
trouv
é
mais
vide
1943
-
295
X
-
pas
trouv
é
1878
-
2434
-
pas
trouv
é
1873
-
2402
-
trouv
é
mais
vide
1872
-
6240
-
trouv
é
mais
vide
1365
-
2133
-
pas
trouv
é
0007
-
4403
-
trouv
é
mais
vide
1968
-
3766
-
pas
trouv
é
0008
-
042
X
-
trouv
é
mais
vide
2104
-
3329
-
pas
trouv
é
2268
-
7963
-
pas
trouv
é
1873
-
3948
-
trouv
é
mais
vide
1873
-
4405
-
trouv
é
mais
vide
1872
-
6836
-
trouv
é
mais
vide
1873
-
4448
-
trouv
é
mais
vide
1524
-
4571
-
trouv
é
mais
vide
1873
-
7838
-
trouv
é
mais
vide
1879
-
2944
-
trouv
é
mais
vide
1873
-
3840
-
trouv
é
mais
vide
1973
-
8102
-
trouv
é
mais
vide
0011
-
1600
-
trouv
é
mais
vide
1968
-
3901
-
pas
trouv
é
1879
-
2235
-
trouv
é
mais
vide
1095
-
564
X
-
trouv
é
mais
vide
1931
-
3543
-
pas
trouv
é
1385
-
013
X
-
trouv
é
mais
vide
1873
-
3859
-
trouv
é
mais
vide
1873
-
7315
-
trouv
é
mais
vide
0013
-
8584
-
trouv
é
mais
vide
2309
-
4672
-
pas
trouv
é
0014
-
2239
-
trouv
é
mais
vide
2272
-
9011
-
pas
trouv
é
0945
-
5795
-
pas
trouv
é
1432
-
1033
-
pas
trouv
é
1365
-
2362
-
pas
trouv
é
1090
-
2422
-
trouv
é
mais
vide
1026
-
7484
-
trouv
é
mais
vide
1528
-
0012
-
trouv
é
mais
vide
1872
-
9533
-
trouv
é
mais
vide
0016
-
9161
-
trouv
é
mais
vide
2297
-
7953
-
pas
trouv
é
1879
-
2189
-
trouv
é
mais
vide
0018
-
0238
-
trouv
é
mais
vide
2297
-
1971
-
pas
trouv
é
2334
-
3303
-
pas
trouv
é
1070
-
6313
-
pas
trouv
é
1873
-
3255
-
trouv
é
mais
vide
1097
-
0215
-
pas
trouv
é
1879
-
2146
-
trouv
é
mais
vide
0021
-
8170
-
trouv
é
mais
vide
2114
-
6292
-
pas
trouv
é
1090
-
266
X
-
trouv
é
mais
vide
1520
-
8850
-
trouv
é
mais
vide
1879
-
1484
-
trouv
é
mais
vide
1067
-
8832
-
pas
trouv
é
1067
-
8816
-
pas
trouv
é
1873
-
2380
-
trouv
é
mais
vide
1090
-
2694
-
trouv
é
mais
vide
1520
-
9032
-
pas
trouv
é
1873
-
3778
-
trouv
é
mais
vide
1945
-
7197
-
pas
trouv
é
0021
-
9797
-
trouv
é
mais
vide
1090
-
2716
-
trouv
é
mais
vide
1873
-
5002
-
pas
trouv
é
0022
-
0728
-
trouv
é
mais
vide
1879
-
2707
-
trouv
é
mais
vide
1872
-
7883
-
trouv
é
mais
vide
1527
-
2427
-
trouv
é
mais
vide
1089
-
8638
-
trouv
é
mais
vide
1873
-
4820
-
trouv
é
mais
vide
1872
-
8561
-
trouv
é
mais
vide
1531
-
5037
-
trouv
é
mais
vide
1085
-
8695
-
pas
trouv
é
1097
-
6833
-
pas
trouv
é
1879
-
2553
-
trouv
é
mais
vide
1097
-
6841
-
pas
trouv
é
2050
-
5639
-
pas
trouv
é
1873
-
4782
-
trouv
é
mais
vide
1878
-
5883
-
trouv
é
mais
vide
1085
-
8687
-
pas
trouv
é
1097
-
685
X
-
pas
trouv
é
1070
-
6321
-
pas
trouv
é
1091
-
756
X
-
pas
trouv
é
1939
-
5590
-
trouv
é
mais
vide
1939
-
5604
-
pas
trouv
é
1873
-
1856
-
trouv
é
mais
vide
1872
-
6143
-
pas
trouv
é
0025
-
6749
-
trouv
é
mais
vide
1423
-
0356
-
pas
trouv
é
0026
-
4598
-
pas
trouv
é
1432
-
1874
-
pas
trouv
é
0027
-
4054
-
trouv
é
mais
vide
1873
-
3514
-
trouv
é
mais
vide
1873
-
0310
-
trouv
é
mais
vide
1872
-
616
X
-
pas
trouv
é
1402
-
4896
-
pas
trouv
é
0031
-
8965
-
trouv
é
mais
vide
1521
-
396
X
-
pas
trouv
é
1092
-
0145
-
trouv
é
mais
vide
1873
-
3700
-
pas
trouv
é
1532
-
2548
-
pas
trouv
é
1527
-
2400
-
trouv
é
mais
vide
0035
-
1121
-
trouv
é
mais
vide
1760
-
7426
-
pas
trouv
é
0035
-
1784
-
trouv
é
mais
vide
2297
-
1254
-
pas
trouv
é
0035
-
3655
-
trouv
é
mais
vide
2104
-
385
X
-
pas
trouv
é
0036
-
7486
-
trouv
é
mais
vide
1424
-
4004
-
trouv
é
mais
vide
0036
-
7672
-
trouv
é
mais
vide
0036
-
7699
-
trouv
é
mais
vide
0036
-
7893
-
trouv
é
mais
vide
2504
-
1452
-
pas
trouv
é
1471
-
1257
-
pas
trouv
é
1879
-
2766
-
trouv
é
mais
vide
1879
-
2405
-
trouv
é
mais
vide
1879
-
2758
-
trouv
é
mais
vide
1464
-
5416
-
pas
trouv
é
1873
-
3581
-
pas
trouv
é
1664
-
2864
-
pas
trouv
é
1879
-
2731
-
pas
trouv
é
1534
-
6080
-
trouv
é
mais
vide
1873
-
2623
-
pas
trouv
é
1096
-
0341
-
trouv
é
mais
vide
1878
-
5646
-
trouv
é
mais
vide
1879
-
2448
-
pas
trouv
é
1879
-
1298
-
trouv
é
mais
vide
1879
-
2138
-
trouv
é
mais
vide
0046
-
2497
-
trouv
é
mais
vide
1776
-
2936
-
pas
trouv
é
1873
-
7625
-
trouv
é
mais
vide
1879
-
2472
-
pas
trouv
é
2214
-
8019
-
trouv
é
mais
vide
0065
-
7727
-
trouv
é
mais
vide
1070
-
6283
-
pas
trouv
é
0066
-
6653
-
trouv
é
mais
vide
0072
-
0585
-
trouv
é
mais
vide
1079
-
2376
-
pas
trouv
é
1557
-
7988
-
trouv
é
mais
vide
0081
-
1254
-
trouv
é
mais
vide
1523
-
1755
-
pas
trouv
é
1085
-
8725
-
pas
trouv
é
1097
-
6825
-
trouv
é
mais
vide
1096
-
0260
-
pas
trouv
é
1522
-
8541
-
pas
trouv
é
1551
-
7616
-
pas
trouv
é
1935
-
0465
-
pas
trouv
é
1070
-
633
X
-
pas
trouv
é
1873
-
4375
-
trouv
é
mais
vide
1070
-
6291
-
pas
trouv
é
0108
-
2701
-
trouv
é
mais
vide
1600
-
5759
-
pas
trouv
é
1879
-
0097
-
pas
trouv
é
1879
-
2081
-
pas
trouv
é
1873
-
7323
-
trouv
é
mais
vide
1879
-
3452
-
trouv
é
mais
vide
1878
-
5905
-
trouv
é
mais
vide
1532
-
1991
-
pas
trouv
é
1071
-
2763
-
pas
trouv
é
1071
-
8842
-
pas
trouv
é
2156
-
2202
-
pas
trouv
é
1081
-
1281
-
pas
trouv
é
1873
-
7528
-
trouv
é
mais
vide
1773
-
0406
-
trouv
é
mais
vide
0151
-
0193
-
trouv
é
mais
vide
2101
-
0218
-
trouv
é
mais
vide
0161
-
7567
-
trouv
é
mais
vide
2160
-
9292
-
trouv
é
mais
vide
1095
-
3795
-
trouv
é
mais
vide
1872
-
678
X
-
trouv
é
mais
vide
1573
-
2517
-
pas
trouv
é
1872
-
7557
-
trouv
é
mais
vide
1872
-
7123
-
trouv
é
mais
vide
1872
-
7441
-
trouv
é
mais
vide
1872
-
7999
-
pas
trouv
é
1879
-
1514
-
pas
trouv
é
1874
-
1754
-
trouv
é
mais
vide
1872
-
7697
-
trouv
é
mais
vide
1873
-
5568
-
trouv
é
mais
vide
1872
-
7352
-
pas
trouv
é
1872
-
9584
-
trouv
é
mais
vide
1600
-
0641
-
trouv
é
mais
vide
1872
-
9576
-
trouv
é
mais
vide
1873
-
5460
-
pas
trouv
é
1873
-
5584
-
trouv
é
mais
vide
1872
-
695
X
-
pas
trouv
é
1432
-
0827
-
pas
trouv
é
1432
-
1262
-
pas
trouv
é
0181
-
5512
-
trouv
é
mais
vide
1773
-
0597
-
pas
trouv
é
1879
-
2367
-
trouv
é
mais
vide
1532
-
2939
-
trouv
é
mais
vide
1527
-
3296
-
pas
trouv
é
1558
-
1497
-
trouv
é
mais
vide
0221
-
5918
-
trouv
é
mais
vide
0248
-
8663
-
trouv
é
mais
vide
1768
-
3122
-
trouv
é
mais
vide
0252
-
1881
-
trouv
é
mais
vide
0252
-
2969
-
trouv
é
mais
vide
1661
-
5468
-
pas
trouv
é
0254
-
945
X
-
trouv
é
mais
vide
1662
-
9760
-
pas
trouv
é
0255
-
9005
-
trouv
é
mais
vide
0258
-
6800
-
trouv
é
mais
vide
1432
-
0819
-
pas
trouv
é
0259
-
6199
-
trouv
é
mais
vide
1661
-
3171
-
trouv
é
mais
vide
1532
-
1983
-
pas
trouv
é
1873
-
2518
-
trouv
é
mais
vide
1365
-
2346
-
pas
trouv
é
1476
-
5365
-
pas
trouv
é
1067
-
8824
-
pas
trouv
é
0271
-
4302
-
trouv
é
mais
vide
2158
-
1525
-
pas
trouv
é
1536
-
4801
-
pas
trouv
é
1873
-
457
X
-
pas
trouv
é
1531
-
5053
-
pas
trouv
é
1470
-
8752
-
pas
trouv
é
1879
-
176
X
-
pas
trouv
é
1873
-
4421
-
pas
trouv
é
1432
-
1998
-
pas
trouv
é
1873
-
6246
-
pas
trouv
é
1873
-
6777
-
pas
trouv
é
1879
-
3533
-
trouv
é
mais
vide
1872
-
8057
-
trouv
é
mais
vide
1872
-
7972
-
trouv
é
mais
vide
1879
-
2723
-
trouv
é
mais
vide
1879
-
2774
-
pas
trouv
é
1873
-
4766
-
trouv
é
mais
vide
1362
-
4954
-
pas
trouv
é
1365
-
2842
-
pas
trouv
é
1361
-
6447
-
trouv
é
mais
vide
1872
-
9118
-
trouv
é
mais
vide
1873
-
7544
-
trouv
é
mais
vide
1873
-
3360
-
pas
trouv
é
1873
-
2100
-
pas
trouv
é
1872
-
9657
-
trouv
é
mais
vide
1499
-
2752
-
pas
trouv
é
2567
-
689
X
-
trouv
é
mais
vide
1432
-
1238
-
pas
trouv
é
1873
-
684
X
-
trouv
é
mais
vide
1879
-
355
X
-
trouv
é
mais
vide
1879
-
3487
-
trouv
é
mais
vide
1873
-
6785
-
trouv
é
mais
vide
1546
-
3141
-
pas
trouv
é
0362
-
1340
-
trouv
é
mais
vide
1523
-
2867
-
pas
trouv
é
1558
-
1160
-
trouv
é
mais
vide
1432
-
2323
-
pas
trouv
é
0365
-
7116
-
trouv
é
mais
vide
1873
-
2526
-
pas
trouv
é
0368
-
4466
-
trouv
é
mais
vide
1588
-
2926
-
pas
trouv
é
0369
-
3392
-
trouv
é
mais
vide
1873
-
2445
-
trouv
é
mais
vide
0373
-
2525
-
trouv
é
mais
vide
0373
-
2967
-
trouv
é
mais
vide
2235
-
3658
-
pas
trouv
é
0373
-
6156
-
trouv
é
mais
vide
2391
-
1336
-
pas
trouv
é
0374
-
4256
-
trouv
é
mais
vide
0375
-
1457
-
trouv
é
mais
vide
2419
-
8196
-
pas
trouv
é
1873
-
2429
-
trouv
é
mais
vide
1872
-
6097
-
pas
trouv
é
1872
-
6860
-
trouv
é
mais
vide
1574
-
6968
-
pas
trouv
é
1879
-
0038
-
trouv
é
mais
vide
1873
-
3476
-
trouv
é
mais
vide
1873
-
2755
-
trouv
é
mais
vide
1872
-
6178
-
trouv
é
mais
vide
1873
-
2046
-
trouv
é
mais
vide
1872
-
6283
-
trouv
é
mais
vide
0398
-
3412
-
trouv
é
mais
vide
2297
-
5810
-
pas
trouv
é
0409
-
8757
-
trouv
é
mais
vide
1461
-
7412
-
pas
trouv
é
1873
-
1562
-
trouv
é
mais
vide
1089
-
4918
-
trouv
é
mais
vide
1538
-
4500
-
pas
trouv
é
0570
-
0833
-
trouv
é
mais
vide
0583
-
8401
-
trouv
é
mais
vide
1872
-
7727
-
trouv
é
mais
vide
1873
-
264
X
-
trouv
é
mais
vide
1527
-
7755
-
pas
trouv
é
1520
-
8559
-
trouv
é
mais
vide
1558
-
3597
-
trouv
é
mais
vide
1873
-
5134
-
pas
trouv
é
1096
-
3677
-
pas
trouv
é
2213
-
0276
-
pas
trouv
é
1958
-
5381
-
pas
trouv
é
1651
-
2227
-
pas
trouv
é
0884
-
1616
-
trouv
é
mais
vide
1091
-
8876
-
pas
trouv
é
1092
-
8928
-
pas
trouv
é
1089
-
8646
-
pas
trouv
é
0888
-
8809
-
trouv
é
mais
vide
1944
-
9917
-
trouv
é
mais
vide
1532
-
0987
-
pas
trouv
é
0894
-
8275
-
trouv
é
mais
vide
1878
-
5921
-
pas
trouv
é
1520
-
636
X
-
pas
trouv
é
1399
-
3038
-
pas
trouv
é
1873
-
7196
-
trouv
é
mais
vide
1873
-
4308
-
trouv
é
mais
vide
1573
-
2509
-
trouv
é
mais
vide
1879
-
0658
-
trouv
é
mais
vide
1873
-
2135
-
pas
trouv
é
1873
-
2143
-
pas
trouv
é
1873
-
4936
-
trouv
é
mais
vide
1873
-
4944
-
pas
trouv
é
1872
-
793
X
-
trouv
é
mais
vide
1873
-
3069
-
pas
trouv
é
1872
-
8286
-
trouv
é
mais
vide
1873
-
3077
-
pas
trouv
é
1873
-
4669
-
trouv
é
mais
vide
1873
-
3883
-
trouv
é
mais
vide
0926
-
9630
-
trouv
é
mais
vide
1879
-
8365
-
trouv
é
mais
vide
1879
-
3398
-
trouv
é
mais
vide
1873
-
4359
-
trouv
é
mais
vide
1879
-
0720
-
trouv
é
mais
vide
1769
-
664
X
-
pas
trouv
é
1432
-
2218
-
pas
trouv
é
1866
-
6817
-
pas
trouv
é
1432
-
2277
-
pas
trouv
é
1435
-
4373
-
pas
trouv
é
1433
-
2965
-
pas
trouv
é
1873
-
3441
-
pas
trouv
é
1362
-
3044
-
pas
trouv
é
1879
-
0526
-
trouv
é
mais
vide
1879
-
0828
-
pas
trouv
é
1879
-
0410
-
trouv
é
mais
vide
1873
-
619
X
-
trouv
é
mais
vide
1873
-
4235
-
trouv
é
mais
vide
1362
-
511
X
-
pas
trouv
é
1879
-
0429
-
trouv
é
mais
vide
1879
-
1786
-
trouv
é
mais
vide
1879
-
0852
-
pas
trouv
é
1879
-
0682
-
pas
trouv
é
1873
-
2976
-
trouv
é
mais
vide
1464
-
3405
-
trouv
é
mais
vide
1466
-
1861
-
pas
trouv
é
1555
-
3892
-
pas
trouv
é
1360
-
0443
-
pas
trouv
é
1464
-
3391
-
trouv
é
mais
vide
1879
-
2359
-
pas
trouv
é
0992
-
986
X
-
trouv
é
mais
vide
2119
-
4130
-
pas
trouv
é
0995
-
3817
-
trouv
é
mais
vide
2219
-
2840
-
pas
trouv
é
1010
-
2248
-
trouv
é
mais
vide
1664
-
9885
-
pas
trouv
é
1873
-
2666
-
pas
trouv
é
1017
-
0588
-
trouv
é
mais
vide
1018
-
7987
-
trouv
é
mais
vide
1019
-
0406
-
trouv
é
mais
vide
1023
-
2044
-
trouv
é
mais
vide
1023
-
9332
-
trouv
é
mais
vide
2235
-
1884
-
pas
trouv
é
1560
-
7917
-
pas
trouv
é
1026
-
7530
-
pas
trouv
é
1607
-
8489
-
pas
trouv
é
1127
-
2236
-
pas
trouv
é
1938
-
808
X
-
pas
trouv
é
1095
-
8657
-
trouv
é
mais
vide
1536
-
3732
-
pas
trouv
é
1049
-
5258
-
trouv
é
mais
vide
1538
-
4446
-
pas
trouv
é
1095
-
9572
-
trouv
é
mais
vide
1532
-
6500
-
trouv
é
mais
vide
1059
-
1524
-
trouv
é
mais
vide
1095
-
3787
-
trouv
é
mais
vide
1538
-
4519
-
trouv
é
mais
vide
1063
-
6919
-
trouv
é
mais
vide
2332
-
564
X
-
pas
trouv
é
2575
-
7075
-
pas
trouv
é
1940
-
6029
-
trouv
é
mais
vide
1527
-
2435
-
pas
trouv
é
1527
-
2419
-
pas
trouv
é
1071
-
1023
-
trouv
é
mais
vide
1520
-
8567
-
pas
trouv
é
1090
-
235
X
-
trouv
é
mais
vide
1532
-
2130
-
pas
trouv
é
1096
-
0856
-
trouv
é
mais
vide
1538
-
4489
-
pas
trouv
é
1155
-
4339
-
trouv
é
mais
vide
1764
-
7177
-
pas
trouv
é
1460
-
9592
-
pas
trouv
é
1878
-
3511
-
pas
trouv
é
1778
-
7254
-
pas
trouv
é
1873
-
4030
-
pas
trouv
é
1873
-
2844
-
trouv
é
mais
vide
1873
-
5126
-
trouv
é
mais
vide
1873
-
5606
-
pas
trouv
é
1873
-
2453
-
trouv
é
mais
vide
1872
-
8456
-
pas
trouv
é
2040
-
2058
-
pas
trouv
é
1878
-
5840
-
trouv
é
mais
vide
1473
-
6519
-
pas
trouv
é
1879
-
0690
-
trouv
é
mais
vide
1466
-
609
X
-
pas
trouv
é
1367
-
4811
-
trouv
é
mais
vide
1873
-
4286
-
pas
trouv
é
1873
-
3212
-
trouv
é
mais
vide
1873
-
1759
-
pas
trouv
é
1875
-
8908
-
trouv
é
mais
vide
1872
-
8952
-
trouv
é
mais
vide
1873
-
1902
-
trouv
é
mais
vide
1600
-
0854
-
pas
trouv
é
1420
-
5556
-
trouv
é
mais
vide
1420
-
7192
-
trouv
é
mais
vide
1662
-
0879
-
pas
trouv
é
1422
-
2019
-
trouv
é
mais
vide
1422
-
3449
-
trouv
é
mais
vide
1422
-
5778
-
trouv
é
mais
vide
2504
-
1436
-
pas
trouv
é
1423
-
3967
-
trouv
é
mais
vide
1663
-
3997
-
pas
trouv
é
1424
-
1811
-
trouv
é
mais
vide
2504
-
1460
-
pas
trouv
é
1424
-
4020
-
pas
trouv
é
1424
-
7410
-
trouv
é
mais
vide
1424
-
7755
-
trouv
é
mais
vide
1436
-
3771
-
pas
trouv
é
1434
-
6028
-
trouv
é
mais
vide
1434
-
6036
-
trouv
é
mais
vide
1439
-
4456
-
pas
trouv
é
1449
-
8979
-
pas
trouv
é
1873
-
6416
-
trouv
é
mais
vide
1465
-
6914
-
trouv
é
mais
vide
1478
-
6362
-
pas
trouv
é
1520
-
6149
-
trouv
é
mais
vide
2379
-
190
X
-
trouv
é
mais
vide
1522
-
1601
-
pas
trouv
é
1708
-
8208
-
pas
trouv
é
1944
-
7884
-
pas
trouv
é
1527
-
6473
-
pas
trouv
é
1947
-
3893
-
pas
trouv
é
1530
-
1591
-
trouv
é
mais
vide
1558
-
1101
-
pas
trouv
é
1860
-
2002
-
pas
trouv
é
1552
-
5279
-
pas
trouv
é
1557
-
170
X
-
trouv
é
mais
vide
1878
-
5530
-
trouv
é
mais
vide
1878
-
1519
-
trouv
é
mais
vide
1569
-
9293
-
pas
trouv
é
1873
-
376
X
-
pas
trouv
é
1720
-
8319
-
pas
trouv
é
1610
-
0379
-
trouv
é
mais
vide
1610
-
0387
-
pas
trouv
é
1778
-
3569
-
trouv
é
mais
vide
1660
-
3362
-
trouv
é
mais
vide
1660
-
9379
-
trouv
é
mais
vide
1660
-
9603
-
trouv
é
mais
vide
1661
-
1179
-
trouv
é
mais
vide
1661
-
2620
-
trouv
é
mais
vide
1661
-
464
X
-
trouv
é
mais
vide
1661
-
4941
-
trouv
é
mais
vide
1661
-
8165
-
pas
trouv
é
1662
-
551
X
-
pas
trouv
é
1662
-
5536
-
trouv
é
mais
vide
1662
-
6001
-
trouv
é
mais
vide
1662
-
601
X
-
pas
trouv
é
1662
-
8705
-
trouv
é
mais
vide
1777
-
5477
-
trouv
é
mais
vide
1810
-
7621
-
pas
trouv
é
1863
-
2300
-
pas
trouv
é
1873
-
2763
-
trouv
é
mais
vide
1876
-
7737
-
pas
trouv
é
1878
-
8769
-
trouv
é
mais
vide
1939
-
5175
-
trouv
é
mais
vide
1945
-
7928
-
trouv
é
mais
vide
1945
-
7936
-
pas
trouv
é
1945
-
8452
-
trouv
é
mais
vide
1992
-
2655
-
trouv
é
mais
vide
2050
-
7534
-
trouv
é
mais
vide
2101
-
6275
-
pas
trouv
é
2161
-
2129
-
pas
trouv
é
2160
-
5033
-
trouv
é
mais
vide
2160
-
5041
-
pas
trouv
é
2160
-
9020
-
trouv
é
mais
vide
2160
-
9047
-
pas
trouv
é
2164
-
3342
-
trouv
é
mais
vide
2174
-
8454
-
trouv
é
mais
vide
2340
-
115
X
-
pas
trouv
é
2211
-
3282
-
trouv
é
mais
vide
2264
-
7228
-
trouv
é
mais
vide
2297
-
0703
-
trouv
é
mais
vide
2297
-
6981
-
trouv
é
mais
vide
2297
-
7007
-
pas
trouv
é
2352
-
1791
-
trouv
é
mais
vide
2504
-
4427
-
trouv
é
mais
vide
2504
-
4435
-
trouv
é
mais
vide
```
python
publisher_sherpa
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
journal
</
th
>
<
th
>
publisher_id
</
th
>
<
th
>
name
</
th
>
<
th
>
country
</
th
>
<
th
>
type
</
th
>
<
th
>
url
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
532
</
td
>
<
td
>
45
</
td
>
<
td
>
John
Wiley
and
Sons
</
td
>
<
td
>
gb
</
td
>
<
td
>
former_publisher
</
td
>
<
td
>
http
:
//www.wiley.com/</td>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
498
</
td
>
<
td
>
4
</
td
>
<
td
>
American
Chemical
Society
</
td
>
<
td
>
us
</
td
>
<
td
>
society_publisher
</
td
>
<
td
>
http
:
//pubs.acs.org/</td>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
498
</
td
>
<
td
>
4
</
td
>
<
td
>
American
Chemical
Society
</
td
>
<
td
>
us
</
td
>
<
td
>
society_publisher
</
td
>
<
td
>
http
:
//pubs.acs.org/</td>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
789
</
td
>
<
td
>
126
</
td
>
<
td
>
Acoustical
Society
of
America
</
td
>
<
td
>
us
</
td
>
<
td
>
society_publisher
</
td
>
<
td
>
http
:
//acousticalsociety.org/</td>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
166
</
td
>
<
td
>
3291
</
td
>
<
td
>
Springer
</
td
>
<
td
>
gb
</
td
>
<
td
>
commercial_publisher
</
td
>
<
td
>
https
:
//www.springernature.com/gp/products/jou...</td>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
1238
</
td
>
<
td
>
80
</
td
>
<
td
>
10
</
td
>
<
td
>
American
Physical
Society
</
td
>
<
td
>
us
</
td
>
<
td
>
society_publisher
</
td
>
<
td
>
http
:
//www.aps.org/</td>
</
tr
>
<
tr
>
<
td
>
1239
</
td
>
<
td
>
80
</
td
>
<
td
>
10
</
td
>
<
td
>
American
Physical
Society
</
td
>
<
td
>
us
</
td
>
<
td
>
society_publisher
</
td
>
<
td
>
http
:
//www.aps.org/</td>
</
tr
>
<
tr
>
<
td
>
1240
</
td
>
<
td
>
533
</
td
>
<
td
>
10
</
td
>
<
td
>
American
Physical
Society
</
td
>
<
td
>
us
</
td
>
<
td
>
society_publisher
</
td
>
<
td
>
http
:
//www.aps.org/</td>
</
tr
>
<
tr
>
<
td
>
1241
</
td
>
<
td
>
533
</
td
>
<
td
>
10
</
td
>
<
td
>
American
Physical
Society
</
td
>
<
td
>
us
</
td
>
<
td
>
society_publisher
</
td
>
<
td
>
http
:
//www.aps.org/</td>
</
tr
>
<
tr
>
<
td
>
1242
</
td
>
<
td
>
608
</
td
>
<
td
>
10
</
td
>
<
td
>
American
Physical
Society
</
td
>
<
td
>
us
</
td
>
<
td
>
society_publisher
</
td
>
<
td
>
http
:
//www.aps.org/</td>
</
tr
>
</
tbody
>
</
table
>
<
p
>
1243
rows
×
6
columns
</
p
>
</
div
>
```
python
sherpa_match_issn
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
issn
</
th
>
<
th
>
sherpa_match
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
0001
-
2815
</
td
>
<
td
>
OK
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
1399
-
0039
</
td
>
<
td
>
missing
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
0001
-
4842
</
td
>
<
td
>
OK
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
1520
-
4898
</
td
>
<
td
>
OK
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
0001
-
4966
</
td
>
<
td
>
OK
</
td
>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
1755
</
td
>
<
td
>
2470
-
0045
</
td
>
<
td
>
OK
</
td
>
</
tr
>
<
tr
>
<
td
>
1756
</
td
>
<
td
>
2470
-
0053
</
td
>
<
td
>
OK
</
td
>
</
tr
>
<
tr
>
<
td
>
1757
</
td
>
<
td
>
2475
-
9953
</
td
>
<
td
>
OK
</
td
>
</
tr
>
<
tr
>
<
td
>
1758
</
td
>
<
td
>
2504
-
4427
</
td
>
<
td
>
empty
</
td
>
</
tr
>
<
tr
>
<
td
>
1759
</
td
>
<
td
>
2504
-
4435
</
td
>
<
td
>
empty
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
1760
rows
×
2
columns
</
p
>
</
div
>
```
python
#
dedup
publisher_sherpa_dedup
=
publisher_sherpa
.
drop_duplicates
()
publisher_sherpa_dedup
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
journal
</
th
>
<
th
>
publisher_id
</
th
>
<
th
>
name
</
th
>
<
th
>
country
</
th
>
<
th
>
type
</
th
>
<
th
>
url
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
532
</
td
>
<
td
>
45
</
td
>
<
td
>
John
Wiley
and
Sons
</
td
>
<
td
>
gb
</
td
>
<
td
>
former_publisher
</
td
>
<
td
>
http
:
//www.wiley.com/</td>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
498
</
td
>
<
td
>
4
</
td
>
<
td
>
American
Chemical
Society
</
td
>
<
td
>
us
</
td
>
<
td
>
society_publisher
</
td
>
<
td
>
http
:
//pubs.acs.org/</td>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
789
</
td
>
<
td
>
126
</
td
>
<
td
>
Acoustical
Society
of
America
</
td
>
<
td
>
us
</
td
>
<
td
>
society_publisher
</
td
>
<
td
>
http
:
//acousticalsociety.org/</td>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
166
</
td
>
<
td
>
3291
</
td
>
<
td
>
Springer
</
td
>
<
td
>
gb
</
td
>
<
td
>
commercial_publisher
</
td
>
<
td
>
https
:
//www.springernature.com/gp/products/jou...</td>
</
tr
>
<
tr
>
<
td
>
6
</
td
>
<
td
>
807
</
td
>
<
td
>
3291
</
td
>
<
td
>
Springer
</
td
>
<
td
>
gb
</
td
>
<
td
>
commercial_publisher
</
td
>
<
td
>
https
:
//www.springernature.com/gp/products/jou...</td>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
1235
</
td
>
<
td
>
870
</
td
>
<
td
>
10
</
td
>
<
td
>
American
Physical
Society
</
td
>
<
td
>
us
</
td
>
<
td
>
society_publisher
</
td
>
<
td
>
http
:
//www.aps.org/</td>
</
tr
>
<
tr
>
<
td
>
1236
</
td
>
<
td
>
41
</
td
>
<
td
>
10
</
td
>
<
td
>
American
Physical
Society
</
td
>
<
td
>
us
</
td
>
<
td
>
society_publisher
</
td
>
<
td
>
http
:
//www.aps.org/</td>
</
tr
>
<
tr
>
<
td
>
1238
</
td
>
<
td
>
80
</
td
>
<
td
>
10
</
td
>
<
td
>
American
Physical
Society
</
td
>
<
td
>
us
</
td
>
<
td
>
society_publisher
</
td
>
<
td
>
http
:
//www.aps.org/</td>
</
tr
>
<
tr
>
<
td
>
1240
</
td
>
<
td
>
533
</
td
>
<
td
>
10
</
td
>
<
td
>
American
Physical
Society
</
td
>
<
td
>
us
</
td
>
<
td
>
society_publisher
</
td
>
<
td
>
http
:
//www.aps.org/</td>
</
tr
>
<
tr
>
<
td
>
1242
</
td
>
<
td
>
608
</
td
>
<
td
>
10
</
td
>
<
td
>
American
Physical
Society
</
td
>
<
td
>
us
</
td
>
<
td
>
society_publisher
</
td
>
<
td
>
http
:
//www.aps.org/</td>
</
tr
>
</
tbody
>
</
table
>
<
p
>
808
rows
×
6
columns
</
p
>
</
div
>
```
python
sherpa_match_issn
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
issn
</
th
>
<
th
>
sherpa_match
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
0001
-
2815
</
td
>
<
td
>
OK
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
1399
-
0039
</
td
>
<
td
>
missing
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
0001
-
4842
</
td
>
<
td
>
OK
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
1520
-
4898
</
td
>
<
td
>
OK
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
0001
-
4966
</
td
>
<
td
>
OK
</
td
>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
1755
</
td
>
<
td
>
2470
-
0045
</
td
>
<
td
>
OK
</
td
>
</
tr
>
<
tr
>
<
td
>
1756
</
td
>
<
td
>
2470
-
0053
</
td
>
<
td
>
OK
</
td
>
</
tr
>
<
tr
>
<
td
>
1757
</
td
>
<
td
>
2475
-
9953
</
td
>
<
td
>
OK
</
td
>
</
tr
>
<
tr
>
<
td
>
1758
</
td
>
<
td
>
2504
-
4427
</
td
>
<
td
>
empty
</
td
>
</
tr
>
<
tr
>
<
td
>
1759
</
td
>
<
td
>
2504
-
4435
</
td
>
<
td
>
empty
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
1760
rows
×
2
columns
</
p
>
</
div
>
```
python
#
ajout
du
issnl
et
du
titre
sherpa_match_issn
=
pd
.
merge
(
sherpa_match_issn
,
issn_ids
,
on
=
'
issn
'
,
how
=
'
left
'
)
sherpa_match_issn
=
pd
.
merge
(
sherpa_match_issn
,
journal
[[
'
issnl
'
,
'
title
'
]],
on
=
'
issnl
'
,
how
=
'
left
'
)
sherpa_match_issn
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
issn
</
th
>
<
th
>
sherpa_match
</
th
>
<
th
>
id
</
th
>
<
th
>
issnl
</
th
>
<
th
>
journal
</
th
>
<
th
>
title
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
0001
-
2815
</
td
>
<
td
>
OK
</
td
>
<
td
>
1
</
td
>
<
td
>
0001
-
2815
</
td
>
<
td
>
532
</
td
>
<
td
>
Tissue
antigens
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
1399
-
0039
</
td
>
<
td
>
missing
</
td
>
<
td
>
2
</
td
>
<
td
>
0001
-
2815
</
td
>
<
td
>
532
</
td
>
<
td
>
Tissue
antigens
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
0001
-
4842
</
td
>
<
td
>
OK
</
td
>
<
td
>
3
</
td
>
<
td
>
0001
-
4842
</
td
>
<
td
>
498
</
td
>
<
td
>
Accounts
of
chemical
research
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
1520
-
4898
</
td
>
<
td
>
OK
</
td
>
<
td
>
4
</
td
>
<
td
>
0001
-
4842
</
td
>
<
td
>
498
</
td
>
<
td
>
Accounts
of
chemical
research
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
0001
-
4966
</
td
>
<
td
>
OK
</
td
>
<
td
>
5
</
td
>
<
td
>
0001
-
4966
</
td
>
<
td
>
789
</
td
>
<
td
>
The
Journal
of
the
Acoustical
Society
of
America
</
td
>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
1755
</
td
>
<
td
>
2470
-
0045
</
td
>
<
td
>
OK
</
td
>
<
td
>
1756
</
td
>
<
td
>
2470
-
0045
</
td
>
<
td
>
533
</
td
>
<
td
>
Physical
review
.
E
(
Print
)</
td
>
</
tr
>
<
tr
>
<
td
>
1756
</
td
>
<
td
>
2470
-
0053
</
td
>
<
td
>
OK
</
td
>
<
td
>
1757
</
td
>
<
td
>
2470
-
0045
</
td
>
<
td
>
533
</
td
>
<
td
>
Physical
review
.
E
(
Print
)</
td
>
</
tr
>
<
tr
>
<
td
>
1757
</
td
>
<
td
>
2475
-
9953
</
td
>
<
td
>
OK
</
td
>
<
td
>
1758
</
td
>
<
td
>
2475
-
9953
</
td
>
<
td
>
608
</
td
>
<
td
>
Physical
review
materials
</
td
>
</
tr
>
<
tr
>
<
td
>
1758
</
td
>
<
td
>
2504
-
4427
</
td
>
<
td
>
empty
</
td
>
<
td
>
1759
</
td
>
<
td
>
2504
-
4427
</
td
>
<
td
>
994
</
td
>
<
td
>
GG
@
G
(
Print
)</
td
>
</
tr
>
<
tr
>
<
td
>
1759
</
td
>
<
td
>
2504
-
4435
</
td
>
<
td
>
empty
</
td
>
<
td
>
1760
</
td
>
<
td
>
2504
-
4427
</
td
>
<
td
>
994
</
td
>
<
td
>
GG
@
G
(
Print
)</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
1760
rows
×
6
columns
</
p
>
</
div
>
```
python
sherpa_match_results
=
sherpa_match_issn
[[
'
id
'
,
'
issnl
'
,
'
sherpa_match
'
]].
groupby
([
'
issnl
'
,
'
sherpa_match
'
]).
count
()
sherpa_match_results
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
></
th
>
<
th
>
id
</
th
>
</
tr
>
<
tr
>
<
th
>
issnl
</
th
>
<
th
>
sherpa_match
</
th
>
<
th
></
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
rowspan
=
"2"
valign
=
"top"
>
0001
-
2815
</
td
>
<
td
>
OK
</
td
>
<
td
>
1
</
td
>
</
tr
>
<
tr
>
<
td
>
missing
</
td
>
<
td
>
1
</
td
>
</
tr
>
<
tr
>
<
td
>
0001
-
4842
</
td
>
<
td
>
OK
</
td
>
<
td
>
2
</
td
>
</
tr
>
<
tr
>
<
td
rowspan
=
"2"
valign
=
"top"
>
0001
-
4966
</
td
>
<
td
>
OK
</
td
>
<
td
>
1
</
td
>
</
tr
>
<
tr
>
<
td
>
empty
</
td
>
<
td
>
1
</
td
>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
2469
-
9950
</
td
>
<
td
>
OK
</
td
>
<
td
>
2
</
td
>
</
tr
>
<
tr
>
<
td
>
2470
-
0010
</
td
>
<
td
>
OK
</
td
>
<
td
>
2
</
td
>
</
tr
>
<
tr
>
<
td
>
2470
-
0045
</
td
>
<
td
>
OK
</
td
>
<
td
>
2
</
td
>
</
tr
>
<
tr
>
<
td
>
2475
-
9953
</
td
>
<
td
>
OK
</
td
>
<
td
>
1
</
td
>
</
tr
>
<
tr
>
<
td
>
2504
-
4427
</
td
>
<
td
>
empty
</
td
>
<
td
>
2
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
1302
rows
×
1
columns
</
p
>
</
div
>
```
python
sherpa_match_results
=
sherpa_match_results
.
reset_index
()
sherpa_match_results
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
issnl
</
th
>
<
th
>
sherpa_match
</
th
>
<
th
>
id
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
0001
-
2815
</
td
>
<
td
>
OK
</
td
>
<
td
>
1
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
0001
-
2815
</
td
>
<
td
>
missing
</
td
>
<
td
>
1
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
0001
-
4842
</
td
>
<
td
>
OK
</
td
>
<
td
>
2
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
0001
-
4966
</
td
>
<
td
>
OK
</
td
>
<
td
>
1
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
0001
-
4966
</
td
>
<
td
>
empty
</
td
>
<
td
>
1
</
td
>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
1297
</
td
>
<
td
>
2469
-
9950
</
td
>
<
td
>
OK
</
td
>
<
td
>
2
</
td
>
</
tr
>
<
tr
>
<
td
>
1298
</
td
>
<
td
>
2470
-
0010
</
td
>
<
td
>
OK
</
td
>
<
td
>
2
</
td
>
</
tr
>
<
tr
>
<
td
>
1299
</
td
>
<
td
>
2470
-
0045
</
td
>
<
td
>
OK
</
td
>
<
td
>
2
</
td
>
</
tr
>
<
tr
>
<
td
>
1300
</
td
>
<
td
>
2475
-
9953
</
td
>
<
td
>
OK
</
td
>
<
td
>
1
</
td
>
</
tr
>
<
tr
>
<
td
>
1301
</
td
>
<
td
>
2504
-
4427
</
td
>
<
td
>
empty
</
td
>
<
td
>
2
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
1302
rows
×
3
columns
</
p
>
</
div
>
```
python
sherpa_match_results_ok
=
sherpa_match_results
.
loc
[
sherpa_match_results
[
'
sherpa_match
'
]
==
'
OK
'
]
issn_ids_issnl
=
issn_ids
[[
'
issnl
'
,
'
journal
'
]].
drop_duplicates
(
subset
=
'
issnl
'
)
issn_ids_issnl
=
pd
.
merge
(
issn_ids_issnl
,
sherpa_match_results_ok
,
on
=
'
issnl
'
,
how
=
'
left
'
)
issn_ids_issnl
=
pd
.
merge
(
issn_ids_issnl
,
journal
[[
'
issnl
'
,
'
title
'
]],
on
=
'
issnl
'
,
how
=
'
left
'
)
issn_ids_issnl
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
issnl
</
th
>
<
th
>
journal
</
th
>
<
th
>
sherpa_match
</
th
>
<
th
>
id
</
th
>
<
th
>
title
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
0001
-
2815
</
td
>
<
td
>
532
</
td
>
<
td
>
OK
</
td
>
<
td
>
1.0
</
td
>
<
td
>
Tissue
antigens
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
0001
-
4842
</
td
>
<
td
>
498
</
td
>
<
td
>
OK
</
td
>
<
td
>
2.0
</
td
>
<
td
>
Accounts
of
chemical
research
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
0001
-
4966
</
td
>
<
td
>
789
</
td
>
<
td
>
OK
</
td
>
<
td
>
1.0
</
td
>
<
td
>
The
Journal
of
the
Acoustical
Society
of
America
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
0001
-
6268
</
td
>
<
td
>
166
</
td
>
<
td
>
OK
</
td
>
<
td
>
2.0
</
td
>
<
td
>
Acta
neurochirurgica
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
0001
-
6322
</
td
>
<
td
>
807
</
td
>
<
td
>
OK
</
td
>
<
td
>
2.0
</
td
>
<
td
>
Acta
neuropathologica
</
td
>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
904
</
td
>
<
td
>
2469
-
9950
</
td
>
<
td
>
41
</
td
>
<
td
>
OK
</
td
>
<
td
>
2.0
</
td
>
<
td
>
Physical
review
.
B
</
td
>
</
tr
>
<
tr
>
<
td
>
905
</
td
>
<
td
>
2470
-
0010
</
td
>
<
td
>
80
</
td
>
<
td
>
OK
</
td
>
<
td
>
2.0
</
td
>
<
td
>
Physical
review
.
D
</
td
>
</
tr
>
<
tr
>
<
td
>
906
</
td
>
<
td
>
2470
-
0045
</
td
>
<
td
>
533
</
td
>
<
td
>
OK
</
td
>
<
td
>
2.0
</
td
>
<
td
>
Physical
review
.
E
(
Print
)</
td
>
</
tr
>
<
tr
>
<
td
>
907
</
td
>
<
td
>
2475
-
9953
</
td
>
<
td
>
608
</
td
>
<
td
>
OK
</
td
>
<
td
>
1.0
</
td
>
<
td
>
Physical
review
materials
</
td
>
</
tr
>
<
tr
>
<
td
>
908
</
td
>
<
td
>
2504
-
4427
</
td
>
<
td
>
994
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
GG
@
G
(
Print
)</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
909
rows
×
5
columns
</
p
>
</
div
>
```
python
journals_not_sherpa
=
issn_ids_issnl
.
loc
[
issn_ids_issnl
[
'
sherpa_match
'
].
isna
()]
journals_not_sherpa
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
issnl
</
th
>
<
th
>
journal
</
th
>
<
th
>
sherpa_match
</
th
>
<
th
>
id
</
th
>
<
th
>
title
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
24
</
td
>
<
td
>
0003
-
6935
</
td
>
<
td
>
398
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Applied
optics
</
td
>
</
tr
>
<
tr
>
<
td
>
27
</
td
>
<
td
>
0003
-
9926
</
td
>
<
td
>
605
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Archives
of
internal
medicine
(
1960
)</
td
>
</
tr
>
<
tr
>
<
td
>
28
</
td
>
<
td
>
0003
-
9942
</
td
>
<
td
>
974
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Archives
of
neurology
(
Chicago
)</
td
>
</
tr
>
<
tr
>
<
td
>
47
</
td
>
<
td
>
0007
-
4403
</
td
>
<
td
>
885
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Bulletin
de
psychologie
</
td
>
</
tr
>
<
tr
>
<
td
>
48
</
td
>
<
td
>
0008
-
042
X
</
td
>
<
td
>
180
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Cahiers
p
é
dagogiques
(
Revue
)</
td
>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
889
</
td
>
<
td
>
2264
-
7228
</
td
>
<
td
>
503
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Distances
et
me
́
diations
des
savoirs
</
td
>
</
tr
>
<
tr
>
<
td
>
892
</
td
>
<
td
>
2297
-
0703
</
td
>
<
td
>
989
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Schweizer
Krebs
-
Bulletin
</
td
>
</
tr
>
<
tr
>
<
td
>
893
</
td
>
<
td
>
2297
-
6981
</
td
>
<
td
>
618
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Swiss
archives
of
neurology
,
psychiatry
and
ps
...</
td
>
</
tr
>
<
tr
>
<
td
>
898
</
td
>
<
td
>
2352
-
1791
</
td
>
<
td
>
639
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Nuclear
materials
and
energy
</
td
>
</
tr
>
<
tr
>
<
td
>
908
</
td
>
<
td
>
2504
-
4427
</
td
>
<
td
>
994
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
GG
@
G
(
Print
)</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
101
rows
×
5
columns
</
p
>
</
div
>
```
python
sherpa_match_results_empty
=
sherpa_match_results
.
loc
[
sherpa_match_results
[
'
sherpa_match
'
]
==
'
empty
'
]
sherpa_match_results_missing
=
sherpa_match_results
.
loc
[
sherpa_match_results
[
'
sherpa_match
'
]
==
'
missing
'
]
del
journals_not_sherpa
[
'
sherpa_match
'
]
del
journals_not_sherpa
[
'
id
'
]
journals_not_sherpa
=
pd
.
merge
(
journals_not_sherpa
,
sherpa_match_results_empty
,
on
=
'
issnl
'
,
how
=
'
left
'
)
del
journals_not_sherpa
[
'
id
'
]
journals_not_sherpa
=
pd
.
merge
(
journals_not_sherpa
,
sherpa_match_results_missing
,
on
=
'
issnl
'
,
how
=
'
left
'
)
del
journals_not_sherpa
[
'
id
'
]
journals_not_sherpa
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
issnl
</
th
>
<
th
>
journal
</
th
>
<
th
>
title
</
th
>
<
th
>
sherpa_match_x
</
th
>
<
th
>
sherpa_match_y
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
0003
-
6935
</
td
>
<
td
>
398
</
td
>
<
td
>
Applied
optics
</
td
>
<
td
>
empty
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
0003
-
9926
</
td
>
<
td
>
605
</
td
>
<
td
>
Archives
of
internal
medicine
(
1960
)</
td
>
<
td
>
empty
</
td
>
<
td
>
missing
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
0003
-
9942
</
td
>
<
td
>
974
</
td
>
<
td
>
Archives
of
neurology
(
Chicago
)</
td
>
<
td
>
empty
</
td
>
<
td
>
missing
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
0007
-
4403
</
td
>
<
td
>
885
</
td
>
<
td
>
Bulletin
de
psychologie
</
td
>
<
td
>
empty
</
td
>
<
td
>
missing
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
0008
-
042
X
</
td
>
<
td
>
180
</
td
>
<
td
>
Cahiers
p
é
dagogiques
(
Revue
)</
td
>
<
td
>
empty
</
td
>
<
td
>
missing
</
td
>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
96
</
td
>
<
td
>
2264
-
7228
</
td
>
<
td
>
503
</
td
>
<
td
>
Distances
et
me
́
diations
des
savoirs
</
td
>
<
td
>
empty
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
97
</
td
>
<
td
>
2297
-
0703
</
td
>
<
td
>
989
</
td
>
<
td
>
Schweizer
Krebs
-
Bulletin
</
td
>
<
td
>
empty
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
98
</
td
>
<
td
>
2297
-
6981
</
td
>
<
td
>
618
</
td
>
<
td
>
Swiss
archives
of
neurology
,
psychiatry
and
ps
...</
td
>
<
td
>
empty
</
td
>
<
td
>
missing
</
td
>
</
tr
>
<
tr
>
<
td
>
99
</
td
>
<
td
>
2352
-
1791
</
td
>
<
td
>
639
</
td
>
<
td
>
Nuclear
materials
and
energy
</
td
>
<
td
>
empty
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
100
</
td
>
<
td
>
2504
-
4427
</
td
>
<
td
>
994
</
td
>
<
td
>
GG
@
G
(
Print
)</
td
>
<
td
>
empty
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
101
rows
×
5
columns
</
p
>
</
div
>
```
python
#
extraction
des
informations
des
journaux
à
partir
des
donn
é
es
Sherpa
/
Romeo
for
index
,
row
in
issn
.
iterrows
():
journal_id
=
row
[
'
journal
'
]
journal_issn
=
row
[
'
issn
'
]
#
boucle
des
fichiers
json
#
test
d
'
existance
du
fichier
#
print
(
row
[
'
format
'
])
if
(((
index
/
10
)
-
int
(
index
/
10
))
==
0
)
:
print
(
index
)
if
os
.
path
.
exists
(
'
sherpa
/
data
/
'
+
journal_issn
+
'
.
json
'
):
with
open
(
'
sherpa
/
data
/
'
+
journal_issn
+
'
.
json
'
,
'r'
,
encoding
=
'
utf
-
8
'
)
as
f
:
data
=
json
.
load
(
f
)
title
=
np
.
nan
url
=
np
.
nan
if
(
len
(
data
[
'
items
'
])
>
0
):
if
(
'
url
'
in
data
[
'
items
'
][
0
]):
url
=
data
[
'
items
'
][
0
][
'
url
'
]
if
(
'
title
'
in
data
[
'
items
'
][
0
][
'
title
'
][
0
]):
title
=
data
[
'
items
'
][
0
][
'
title
'
][
0
][
'
title
'
]
sherpa_journal
=
sherpa_journal
.
append
({
'
journal
'
:
journal_id
,
'
title
'
:
title
,
'
url
'
:
url
},
ignore_index
=
True
)
```
0
10
20
30
40
50
60
70
80
90
100
110
120
130
140
150
160
170
180
190
200
210
220
230
240
250
260
270
280
290
300
310
320
330
340
350
360
370
380
390
400
410
420
430
440
450
460
470
480
490
500
510
520
530
540
550
560
570
580
590
600
610
620
630
640
650
660
670
680
690
700
710
720
730
740
750
760
770
780
790
800
810
820
830
840
850
860
870
880
890
900
910
920
930
940
950
960
970
980
990
1000
1010
1020
1030
1040
1050
1060
1070
1080
1090
1100
1110
1120
1130
1140
1150
1160
1170
1180
1190
1200
1210
1220
1230
1240
1250
1260
1270
1280
1290
1300
1310
1320
1330
1340
1350
1360
1370
1380
1390
1400
1410
1420
1430
1440
1450
1460
1470
1480
1490
1500
1510
1520
1530
1540
1550
1560
1570
1580
1590
1600
1610
1620
1630
1640
1650
1660
1670
1680
1690
1700
1710
1720
1730
1740
1750
```
python
sherpa_journal
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
journal
</
th
>
<
th
>
title
</
th
>
<
th
>
url
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
532
</
td
>
<
td
>
Tissue
Antigens
</
td
>
<
td
>
http
:
//onlinelibrary.wiley.com/journal/10.1111...</td>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
498
</
td
>
<
td
>
Accounts
of
Chemical
Research
</
td
>
<
td
>
http
:
//pubs.acs.org/journal/achre4</td>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
498
</
td
>
<
td
>
Accounts
of
Chemical
Research
</
td
>
<
td
>
http
:
//pubs.acs.org/journal/achre4</td>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
789
</
td
>
<
td
>
The
Journal
of
the
Acoustical
Society
of
America
</
td
>
<
td
>
http
:
//asa.scitation.org/journal/jas</td>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
166
</
td
>
<
td
>
Acta
Neurochirurgica
</
td
>
<
td
>
http
:
//link.springer.com/journal/701</td>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
1238
</
td
>
<
td
>
80
</
td
>
<
td
>
Physical
Review
D
</
td
>
<
td
>
http
:
//prd.aps.org/</td>
</
tr
>
<
tr
>
<
td
>
1239
</
td
>
<
td
>
80
</
td
>
<
td
>
Physical
Review
D
</
td
>
<
td
>
http
:
//prd.aps.org/</td>
</
tr
>
<
tr
>
<
td
>
1240
</
td
>
<
td
>
533
</
td
>
<
td
>
Physical
Review
E
</
td
>
<
td
>
http
:
//journals.aps.org/pre/abstract/10.1103/P...</td>
</
tr
>
<
tr
>
<
td
>
1241
</
td
>
<
td
>
533
</
td
>
<
td
>
Physical
Review
E
</
td
>
<
td
>
http
:
//journals.aps.org/pre/abstract/10.1103/P...</td>
</
tr
>
<
tr
>
<
td
>
1242
</
td
>
<
td
>
608
</
td
>
<
td
>
Physical
Review
Materials
</
td
>
<
td
>
http
:
//journals.aps.org/prmaterials/</td>
</
tr
>
</
tbody
>
</
table
>
<
p
>
1243
rows
×
3
columns
</
p
>
</
div
>
```
python
#
extraction
des
informations
à
partir
des
donn
é
es
Sherpa
/
Romeo
for
index
,
row
in
issn
.
iterrows
():
journal_id
=
row
[
'
journal
'
]
journal_issn
=
row
[
'
issn
'
]
#
boucle
des
fichiers
json
#
test
d
'
existance
du
fichier
#
print
(
row
[
'
format
'
])
if
(((
index
/
10
)
-
int
(
index
/
10
))
==
0
)
:
print
(
index
)
if
os
.
path
.
exists
(
'
sherpa
/
data
/
'
+
journal_issn
+
'
.
json
'
):
with
open
(
'
sherpa
/
data
/
'
+
journal_issn
+
'
.
json
'
,
'r'
,
encoding
=
'
utf
-
8
'
)
as
f
:
myissn
=
np
.
nan
mytype
=
np
.
nan
data
=
json
.
load
(
f
)
if
(
len
(
data
[
'
items
'
])
>
0
):
if
(
'
issns
'
in
data
[
'
items
'
][
0
]):
issns
=
data
[
'
items
'
][
0
][
'
issns
'
]
for
i
in
issns
:
if
(
'
issn
'
in
i
):
myissn
=
i
[
'
issn
'
]
if
(
'
type
'
in
i
):
mytype
=
i
[
'
type
'
]
sherpa_issn
=
sherpa_issn
.
append
({
'
issn
'
:
myissn
,
'
type
'
:
mytype
},
ignore_index
=
True
)
```
0
10
20
30
40
50
60
70
80
90
100
110
120
130
140
150
160
170
180
190
200
210
220
230
240
250
260
270
280
290
300
310
320
330
340
350
360
370
380
390
400
410
420
430
440
450
460
470
480
490
500
510
520
530
540
550
560
570
580
590
600
610
620
630
640
650
660
670
680
690
700
710
720
730
740
750
760
770
780
790
800
810
820
830
840
850
860
870
880
890
900
910
920
930
940
950
960
970
980
990
1000
1010
1020
1030
1040
1050
1060
1070
1080
1090
1100
1110
1120
1130
1140
1150
1160
1170
1180
1190
1200
1210
1220
1230
1240
1250
1260
1270
1280
1290
1300
1310
1320
1330
1340
1350
1360
1370
1380
1390
1400
1410
1420
1430
1440
1450
1460
1470
1480
1490
1500
1510
1520
1530
1540
1550
1560
1570
1580
1590
1600
1610
1620
1630
1640
1650
1660
1670
1680
1690
1700
1710
1720
1730
1740
1750
```
python
sherpa_issn
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
issn
</
th
>
<
th
>
type
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
0001
-
2815
</
td
>
<
td
>
print
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
1399
-
0039
</
td
>
<
td
>
electronic
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
0001
-
4842
</
td
>
<
td
>
print
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
1520
-
4898
</
td
>
<
td
>
electronic
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
0001
-
4842
</
td
>
<
td
>
print
</
td
>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
2196
</
td
>
<
td
>
2470
-
0045
</
td
>
<
td
>
print
</
td
>
</
tr
>
<
tr
>
<
td
>
2197
</
td
>
<
td
>
2470
-
0053
</
td
>
<
td
>
electronic
</
td
>
</
tr
>
<
tr
>
<
td
>
2198
</
td
>
<
td
>
2470
-
0045
</
td
>
<
td
>
print
</
td
>
</
tr
>
<
tr
>
<
td
>
2199
</
td
>
<
td
>
2470
-
0053
</
td
>
<
td
>
electronic
</
td
>
</
tr
>
<
tr
>
<
td
>
2200
</
td
>
<
td
>
2475
-
9953
</
td
>
<
td
>
electronic
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
2201
rows
×
2
columns
</
p
>
</
div
>
```
python
#
dedup
sherpa_issn
=
sherpa_issn
.
drop_duplicates
()
sherpa_issn
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
issn
</
th
>
<
th
>
type
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
0001
-
2815
</
td
>
<
td
>
print
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
1399
-
0039
</
td
>
<
td
>
electronic
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
0001
-
4842
</
td
>
<
td
>
print
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
1520
-
4898
</
td
>
<
td
>
electronic
</
td
>
</
tr
>
<
tr
>
<
td
>
6
</
td
>
<
td
>
0001
-
4966
</
td
>
<
td
>
print
</
td
>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
2192
</
td
>
<
td
>
2470
-
0010
</
td
>
<
td
>
print
</
td
>
</
tr
>
<
tr
>
<
td
>
2193
</
td
>
<
td
>
2470
-
0029
</
td
>
<
td
>
electronic
</
td
>
</
tr
>
<
tr
>
<
td
>
2196
</
td
>
<
td
>
2470
-
0045
</
td
>
<
td
>
print
</
td
>
</
tr
>
<
tr
>
<
td
>
2197
</
td
>
<
td
>
2470
-
0053
</
td
>
<
td
>
electronic
</
td
>
</
tr
>
<
tr
>
<
td
>
2200
</
td
>
<
td
>
2475
-
9953
</
td
>
<
td
>
electronic
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
1333
rows
×
2
columns
</
p
>
</
div
>
```
python
#
completer
le
fichier
des
issns
avec
les
types
de
sherpa
issn2
=
pd
.
merge
(
issn
,
sherpa_issn
,
on
=
'
issn
'
,
how
=
'
left
'
)
issn2
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
issn
</
th
>
<
th
>
issnl
</
th
>
<
th
>
journal
</
th
>
<
th
>
format
</
th
>
<
th
>
issn_type
</
th
>
<
th
>
id
</
th
>
<
th
>
type
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
0001
-
2815
</
td
>
<
td
>
0001
-
2815
</
td
>
<
td
>
532
</
td
>
<
td
>
PRINT
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
print
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
1399
-
0039
</
td
>
<
td
>
0001
-
2815
</
td
>
<
td
>
532
</
td
>
<
td
>
NaN
</
td
>
<
td
>
3
</
td
>
<
td
>
2
</
td
>
<
td
>
electronic
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
0001
-
4842
</
td
>
<
td
>
0001
-
4842
</
td
>
<
td
>
498
</
td
>
<
td
>
PRINT
</
td
>
<
td
>
1
</
td
>
<
td
>
3
</
td
>
<
td
>
print
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
1520
-
4898
</
td
>
<
td
>
0001
-
4842
</
td
>
<
td
>
498
</
td
>
<
td
>
NaN
</
td
>
<
td
>
3
</
td
>
<
td
>
4
</
td
>
<
td
>
electronic
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
0001
-
4966
</
td
>
<
td
>
0001
-
4966
</
td
>
<
td
>
789
</
td
>
<
td
>
PRINT
</
td
>
<
td
>
1
</
td
>
<
td
>
5
</
td
>
<
td
>
print
</
td
>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
1755
</
td
>
<
td
>
2470
-
0045
</
td
>
<
td
>
2470
-
0045
</
td
>
<
td
>
533
</
td
>
<
td
>
OTHER
</
td
>
<
td
>
3
</
td
>
<
td
>
1756
</
td
>
<
td
>
print
</
td
>
</
tr
>
<
tr
>
<
td
>
1756
</
td
>
<
td
>
2470
-
0053
</
td
>
<
td
>
2470
-
0045
</
td
>
<
td
>
533
</
td
>
<
td
>
NaN
</
td
>
<
td
>
3
</
td
>
<
td
>
1757
</
td
>
<
td
>
electronic
</
td
>
</
tr
>
<
tr
>
<
td
>
1757
</
td
>
<
td
>
2475
-
9953
</
td
>
<
td
>
2475
-
9953
</
td
>
<
td
>
608
</
td
>
<
td
>
ELECTRONIC
</
td
>
<
td
>
2
</
td
>
<
td
>
1758
</
td
>
<
td
>
electronic
</
td
>
</
tr
>
<
tr
>
<
td
>
1758
</
td
>
<
td
>
2504
-
4427
</
td
>
<
td
>
2504
-
4427
</
td
>
<
td
>
994
</
td
>
<
td
>
PRINT
</
td
>
<
td
>
1
</
td
>
<
td
>
1759
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
1759
</
td
>
<
td
>
2504
-
4435
</
td
>
<
td
>
2504
-
4427
</
td
>
<
td
>
994
</
td
>
<
td
>
NaN
</
td
>
<
td
>
3
</
td
>
<
td
>
1760
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
1760
rows
×
7
columns
</
p
>
</
div
>
```
python
#
exports
csv
publisher_sherpa_dedup
.
to_csv
(
'
sample
/
publisher_sherpa
.
tsv
'
,
sep
=
'\t'
,
encoding
=
'
utf
-
8
'
,
index
=
False
)
sherpa_match_issn
.
to_csv
(
'
sample
/
sherpa_match_issn
.
tsv
'
,
sep
=
'\t'
,
encoding
=
'
utf
-
8
'
,
index
=
False
)
sherpa_journal
.
to_csv
(
'
sample
/
sherpa_journal
.
tsv
'
,
sep
=
'\t'
,
encoding
=
'
utf
-
8
'
,
index
=
False
)
issn2
.
to_csv
(
'
sample
/
issn_sherpa
.
tsv
'
,
sep
=
'\t'
,
encoding
=
'
utf
-
8
'
,
index
=
False
)
journals_not_sherpa
.
to_csv
(
'
sample
/
journals_not_sherpa
.
tsv
'
,
sep
=
'\t'
,
encoding
=
'
utf
-
8
'
,
index
=
False
)
```
```
python
#
exports
excel
publisher_sherpa_dedup
.
to_excel
(
'
sample
/
publisher_sherpa
.
xlsx
'
,
index
=
False
)
sherpa_match_issn
.
to_excel
(
'
sample
/
sherpa_match_issn
.
xlsx
'
,
index
=
False
)
sherpa_journal
.
to_excel
(
'
sample
/
sherpa_journal
.
xlsx
'
,
index
=
False
)
issn2
.
to_excel
(
'
sample
/
issn_sherpa
.
xlsx
'
,
index
=
False
)
journals_not_sherpa
.
to_excel
(
'
sample
/
journals_not_sherpa
.
xlsx
'
,
index
=
False
)
```
```
python
#
ajout
des
titres
Sherpa
a
la
table
des
revues
#
renommer
les
colonnes
sherpa_journal
=
sherpa_journal
.
rename
(
columns
={
'
journal
'
:
'
id
'
})
journal
=
pd
.
merge
(
journal
,
sherpa_journal
,
on
=
'
id
'
,
how
=
'
left
'
)
journal
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
id
</
th
>
<
th
>
issn
</
th
>
<
th
>
issnl
</
th
>
<
th
>
title_x
</
th
>
<
th
>
starting_year
</
th
>
<
th
>
end_year
</
th
>
<
th
>
url_x
</
th
>
<
th
>
name_short_iso_4
</
th
>
<
th
>
language
</
th
>
<
th
>
country
</
th
>
<
th
>
doaj_title
</
th
>
<
th
>
doaj_seal
</
th
>
<
th
>
APC
</
th
>
<
th
>
doaj_status
</
th
>
<
th
>
lockss_title
</
th
>
<
th
>
lockss
</
th
>
<
th
>
portico_status
</
th
>
<
th
>
portico
</
th
>
<
th
>
nlch_title
</
th
>
<
th
>
nlch
</
th
>
<
th
>
qoam_av_score
</
th
>
<
th
>
doublon_issnl
</
th
>
<
th
>
oa_status
</
th
>
<
th
>
publisher
</
th
>
<
th
>
title_y
</
th
>
<
th
>
url_y
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
1660
-
9379
</
td
>
<
td
>
1660
-
9379
</
td
>
<
td
>
Revue
m
é
dicale
suisse
</
td
>
<
td
>
2005
</
td
>
<
td
>
9999
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Rev
.
m
é
d
.
suisse
</
td
>
<
td
>
138
</
td
>
<
td
>
215
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
2
</
td
>
<
td
>
0031
-
9007
</
td
>
<
td
>
0031
-
9007
</
td
>
<
td
>
Physical
review
letters
(
Print
)</
td
>
<
td
>
1958
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//prl.aps.org/</td>
<
td
>
Phys
.
rev
.
lett
.
(
Print
)</
td
>
<
td
>
124
</
td
>
<
td
>
236
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
preserved
</
td
>
<
td
>
1.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1.0
</
td
>
<
td
>
1
</
td
>
<
td
>
2
</
td
>
<
td
>
Physical
Review
Letters
</
td
>
<
td
>
http
:
//prl.aps.org/</td>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
2
</
td
>
<
td
>
0031
-
9007
</
td
>
<
td
>
0031
-
9007
</
td
>
<
td
>
Physical
review
letters
(
Print
)</
td
>
<
td
>
1958
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//prl.aps.org/</td>
<
td
>
Phys
.
rev
.
lett
.
(
Print
)</
td
>
<
td
>
124
</
td
>
<
td
>
236
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
preserved
</
td
>
<
td
>
1.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1.0
</
td
>
<
td
>
1
</
td
>
<
td
>
2
</
td
>
<
td
>
Physical
Review
Letters
</
td
>
<
td
>
http
:
//prl.aps.org/</td>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
3
</
td
>
<
td
>
1932
-
6203
</
td
>
<
td
>
1932
-
6203
</
td
>
<
td
>
PloS
one
</
td
>
<
td
>
2006
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.plosone.org/</td>
<
td
>
NaN
</
td
>
<
td
>
124
</
td
>
<
td
>
236
</
td
>
<
td
>
PLoS
ONE
</
td
>
<
td
>
1.0
</
td
>
<
td
>
Yes
</
td
>
<
td
>
1.0
</
td
>
<
td
>
PLoS
One
</
td
>
<
td
>
1.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
4.035714
</
td
>
<
td
>
NaN
</
td
>
<
td
>
5
</
td
>
<
td
>
3
</
td
>
<
td
>
PLoS
ONE
</
td
>
<
td
>
http
:
//www.plosone.org/</td>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
4
</
td
>
<
td
>
2174
-
8454
</
td
>
<
td
>
2174
-
8454
</
td
>
<
td
>
EU
-
top
í
as
</
td
>
<
td
>
2011
</
td
>
<
td
>
9999
</
td
>
<
td
>
NaN
</
td
>
<
td
>
EU
-
top
í
as
</
td
>
<
td
>
124
,
138
,
402
,
292
</
td
>
<
td
>
209
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1
</
td
>
<
td
>
4
,
5
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
1341
</
td
>
<
td
>
998
</
td
>
<
td
>
0022
-
3468
</
td
>
<
td
>
0022
-
3468
</
td
>
<
td
>
Journal
of
pediatric
surgery
(
Print
)</
td
>
<
td
>
1966
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.jpedsurg.org</td>
<
td
>
J
.
pediatr
.
surg
.
(
Print
)</
td
>
<
td
>
124
</
td
>
<
td
>
236
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
preserved
</
td
>
<
td
>
1.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1
</
td
>
<
td
>
75
</
td
>
<
td
>
Journal
of
Pediatric
Surgery
</
td
>
<
td
>
http
:
//www.jpedsurg.org/</td>
</
tr
>
<
tr
>
<
td
>
1342
</
td
>
<
td
>
999
</
td
>
<
td
>
1432
-
2064
</
td
>
<
td
>
0178
-
8051
</
td
>
<
td
>
Probability
theory
and
related
fields
(
Internet
)</
td
>
<
td
>
uuuu
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.springerlink.com/content/100451</td>
<
td
>
Probab
.
theory
relat
.
fields
(
Internet
)</
td
>
<
td
>
124
</
td
>
<
td
>
83
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
Probability
Theory
and
Related
Fields
</
td
>
<
td
>
1.0
</
td
>
<
td
>
preserved
</
td
>
<
td
>
1.0
</
td
>
<
td
>
Probability
Theory
and
Related
Fields
</
td
>
<
td
>
1.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1
</
td
>
<
td
>
8
</
td
>
<
td
>
Probability
Theory
and
Related
Fields
</
td
>
<
td
>
http
:
//www.springerlink.com/content/100451/?p=...</td>
</
tr
>
<
tr
>
<
td
>
1343
</
td
>
<
td
>
999
</
td
>
<
td
>
1432
-
2064
</
td
>
<
td
>
0178
-
8051
</
td
>
<
td
>
Probability
theory
and
related
fields
(
Internet
)</
td
>
<
td
>
uuuu
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.springerlink.com/content/100451</td>
<
td
>
Probab
.
theory
relat
.
fields
(
Internet
)</
td
>
<
td
>
124
</
td
>
<
td
>
83
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
Probability
Theory
and
Related
Fields
</
td
>
<
td
>
1.0
</
td
>
<
td
>
preserved
</
td
>
<
td
>
1.0
</
td
>
<
td
>
Probability
Theory
and
Related
Fields
</
td
>
<
td
>
1.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1
</
td
>
<
td
>
8
</
td
>
<
td
>
Probability
Theory
and
Related
Fields
</
td
>
<
td
>
http
:
//www.springerlink.com/content/100451/?p=...</td>
</
tr
>
<
tr
>
<
td
>
1344
</
td
>
<
td
>
1000
</
td
>
<
td
>
0960
-
1481
</
td
>
<
td
>
0960
-
1481
</
td
>
<
td
>
Renewable
energy
</
td
>
<
td
>
1991
</
td
>
<
td
>
9999
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Renew
.
energy
</
td
>
<
td
>
124
</
td
>
<
td
>
234
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
preserved
</
td
>
<
td
>
1.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1
</
td
>
<
td
>
119
</
td
>
<
td
>
Renewable
Energy
</
td
>
<
td
>
http
:
//www.elsevier.com/wps/product/cws_home/9...</td>
</
tr
>
<
tr
>
<
td
>
1345
</
td
>
<
td
>
1001
</
td
>
<
td
>
0161
-
7567
</
td
>
<
td
>
0161
-
7567
</
td
>
<
td
>
Journal
of
applied
physiology
:
respiratory
,
en
...</
td
>
<
td
>
1977
</
td
>
<
td
>
1984
</
td
>
<
td
>
https
:
//www.physiology.org/journal/jappl</td>
<
td
>
J
.
appl
.
physiol
.:
respir
.,
environ
.
exercise
...</
td
>
<
td
>
124
</
td
>
<
td
>
236
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1
</
td
>
<
td
>
217
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
1346
rows
×
26
columns
</
p
>
</
div
>
```
python
#
choix
du
titre
et
url
journal
[
'
url
'
]
=
journal
[
'
url_y
'
]
journal
.
loc
[
journal
[
'
url_y
'
].
isna
(),
'
url
'
]
=
journal
[
'
url_x
'
]
journal
[
'
title
'
]
=
journal
[
'
title_y
'
]
journal
.
loc
[
journal
[
'
title_y
'
].
isna
(),
'
title
'
]
=
journal
[
'
title_x
'
]
journal
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
id
</
th
>
<
th
>
issn
</
th
>
<
th
>
issnl
</
th
>
<
th
>
title_x
</
th
>
<
th
>
starting_year
</
th
>
<
th
>
end_year
</
th
>
<
th
>
url_x
</
th
>
<
th
>
name_short_iso_4
</
th
>
<
th
>
language
</
th
>
<
th
>
country
</
th
>
<
th
>
doaj_title
</
th
>
<
th
>
doaj_seal
</
th
>
<
th
>
APC
</
th
>
<
th
>
doaj_status
</
th
>
<
th
>
lockss_title
</
th
>
<
th
>
lockss
</
th
>
<
th
>
portico_status
</
th
>
<
th
>
portico
</
th
>
<
th
>
nlch_title
</
th
>
<
th
>
nlch
</
th
>
<
th
>
qoam_av_score
</
th
>
<
th
>
doublon_issnl
</
th
>
<
th
>
oa_status
</
th
>
<
th
>
publisher
</
th
>
<
th
>
title_y
</
th
>
<
th
>
url_y
</
th
>
<
th
>
url
</
th
>
<
th
>
title
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
1660
-
9379
</
td
>
<
td
>
1660
-
9379
</
td
>
<
td
>
Revue
m
é
dicale
suisse
</
td
>
<
td
>
2005
</
td
>
<
td
>
9999
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Rev
.
m
é
d
.
suisse
</
td
>
<
td
>
138
</
td
>
<
td
>
215
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Revue
m
é
dicale
suisse
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
2
</
td
>
<
td
>
0031
-
9007
</
td
>
<
td
>
0031
-
9007
</
td
>
<
td
>
Physical
review
letters
(
Print
)</
td
>
<
td
>
1958
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//prl.aps.org/</td>
<
td
>
Phys
.
rev
.
lett
.
(
Print
)</
td
>
<
td
>
124
</
td
>
<
td
>
236
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
preserved
</
td
>
<
td
>
1.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1.0
</
td
>
<
td
>
1
</
td
>
<
td
>
2
</
td
>
<
td
>
Physical
Review
Letters
</
td
>
<
td
>
http
:
//prl.aps.org/</td>
<
td
>
http
:
//prl.aps.org/</td>
<
td
>
Physical
Review
Letters
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
2
</
td
>
<
td
>
0031
-
9007
</
td
>
<
td
>
0031
-
9007
</
td
>
<
td
>
Physical
review
letters
(
Print
)</
td
>
<
td
>
1958
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//prl.aps.org/</td>
<
td
>
Phys
.
rev
.
lett
.
(
Print
)</
td
>
<
td
>
124
</
td
>
<
td
>
236
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
preserved
</
td
>
<
td
>
1.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1.0
</
td
>
<
td
>
1
</
td
>
<
td
>
2
</
td
>
<
td
>
Physical
Review
Letters
</
td
>
<
td
>
http
:
//prl.aps.org/</td>
<
td
>
http
:
//prl.aps.org/</td>
<
td
>
Physical
Review
Letters
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
3
</
td
>
<
td
>
1932
-
6203
</
td
>
<
td
>
1932
-
6203
</
td
>
<
td
>
PloS
one
</
td
>
<
td
>
2006
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.plosone.org/</td>
<
td
>
NaN
</
td
>
<
td
>
124
</
td
>
<
td
>
236
</
td
>
<
td
>
PLoS
ONE
</
td
>
<
td
>
1.0
</
td
>
<
td
>
Yes
</
td
>
<
td
>
1.0
</
td
>
<
td
>
PLoS
One
</
td
>
<
td
>
1.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
4.035714
</
td
>
<
td
>
NaN
</
td
>
<
td
>
5
</
td
>
<
td
>
3
</
td
>
<
td
>
PLoS
ONE
</
td
>
<
td
>
http
:
//www.plosone.org/</td>
<
td
>
http
:
//www.plosone.org/</td>
<
td
>
PLoS
ONE
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
4
</
td
>
<
td
>
2174
-
8454
</
td
>
<
td
>
2174
-
8454
</
td
>
<
td
>
EU
-
top
í
as
</
td
>
<
td
>
2011
</
td
>
<
td
>
9999
</
td
>
<
td
>
NaN
</
td
>
<
td
>
EU
-
top
í
as
</
td
>
<
td
>
124
,
138
,
402
,
292
</
td
>
<
td
>
209
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1
</
td
>
<
td
>
4
,
5
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
EU
-
top
í
as
</
td
>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
1341
</
td
>
<
td
>
998
</
td
>
<
td
>
0022
-
3468
</
td
>
<
td
>
0022
-
3468
</
td
>
<
td
>
Journal
of
pediatric
surgery
(
Print
)</
td
>
<
td
>
1966
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.jpedsurg.org</td>
<
td
>
J
.
pediatr
.
surg
.
(
Print
)</
td
>
<
td
>
124
</
td
>
<
td
>
236
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
preserved
</
td
>
<
td
>
1.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1
</
td
>
<
td
>
75
</
td
>
<
td
>
Journal
of
Pediatric
Surgery
</
td
>
<
td
>
http
:
//www.jpedsurg.org/</td>
<
td
>
http
:
//www.jpedsurg.org/</td>
<
td
>
Journal
of
Pediatric
Surgery
</
td
>
</
tr
>
<
tr
>
<
td
>
1342
</
td
>
<
td
>
999
</
td
>
<
td
>
1432
-
2064
</
td
>
<
td
>
0178
-
8051
</
td
>
<
td
>
Probability
theory
and
related
fields
(
Internet
)</
td
>
<
td
>
uuuu
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.springerlink.com/content/100451</td>
<
td
>
Probab
.
theory
relat
.
fields
(
Internet
)</
td
>
<
td
>
124
</
td
>
<
td
>
83
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
Probability
Theory
and
Related
Fields
</
td
>
<
td
>
1.0
</
td
>
<
td
>
preserved
</
td
>
<
td
>
1.0
</
td
>
<
td
>
Probability
Theory
and
Related
Fields
</
td
>
<
td
>
1.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1
</
td
>
<
td
>
8
</
td
>
<
td
>
Probability
Theory
and
Related
Fields
</
td
>
<
td
>
http
:
//www.springerlink.com/content/100451/?p=...</td>
<
td
>
http
:
//www.springerlink.com/content/100451/?p=...</td>
<
td
>
Probability
Theory
and
Related
Fields
</
td
>
</
tr
>
<
tr
>
<
td
>
1343
</
td
>
<
td
>
999
</
td
>
<
td
>
1432
-
2064
</
td
>
<
td
>
0178
-
8051
</
td
>
<
td
>
Probability
theory
and
related
fields
(
Internet
)</
td
>
<
td
>
uuuu
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.springerlink.com/content/100451</td>
<
td
>
Probab
.
theory
relat
.
fields
(
Internet
)</
td
>
<
td
>
124
</
td
>
<
td
>
83
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
Probability
Theory
and
Related
Fields
</
td
>
<
td
>
1.0
</
td
>
<
td
>
preserved
</
td
>
<
td
>
1.0
</
td
>
<
td
>
Probability
Theory
and
Related
Fields
</
td
>
<
td
>
1.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1
</
td
>
<
td
>
8
</
td
>
<
td
>
Probability
Theory
and
Related
Fields
</
td
>
<
td
>
http
:
//www.springerlink.com/content/100451/?p=...</td>
<
td
>
http
:
//www.springerlink.com/content/100451/?p=...</td>
<
td
>
Probability
Theory
and
Related
Fields
</
td
>
</
tr
>
<
tr
>
<
td
>
1344
</
td
>
<
td
>
1000
</
td
>
<
td
>
0960
-
1481
</
td
>
<
td
>
0960
-
1481
</
td
>
<
td
>
Renewable
energy
</
td
>
<
td
>
1991
</
td
>
<
td
>
9999
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Renew
.
energy
</
td
>
<
td
>
124
</
td
>
<
td
>
234
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
preserved
</
td
>
<
td
>
1.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1
</
td
>
<
td
>
119
</
td
>
<
td
>
Renewable
Energy
</
td
>
<
td
>
http
:
//www.elsevier.com/wps/product/cws_home/9...</td>
<
td
>
http
:
//www.elsevier.com/wps/product/cws_home/9...</td>
<
td
>
Renewable
Energy
</
td
>
</
tr
>
<
tr
>
<
td
>
1345
</
td
>
<
td
>
1001
</
td
>
<
td
>
0161
-
7567
</
td
>
<
td
>
0161
-
7567
</
td
>
<
td
>
Journal
of
applied
physiology
:
respiratory
,
en
...</
td
>
<
td
>
1977
</
td
>
<
td
>
1984
</
td
>
<
td
>
https
:
//www.physiology.org/journal/jappl</td>
<
td
>
J
.
appl
.
physiol
.:
respir
.,
environ
.
exercise
...</
td
>
<
td
>
124
</
td
>
<
td
>
236
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1
</
td
>
<
td
>
217
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
https
:
//www.physiology.org/journal/jappl</td>
<
td
>
Journal
of
applied
physiology
:
respiratory
,
en
...</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
1346
rows
×
28
columns
</
p
>
</
div
>
```
python
journals_export
=
journal
[[
'
id
'
,
'
title
'
,
'
name_short_iso_4
'
,
'
starting_year
'
,
'
end_year
'
,
'
url
'
,
'
country
'
,
'
language
'
,
'
oa_status
'
,
'
publisher
'
,
'
doaj_seal
'
,
'
doaj_status
'
,
'
lockss
'
,
'
portico
'
,
'
nlch
'
,
'
qoam_av_score
'
]]
journals_export
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
id
</
th
>
<
th
>
title
</
th
>
<
th
>
name_short_iso_4
</
th
>
<
th
>
starting_year
</
th
>
<
th
>
end_year
</
th
>
<
th
>
url
</
th
>
<
th
>
country
</
th
>
<
th
>
language
</
th
>
<
th
>
oa_status
</
th
>
<
th
>
publisher
</
th
>
<
th
>
doaj_seal
</
th
>
<
th
>
doaj_status
</
th
>
<
th
>
lockss
</
th
>
<
th
>
portico
</
th
>
<
th
>
nlch
</
th
>
<
th
>
qoam_av_score
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
Revue
m
é
dicale
suisse
</
td
>
<
td
>
Rev
.
m
é
d
.
suisse
</
td
>
<
td
>
2005
</
td
>
<
td
>
9999
</
td
>
<
td
>
NaN
</
td
>
<
td
>
215
</
td
>
<
td
>
138
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
0.0
</
td
>
<
td
>
0.0
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
2
</
td
>
<
td
>
Physical
Review
Letters
</
td
>
<
td
>
Phys
.
rev
.
lett
.
(
Print
)</
td
>
<
td
>
1958
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//prl.aps.org/</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
2
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
0.0
</
td
>
<
td
>
1.0
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
2
</
td
>
<
td
>
Physical
Review
Letters
</
td
>
<
td
>
Phys
.
rev
.
lett
.
(
Print
)</
td
>
<
td
>
1958
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//prl.aps.org/</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
2
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
0.0
</
td
>
<
td
>
1.0
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
3
</
td
>
<
td
>
PLoS
ONE
</
td
>
<
td
>
NaN
</
td
>
<
td
>
2006
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.plosone.org/</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
5
</
td
>
<
td
>
3
</
td
>
<
td
>
1.0
</
td
>
<
td
>
1.0
</
td
>
<
td
>
1.0
</
td
>
<
td
>
0.0
</
td
>
<
td
>
0.0
</
td
>
<
td
>
4.035714
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
4
</
td
>
<
td
>
EU
-
top
í
as
</
td
>
<
td
>
EU
-
top
í
as
</
td
>
<
td
>
2011
</
td
>
<
td
>
9999
</
td
>
<
td
>
NaN
</
td
>
<
td
>
209
</
td
>
<
td
>
124
,
138
,
402
,
292
</
td
>
<
td
>
1
</
td
>
<
td
>
4
,
5
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
0.0
</
td
>
<
td
>
0.0
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
1341
</
td
>
<
td
>
998
</
td
>
<
td
>
Journal
of
Pediatric
Surgery
</
td
>
<
td
>
J
.
pediatr
.
surg
.
(
Print
)</
td
>
<
td
>
1966
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.jpedsurg.org/</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
75
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
0.0
</
td
>
<
td
>
1.0
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
1342
</
td
>
<
td
>
999
</
td
>
<
td
>
Probability
Theory
and
Related
Fields
</
td
>
<
td
>
Probab
.
theory
relat
.
fields
(
Internet
)</
td
>
<
td
>
uuuu
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.springerlink.com/content/100451/?p=...</td>
<
td
>
83
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
8
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
1.0
</
td
>
<
td
>
1.0
</
td
>
<
td
>
1.0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
1343
</
td
>
<
td
>
999
</
td
>
<
td
>
Probability
Theory
and
Related
Fields
</
td
>
<
td
>
Probab
.
theory
relat
.
fields
(
Internet
)</
td
>
<
td
>
uuuu
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.springerlink.com/content/100451/?p=...</td>
<
td
>
83
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
8
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
1.0
</
td
>
<
td
>
1.0
</
td
>
<
td
>
1.0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
1344
</
td
>
<
td
>
1000
</
td
>
<
td
>
Renewable
Energy
</
td
>
<
td
>
Renew
.
energy
</
td
>
<
td
>
1991
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.elsevier.com/wps/product/cws_home/9...</td>
<
td
>
234
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
119
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
0.0
</
td
>
<
td
>
1.0
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
1345
</
td
>
<
td
>
1001
</
td
>
<
td
>
Journal
of
applied
physiology
:
respiratory
,
en
...</
td
>
<
td
>
J
.
appl
.
physiol
.:
respir
.,
environ
.
exercise
...</
td
>
<
td
>
1977
</
td
>
<
td
>
1984
</
td
>
<
td
>
https
:
//www.physiology.org/journal/jappl</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
217
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0.0
</
td
>
<
td
>
0.0
</
td
>
<
td
>
0.0
</
td
>
<
td
>
0.0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
1346
rows
×
16
columns
</
p
>
</
div
>
```
python
#
renommage
des
champs
finaux
journals_export
=
journals_export
.
rename
(
columns
={
'
title
'
:
'
name
'
,
'
url
'
:
'
website
'
})
#
remplacement
des
vides
et
id
à
int
journals_export
[
'
starting_year
'
]
=
journals_export
[
'
starting_year
'
].
fillna
(
0
)
journals_export
[
'
end_year
'
]
=
journals_export
[
'
end_year
'
].
fillna
(
9999
)
journals_export
[
'
name_short_iso_4
'
]
=
journals_export
[
'
name_short_iso_4
'
].
fillna
(
''
)
journals_export
[
'
website
'
]
=
journals_export
[
'
website
'
].
fillna
(
''
)
journals_export
[
'
doaj_seal
'
]
=
journals_export
[
'
doaj_seal
'
].
fillna
(
'0'
)
journals_export
[
'
country
'
]
=
journals_export
[
'
country
'
].
fillna
(
'
999999
'
)
journals_export
[
'
language
'
]
=
journals_export
[
'
language
'
].
fillna
(
'
999999
'
)
journals_export
[
'
doaj_status
'
]
=
journals_export
[
'
doaj_status
'
].
astype
(
int
)
journals_export
[
'
doaj_seal
'
]
=
journals_export
[
'
doaj_seal
'
].
astype
(
int
)
journals_export
[
'
lockss
'
]
=
journals_export
[
'
lockss
'
].
astype
(
int
)
journals_export
[
'
portico
'
]
=
journals_export
[
'
portico
'
].
astype
(
int
)
journals_export
[
'
nlch
'
]
=
journals_export
[
'
nlch
'
].
astype
(
int
)
journals_export
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
id
</
th
>
<
th
>
name
</
th
>
<
th
>
name_short_iso_4
</
th
>
<
th
>
starting_year
</
th
>
<
th
>
end_year
</
th
>
<
th
>
website
</
th
>
<
th
>
country
</
th
>
<
th
>
language
</
th
>
<
th
>
oa_status
</
th
>
<
th
>
publisher
</
th
>
<
th
>
doaj_seal
</
th
>
<
th
>
doaj_status
</
th
>
<
th
>
lockss
</
th
>
<
th
>
portico
</
th
>
<
th
>
nlch
</
th
>
<
th
>
qoam_av_score
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
Revue
m
é
dicale
suisse
</
td
>
<
td
>
Rev
.
m
é
d
.
suisse
</
td
>
<
td
>
2005
</
td
>
<
td
>
9999
</
td
>
<
td
></
td
>
<
td
>
215
</
td
>
<
td
>
138
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
2
</
td
>
<
td
>
Physical
Review
Letters
</
td
>
<
td
>
Phys
.
rev
.
lett
.
(
Print
)</
td
>
<
td
>
1958
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//prl.aps.org/</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
2
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
2
</
td
>
<
td
>
Physical
Review
Letters
</
td
>
<
td
>
Phys
.
rev
.
lett
.
(
Print
)</
td
>
<
td
>
1958
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//prl.aps.org/</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
2
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
3
</
td
>
<
td
>
PLoS
ONE
</
td
>
<
td
></
td
>
<
td
>
2006
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.plosone.org/</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
5
</
td
>
<
td
>
3
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
4.035714
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
4
</
td
>
<
td
>
EU
-
top
í
as
</
td
>
<
td
>
EU
-
top
í
as
</
td
>
<
td
>
2011
</
td
>
<
td
>
9999
</
td
>
<
td
></
td
>
<
td
>
209
</
td
>
<
td
>
124
,
138
,
402
,
292
</
td
>
<
td
>
1
</
td
>
<
td
>
4
,
5
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
1341
</
td
>
<
td
>
998
</
td
>
<
td
>
Journal
of
Pediatric
Surgery
</
td
>
<
td
>
J
.
pediatr
.
surg
.
(
Print
)</
td
>
<
td
>
1966
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.jpedsurg.org/</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
75
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
1342
</
td
>
<
td
>
999
</
td
>
<
td
>
Probability
Theory
and
Related
Fields
</
td
>
<
td
>
Probab
.
theory
relat
.
fields
(
Internet
)</
td
>
<
td
>
uuuu
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.springerlink.com/content/100451/?p=...</td>
<
td
>
83
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
8
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
1343
</
td
>
<
td
>
999
</
td
>
<
td
>
Probability
Theory
and
Related
Fields
</
td
>
<
td
>
Probab
.
theory
relat
.
fields
(
Internet
)</
td
>
<
td
>
uuuu
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.springerlink.com/content/100451/?p=...</td>
<
td
>
83
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
8
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
1344
</
td
>
<
td
>
1000
</
td
>
<
td
>
Renewable
Energy
</
td
>
<
td
>
Renew
.
energy
</
td
>
<
td
>
1991
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.elsevier.com/wps/product/cws_home/9...</td>
<
td
>
234
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
119
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
1345
</
td
>
<
td
>
1001
</
td
>
<
td
>
Journal
of
applied
physiology
:
respiratory
,
en
...</
td
>
<
td
>
J
.
appl
.
physiol
.:
respir
.,
environ
.
exercise
...</
td
>
<
td
>
1977
</
td
>
<
td
>
1984
</
td
>
<
td
>
https
:
//www.physiology.org/journal/jappl</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
217
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
1346
rows
×
16
columns
</
p
>
</
div
>
```
python
journals_export
=
journals_export
.
drop_duplicates
(
subset
=
'
id
'
)
journals_export
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
id
</
th
>
<
th
>
name
</
th
>
<
th
>
name_short_iso_4
</
th
>
<
th
>
starting_year
</
th
>
<
th
>
end_year
</
th
>
<
th
>
website
</
th
>
<
th
>
country
</
th
>
<
th
>
language
</
th
>
<
th
>
oa_status
</
th
>
<
th
>
publisher
</
th
>
<
th
>
doaj_seal
</
th
>
<
th
>
doaj_status
</
th
>
<
th
>
lockss
</
th
>
<
th
>
portico
</
th
>
<
th
>
nlch
</
th
>
<
th
>
qoam_av_score
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
Revue
m
é
dicale
suisse
</
td
>
<
td
>
Rev
.
m
é
d
.
suisse
</
td
>
<
td
>
2005
</
td
>
<
td
>
9999
</
td
>
<
td
></
td
>
<
td
>
215
</
td
>
<
td
>
138
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
2
</
td
>
<
td
>
Physical
Review
Letters
</
td
>
<
td
>
Phys
.
rev
.
lett
.
(
Print
)</
td
>
<
td
>
1958
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//prl.aps.org/</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
2
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
3
</
td
>
<
td
>
PLoS
ONE
</
td
>
<
td
></
td
>
<
td
>
2006
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.plosone.org/</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
5
</
td
>
<
td
>
3
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
4.035714
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
4
</
td
>
<
td
>
EU
-
top
í
as
</
td
>
<
td
>
EU
-
top
í
as
</
td
>
<
td
>
2011
</
td
>
<
td
>
9999
</
td
>
<
td
></
td
>
<
td
>
209
</
td
>
<
td
>
124
,
138
,
402
,
292
</
td
>
<
td
>
1
</
td
>
<
td
>
4
,
5
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
5
</
td
>
<
td
>
5
</
td
>
<
td
>
Physical
review
B
:
Condensed
matter
and
materi
...</
td
>
<
td
>
Phys
.
rev
.,
B
,
Condens
.
matter
mater
.
phys
.</
td
>
<
td
>
1998
</
td
>
<
td
>
2015
</
td
>
<
td
>
http
:
//journals.aps.org/prb/</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
6
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
1339
</
td
>
<
td
>
997
</
td
>
<
td
>
Smart
Materials
and
Structures
</
td
>
<
td
>
Smart
mater
.
struct
.
(
Print
)</
td
>
<
td
>
1992
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//iopscience.iop.org/0964-1726</td>
<
td
>
234
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
47
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
1341
</
td
>
<
td
>
998
</
td
>
<
td
>
Journal
of
Pediatric
Surgery
</
td
>
<
td
>
J
.
pediatr
.
surg
.
(
Print
)</
td
>
<
td
>
1966
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.jpedsurg.org/</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
75
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
1342
</
td
>
<
td
>
999
</
td
>
<
td
>
Probability
Theory
and
Related
Fields
</
td
>
<
td
>
Probab
.
theory
relat
.
fields
(
Internet
)</
td
>
<
td
>
uuuu
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.springerlink.com/content/100451/?p=...</td>
<
td
>
83
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
8
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
1344
</
td
>
<
td
>
1000
</
td
>
<
td
>
Renewable
Energy
</
td
>
<
td
>
Renew
.
energy
</
td
>
<
td
>
1991
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.elsevier.com/wps/product/cws_home/9...</td>
<
td
>
234
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
119
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
1345
</
td
>
<
td
>
1001
</
td
>
<
td
>
Journal
of
applied
physiology
:
respiratory
,
en
...</
td
>
<
td
>
J
.
appl
.
physiol
.:
respir
.,
environ
.
exercise
...</
td
>
<
td
>
1977
</
td
>
<
td
>
1984
</
td
>
<
td
>
https
:
//www.physiology.org/journal/jappl</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
217
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
911
rows
×
16
columns
</
p
>
</
div
>
```
python
#
test
journaux
sans
titre
journals_export
.
loc
[
journals_export
[
'
name
'
].
isna
()]
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
id
</
th
>
<
th
>
name
</
th
>
<
th
>
name_short_iso_4
</
th
>
<
th
>
starting_year
</
th
>
<
th
>
end_year
</
th
>
<
th
>
website
</
th
>
<
th
>
country
</
th
>
<
th
>
language
</
th
>
<
th
>
oa_status
</
th
>
<
th
>
publisher
</
th
>
<
th
>
doaj_seal
</
th
>
<
th
>
doaj_status
</
th
>
<
th
>
lockss
</
th
>
<
th
>
portico
</
th
>
<
th
>
nlch
</
th
>
<
th
>
qoam_av_score
</
th
>
</
tr
>
</
thead
>
<
tbody
>
</
tbody
>
</
table
>
</
div
>
```
python
#
export
et
suppression
des
journaux
sans
titre
#
export
csv
journals_export
.
loc
[
journals_export
[
'
name
'
].
isna
()].
to_csv
(
'
sample
/
sherpa_journals_without_title
.
tsv
'
,
sep
=
'\t'
,
encoding
=
'
utf
-
8
'
,
index
=
False
)
#
export
excel
journals_export
.
loc
[
journals_export
[
'
name
'
].
isna
()].
to_excel
(
'
sample
/
sherpa_journals_without_title
.
xlsx
'
,
index
=
False
)
journals_export
=
journals_export
.
loc
[
journals_export
[
'
name
'
].
notna
()]
journals_export
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
id
</
th
>
<
th
>
name
</
th
>
<
th
>
name_short_iso_4
</
th
>
<
th
>
starting_year
</
th
>
<
th
>
end_year
</
th
>
<
th
>
website
</
th
>
<
th
>
country
</
th
>
<
th
>
language
</
th
>
<
th
>
oa_status
</
th
>
<
th
>
publisher
</
th
>
<
th
>
doaj_seal
</
th
>
<
th
>
doaj_status
</
th
>
<
th
>
lockss
</
th
>
<
th
>
portico
</
th
>
<
th
>
nlch
</
th
>
<
th
>
qoam_av_score
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
Revue
m
é
dicale
suisse
</
td
>
<
td
>
Rev
.
m
é
d
.
suisse
</
td
>
<
td
>
2005
</
td
>
<
td
>
9999
</
td
>
<
td
></
td
>
<
td
>
215
</
td
>
<
td
>
138
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
2
</
td
>
<
td
>
Physical
Review
Letters
</
td
>
<
td
>
Phys
.
rev
.
lett
.
(
Print
)</
td
>
<
td
>
1958
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//prl.aps.org/</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
2
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
3
</
td
>
<
td
>
PLoS
ONE
</
td
>
<
td
></
td
>
<
td
>
2006
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.plosone.org/</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
5
</
td
>
<
td
>
3
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
4.035714
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
4
</
td
>
<
td
>
EU
-
top
í
as
</
td
>
<
td
>
EU
-
top
í
as
</
td
>
<
td
>
2011
</
td
>
<
td
>
9999
</
td
>
<
td
></
td
>
<
td
>
209
</
td
>
<
td
>
124
,
138
,
402
,
292
</
td
>
<
td
>
1
</
td
>
<
td
>
4
,
5
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
5
</
td
>
<
td
>
5
</
td
>
<
td
>
Physical
review
B
:
Condensed
matter
and
materi
...</
td
>
<
td
>
Phys
.
rev
.,
B
,
Condens
.
matter
mater
.
phys
.</
td
>
<
td
>
1998
</
td
>
<
td
>
2015
</
td
>
<
td
>
http
:
//journals.aps.org/prb/</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
6
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
1339
</
td
>
<
td
>
997
</
td
>
<
td
>
Smart
Materials
and
Structures
</
td
>
<
td
>
Smart
mater
.
struct
.
(
Print
)</
td
>
<
td
>
1992
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//iopscience.iop.org/0964-1726</td>
<
td
>
234
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
47
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
1341
</
td
>
<
td
>
998
</
td
>
<
td
>
Journal
of
Pediatric
Surgery
</
td
>
<
td
>
J
.
pediatr
.
surg
.
(
Print
)</
td
>
<
td
>
1966
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.jpedsurg.org/</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
75
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
1342
</
td
>
<
td
>
999
</
td
>
<
td
>
Probability
Theory
and
Related
Fields
</
td
>
<
td
>
Probab
.
theory
relat
.
fields
(
Internet
)</
td
>
<
td
>
uuuu
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.springerlink.com/content/100451/?p=...</td>
<
td
>
83
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
8
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
1344
</
td
>
<
td
>
1000
</
td
>
<
td
>
Renewable
Energy
</
td
>
<
td
>
Renew
.
energy
</
td
>
<
td
>
1991
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.elsevier.com/wps/product/cws_home/9...</td>
<
td
>
234
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
119
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
1345
</
td
>
<
td
>
1001
</
td
>
<
td
>
Journal
of
applied
physiology
:
respiratory
,
en
...</
td
>
<
td
>
J
.
appl
.
physiol
.:
respir
.,
environ
.
exercise
...</
td
>
<
td
>
1977
</
td
>
<
td
>
1984
</
td
>
<
td
>
https
:
//www.physiology.org/journal/jappl</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
217
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
911
rows
×
16
columns
</
p
>
</
div
>
```
python
journals_export
.
loc
[
journals_export
[
'
name
'
].
str
.
contains
(
'
(
Print
)
'
)]
```
C
:\
Users
\
iriarte
\
AppData
\
Local
\
Continuum
\
anaconda3
\
lib
\
site
-
packages
\
pandas
\
core
\
strings
.
py
:
1843
:
UserWarning
:
This
pattern
has
match
groups
.
To
actually
get
the
groups
,
use
str
.
extract
.
return
func
(
self
,
*
args
,
**
kwargs
)
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
id
</
th
>
<
th
>
name
</
th
>
<
th
>
name_short_iso_4
</
th
>
<
th
>
starting_year
</
th
>
<
th
>
end_year
</
th
>
<
th
>
website
</
th
>
<
th
>
country
</
th
>
<
th
>
language
</
th
>
<
th
>
oa_status
</
th
>
<
th
>
publisher
</
th
>
<
th
>
doaj_seal
</
th
>
<
th
>
doaj_status
</
th
>
<
th
>
lockss
</
th
>
<
th
>
portico
</
th
>
<
th
>
nlch
</
th
>
<
th
>
qoam_av_score
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
86
</
td
>
<
td
>
54
</
td
>
<
td
>
Helvetica
physica
acta
(
Print
)</
td
>
<
td
>
Helv
.
phys
.
acta
(
Print
)</
td
>
<
td
>
1928
</
td
>
<
td
>
1999
</
td
>
<
td
></
td
>
<
td
>
215
</
td
>
<
td
>
124
,
138
,
151
</
td
>
<
td
>
1
</
td
>
<
td
>
41
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
239
</
td
>
<
td
>
155
</
td
>
<
td
>
Studies
in
health
technology
and
informatics
(...</
td
>
<
td
>
Stud
.
health
technol
.
inform
.
(
Print
)</
td
>
<
td
>
1991
</
td
>
<
td
>
9999
</
td
>
<
td
></
td
>
<
td
>
156
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
90
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
441
</
td
>
<
td
>
306
</
td
>
<
td
>
Bioethica
Forum
(
Basel
.
2008
.
Print
)</
td
>
<
td
>
Bioeth
.
Forum
(
Basel
,
2008
,
Print
)</
td
>
<
td
>
2008
</
td
>
<
td
>
9999
</
td
>
<
td
></
td
>
<
td
>
215
</
td
>
<
td
>
138
,
124
,
151
</
td
>
<
td
>
1
</
td
>
<
td
>
143
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
534
</
td
>
<
td
>
373
</
td
>
<
td
>
Schweizerische
Ä
rztezeitung
(
Print
)</
td
>
<
td
>
Schweiz
.
Ä
rzteztg
.
(
Print
)</
td
>
<
td
>
1952
</
td
>
<
td
>
9999
</
td
>
<
td
></
td
>
<
td
>
215
</
td
>
<
td
>
203
,
151
,
138
</
td
>
<
td
>
1
</
td
>
<
td
>
170
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
601
</
td
>
<
td
>
430
</
td
>
<
td
>
The
European
physical
journal
.
B
,
Condensed
ma
...</
td
>
<
td
>
Eur
.
phys
.
j
.,
B
Cond
.
matter
phys
.
(
Print
)</
td
>
<
td
>
1998
</
td
>
<
td
>
9999
</
td
>
<
td
></
td
>
<
td
>
76
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
195
,
43
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
1.25
</
td
>
</
tr
>
<
tr
>
<
td
>
650
</
td
>
<
td
>
467
</
td
>
<
td
>
Conference
on
Lasers
and
Electro
-
optics
(
Print
)</
td
>
<
td
>
Conf
.
Lasers
Electro
-
opt
.
(
Print
)</
td
>
<
td
>
2003
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.cleoconference.org/</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
39
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
850
</
td
>
<
td
>
618
</
td
>
<
td
>
Swiss
archives
of
neurology
,
psychiatry
and
ps
...</
td
>
<
td
>
Swiss
arch
.
neurol
.
psychiatry
psychother
.
(
Pr
...</
td
>
<
td
>
2016
</
td
>
<
td
>
9999
</
td
>
<
td
></
td
>
<
td
>
215
</
td
>
<
td
>
151
,
124
,
138
</
td
>
<
td
>
6
</
td
>
<
td
>
20
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
901
</
td
>
<
td
>
660
</
td
>
<
td
>
Journal
der
Deutschen
Dermatologischen
Gesells
...</
td
>
<
td
></
td
>
<
td
>
2003
</
td
>
<
td
>
9999
</
td
>
<
td
></
td
>
<
td
>
234
</
td
>
<
td
>
151
,
124
</
td
>
<
td
>
1
</
td
>
<
td
>
283
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
957
</
td
>
<
td
>
702
</
td
>
<
td
>
IEEE
/
LEOS
International
Conference
on
Optical
...</
td
>
<
td
>
IEEE
/
LEOS
Int
.
Conf
.
Opt
.
MEMS
Nanophotonics
(...</
td
>
<
td
>
2007
</
td
>
<
td
>
20
uu
</
td
>
<
td
>
http
:
//ieeexplore.ieee.org/xpl/conhome.jsp?pun...</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
280
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
1104
</
td
>
<
td
>
814
</
td
>
<
td
>
Forumpoenale
(
Print
)</
td
>
<
td
>
Forumpoenale
(
Print
)</
td
>
<
td
>
2008
</
td
>
<
td
>
9999
</
td
>
<
td
></
td
>
<
td
>
215
</
td
>
<
td
>
151
,
203
,
138
</
td
>
<
td
>
1
</
td
>
<
td
>
204
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
1182
</
td
>
<
td
>
877
</
td
>
<
td
>
Gesnerus
(
Print
)</
td
>
<
td
>
Gesnerus
(
Print
)</
td
>
<
td
>
1943
</
td
>
<
td
>
9999
</
td
>
<
td
></
td
>
<
td
>
215
</
td
>
<
td
>
124
,
138
,
151
,
203
</
td
>
<
td
>
1
</
td
>
<
td
>
143
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
1336
</
td
>
<
td
>
994
</
td
>
<
td
>
GG
@
G
(
Print
)</
td
>
<
td
>
GG
@
G
(
Print
)</
td
>
<
td
>
2000
</
td
>
<
td
>
9999
</
td
>
<
td
></
td
>
<
td
>
215
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
380
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
</
tbody
>
</
table
>
</
div
>
```
python
journals_export
.
loc
[
journals_export
[
'
name
'
].
str
.
contains
(
'
(
Online
)
'
)]
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
id
</
th
>
<
th
>
name
</
th
>
<
th
>
name_short_iso_4
</
th
>
<
th
>
starting_year
</
th
>
<
th
>
end_year
</
th
>
<
th
>
website
</
th
>
<
th
>
country
</
th
>
<
th
>
language
</
th
>
<
th
>
oa_status
</
th
>
<
th
>
publisher
</
th
>
<
th
>
doaj_seal
</
th
>
<
th
>
doaj_status
</
th
>
<
th
>
lockss
</
th
>
<
th
>
portico
</
th
>
<
th
>
nlch
</
th
>
<
th
>
qoam_av_score
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
1257
</
td
>
<
td
>
936
</
td
>
<
td
>
Plastic
and
reconstructive
surgery
(
Online
)</
td
>
<
td
>
Plast
.
reconstr
.
surg
.
(
Online
)</
td
>
<
td
>
1963
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//gateway.ovid.com/ovidweb.cgi?T=JS&MODE=...</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
363
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
</
tbody
>
</
table
>
</
div
>
```
python
#
remplacement
des
mentions
" (Print)"
et
" (Online)"
dans
les
titres
journals_export
[
'
name
'
]
=
journals_export
[
'
name
'
].
str
.
replace
(
'
(
Print
)
'
,
''
)
journals_export
[
'
name
'
]
=
journals_export
[
'
name
'
].
str
.
replace
(
'
(
Online
)
'
,
''
)
journals_export
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
id
</
th
>
<
th
>
name
</
th
>
<
th
>
name_short_iso_4
</
th
>
<
th
>
starting_year
</
th
>
<
th
>
end_year
</
th
>
<
th
>
website
</
th
>
<
th
>
country
</
th
>
<
th
>
language
</
th
>
<
th
>
oa_status
</
th
>
<
th
>
publisher
</
th
>
<
th
>
doaj_seal
</
th
>
<
th
>
doaj_status
</
th
>
<
th
>
lockss
</
th
>
<
th
>
portico
</
th
>
<
th
>
nlch
</
th
>
<
th
>
qoam_av_score
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
Revue
m
é
dicale
suisse
</
td
>
<
td
>
Rev
.
m
é
d
.
suisse
</
td
>
<
td
>
2005
</
td
>
<
td
>
9999
</
td
>
<
td
></
td
>
<
td
>
215
</
td
>
<
td
>
138
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
2
</
td
>
<
td
>
Physical
Review
Letters
</
td
>
<
td
>
Phys
.
rev
.
lett
.
(
Print
)</
td
>
<
td
>
1958
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//prl.aps.org/</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
2
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
3
</
td
>
<
td
>
PLoS
ONE
</
td
>
<
td
></
td
>
<
td
>
2006
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.plosone.org/</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
5
</
td
>
<
td
>
3
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
4.035714
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
4
</
td
>
<
td
>
EU
-
top
í
as
</
td
>
<
td
>
EU
-
top
í
as
</
td
>
<
td
>
2011
</
td
>
<
td
>
9999
</
td
>
<
td
></
td
>
<
td
>
209
</
td
>
<
td
>
124
,
138
,
402
,
292
</
td
>
<
td
>
1
</
td
>
<
td
>
4
,
5
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
5
</
td
>
<
td
>
5
</
td
>
<
td
>
Physical
review
B
:
Condensed
matter
and
materi
...</
td
>
<
td
>
Phys
.
rev
.,
B
,
Condens
.
matter
mater
.
phys
.</
td
>
<
td
>
1998
</
td
>
<
td
>
2015
</
td
>
<
td
>
http
:
//journals.aps.org/prb/</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
6
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
1339
</
td
>
<
td
>
997
</
td
>
<
td
>
Smart
Materials
and
Structures
</
td
>
<
td
>
Smart
mater
.
struct
.
(
Print
)</
td
>
<
td
>
1992
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//iopscience.iop.org/0964-1726</td>
<
td
>
234
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
47
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
1341
</
td
>
<
td
>
998
</
td
>
<
td
>
Journal
of
Pediatric
Surgery
</
td
>
<
td
>
J
.
pediatr
.
surg
.
(
Print
)</
td
>
<
td
>
1966
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.jpedsurg.org/</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
75
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
1342
</
td
>
<
td
>
999
</
td
>
<
td
>
Probability
Theory
and
Related
Fields
</
td
>
<
td
>
Probab
.
theory
relat
.
fields
(
Internet
)</
td
>
<
td
>
uuuu
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.springerlink.com/content/100451/?p=...</td>
<
td
>
83
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
8
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
1344
</
td
>
<
td
>
1000
</
td
>
<
td
>
Renewable
Energy
</
td
>
<
td
>
Renew
.
energy
</
td
>
<
td
>
1991
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.elsevier.com/wps/product/cws_home/9...</td>
<
td
>
234
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
119
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
1345
</
td
>
<
td
>
1001
</
td
>
<
td
>
Journal
of
applied
physiology
:
respiratory
,
en
...</
td
>
<
td
>
J
.
appl
.
physiol
.:
respir
.,
environ
.
exercise
...</
td
>
<
td
>
1977
</
td
>
<
td
>
1984
</
td
>
<
td
>
https
:
//www.physiology.org/journal/jappl</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
217
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
911
rows
×
16
columns
</
p
>
</
div
>
```
python
journals_export
.
loc
[
journals_export
[
'
name
'
].
str
.
contains
(
'
(
Print
)
'
)]
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
id
</
th
>
<
th
>
name
</
th
>
<
th
>
name_short_iso_4
</
th
>
<
th
>
starting_year
</
th
>
<
th
>
end_year
</
th
>
<
th
>
website
</
th
>
<
th
>
country
</
th
>
<
th
>
language
</
th
>
<
th
>
oa_status
</
th
>
<
th
>
publisher
</
th
>
<
th
>
doaj_seal
</
th
>
<
th
>
doaj_status
</
th
>
<
th
>
lockss
</
th
>
<
th
>
portico
</
th
>
<
th
>
nlch
</
th
>
<
th
>
qoam_av_score
</
th
>
</
tr
>
</
thead
>
<
tbody
>
</
tbody
>
</
table
>
</
div
>
```
python
journals_export
.
loc
[
journals_export
[
'
name
'
].
str
.
contains
(
'
(
Online
)
'
)]
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
id
</
th
>
<
th
>
name
</
th
>
<
th
>
name_short_iso_4
</
th
>
<
th
>
starting_year
</
th
>
<
th
>
end_year
</
th
>
<
th
>
website
</
th
>
<
th
>
country
</
th
>
<
th
>
language
</
th
>
<
th
>
oa_status
</
th
>
<
th
>
publisher
</
th
>
<
th
>
doaj_seal
</
th
>
<
th
>
doaj_status
</
th
>
<
th
>
lockss
</
th
>
<
th
>
portico
</
th
>
<
th
>
nlch
</
th
>
<
th
>
qoam_av_score
</
th
>
</
tr
>
</
thead
>
<
tbody
>
</
tbody
>
</
table
>
</
div
>
##
Table
sherpa_policies
```
python
#
creation
du
DF
col_names
=
[
'
journal
'
,
'
issn
'
,
'
sherpa_id
'
,
'
sherpa_uri
'
,
'
open_access_prohibited
'
,
'
additional_oa_fee
'
,
'
article_version
'
,
'
license
'
,
'
embargo
'
,
'
prerequisites
'
,
'
prerequisite_funders
'
,
'
prerequisite_funders_name
'
,
'
prerequisite_funders_fundref
'
,
'
prerequisite_funders_ror
'
,
'
prerequisite_funders_country
'
,
'
prerequisite_funders_url
'
,
'
prerequisite_funders_sherpa_id
'
,
'
prerequisite_subjects
'
,
'
location
'
,
'
locations_ir
'
,
'
locations_not_ir
'
,
'
named_repository
'
,
'
named_academic_social_network
'
,
'
copyright_owner
'
,
'
publisher_deposit
'
,
'
archiving
'
,
'
conditions
'
,
'
public_notes
'
]
sherpa_policies
=
pd
.
DataFrame
(
columns
=
col_names
)
sherpa_policies
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
journal
</
th
>
<
th
>
issn
</
th
>
<
th
>
sherpa_id
</
th
>
<
th
>
sherpa_uri
</
th
>
<
th
>
open_access_prohibited
</
th
>
<
th
>
additional_oa_fee
</
th
>
<
th
>
article_version
</
th
>
<
th
>
license
</
th
>
<
th
>
embargo
</
th
>
<
th
>
prerequisites
</
th
>
<
th
>
prerequisite_funders
</
th
>
<
th
>
prerequisite_funders_name
</
th
>
<
th
>
prerequisite_funders_fundref
</
th
>
<
th
>
prerequisite_funders_ror
</
th
>
<
th
>
prerequisite_funders_country
</
th
>
<
th
>
prerequisite_funders_url
</
th
>
<
th
>
prerequisite_funders_sherpa_id
</
th
>
<
th
>
prerequisite_subjects
</
th
>
<
th
>
location
</
th
>
<
th
>
locations_ir
</
th
>
<
th
>
locations_not_ir
</
th
>
<
th
>
named_repository
</
th
>
<
th
>
named_academic_social_network
</
th
>
<
th
>
copyright_owner
</
th
>
<
th
>
publisher_deposit
</
th
>
<
th
>
archiving
</
th
>
<
th
>
conditions
</
th
>
<
th
>
public_notes
</
th
>
</
tr
>
</
thead
>
<
tbody
>
</
tbody
>
</
table
>
</
div
>
```
python
#
d
é
doublonage
par
journal
id
issn_dedup
=
issn
.
drop_duplicates
(
subset
=
'
journal
'
)
issn_dedup
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
issn
</
th
>
<
th
>
issnl
</
th
>
<
th
>
journal
</
th
>
<
th
>
format
</
th
>
<
th
>
issn_type
</
th
>
<
th
>
id
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
0001
-
2815
</
td
>
<
td
>
0001
-
2815
</
td
>
<
td
>
532
</
td
>
<
td
>
PRINT
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
0001
-
4842
</
td
>
<
td
>
0001
-
4842
</
td
>
<
td
>
498
</
td
>
<
td
>
PRINT
</
td
>
<
td
>
1
</
td
>
<
td
>
3
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
0001
-
4966
</
td
>
<
td
>
0001
-
4966
</
td
>
<
td
>
789
</
td
>
<
td
>
PRINT
</
td
>
<
td
>
1
</
td
>
<
td
>
5
</
td
>
</
tr
>
<
tr
>
<
td
>
7
</
td
>
<
td
>
0001
-
6268
</
td
>
<
td
>
0001
-
6268
</
td
>
<
td
>
166
</
td
>
<
td
>
PRINT
</
td
>
<
td
>
1
</
td
>
<
td
>
8
</
td
>
</
tr
>
<
tr
>
<
td
>
9
</
td
>
<
td
>
0001
-
6322
</
td
>
<
td
>
0001
-
6322
</
td
>
<
td
>
807
</
td
>
<
td
>
PRINT
</
td
>
<
td
>
1
</
td
>
<
td
>
10
</
td
>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
1751
</
td
>
<
td
>
2469
-
9950
</
td
>
<
td
>
2469
-
9950
</
td
>
<
td
>
41
</
td
>
<
td
>
PRINT
</
td
>
<
td
>
1
</
td
>
<
td
>
1752
</
td
>
</
tr
>
<
tr
>
<
td
>
1753
</
td
>
<
td
>
2470
-
0010
</
td
>
<
td
>
2470
-
0010
</
td
>
<
td
>
80
</
td
>
<
td
>
PRINT
</
td
>
<
td
>
1
</
td
>
<
td
>
1754
</
td
>
</
tr
>
<
tr
>
<
td
>
1755
</
td
>
<
td
>
2470
-
0045
</
td
>
<
td
>
2470
-
0045
</
td
>
<
td
>
533
</
td
>
<
td
>
OTHER
</
td
>
<
td
>
3
</
td
>
<
td
>
1756
</
td
>
</
tr
>
<
tr
>
<
td
>
1757
</
td
>
<
td
>
2475
-
9953
</
td
>
<
td
>
2475
-
9953
</
td
>
<
td
>
608
</
td
>
<
td
>
ELECTRONIC
</
td
>
<
td
>
2
</
td
>
<
td
>
1758
</
td
>
</
tr
>
<
tr
>
<
td
>
1758
</
td
>
<
td
>
2504
-
4427
</
td
>
<
td
>
2504
-
4427
</
td
>
<
td
>
994
</
td
>
<
td
>
PRINT
</
td
>
<
td
>
1
</
td
>
<
td
>
1759
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
909
rows
×
6
columns
</
p
>
</
div
>
```
python
#
type
de
repositories
qui
provoquent
archiving
=
1
:
#
tous
les
types
:
'
academic_social_network
'
,
'
any_repository
'
,
'
any_website
'
,
'
authors_homepage
'
,
#
'
funder_designated_location
'
,
'
institutional_repository
'
,
'
institutional_website
'
,
'
named_academic_social_network
'
,
#
'
named_repository
'
,
'
non_commercial_institutional_repository
'
,
'
non_commercial_repository
'
,
#
'
non_commercial_social_network
'
,
'
non_commercial_subject_repository
'
,
'
non_commercial_website
'
,
#
'
preprint_repository
'
,
'
subject_repository
'
,
'
this_journal
'
repositories_archiving
=
[
'
any_repository
'
,
'
institutional_repository
'
,
'
institutional_website
'
,
'
non_commercial_institutional_repository
'
,
'
non_commercial_repository
'
,
'
any_website
'
,
'
non_commercial_website
'
]
#
extraction
des
termes
for
index
,
row
in
issn_dedup
.
iterrows
():
journal_id
=
row
[
'
journal
'
]
journal_issn
=
row
[
'
issn
'
]
#
boucle
des
fichiers
json
#
print
(
row
[
'
format
'
])
if
(((
index
/
10
)
-
int
(
index
/
10
))
==
0
)
:
print
(
index
)
#
test
d
'
existance
du
fichier
if
os
.
path
.
exists
(
'
sherpa
/
data
/
'
+
journal_issn
+
'
.
json
'
):
with
open
(
'
sherpa
/
data
/
'
+
journal_issn
+
'
.
json
'
,
'r'
,
encoding
=
'
utf
-
8
'
)
as
f
:
data
=
json
.
load
(
f
)
#
initialisation
des
variables
à
extraire
sherpa_id
=
np
.
nan
sherpa_uri
=
np
.
nan
open_access_prohibited
=
np
.
nan
location
=
np
.
nan
locations_ir
=
''
locations_not_ir
=
''
additional_oa_fee
=
np
.
nan
article_versions
=
np
.
nan
article_version
=
np
.
nan
licenses
=
[]
embargo
=
0
prerequisites
=
np
.
nan
prerequisite_funders
=
np
.
nan
prerequisite_funders_name
=
np
.
nan
prerequisite_funders_fundref
=
np
.
nan
prerequisite_funders_ror
=
np
.
nan
prerequisite_funders_country
=
np
.
nan
prerequisite_funders_url
=
np
.
nan
prerequisite_funders_sherpa_id
=
np
.
nan
prerequisite_subjects
=
np
.
nan
named_repository
=
np
.
nan
named_academic_social_network
=
np
.
nan
copyright_owner
=
np
.
nan
publisher_deposit
=
np
.
nan
archiving
=
np
.
nan
conditions
=
np
.
nan
public_notes
=
np
.
nan
if
(
len
(
data
[
'
items
'
])
>
0
):
if
(
'
id
'
in
data
[
'
items
'
][
0
]):
sherpa_id
=
data
[
'
items
'
][
0
][
'
id
'
]
#
test
si
l
'
id
est
d
é
j
à
pr
é
sent
if
sherpa_id
in
sherpa_policies
[
'
sherpa_id
'
]
:
print
(
'
SKIP
'
+
str
(
sherpa_id
))
else
:
poilicies
=
data
[
'
items
'
][
0
][
'
publisher_policy
'
]
for
poilicy
in
poilicies
:
#
initialisation
des
variables
à
extraire
sherpa_uri
=
np
.
nan
open_access_prohibited
=
np
.
nan
if
(
'
uri
'
in
poilicy
):
sherpa_uri
=
poilicy
[
'
uri
'
]
if
(
'
open_access_prohibited
'
in
poilicy
):
open_access_prohibited
=
poilicy
[
'
open_access_prohibited
'
]
if
(
'
permitted_oa
'
in
poilicy
):
poas
=
poilicy
[
'
permitted_oa
'
]
for
poa
in
poas
:
additional_oa_fee
=
np
.
nan
article_versions
=
np
.
nan
article_version
=
np
.
nan
licenses
=
[]
embargo
=
0
prerequisites
=
np
.
nan
prerequisite_funders
=
np
.
nan
prerequisite_funders_name
=
np
.
nan
prerequisite_funders_fundref
=
np
.
nan
prerequisite_funders_ror
=
np
.
nan
prerequisite_funders_country
=
np
.
nan
prerequisite_funders_url
=
np
.
nan
prerequisite_funders_sherpa_id
=
np
.
nan
prerequisite_subjects
=
np
.
nan
named_repository
=
np
.
nan
named_academic_social_network
=
np
.
nan
locations_ir
=
''
locations_not_ir
=
''
copyright_owner
=
np
.
nan
conditions
=
np
.
nan
public_notes
=
np
.
nan
if
(
'
additional_oa_fee
'
in
poa
):
additional_oa_fee
=
poa
[
'
additional_oa_fee
'
]
if
(
'
location
'
in
poa
):
archiving
=
0
location
=
''
mylocations
=
poa
[
'
location
'
][
'
location
'
]
mylocations_text
=
poa
[
'
location
'
][
'
location_phrases
'
]
if
(
type
(
mylocations
)
is
not
list
):
mylocations
=
[
mylocations
]
location
=
'
;
'
.
join
(
mylocations
)
for
locationi
in
mylocations
:
if
locationi
in
repositories_archiving
:
archiving
=
archiving
+
1
for
locationi_text
in
mylocations_text
:
if
locationi_text
[
'
value
'
]
==
locationi
:
if
locations_ir
==
''
:
locations_ir
=
locations_ir
+
locationi_text
[
'
phrase
'
]
else
:
if
locationi_text
[
'
phrase
'
]
not
in
locations_ir
:
locations_ir
=
locations_ir
+
'
;
'
+
locationi_text
[
'
phrase
'
]
else
:
for
locationi_text
in
mylocations_text
:
if
locationi_text
[
'
value
'
]
==
locationi
:
if
locations_not_ir
==
''
:
locations_not_ir
=
locations_not_ir
+
locationi_text
[
'
phrase
'
]
else
:
if
locationi_text
[
'
phrase
'
]
not
in
locations_not_ir
:
locations_not_ir
=
locations_not_ir
+
'
;
'
+
locationi_text
[
'
phrase
'
]
#
print
(
archiving
)
if
archiving
>
0
:
archiving
=
True
else
:
archiving
=
False
if
(
'
named_repository
'
in
poa
[
'
location
'
]):
if
(
type
(
poa
[
'
location
'
][
'
named_repository
'
])
is
list
):
named_repository
=
'
;
'
.
join
(
poa
[
'
location
'
][
'
named_repository
'
])
else
:
named_repository
=
poa
[
'
location
'
][
'
named_repository
'
]
locations_not_ir
=
locations_not_ir
.
replace
(
'
Named
Repository
'
,
named_repository
)
locations_ir
=
locations_ir
.
replace
(
'
Named
Repository
'
,
named_repository
)
if
(
'
named_academic_social_network
'
in
poa
[
'
location
'
]):
if
(
type
(
poa
[
'
location
'
][
'
named_academic_social_network
'
])
is
list
):
named_academic_social_network
=
'
;
'
.
join
(
poa
[
'
location
'
][
'
named_academic_social_network
'
])
else
:
named_academic_social_network
=
poa
[
'
location
'
][
'
named_academic_social_network
'
]
locations_not_ir
=
locations_not_ir
.
replace
(
'
Named
Academic
Social
Network
'
,
named_academic_social_network
)
locations_ir
=
locations_ir
.
replace
(
'
Named
Academic
Social
Network
'
,
named_academic_social_network
)
if
(
'
embargo
'
in
poa
):
#
print
(
poa
[
'
embargo
'
])
embargo_amount
=
0
if
(
'
amount
'
in
poa
[
'
embargo
'
]):
embargo_amount
=
poa
[
'
embargo
'
][
'
amount
'
]
if
(
'
units
'
in
poa
[
'
embargo
'
]):
if
(
poa
[
'
embargo
'
][
'
units
'
]
==
'
months
'
)
:
embargo
=
embargo_amount
elif
(
poa
[
'
embargo
'
][
'
units
'
]
==
'
years
'
)
:
embargo
=
embargo_amount
*
12
elif
(
poa
[
'
embargo
'
][
'
units
'
]
==
'
weeks
'
)
:
embargo
=
int
(
embargo_amount
/
4
)
if
(
embargo
==
0
):
embargo
=
1
elif
(
poa
[
'
embargo
'
][
'
units
'
]
==
'
days
'
)
:
embargo
=
int
(
embargo_amount
/
30
)
if
(
embargo
==
0
):
embargo
=
1
else
:
embargo
=
embargo_amount
if
(
'
prerequisites
'
in
poa
):
if
'
prerequisites
'
in
poa
[
'
prerequisites
'
]
:
if
(
type
(
poa
[
'
prerequisites
'
][
'
prerequisites
'
])
is
list
):
prerequisites
=
'
;
'
.
join
(
poa
[
'
prerequisites
'
][
'
prerequisites
'
])
else
:
prerequisites
=
poa
[
'
prerequisites
'
][
'
prerequisites
'
]
if
(
'
prerequisite_funders
'
in
poa
[
'
prerequisites
'
]):
prerequisite_funders
=
True
#
prerequisite_funders
=
poa
[
'
prerequisites
'
][
'
prerequisite_funders
'
]
#
if
(
type
(
poa
[
'
prerequisites
'
][
'
prerequisite_funders
'
])
is
list
):
#
prerequisite_funders
=
'
;
'
.
join
(
poa
[
'
prerequisites
'
][
'
prerequisite_funders
'
])
#
else
:
#
prerequisite_funders
=
poa
[
'
prerequisites
'
][
'
prerequisite_funders
'
]
if
(
'
prerequisite_subjects
'
in
poa
[
'
prerequisites
'
]):
prerequisite_subjects
=
True
#
prerequisite_subjects
=
poa
[
'
prerequisites
'
][
'
prerequisite_subjects
'
]
#
if
(
type
(
poa
[
'
prerequisite_subjects
'
])
is
list
):
#
prerequisite_subjects
=
'
;
'
.
join
(
poa
[
'
prerequisite_subjects
'
])
#
else
:
#
prerequisite_subjects
=
poa
[
'
prerequisite_subjects
'
]
if
(
'
copyright_owner
'
in
poa
):
copyright_owner
=
poa
[
'
copyright_owner
'
]
if
(
'
publisher_deposit
'
in
poa
):
publisher_deposit
=
''
if
(
type
(
poa
[
'
publisher_deposit
'
])
is
list
):
for
deposit
in
poa
[
'
publisher_deposit
'
]:
if
'
type
'
in
deposit
[
'
repository_metadata
'
]:
publisher_deposit
=
publisher_deposit
+
deposit
[
'
repository_metadata
'
][
'
type
'
]
if
'
name
'
in
deposit
[
'
repository_metadata
'
]:
publisher_deposit
=
publisher_deposit
+
'
(
'
+
deposit
[
'
repository_metadata
'
][
'
name
'
][
0
][
'
name
'
]
+
')'
else
:
if
'
name
'
in
deposit
[
'
repository_metadata
'
]:
publisher_deposit
=
publisher_deposit
+
deposit
[
'
repository_metadata
'
][
'
name
'
][
0
][
'
name
'
]
publisher_deposit
=
publisher_deposit
+
'
;
'
else
:
deposit
=
poa
[
'
publisher_deposit
'
]
if
'
type
'
in
deposit
[
'
repository_metadata
'
]:
publisher_deposit
=
publisher_deposit
+
deposit
[
'
repository_metadata
'
][
'
type
'
]
if
'
name
'
in
deposit
[
'
repository_metadata
'
]:
publisher_deposit
=
publisher_deposit
+
'
(
'
+
deposit
[
'
repository_metadata
'
][
'
name
'
][
0
][
'
name
'
]
+
')'
else
:
if
'
name
'
in
deposit
[
'
repository_metadata
'
]:
publisher_deposit
=
publisher_deposit
+
deposit
[
'
repository_metadata
'
][
'
name
'
][
0
][
'
name
'
]
publisher_deposit
=
publisher_deposit
+
'
;
'
#
print
(
publisher_deposit
)
if
(
'
conditions
'
in
poa
):
if
(
type
(
poa
[
'
conditions
'
])
is
list
):
conditions
=
'
;
'
.
join
(
poa
[
'
conditions
'
])
else
:
conditions
=
poa
[
'
conditions
'
]
if
(
'
public_notes
'
in
poa
):
if
(
type
(
poa
[
'
public_notes
'
])
is
list
):
public_notes
=
'
;
'
.
join
(
poa
[
'
public_notes
'
])
else
:
public_notes
=
poa
[
'
public_notes
'
]
if
(
'
license
'
in
poa
):
licenses
=
poa
[
'
license
'
]
if
(
type
(
licenses
)
is
not
list
):
licenses
=
[
licenses
]
else
:
licenses
=
[
''
]
#
avec
article
version
if
(
'
article_version
'
in
poa
):
article_versions
=
poa
[
'
article_version
'
]
for
article_version
in
article_versions
:
for
license
in
licenses
:
if
(
'
license
'
in
license
):
mylicense
=
license
[
'
license
'
]
else
:
mylicense
=
''
#
avec
prerequisites
if
(
'
prerequisites
'
in
poa
)
:
#
avec
prerequisites_funders
if
(
'
prerequisite_funders
'
in
poa
[
'
prerequisites
'
]):
for
prerequisite_fundersi
in
poa
[
'
prerequisites
'
][
'
prerequisite_funders
'
]
:
prerequisite_funders_name
=
prerequisite_fundersi
[
'
funder_metadata
'
][
'
name
'
][
0
][
'
name
'
]
if
'
acronym
'
in
prerequisite_fundersi
[
'
funder_metadata
'
][
'
name
'
][
0
]:
prerequisite_funders_name
=
prerequisite_funders_name
+
'
(
'
+
prerequisite_fundersi
[
'
funder_metadata
'
][
'
name
'
][
0
][
'
acronym
'
]
+
')'
if
'
identifiers
'
in
prerequisite_fundersi
[
'
funder_metadata
'
]
:
for
fund_identifier
in
prerequisite_fundersi
[
'
funder_metadata
'
][
'
identifiers
'
]
:
if
fund_identifier
[
'
type
'
]
==
'
fundref
'
:
prerequisite_funders_fundref
=
fund_identifier
[
'
identifier
'
]
if
fund_identifier
[
'
type
'
]
==
'
ror
'
:
prerequisite_funders_ror
=
fund_identifier
[
'
identifier
'
]
if
'
country
'
in
prerequisite_fundersi
[
'
funder_metadata
'
]:
prerequisite_funders_country
=
prerequisite_fundersi
[
'
funder_metadata
'
][
'
country
'
]
if
'
url
'
in
prerequisite_fundersi
[
'
funder_metadata
'
]:
prerequisite_funders_url
=
prerequisite_fundersi
[
'
funder_metadata
'
][
'
url
'
][
0
][
'
url
'
]
prerequisite_funders_sherpa_id
=
prerequisite_fundersi
[
'
funder_metadata
'
][
'
id
'
]
sherpa_policies
=
sherpa_policies
.
append
({
'
journal
'
:
journal_id
,
'
issn
'
:
journal_issn
,
'
sherpa_id
'
:
sherpa_id
,
'
sherpa_uri
'
:
sherpa_uri
,
'
open_access_prohibited
'
:
open_access_prohibited
,
'
additional_oa_fee
'
:
additional_oa_fee
,
'
article_version
'
:
article_version
,
'
license
'
:
mylicense
,
'
embargo
'
:
embargo
,
'
prerequisites
'
:
prerequisites
,
'
prerequisite_funders
'
:
prerequisite_funders
,
'
prerequisite_funders_name
'
:
prerequisite_funders_name
,
'
prerequisite_funders_fundref
'
:
prerequisite_funders_fundref
,
'
prerequisite_funders_ror
'
:
prerequisite_funders_ror
,
'
prerequisite_funders_country
'
:
prerequisite_funders_country
,
'
prerequisite_funders_url
'
:
prerequisite_funders_url
,
'
prerequisite_funders_sherpa_id
'
:
prerequisite_funders_sherpa_id
,
'
prerequisite_subjects
'
:
prerequisite_subjects
,
'
location
'
:
location
,
'
locations_ir
'
:
locations_ir
,
'
locations_not_ir
'
:
locations_not_ir
,
'
named_repository
'
:
named_repository
,
'
named_academic_social_network
'
:
named_academic_social_network
,
'
copyright_owner
'
:
copyright_owner
,
'
publisher_deposit
'
:
publisher_deposit
,
'
archiving
'
:
archiving
,
'
conditions
'
:
conditions
,
'
public_notes
'
:
public_notes
},
ignore_index
=
True
)
#
sans
prerequisites_funders
else
:
sherpa_policies
=
sherpa_policies
.
append
({
'
journal
'
:
journal_id
,
'
issn
'
:
journal_issn
,
'
sherpa_id
'
:
sherpa_id
,
'
sherpa_uri
'
:
sherpa_uri
,
'
open_access_prohibited
'
:
open_access_prohibited
,
'
additional_oa_fee
'
:
additional_oa_fee
,
'
article_version
'
:
article_version
,
'
license
'
:
mylicense
,
'
embargo
'
:
embargo
,
'
prerequisites
'
:
prerequisites
,
'
prerequisite_funders
'
:
prerequisite_funders
,
'
prerequisite_funders_name
'
:
prerequisite_funders_name
,
'
prerequisite_funders_fundref
'
:
prerequisite_funders_fundref
,
'
prerequisite_funders_ror
'
:
prerequisite_funders_ror
,
'
prerequisite_funders_country
'
:
prerequisite_funders_country
,
'
prerequisite_funders_url
'
:
prerequisite_funders_url
,
'
prerequisite_funders_sherpa_id
'
:
prerequisite_funders_sherpa_id
,
'
prerequisite_subjects
'
:
prerequisite_subjects
,
'
location
'
:
location
,
'
locations_ir
'
:
locations_ir
,
'
locations_not_ir
'
:
locations_not_ir
,
'
named_repository
'
:
named_repository
,
'
named_academic_social_network
'
:
named_academic_social_network
,
'
copyright_owner
'
:
copyright_owner
,
'
publisher_deposit
'
:
publisher_deposit
,
'
archiving
'
:
archiving
,
'
conditions
'
:
conditions
,
'
public_notes
'
:
public_notes
},
ignore_index
=
True
)
#
sans
prerequisites
else
:
sherpa_policies
=
sherpa_policies
.
append
({
'
journal
'
:
journal_id
,
'
issn
'
:
journal_issn
,
'
sherpa_id
'
:
sherpa_id
,
'
sherpa_uri
'
:
sherpa_uri
,
'
open_access_prohibited
'
:
open_access_prohibited
,
'
additional_oa_fee
'
:
additional_oa_fee
,
'
article_version
'
:
article_version
,
'
license
'
:
mylicense
,
'
embargo
'
:
embargo
,
'
prerequisites
'
:
prerequisites
,
'
prerequisite_funders
'
:
prerequisite_funders
,
'
prerequisite_funders_name
'
:
prerequisite_funders_name
,
'
prerequisite_funders_fundref
'
:
prerequisite_funders_fundref
,
'
prerequisite_funders_ror
'
:
prerequisite_funders_ror
,
'
prerequisite_funders_country
'
:
prerequisite_funders_country
,
'
prerequisite_funders_url
'
:
prerequisite_funders_url
,
'
prerequisite_funders_sherpa_id
'
:
prerequisite_funders_sherpa_id
,
'
prerequisite_subjects
'
:
prerequisite_subjects
,
'
location
'
:
location
,
'
locations_ir
'
:
locations_ir
,
'
locations_not_ir
'
:
locations_not_ir
,
'
named_repository
'
:
named_repository
,
'
named_academic_social_network
'
:
named_academic_social_network
,
'
copyright_owner
'
:
copyright_owner
,
'
publisher_deposit
'
:
publisher_deposit
,
'
archiving
'
:
archiving
,
'
conditions
'
:
conditions
,
'
public_notes
'
:
public_notes
},
ignore_index
=
True
)
#
sans
article
version
else
:
if
(
type
(
licenses
)
is
not
list
):
licenses
=
[
licenses
]
for
license
in
licenses
:
if
(
'
license
'
in
license
):
mylicense
=
license
[
'
license
'
]
else
:
mylicense
=
''
#
avec
prerequisites
if
(
'
prerequisites
'
in
poa
)
:
#
avec
prerequisites_funders
if
(
'
prerequisite_funders
'
in
poa
[
'
prerequisites
'
]):
for
prerequisite_fundersi
in
poa
[
'
prerequisites
'
][
'
prerequisite_funders
'
]
:
prerequisite_funders_name
=
prerequisite_fundersi
[
'
funder_metadata
'
][
'
name
'
][
0
][
'
name
'
]
if
'
acronym
'
in
prerequisite_fundersi
[
'
funder_metadata
'
][
'
name
'
][
0
]:
prerequisite_funders_name
=
prerequisite_funders_name
+
'
(
'
+
prerequisite_fundersi
[
'
funder_metadata
'
][
'
name
'
][
0
][
'
acronym
'
]
+
')'
if
'
identifiers
'
in
prerequisite_fundersi
[
'
funder_metadata
'
]
:
for
fund_identifier
in
prerequisite_fundersi
[
'
funder_metadata
'
][
'
identifiers
'
]
:
if
fund_identifier
[
'
type
'
]
==
'
fundref
'
:
prerequisite_funders_fundref
=
fund_identifier
[
'
identifier
'
]
if
fund_identifier
[
'
type
'
]
==
'
ror
'
:
prerequisite_funders_ror
=
fund_identifier
[
'
identifier
'
]
if
'
country
'
in
prerequisite_fundersi
[
'
funder_metadata
'
]:
prerequisite_funders_country
=
prerequisite_fundersi
[
'
funder_metadata
'
][
'
country
'
]
if
'
url
'
in
prerequisite_fundersi
[
'
funder_metadata
'
]:
prerequisite_funders_url
=
prerequisite_fundersi
[
'
funder_metadata
'
][
'
url
'
][
0
][
'
url
'
]
prerequisite_funders_sherpa_id
=
prerequisite_fundersi
[
'
funder_metadata
'
][
'
id
'
]
sherpa_policies
=
sherpa_policies
.
append
({
'
journal
'
:
journal_id
,
'
issn
'
:
journal_issn
,
'
sherpa_id
'
:
sherpa_id
,
'
sherpa_uri
'
:
sherpa_uri
,
'
open_access_prohibited
'
:
open_access_prohibited
,
'
additional_oa_fee
'
:
additional_oa_fee
,
'
article_version
'
:
article_version
,
'
license
'
:
mylicense
,
'
embargo
'
:
embargo
,
'
prerequisites
'
:
prerequisites
,
'
prerequisite_funders
'
:
prerequisite_funders
,
'
prerequisite_funders_name
'
:
prerequisite_funders_name
,
'
prerequisite_funders_fundref
'
:
prerequisite_funders_fundref
,
'
prerequisite_funders_ror
'
:
prerequisite_funders_ror
,
'
prerequisite_funders_country
'
:
prerequisite_funders_country
,
'
prerequisite_funders_url
'
:
prerequisite_funders_url
,
'
prerequisite_funders_sherpa_id
'
:
prerequisite_funders_sherpa_id
,
'
prerequisite_subjects
'
:
prerequisite_subjects
,
'
location
'
:
location
,
'
locations_ir
'
:
locations_ir
,
'
locations_not_ir
'
:
locations_not_ir
,
'
named_repository
'
:
named_repository
,
'
named_academic_social_network
'
:
named_academic_social_network
,
'
copyright_owner
'
:
copyright_owner
,
'
publisher_deposit
'
:
publisher_deposit
,
'
archiving
'
:
archiving
,
'
conditions
'
:
conditions
,
'
public_notes
'
:
public_notes
},
ignore_index
=
True
)
#
sans
prerequisites_funders
else
:
sherpa_policies
=
sherpa_policies
.
append
({
'
journal
'
:
journal_id
,
'
issn
'
:
journal_issn
,
'
sherpa_id
'
:
sherpa_id
,
'
sherpa_uri
'
:
sherpa_uri
,
'
open_access_prohibited
'
:
open_access_prohibited
,
'
additional_oa_fee
'
:
additional_oa_fee
,
'
article_version
'
:
article_version
,
'
license
'
:
mylicense
,
'
embargo
'
:
embargo
,
'
prerequisites
'
:
prerequisites
,
'
prerequisite_funders
'
:
prerequisite_funders
,
'
prerequisite_funders_name
'
:
prerequisite_funders_name
,
'
prerequisite_funders_fundref
'
:
prerequisite_funders_fundref
,
'
prerequisite_funders_ror
'
:
prerequisite_funders_ror
,
'
prerequisite_funders_country
'
:
prerequisite_funders_country
,
'
prerequisite_funders_url
'
:
prerequisite_funders_url
,
'
prerequisite_funders_sherpa_id
'
:
prerequisite_funders_sherpa_id
,
'
prerequisite_subjects
'
:
prerequisite_subjects
,
'
location
'
:
location
,
'
locations_ir
'
:
locations_ir
,
'
locations_not_ir
'
:
locations_not_ir
,
'
named_repository
'
:
named_repository
,
'
named_academic_social_network
'
:
named_academic_social_network
,
'
copyright_owner
'
:
copyright_owner
,
'
publisher_deposit
'
:
publisher_deposit
,
'
archiving
'
:
archiving
,
'
conditions
'
:
conditions
,
'
public_notes
'
:
public_notes
},
ignore_index
=
True
)
#
sans
prerequisites
else
:
sherpa_policies
=
sherpa_policies
.
append
({
'
journal
'
:
journal_id
,
'
issn
'
:
journal_issn
,
'
sherpa_id
'
:
sherpa_id
,
'
sherpa_uri
'
:
sherpa_uri
,
'
open_access_prohibited
'
:
open_access_prohibited
,
'
additional_oa_fee
'
:
additional_oa_fee
,
'
article_version
'
:
article_version
,
'
license
'
:
mylicense
,
'
embargo
'
:
embargo
,
'
prerequisites
'
:
prerequisites
,
'
prerequisite_funders
'
:
prerequisite_funders
,
'
prerequisite_funders_name
'
:
prerequisite_funders_name
,
'
prerequisite_funders_fundref
'
:
prerequisite_funders_fundref
,
'
prerequisite_funders_ror
'
:
prerequisite_funders_ror
,
'
prerequisite_funders_country
'
:
prerequisite_funders_country
,
'
prerequisite_funders_url
'
:
prerequisite_funders_url
,
'
prerequisite_funders_sherpa_id
'
:
prerequisite_funders_sherpa_id
,
'
prerequisite_subjects
'
:
prerequisite_subjects
,
'
location
'
:
location
,
'
locations_ir
'
:
locations_ir
,
'
locations_not_ir
'
:
locations_not_ir
,
'
named_repository
'
:
named_repository
,
'
named_academic_social_network
'
:
named_academic_social_network
,
'
copyright_owner
'
:
copyright_owner
,
'
publisher_deposit
'
:
publisher_deposit
,
'
archiving
'
:
archiving
,
'
conditions
'
:
conditions
,
'
public_notes
'
:
public_notes
},
ignore_index
=
True
)
#
sans
permitted_oa
else
:
print
(
'
permitted_oa
MISSING
'
)
else
:
print
(
'
id
MISSING
'
)
```
0
20
40
50
60
SKIP
321
110
SKIP
475
SKIP
476
180
220
250
260
290
300
330
340
360
370
380
420
permitted_oa
MISSING
430
permitted_oa
MISSING
SKIP
1319
SKIP
880
permitted_oa
MISSING
510
permitted_oa
MISSING
530
540
550
560
SKIP
1342
570
590
SKIP
3082
SKIP
2465
SKIP
1682
SKIP
325
SKIP
3179
670
680
SKIP
1641
SKIP
1202
720
SKIP
3995
730
SKIP
3475
SKIP
3490
740
750
760
SKIP
1383
SKIP
1357
permitted_oa
MISSING
830
840
SKIP
1868
850
SKIP
883
880
890
SKIP
1392
900
910
SKIP
1377
920
SKIP
3443
930
940
SKIP
1123
SKIP
3581
SKIP
3558
SKIP
745
980
990
SKIP
11
SKIP
2499
1000
SKIP
42
1010
1020
SKIP
314
1030
1040
SKIP
1380
SKIP
229
SKIP
1518
SKIP
5682
SKIP
4708
SKIP
1661
1130
SKIP
6585
1140
SKIP
3212
1150
SKIP
335
SKIP
6774
1160
SKIP
6590
1180
SKIP
1639
SKIP
5094
SKIP
1254
1200
SKIP
6325
SKIP
3539
SKIP
1444
SKIP
250
SKIP
1543
SKIP
3415
SKIP
3571
SKIP
3474
SKIP
3586
SKIP
3220
SKIP
3837
SKIP
1650
SKIP
1051
SKIP
3572
SKIP
612
SKIP
6587
SKIP
3567
SKIP
1654
SKIP
4070
SKIP
1643
SKIP
6588
SKIP
1657
SKIP
1687
SKIP
1692
SKIP
1341
1320
SKIP
7150
SKIP
876
1330
SKIP
7007
SKIP
7091
1340
1350
SKIP
173
SKIP
4703
1360
SKIP
2515
1370
SKIP
242
SKIP
3930
SKIP
2004
1400
1410
SKIP
2123
SKIP
1320
SKIP
1459
SKIP
1588
SKIP
7678
SKIP
1391
SKIP
878
SKIP
138
SKIP
7632
SKIP
1644
SKIP
1637
SKIP
2207
SKIP
2428
SKIP
2432
1460
SKIP
2477
SKIP
2430
SKIP
1653
SKIP
2397
SKIP
5935
SKIP
3527
SKIP
148
SKIP
7793
SKIP
4005
SKIP
7768
SKIP
3455
SKIP
1652
SKIP
3570
SKIP
7792
SKIP
3533
SKIP
6586
1520
SKIP
7787
SKIP
3355
1530
SKIP
226
SKIP
1655
SKIP
7783
1540
SKIP
6582
1550
SKIP
7762
SKIP
4691
SKIP
1911
SKIP
1447
SKIP
1778
SKIP
1888
SKIP
228
SKIP
7407
SKIP
7965
1590
1600
1610
SKIP
821
SKIP
823
SKIP
7714
1620
SKIP
172
SKIP
2624
SKIP
3654
SKIP
1659
SKIP
1656
SKIP
1658
SKIP
1393
1640
SKIP
6778
SKIP
8220
SKIP
7872
SKIP
1587
SKIP
822
SKIP
1460
SKIP
6581
SKIP
3568
1670
SKIP
7509
SKIP
7799
SKIP
7765
1680
SKIP
7761
SKIP
7800
1690
SKIP
1244
1710
SKIP
6222
1730
1740
1750
```
python
sherpa_policies
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
journal
</
th
>
<
th
>
issn
</
th
>
<
th
>
sherpa_id
</
th
>
<
th
>
sherpa_uri
</
th
>
<
th
>
open_access_prohibited
</
th
>
<
th
>
additional_oa_fee
</
th
>
<
th
>
article_version
</
th
>
<
th
>
license
</
th
>
<
th
>
embargo
</
th
>
<
th
>
prerequisites
</
th
>
<
th
>
prerequisite_funders
</
th
>
<
th
>
prerequisite_funders_name
</
th
>
<
th
>
prerequisite_funders_fundref
</
th
>
<
th
>
prerequisite_funders_ror
</
th
>
<
th
>
prerequisite_funders_country
</
th
>
<
th
>
prerequisite_funders_url
</
th
>
<
th
>
prerequisite_funders_sherpa_id
</
th
>
<
th
>
prerequisite_subjects
</
th
>
<
th
>
location
</
th
>
<
th
>
locations_ir
</
th
>
<
th
>
locations_not_ir
</
th
>
<
th
>
named_repository
</
th
>
<
th
>
named_academic_social_network
</
th
>
<
th
>
copyright_owner
</
th
>
<
th
>
publisher_deposit
</
th
>
<
th
>
archiving
</
th
>
<
th
>
conditions
</
th
>
<
th
>
public_notes
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
532
</
td
>
<
td
>
0001
-
2815
</
td
>
<
td
>
11905
</
td
>
<
td
>
https
:
//v2.sherpa.ac.uk/id/publisher_policy/2050</td>
<
td
>
no
</
td
>
<
td
>
no
</
td
>
<
td
>
submitted
</
td
>
<
td
></
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
authors_homepage
;
named_repository
;
non_comm
...</
td
>
<
td
>
Non
-
Commercial
Institutional
Repository
</
td
>
<
td
>
Author
'
s
Homepage
;
arXiv
;
AgEcon
;
PhilPaper
...</
td
>
<
td
>
arXiv
;
AgEcon
;
PhilPapers
;
PubMed
Central
;...</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
Must
acknowledge
acceptance
for
publication
;
...</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
532
</
td
>
<
td
>
0001
-
2815
</
td
>
<
td
>
11905
</
td
>
<
td
>
https
:
//v2.sherpa.ac.uk/id/publisher_policy/2050</td>
<
td
>
no
</
td
>
<
td
>
no
</
td
>
<
td
>
accepted
</
td
>
<
td
></
td
>
<
td
>
12
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
authors_homepage
;
named_repository
;
non_comm
...</
td
>
<
td
>
Non
-
Commercial
Institutional
Repository
</
td
>
<
td
>
Author
'
s
Homepage
;
arXiv
;
AgEcon
;
PhilPaper
...</
td
>
<
td
>
arXiv
;
AgEcon
;
PhilPapers
;
PubMed
Central
;...</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
Publisher
source
must
be
acknowledged
with
cit
...</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
532
</
td
>
<
td
>
0001
-
2815
</
td
>
<
td
>
11905
</
td
>
<
td
>
https
:
//v2.sherpa.ac.uk/id/publisher_policy/3315</td>
<
td
>
no
</
td
>
<
td
>
yes
</
td
>
<
td
>
published
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
any_website
;
institutional_repository
;
named
...</
td
>
<
td
>
Any
Website
;
Institutional
Repository
</
td
>
<
td
>
PubMed
Central
;
Subject
Repository
;
Journal
...</
td
>
<
td
>
PubMed
Central
</
td
>
<
td
>
NaN
</
td
>
<
td
>
authors
</
td
>
<
td
>
disciplinary
(
PubMed
Central
)
;</
td
>
<
td
>
True
</
td
>
<
td
>
Published
source
must
be
acknowledged
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
532
</
td
>
<
td
>
0001
-
2815
</
td
>
<
td
>
11905
</
td
>
<
td
>
https
:
//v2.sherpa.ac.uk/id/publisher_policy/3315</td>
<
td
>
no
</
td
>
<
td
>
yes
</
td
>
<
td
>
published
</
td
>
<
td
>
cc_by_nc_nd
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
any_website
;
named_repository
;
non_commercia
...</
td
>
<
td
>
Any
Website
;
Non
-
Commercial
Institutional
Rep
...</
td
>
<
td
>
PubMed
Central
;
Non
-
Commercial
Subject
Reposi
...</
td
>
<
td
>
PubMed
Central
</
td
>
<
td
>
NaN
</
td
>
<
td
>
authors
</
td
>
<
td
>
disciplinary
(
PubMed
Central
)
;</
td
>
<
td
>
True
</
td
>
<
td
>
Published
source
must
be
acknowledged
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
498
</
td
>
<
td
>
0001
-
4842
</
td
>
<
td
>
7760
</
td
>
<
td
>
https
:
//v2.sherpa.ac.uk/id/publisher_policy/4</td>
<
td
>
no
</
td
>
<
td
>
no
</
td
>
<
td
>
submitted
</
td
>
<
td
></
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
named_repository
;
preprint_repository
;
subje
...</
td
>
<
td
></
td
>
<
td
>
ChemRxiv
;
bioRxiv
;
arXiv
;
Preprint
Reposito
...</
td
>
<
td
>
ChemRxiv
;
bioRxiv
;
arXiv
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
False
</
td
>
<
td
>
Must
not
violate
ACS
ethical
Guidelines
;
Must
...</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
8590
</
td
>
<
td
>
608
</
td
>
<
td
>
2475
-
9953
</
td
>
<
td
>
33503
</
td
>
<
td
>
https
:
//v2.sherpa.ac.uk/id/publisher_policy/10</td>
<
td
>
no
</
td
>
<
td
>
no
</
td
>
<
td
>
submitted
</
td
>
<
td
></
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
authors_homepage
;
institutional_repository
;
...</
td
>
<
td
>
Institutional
Repository
;
Institutional
Website
</
td
>
<
td
>
Author
'
s
Homepage
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
Must
link
to
published
article
;
Publisher
cop
...</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
8591
</
td
>
<
td
>
608
</
td
>
<
td
>
2475
-
9953
</
td
>
<
td
>
33503
</
td
>
<
td
>
https
:
//v2.sherpa.ac.uk/id/publisher_policy/10</td>
<
td
>
no
</
td
>
<
td
>
no
</
td
>
<
td
>
accepted
</
td
>
<
td
></
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
authors_homepage
;
institutional_repository
;
...</
td
>
<
td
>
Institutional
Repository
;
Institutional
Website
</
td
>
<
td
>
Author
'
s
Homepage
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
Must
link
to
published
article
;
Publisher
cop
...</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
8592
</
td
>
<
td
>
608
</
td
>
<
td
>
2475
-
9953
</
td
>
<
td
>
33503
</
td
>
<
td
>
https
:
//v2.sherpa.ac.uk/id/publisher_policy/10</td>
<
td
>
no
</
td
>
<
td
>
no
</
td
>
<
td
>
published
</
td
>
<
td
></
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
authors_homepage
;
institutional_repository
;
...</
td
>
<
td
>
Institutional
Repository
;
Institutional
Website
</
td
>
<
td
>
Author
'
s
Homepage
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
Must
link
to
published
article
;
Publisher
cop
...</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
8593
</
td
>
<
td
>
608
</
td
>
<
td
>
2475
-
9953
</
td
>
<
td
>
33503
</
td
>
<
td
>
https
:
//v2.sherpa.ac.uk/id/publisher_policy/10</td>
<
td
>
no
</
td
>
<
td
>
yes
</
td
>
<
td
>
published
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
any_repository
;
this_journal
</
td
>
<
td
>
Any
Repository
</
td
>
<
td
>
Journal
Website
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
8594
</
td
>
<
td
>
608
</
td
>
<
td
>
2475
-
9953
</
td
>
<
td
>
33503
</
td
>
<
td
>
https
:
//v2.sherpa.ac.uk/id/publisher_policy/10</td>
<
td
>
no
</
td
>
<
td
>
yes
</
td
>
<
td
>
published
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
any_repository
;
this_journal
</
td
>
<
td
>
Any
Repository
</
td
>
<
td
>
Journal
Website
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
8595
rows
×
28
columns
</
p
>
</
div
>
```
python
#
convertir
l
'
index
en
id
sherpa_policies
=
sherpa_policies
.
reset_index
()
#
ajout
de
l
'
id
avec
l
'
index
+
1
sherpa_policies
[
'
id
'
]
=
sherpa_policies
[
'
index
'
]
+
1
del
sherpa_policies
[
'
index
'
]
sherpa_policies
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
journal
</
th
>
<
th
>
issn
</
th
>
<
th
>
sherpa_id
</
th
>
<
th
>
sherpa_uri
</
th
>
<
th
>
open_access_prohibited
</
th
>
<
th
>
additional_oa_fee
</
th
>
<
th
>
article_version
</
th
>
<
th
>
license
</
th
>
<
th
>
embargo
</
th
>
<
th
>
prerequisites
</
th
>
<
th
>
prerequisite_funders
</
th
>
<
th
>
prerequisite_funders_name
</
th
>
<
th
>
prerequisite_funders_fundref
</
th
>
<
th
>
prerequisite_funders_ror
</
th
>
<
th
>
prerequisite_funders_country
</
th
>
<
th
>
prerequisite_funders_url
</
th
>
<
th
>
prerequisite_funders_sherpa_id
</
th
>
<
th
>
prerequisite_subjects
</
th
>
<
th
>
location
</
th
>
<
th
>
locations_ir
</
th
>
<
th
>
locations_not_ir
</
th
>
<
th
>
named_repository
</
th
>
<
th
>
named_academic_social_network
</
th
>
<
th
>
copyright_owner
</
th
>
<
th
>
publisher_deposit
</
th
>
<
th
>
archiving
</
th
>
<
th
>
conditions
</
th
>
<
th
>
public_notes
</
th
>
<
th
>
id
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
532
</
td
>
<
td
>
0001
-
2815
</
td
>
<
td
>
11905
</
td
>
<
td
>
https
:
//v2.sherpa.ac.uk/id/publisher_policy/2050</td>
<
td
>
no
</
td
>
<
td
>
no
</
td
>
<
td
>
submitted
</
td
>
<
td
></
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
authors_homepage
;
named_repository
;
non_comm
...</
td
>
<
td
>
Non
-
Commercial
Institutional
Repository
</
td
>
<
td
>
Author
'
s
Homepage
;
arXiv
;
AgEcon
;
PhilPaper
...</
td
>
<
td
>
arXiv
;
AgEcon
;
PhilPapers
;
PubMed
Central
;...</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
Must
acknowledge
acceptance
for
publication
;
...</
td
>
<
td
>
NaN
</
td
>
<
td
>
1
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
532
</
td
>
<
td
>
0001
-
2815
</
td
>
<
td
>
11905
</
td
>
<
td
>
https
:
//v2.sherpa.ac.uk/id/publisher_policy/2050</td>
<
td
>
no
</
td
>
<
td
>
no
</
td
>
<
td
>
accepted
</
td
>
<
td
></
td
>
<
td
>
12
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
authors_homepage
;
named_repository
;
non_comm
...</
td
>
<
td
>
Non
-
Commercial
Institutional
Repository
</
td
>
<
td
>
Author
'
s
Homepage
;
arXiv
;
AgEcon
;
PhilPaper
...</
td
>
<
td
>
arXiv
;
AgEcon
;
PhilPapers
;
PubMed
Central
;...</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
Publisher
source
must
be
acknowledged
with
cit
...</
td
>
<
td
>
NaN
</
td
>
<
td
>
2
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
532
</
td
>
<
td
>
0001
-
2815
</
td
>
<
td
>
11905
</
td
>
<
td
>
https
:
//v2.sherpa.ac.uk/id/publisher_policy/3315</td>
<
td
>
no
</
td
>
<
td
>
yes
</
td
>
<
td
>
published
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
any_website
;
institutional_repository
;
named
...</
td
>
<
td
>
Any
Website
;
Institutional
Repository
</
td
>
<
td
>
PubMed
Central
;
Subject
Repository
;
Journal
...</
td
>
<
td
>
PubMed
Central
</
td
>
<
td
>
NaN
</
td
>
<
td
>
authors
</
td
>
<
td
>
disciplinary
(
PubMed
Central
)
;</
td
>
<
td
>
True
</
td
>
<
td
>
Published
source
must
be
acknowledged
</
td
>
<
td
>
NaN
</
td
>
<
td
>
3
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
532
</
td
>
<
td
>
0001
-
2815
</
td
>
<
td
>
11905
</
td
>
<
td
>
https
:
//v2.sherpa.ac.uk/id/publisher_policy/3315</td>
<
td
>
no
</
td
>
<
td
>
yes
</
td
>
<
td
>
published
</
td
>
<
td
>
cc_by_nc_nd
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
any_website
;
named_repository
;
non_commercia
...</
td
>
<
td
>
Any
Website
;
Non
-
Commercial
Institutional
Rep
...</
td
>
<
td
>
PubMed
Central
;
Non
-
Commercial
Subject
Reposi
...</
td
>
<
td
>
PubMed
Central
</
td
>
<
td
>
NaN
</
td
>
<
td
>
authors
</
td
>
<
td
>
disciplinary
(
PubMed
Central
)
;</
td
>
<
td
>
True
</
td
>
<
td
>
Published
source
must
be
acknowledged
</
td
>
<
td
>
NaN
</
td
>
<
td
>
4
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
498
</
td
>
<
td
>
0001
-
4842
</
td
>
<
td
>
7760
</
td
>
<
td
>
https
:
//v2.sherpa.ac.uk/id/publisher_policy/4</td>
<
td
>
no
</
td
>
<
td
>
no
</
td
>
<
td
>
submitted
</
td
>
<
td
></
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
named_repository
;
preprint_repository
;
subje
...</
td
>
<
td
></
td
>
<
td
>
ChemRxiv
;
bioRxiv
;
arXiv
;
Preprint
Reposito
...</
td
>
<
td
>
ChemRxiv
;
bioRxiv
;
arXiv
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
False
</
td
>
<
td
>
Must
not
violate
ACS
ethical
Guidelines
;
Must
...</
td
>
<
td
>
NaN
</
td
>
<
td
>
5
</
td
>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
8590
</
td
>
<
td
>
608
</
td
>
<
td
>
2475
-
9953
</
td
>
<
td
>
33503
</
td
>
<
td
>
https
:
//v2.sherpa.ac.uk/id/publisher_policy/10</td>
<
td
>
no
</
td
>
<
td
>
no
</
td
>
<
td
>
submitted
</
td
>
<
td
></
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
authors_homepage
;
institutional_repository
;
...</
td
>
<
td
>
Institutional
Repository
;
Institutional
Website
</
td
>
<
td
>
Author
'
s
Homepage
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
Must
link
to
published
article
;
Publisher
cop
...</
td
>
<
td
>
NaN
</
td
>
<
td
>
8591
</
td
>
</
tr
>
<
tr
>
<
td
>
8591
</
td
>
<
td
>
608
</
td
>
<
td
>
2475
-
9953
</
td
>
<
td
>
33503
</
td
>
<
td
>
https
:
//v2.sherpa.ac.uk/id/publisher_policy/10</td>
<
td
>
no
</
td
>
<
td
>
no
</
td
>
<
td
>
accepted
</
td
>
<
td
></
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
authors_homepage
;
institutional_repository
;
...</
td
>
<
td
>
Institutional
Repository
;
Institutional
Website
</
td
>
<
td
>
Author
'
s
Homepage
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
Must
link
to
published
article
;
Publisher
cop
...</
td
>
<
td
>
NaN
</
td
>
<
td
>
8592
</
td
>
</
tr
>
<
tr
>
<
td
>
8592
</
td
>
<
td
>
608
</
td
>
<
td
>
2475
-
9953
</
td
>
<
td
>
33503
</
td
>
<
td
>
https
:
//v2.sherpa.ac.uk/id/publisher_policy/10</td>
<
td
>
no
</
td
>
<
td
>
no
</
td
>
<
td
>
published
</
td
>
<
td
></
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
authors_homepage
;
institutional_repository
;
...</
td
>
<
td
>
Institutional
Repository
;
Institutional
Website
</
td
>
<
td
>
Author
'
s
Homepage
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
Must
link
to
published
article
;
Publisher
cop
...</
td
>
<
td
>
NaN
</
td
>
<
td
>
8593
</
td
>
</
tr
>
<
tr
>
<
td
>
8593
</
td
>
<
td
>
608
</
td
>
<
td
>
2475
-
9953
</
td
>
<
td
>
33503
</
td
>
<
td
>
https
:
//v2.sherpa.ac.uk/id/publisher_policy/10</td>
<
td
>
no
</
td
>
<
td
>
yes
</
td
>
<
td
>
published
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
any_repository
;
this_journal
</
td
>
<
td
>
Any
Repository
</
td
>
<
td
>
Journal
Website
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
8594
</
td
>
</
tr
>
<
tr
>
<
td
>
8594
</
td
>
<
td
>
608
</
td
>
<
td
>
2475
-
9953
</
td
>
<
td
>
33503
</
td
>
<
td
>
https
:
//v2.sherpa.ac.uk/id/publisher_policy/10</td>
<
td
>
no
</
td
>
<
td
>
yes
</
td
>
<
td
>
published
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
any_repository
;
this_journal
</
td
>
<
td
>
Any
Repository
</
td
>
<
td
>
Journal
Website
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
8595
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
8595
rows
×
29
columns
</
p
>
</
div
>
```
python
#
export
csv
sherpa_policies
.
to_csv
(
'
sample
/
sherpa_policies_brut
.
tsv
'
,
sep
=
'\t'
,
encoding
=
'
utf
-
8
'
,
index
=
False
)
```
```
python
#
export
excel
sherpa_policies
.
to_excel
(
'
sample
/
sherpa_policies_brut
.
xlsx
'
,
index
=
False
)
```
##
Calcul
de
la
cat
é
gorie
"green"
et
export
final
des
journaux
```
python
sherpa_policies
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
journal
</
th
>
<
th
>
issn
</
th
>
<
th
>
sherpa_id
</
th
>
<
th
>
sherpa_uri
</
th
>
<
th
>
open_access_prohibited
</
th
>
<
th
>
additional_oa_fee
</
th
>
<
th
>
article_version
</
th
>
<
th
>
license
</
th
>
<
th
>
embargo
</
th
>
<
th
>
prerequisites
</
th
>
<
th
>
prerequisite_funders
</
th
>
<
th
>
prerequisite_funders_name
</
th
>
<
th
>
prerequisite_funders_fundref
</
th
>
<
th
>
prerequisite_funders_ror
</
th
>
<
th
>
prerequisite_funders_country
</
th
>
<
th
>
prerequisite_funders_url
</
th
>
<
th
>
prerequisite_funders_sherpa_id
</
th
>
<
th
>
prerequisite_subjects
</
th
>
<
th
>
location
</
th
>
<
th
>
locations_ir
</
th
>
<
th
>
locations_not_ir
</
th
>
<
th
>
named_repository
</
th
>
<
th
>
named_academic_social_network
</
th
>
<
th
>
copyright_owner
</
th
>
<
th
>
publisher_deposit
</
th
>
<
th
>
archiving
</
th
>
<
th
>
conditions
</
th
>
<
th
>
public_notes
</
th
>
<
th
>
id
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
532
</
td
>
<
td
>
0001
-
2815
</
td
>
<
td
>
11905
</
td
>
<
td
>
https
:
//v2.sherpa.ac.uk/id/publisher_policy/2050</td>
<
td
>
no
</
td
>
<
td
>
no
</
td
>
<
td
>
submitted
</
td
>
<
td
></
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
authors_homepage
;
named_repository
;
non_comm
...</
td
>
<
td
>
Non
-
Commercial
Institutional
Repository
</
td
>
<
td
>
Author
'
s
Homepage
;
arXiv
;
AgEcon
;
PhilPaper
...</
td
>
<
td
>
arXiv
;
AgEcon
;
PhilPapers
;
PubMed
Central
;...</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
Must
acknowledge
acceptance
for
publication
;
...</
td
>
<
td
>
NaN
</
td
>
<
td
>
1
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
532
</
td
>
<
td
>
0001
-
2815
</
td
>
<
td
>
11905
</
td
>
<
td
>
https
:
//v2.sherpa.ac.uk/id/publisher_policy/2050</td>
<
td
>
no
</
td
>
<
td
>
no
</
td
>
<
td
>
accepted
</
td
>
<
td
></
td
>
<
td
>
12
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
authors_homepage
;
named_repository
;
non_comm
...</
td
>
<
td
>
Non
-
Commercial
Institutional
Repository
</
td
>
<
td
>
Author
'
s
Homepage
;
arXiv
;
AgEcon
;
PhilPaper
...</
td
>
<
td
>
arXiv
;
AgEcon
;
PhilPapers
;
PubMed
Central
;...</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
Publisher
source
must
be
acknowledged
with
cit
...</
td
>
<
td
>
NaN
</
td
>
<
td
>
2
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
532
</
td
>
<
td
>
0001
-
2815
</
td
>
<
td
>
11905
</
td
>
<
td
>
https
:
//v2.sherpa.ac.uk/id/publisher_policy/3315</td>
<
td
>
no
</
td
>
<
td
>
yes
</
td
>
<
td
>
published
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
any_website
;
institutional_repository
;
named
...</
td
>
<
td
>
Any
Website
;
Institutional
Repository
</
td
>
<
td
>
PubMed
Central
;
Subject
Repository
;
Journal
...</
td
>
<
td
>
PubMed
Central
</
td
>
<
td
>
NaN
</
td
>
<
td
>
authors
</
td
>
<
td
>
disciplinary
(
PubMed
Central
)
;</
td
>
<
td
>
True
</
td
>
<
td
>
Published
source
must
be
acknowledged
</
td
>
<
td
>
NaN
</
td
>
<
td
>
3
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
532
</
td
>
<
td
>
0001
-
2815
</
td
>
<
td
>
11905
</
td
>
<
td
>
https
:
//v2.sherpa.ac.uk/id/publisher_policy/3315</td>
<
td
>
no
</
td
>
<
td
>
yes
</
td
>
<
td
>
published
</
td
>
<
td
>
cc_by_nc_nd
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
any_website
;
named_repository
;
non_commercia
...</
td
>
<
td
>
Any
Website
;
Non
-
Commercial
Institutional
Rep
...</
td
>
<
td
>
PubMed
Central
;
Non
-
Commercial
Subject
Reposi
...</
td
>
<
td
>
PubMed
Central
</
td
>
<
td
>
NaN
</
td
>
<
td
>
authors
</
td
>
<
td
>
disciplinary
(
PubMed
Central
)
;</
td
>
<
td
>
True
</
td
>
<
td
>
Published
source
must
be
acknowledged
</
td
>
<
td
>
NaN
</
td
>
<
td
>
4
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
498
</
td
>
<
td
>
0001
-
4842
</
td
>
<
td
>
7760
</
td
>
<
td
>
https
:
//v2.sherpa.ac.uk/id/publisher_policy/4</td>
<
td
>
no
</
td
>
<
td
>
no
</
td
>
<
td
>
submitted
</
td
>
<
td
></
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
named_repository
;
preprint_repository
;
subje
...</
td
>
<
td
></
td
>
<
td
>
ChemRxiv
;
bioRxiv
;
arXiv
;
Preprint
Reposito
...</
td
>
<
td
>
ChemRxiv
;
bioRxiv
;
arXiv
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
False
</
td
>
<
td
>
Must
not
violate
ACS
ethical
Guidelines
;
Must
...</
td
>
<
td
>
NaN
</
td
>
<
td
>
5
</
td
>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
8590
</
td
>
<
td
>
608
</
td
>
<
td
>
2475
-
9953
</
td
>
<
td
>
33503
</
td
>
<
td
>
https
:
//v2.sherpa.ac.uk/id/publisher_policy/10</td>
<
td
>
no
</
td
>
<
td
>
no
</
td
>
<
td
>
submitted
</
td
>
<
td
></
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
authors_homepage
;
institutional_repository
;
...</
td
>
<
td
>
Institutional
Repository
;
Institutional
Website
</
td
>
<
td
>
Author
'
s
Homepage
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
Must
link
to
published
article
;
Publisher
cop
...</
td
>
<
td
>
NaN
</
td
>
<
td
>
8591
</
td
>
</
tr
>
<
tr
>
<
td
>
8591
</
td
>
<
td
>
608
</
td
>
<
td
>
2475
-
9953
</
td
>
<
td
>
33503
</
td
>
<
td
>
https
:
//v2.sherpa.ac.uk/id/publisher_policy/10</td>
<
td
>
no
</
td
>
<
td
>
no
</
td
>
<
td
>
accepted
</
td
>
<
td
></
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
authors_homepage
;
institutional_repository
;
...</
td
>
<
td
>
Institutional
Repository
;
Institutional
Website
</
td
>
<
td
>
Author
'
s
Homepage
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
Must
link
to
published
article
;
Publisher
cop
...</
td
>
<
td
>
NaN
</
td
>
<
td
>
8592
</
td
>
</
tr
>
<
tr
>
<
td
>
8592
</
td
>
<
td
>
608
</
td
>
<
td
>
2475
-
9953
</
td
>
<
td
>
33503
</
td
>
<
td
>
https
:
//v2.sherpa.ac.uk/id/publisher_policy/10</td>
<
td
>
no
</
td
>
<
td
>
no
</
td
>
<
td
>
published
</
td
>
<
td
></
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
authors_homepage
;
institutional_repository
;
...</
td
>
<
td
>
Institutional
Repository
;
Institutional
Website
</
td
>
<
td
>
Author
'
s
Homepage
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
Must
link
to
published
article
;
Publisher
cop
...</
td
>
<
td
>
NaN
</
td
>
<
td
>
8593
</
td
>
</
tr
>
<
tr
>
<
td
>
8593
</
td
>
<
td
>
608
</
td
>
<
td
>
2475
-
9953
</
td
>
<
td
>
33503
</
td
>
<
td
>
https
:
//v2.sherpa.ac.uk/id/publisher_policy/10</td>
<
td
>
no
</
td
>
<
td
>
yes
</
td
>
<
td
>
published
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
any_repository
;
this_journal
</
td
>
<
td
>
Any
Repository
</
td
>
<
td
>
Journal
Website
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
8594
</
td
>
</
tr
>
<
tr
>
<
td
>
8594
</
td
>
<
td
>
608
</
td
>
<
td
>
2475
-
9953
</
td
>
<
td
>
33503
</
td
>
<
td
>
https
:
//v2.sherpa.ac.uk/id/publisher_policy/10</td>
<
td
>
no
</
td
>
<
td
>
yes
</
td
>
<
td
>
published
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
any_repository
;
this_journal
</
td
>
<
td
>
Any
Repository
</
td
>
<
td
>
Journal
Website
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
8595
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
8595
rows
×
29
columns
</
p
>
</
div
>
```
python
sherpa_policies_ir
=
sherpa_policies
.
loc
[(
sherpa_policies
[
'
archiving
'
]
==
True
)
&
(
sherpa_policies
[
'
article_version
'
]
==
'
published
'
)
&
(
sherpa_policies
[
'
prerequisite_funders
'
].
isna
())][[
'
journal
'
,
'
embargo
'
,
'
license
'
,
'
conditions
'
]]
sherpa_policies_ir
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
journal
</
th
>
<
th
>
embargo
</
th
>
<
th
>
license
</
th
>
<
th
>
conditions
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
532
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
Published
source
must
be
acknowledged
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
532
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by_nc_nd
</
td
>
<
td
>
Published
source
must
be
acknowledged
</
td
>
</
tr
>
<
tr
>
<
td
>
9
</
td
>
<
td
>
498
</
td
>
<
td
>
12
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
10
</
td
>
<
td
>
498
</
td
>
<
td
>
12
</
td
>
<
td
>
cc_by_nc_nd
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
11
</
td
>
<
td
>
498
</
td
>
<
td
>
12
</
td
>
<
td
>
bespoke_license
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
8588
</
td
>
<
td
>
533
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
8589
</
td
>
<
td
>
533
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
8592
</
td
>
<
td
>
608
</
td
>
<
td
>
0
</
td
>
<
td
></
td
>
<
td
>
Must
link
to
published
article
;
Publisher
cop
...</
td
>
</
tr
>
<
tr
>
<
td
>
8593
</
td
>
<
td
>
608
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
8594
</
td
>
<
td
>
608
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
1118
rows
×
4
columns
</
p
>
</
div
>
```
python
#
dedup
sherpa_policies_ir_id
=
sherpa_policies_ir
[[
'
journal
'
,
'
embargo
'
]].
sort_values
(
by
=[
'
journal
'
,
'
embargo
'
])
sherpa_policies_ir_dedup
=
sherpa_policies_ir_id
.
drop_duplicates
(
subset
=
'
journal
'
)
sherpa_policies_ir_dedup
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
journal
</
th
>
<
th
>
embargo
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
2367
</
td
>
<
td
>
2
</
td
>
<
td
>
0
</
td
>
</
tr
>
<
tr
>
<
td
>
8342
</
td
>
<
td
>
3
</
td
>
<
td
>
0
</
td
>
</
tr
>
<
tr
>
<
td
>
7366
</
td
>
<
td
>
5
</
td
>
<
td
>
0
</
td
>
</
tr
>
<
tr
>
<
td
>
261
</
td
>
<
td
>
6
</
td
>
<
td
>
12
</
td
>
</
tr
>
<
tr
>
<
td
>
7086
</
td
>
<
td
>
7
</
td
>
<
td
>
0
</
td
>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
6479
</
td
>
<
td
>
996
</
td
>
<
td
>
0
</
td
>
</
tr
>
<
tr
>
<
td
>
6873
</
td
>
<
td
>
997
</
td
>
<
td
>
0
</
td
>
</
tr
>
<
tr
>
<
td
>
1823
</
td
>
<
td
>
998
</
td
>
<
td
>
0
</
td
>
</
tr
>
<
tr
>
<
td
>
3944
</
td
>
<
td
>
999
</
td
>
<
td
>
0
</
td
>
</
tr
>
<
tr
>
<
td
>
6750
</
td
>
<
td
>
1000
</
td
>
<
td
>
0
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
579
rows
×
2
columns
</
p
>
</
div
>
```
python
#
ajout
de
la
ct
é
gorie
green
(
2
)
sherpa_policies_ir_dedup
[
'
oa_status
'
]
=
2
sherpa_policies_ir_dedup
```
C
:\
Users
\
iriarte
\
AppData
\
Local
\
Continuum
\
anaconda3
\
lib
\
site
-
packages
\
ipykernel_launcher
.
py
:
2
:
SettingWithCopyWarning
:
A
value
is
trying
to
be
set
on
a
copy
of
a
slice
from
a
DataFrame
.
Try
using
.
loc
[
row_indexer
,
col_indexer
]
=
value
instead
See
the
caveats
in
the
documentation
:
http
:
//pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
journal
</
th
>
<
th
>
embargo
</
th
>
<
th
>
oa_status
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
2367
</
td
>
<
td
>
2
</
td
>
<
td
>
0
</
td
>
<
td
>
2
</
td
>
</
tr
>
<
tr
>
<
td
>
8342
</
td
>
<
td
>
3
</
td
>
<
td
>
0
</
td
>
<
td
>
2
</
td
>
</
tr
>
<
tr
>
<
td
>
7366
</
td
>
<
td
>
5
</
td
>
<
td
>
0
</
td
>
<
td
>
2
</
td
>
</
tr
>
<
tr
>
<
td
>
261
</
td
>
<
td
>
6
</
td
>
<
td
>
12
</
td
>
<
td
>
2
</
td
>
</
tr
>
<
tr
>
<
td
>
7086
</
td
>
<
td
>
7
</
td
>
<
td
>
0
</
td
>
<
td
>
2
</
td
>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
6479
</
td
>
<
td
>
996
</
td
>
<
td
>
0
</
td
>
<
td
>
2
</
td
>
</
tr
>
<
tr
>
<
td
>
6873
</
td
>
<
td
>
997
</
td
>
<
td
>
0
</
td
>
<
td
>
2
</
td
>
</
tr
>
<
tr
>
<
td
>
1823
</
td
>
<
td
>
998
</
td
>
<
td
>
0
</
td
>
<
td
>
2
</
td
>
</
tr
>
<
tr
>
<
td
>
3944
</
td
>
<
td
>
999
</
td
>
<
td
>
0
</
td
>
<
td
>
2
</
td
>
</
tr
>
<
tr
>
<
td
>
6750
</
td
>
<
td
>
1000
</
td
>
<
td
>
0
</
td
>
<
td
>
2
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
579
rows
×
3
columns
</
p
>
</
div
>
```
python
#
merge
avec
les
revues
sherpa_policies_ir_dedup
=
sherpa_policies_ir_dedup
.
rename
(
columns
={
'
journal
'
:
'
id
'
})
journals_export
=
pd
.
merge
(
journals_export
,
sherpa_policies_ir_dedup
,
on
=
'
id
'
,
how
=
'
left
'
)
journals_export
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
id
</
th
>
<
th
>
name
</
th
>
<
th
>
name_short_iso_4
</
th
>
<
th
>
starting_year
</
th
>
<
th
>
end_year
</
th
>
<
th
>
website
</
th
>
<
th
>
country
</
th
>
<
th
>
language
</
th
>
<
th
>
oa_status_x
</
th
>
<
th
>
publisher
</
th
>
<
th
>
doaj_seal
</
th
>
<
th
>
doaj_status
</
th
>
<
th
>
lockss
</
th
>
<
th
>
portico
</
th
>
<
th
>
nlch
</
th
>
<
th
>
qoam_av_score
</
th
>
<
th
>
embargo
</
th
>
<
th
>
oa_status_y
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
Revue
m
é
dicale
suisse
</
td
>
<
td
>
Rev
.
m
é
d
.
suisse
</
td
>
<
td
>
2005
</
td
>
<
td
>
9999
</
td
>
<
td
></
td
>
<
td
>
215
</
td
>
<
td
>
138
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
2
</
td
>
<
td
>
Physical
Review
Letters
</
td
>
<
td
>
Phys
.
rev
.
lett
.
(
Print
)</
td
>
<
td
>
1958
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//prl.aps.org/</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
2
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0
</
td
>
<
td
>
2.0
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
3
</
td
>
<
td
>
PLoS
ONE
</
td
>
<
td
></
td
>
<
td
>
2006
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.plosone.org/</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
5
</
td
>
<
td
>
3
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
4.035714
</
td
>
<
td
>
0
</
td
>
<
td
>
2.0
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
4
</
td
>
<
td
>
EU
-
top
í
as
</
td
>
<
td
>
EU
-
top
í
as
</
td
>
<
td
>
2011
</
td
>
<
td
>
9999
</
td
>
<
td
></
td
>
<
td
>
209
</
td
>
<
td
>
124
,
138
,
402
,
292
</
td
>
<
td
>
1
</
td
>
<
td
>
4
,
5
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
5
</
td
>
<
td
>
Physical
review
B
:
Condensed
matter
and
materi
...</
td
>
<
td
>
Phys
.
rev
.,
B
,
Condens
.
matter
mater
.
phys
.</
td
>
<
td
>
1998
</
td
>
<
td
>
2015
</
td
>
<
td
>
http
:
//journals.aps.org/prb/</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
6
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0
</
td
>
<
td
>
2.0
</
td
>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
906
</
td
>
<
td
>
997
</
td
>
<
td
>
Smart
Materials
and
Structures
</
td
>
<
td
>
Smart
mater
.
struct
.
(
Print
)</
td
>
<
td
>
1992
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//iopscience.iop.org/0964-1726</td>
<
td
>
234
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
47
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0
</
td
>
<
td
>
2.0
</
td
>
</
tr
>
<
tr
>
<
td
>
907
</
td
>
<
td
>
998
</
td
>
<
td
>
Journal
of
Pediatric
Surgery
</
td
>
<
td
>
J
.
pediatr
.
surg
.
(
Print
)</
td
>
<
td
>
1966
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.jpedsurg.org/</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
75
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0
</
td
>
<
td
>
2.0
</
td
>
</
tr
>
<
tr
>
<
td
>
908
</
td
>
<
td
>
999
</
td
>
<
td
>
Probability
Theory
and
Related
Fields
</
td
>
<
td
>
Probab
.
theory
relat
.
fields
(
Internet
)</
td
>
<
td
>
uuuu
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.springerlink.com/content/100451/?p=...</td>
<
td
>
83
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
8
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0
</
td
>
<
td
>
2.0
</
td
>
</
tr
>
<
tr
>
<
td
>
909
</
td
>
<
td
>
1000
</
td
>
<
td
>
Renewable
Energy
</
td
>
<
td
>
Renew
.
energy
</
td
>
<
td
>
1991
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.elsevier.com/wps/product/cws_home/9...</td>
<
td
>
234
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
119
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0
</
td
>
<
td
>
2.0
</
td
>
</
tr
>
<
tr
>
<
td
>
910
</
td
>
<
td
>
1001
</
td
>
<
td
>
Journal
of
applied
physiology
:
respiratory
,
en
...</
td
>
<
td
>
J
.
appl
.
physiol
.:
respir
.,
environ
.
exercise
...</
td
>
<
td
>
1977
</
td
>
<
td
>
1984
</
td
>
<
td
>
https
:
//www.physiology.org/journal/jappl</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
217
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
911
rows
×
18
columns
</
p
>
</
div
>
```
python
#
choix
de
la
cat
é
gorie
OA
journals_export
[
'
oa_status
'
]
=
journals_export
[
'
oa_status_x
'
]
journals_export
.
loc
[(
journals_export
[
'
oa_status_x
'
]
==
1
)
&
(
journals_export
[
'
oa_status_y
'
].
notna
()),
'
oa_status
'
]
=
journals_export
[
'
oa_status_y
'
]
journals_export
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
id
</
th
>
<
th
>
name
</
th
>
<
th
>
name_short_iso_4
</
th
>
<
th
>
starting_year
</
th
>
<
th
>
end_year
</
th
>
<
th
>
website
</
th
>
<
th
>
country
</
th
>
<
th
>
language
</
th
>
<
th
>
oa_status_x
</
th
>
<
th
>
publisher
</
th
>
<
th
>
doaj_seal
</
th
>
<
th
>
doaj_status
</
th
>
<
th
>
lockss
</
th
>
<
th
>
portico
</
th
>
<
th
>
nlch
</
th
>
<
th
>
qoam_av_score
</
th
>
<
th
>
embargo
</
th
>
<
th
>
oa_status_y
</
th
>
<
th
>
oa_status
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
Revue
m
é
dicale
suisse
</
td
>
<
td
>
Rev
.
m
é
d
.
suisse
</
td
>
<
td
>
2005
</
td
>
<
td
>
9999
</
td
>
<
td
></
td
>
<
td
>
215
</
td
>
<
td
>
138
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1.0
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
2
</
td
>
<
td
>
Physical
Review
Letters
</
td
>
<
td
>
Phys
.
rev
.
lett
.
(
Print
)</
td
>
<
td
>
1958
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//prl.aps.org/</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
2
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0
</
td
>
<
td
>
2.0
</
td
>
<
td
>
2.0
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
3
</
td
>
<
td
>
PLoS
ONE
</
td
>
<
td
></
td
>
<
td
>
2006
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.plosone.org/</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
5
</
td
>
<
td
>
3
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
4.035714
</
td
>
<
td
>
0
</
td
>
<
td
>
2.0
</
td
>
<
td
>
5.0
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
4
</
td
>
<
td
>
EU
-
top
í
as
</
td
>
<
td
>
EU
-
top
í
as
</
td
>
<
td
>
2011
</
td
>
<
td
>
9999
</
td
>
<
td
></
td
>
<
td
>
209
</
td
>
<
td
>
124
,
138
,
402
,
292
</
td
>
<
td
>
1
</
td
>
<
td
>
4
,
5
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1.0
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
5
</
td
>
<
td
>
Physical
review
B
:
Condensed
matter
and
materi
...</
td
>
<
td
>
Phys
.
rev
.,
B
,
Condens
.
matter
mater
.
phys
.</
td
>
<
td
>
1998
</
td
>
<
td
>
2015
</
td
>
<
td
>
http
:
//journals.aps.org/prb/</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
6
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0
</
td
>
<
td
>
2.0
</
td
>
<
td
>
2.0
</
td
>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
906
</
td
>
<
td
>
997
</
td
>
<
td
>
Smart
Materials
and
Structures
</
td
>
<
td
>
Smart
mater
.
struct
.
(
Print
)</
td
>
<
td
>
1992
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//iopscience.iop.org/0964-1726</td>
<
td
>
234
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
47
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0
</
td
>
<
td
>
2.0
</
td
>
<
td
>
2.0
</
td
>
</
tr
>
<
tr
>
<
td
>
907
</
td
>
<
td
>
998
</
td
>
<
td
>
Journal
of
Pediatric
Surgery
</
td
>
<
td
>
J
.
pediatr
.
surg
.
(
Print
)</
td
>
<
td
>
1966
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.jpedsurg.org/</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
75
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0
</
td
>
<
td
>
2.0
</
td
>
<
td
>
2.0
</
td
>
</
tr
>
<
tr
>
<
td
>
908
</
td
>
<
td
>
999
</
td
>
<
td
>
Probability
Theory
and
Related
Fields
</
td
>
<
td
>
Probab
.
theory
relat
.
fields
(
Internet
)</
td
>
<
td
>
uuuu
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.springerlink.com/content/100451/?p=...</td>
<
td
>
83
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
8
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0
</
td
>
<
td
>
2.0
</
td
>
<
td
>
2.0
</
td
>
</
tr
>
<
tr
>
<
td
>
909
</
td
>
<
td
>
1000
</
td
>
<
td
>
Renewable
Energy
</
td
>
<
td
>
Renew
.
energy
</
td
>
<
td
>
1991
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.elsevier.com/wps/product/cws_home/9...</td>
<
td
>
234
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
119
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0
</
td
>
<
td
>
2.0
</
td
>
<
td
>
2.0
</
td
>
</
tr
>
<
tr
>
<
td
>
910
</
td
>
<
td
>
1001
</
td
>
<
td
>
Journal
of
applied
physiology
:
respiratory
,
en
...</
td
>
<
td
>
J
.
appl
.
physiol
.:
respir
.,
environ
.
exercise
...</
td
>
<
td
>
1977
</
td
>
<
td
>
1984
</
td
>
<
td
>
https
:
//www.physiology.org/journal/jappl</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
1
</
td
>
<
td
>
217
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1.0
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
911
rows
×
19
columns
</
p
>
</
div
>
```
python
#
6
:
Diamond
#
5
:
Gold
#
4
:
Full
#
3
:
Hybrid
#
2
:
Green
#
1
:
UNKNOWN
journals_export
[
'
oa_status
'
].
value_counts
()
```
2.0
518
1.0
306
5.0
70
6.0
17
Name
:
oa_status
,
dtype
:
int64
```
python
del
journals_export
[
'
embargo
'
]
del
journals_export
[
'
oa_status_x
'
]
del
journals_export
[
'
oa_status_y
'
]
journals_export
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
id
</
th
>
<
th
>
name
</
th
>
<
th
>
name_short_iso_4
</
th
>
<
th
>
starting_year
</
th
>
<
th
>
end_year
</
th
>
<
th
>
website
</
th
>
<
th
>
country
</
th
>
<
th
>
language
</
th
>
<
th
>
publisher
</
th
>
<
th
>
doaj_seal
</
th
>
<
th
>
doaj_status
</
th
>
<
th
>
lockss
</
th
>
<
th
>
portico
</
th
>
<
th
>
nlch
</
th
>
<
th
>
qoam_av_score
</
th
>
<
th
>
oa_status
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
Revue
m
é
dicale
suisse
</
td
>
<
td
>
Rev
.
m
é
d
.
suisse
</
td
>
<
td
>
2005
</
td
>
<
td
>
9999
</
td
>
<
td
></
td
>
<
td
>
215
</
td
>
<
td
>
138
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1.0
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
2
</
td
>
<
td
>
Physical
Review
Letters
</
td
>
<
td
>
Phys
.
rev
.
lett
.
(
Print
)</
td
>
<
td
>
1958
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//prl.aps.org/</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
2
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
2.0
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
3
</
td
>
<
td
>
PLoS
ONE
</
td
>
<
td
></
td
>
<
td
>
2006
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.plosone.org/</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
3
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
4.035714
</
td
>
<
td
>
5.0
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
4
</
td
>
<
td
>
EU
-
top
í
as
</
td
>
<
td
>
EU
-
top
í
as
</
td
>
<
td
>
2011
</
td
>
<
td
>
9999
</
td
>
<
td
></
td
>
<
td
>
209
</
td
>
<
td
>
124
,
138
,
402
,
292
</
td
>
<
td
>
4
,
5
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1.0
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
5
</
td
>
<
td
>
Physical
review
B
:
Condensed
matter
and
materi
...</
td
>
<
td
>
Phys
.
rev
.,
B
,
Condens
.
matter
mater
.
phys
.</
td
>
<
td
>
1998
</
td
>
<
td
>
2015
</
td
>
<
td
>
http
:
//journals.aps.org/prb/</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
6
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
2.0
</
td
>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
906
</
td
>
<
td
>
997
</
td
>
<
td
>
Smart
Materials
and
Structures
</
td
>
<
td
>
Smart
mater
.
struct
.
(
Print
)</
td
>
<
td
>
1992
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//iopscience.iop.org/0964-1726</td>
<
td
>
234
</
td
>
<
td
>
124
</
td
>
<
td
>
47
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
2.0
</
td
>
</
tr
>
<
tr
>
<
td
>
907
</
td
>
<
td
>
998
</
td
>
<
td
>
Journal
of
Pediatric
Surgery
</
td
>
<
td
>
J
.
pediatr
.
surg
.
(
Print
)</
td
>
<
td
>
1966
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.jpedsurg.org/</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
75
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
2.0
</
td
>
</
tr
>
<
tr
>
<
td
>
908
</
td
>
<
td
>
999
</
td
>
<
td
>
Probability
Theory
and
Related
Fields
</
td
>
<
td
>
Probab
.
theory
relat
.
fields
(
Internet
)</
td
>
<
td
>
uuuu
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.springerlink.com/content/100451/?p=...</td>
<
td
>
83
</
td
>
<
td
>
124
</
td
>
<
td
>
8
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
NaN
</
td
>
<
td
>
2.0
</
td
>
</
tr
>
<
tr
>
<
td
>
909
</
td
>
<
td
>
1000
</
td
>
<
td
>
Renewable
Energy
</
td
>
<
td
>
Renew
.
energy
</
td
>
<
td
>
1991
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.elsevier.com/wps/product/cws_home/9...</td>
<
td
>
234
</
td
>
<
td
>
124
</
td
>
<
td
>
119
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
2.0
</
td
>
</
tr
>
<
tr
>
<
td
>
910
</
td
>
<
td
>
1001
</
td
>
<
td
>
Journal
of
applied
physiology
:
respiratory
,
en
...</
td
>
<
td
>
J
.
appl
.
physiol
.:
respir
.,
environ
.
exercise
...</
td
>
<
td
>
1977
</
td
>
<
td
>
1984
</
td
>
<
td
>
https
:
//www.physiology.org/journal/jappl</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
217
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1.0
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
911
rows
×
16
columns
</
p
>
</
div
>
```
python
journals_export
[
'
oa_status
'
]
=
journals_export
[
'
oa_status
'
].
astype
(
int
)
journals_export
```
<
div
>
<
style
scoped
>
.
dataframe
tbody
tr
th
:
only
-
of
-
type
{
vertical
-
align
:
middle
;
}
.
dataframe
tbody
tr
th
{
vertical
-
align
:
top
;
}
.
dataframe
thead
th
{
text
-
align
:
right
;
}
</
style
>
<
table
border
=
"1"
class
=
"dataframe"
>
<
thead
>
<
tr
style
=
"text-align: right;"
>
<
th
></
th
>
<
th
>
id
</
th
>
<
th
>
name
</
th
>
<
th
>
name_short_iso_4
</
th
>
<
th
>
starting_year
</
th
>
<
th
>
end_year
</
th
>
<
th
>
website
</
th
>
<
th
>
country
</
th
>
<
th
>
language
</
th
>
<
th
>
publisher
</
th
>
<
th
>
doaj_seal
</
th
>
<
th
>
doaj_status
</
th
>
<
th
>
lockss
</
th
>
<
th
>
portico
</
th
>
<
th
>
nlch
</
th
>
<
th
>
qoam_av_score
</
th
>
<
th
>
oa_status
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
Revue
m
é
dicale
suisse
</
td
>
<
td
>
Rev
.
m
é
d
.
suisse
</
td
>
<
td
>
2005
</
td
>
<
td
>
9999
</
td
>
<
td
></
td
>
<
td
>
215
</
td
>
<
td
>
138
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
2
</
td
>
<
td
>
Physical
Review
Letters
</
td
>
<
td
>
Phys
.
rev
.
lett
.
(
Print
)</
td
>
<
td
>
1958
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//prl.aps.org/</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
2
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
2
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
3
</
td
>
<
td
>
PLoS
ONE
</
td
>
<
td
></
td
>
<
td
>
2006
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.plosone.org/</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
3
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
4.035714
</
td
>
<
td
>
5
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
4
</
td
>
<
td
>
EU
-
top
í
as
</
td
>
<
td
>
EU
-
top
í
as
</
td
>
<
td
>
2011
</
td
>
<
td
>
9999
</
td
>
<
td
></
td
>
<
td
>
209
</
td
>
<
td
>
124
,
138
,
402
,
292
</
td
>
<
td
>
4
,
5
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
5
</
td
>
<
td
>
Physical
review
B
:
Condensed
matter
and
materi
...</
td
>
<
td
>
Phys
.
rev
.,
B
,
Condens
.
matter
mater
.
phys
.</
td
>
<
td
>
1998
</
td
>
<
td
>
2015
</
td
>
<
td
>
http
:
//journals.aps.org/prb/</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
6
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
2
</
td
>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
906
</
td
>
<
td
>
997
</
td
>
<
td
>
Smart
Materials
and
Structures
</
td
>
<
td
>
Smart
mater
.
struct
.
(
Print
)</
td
>
<
td
>
1992
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//iopscience.iop.org/0964-1726</td>
<
td
>
234
</
td
>
<
td
>
124
</
td
>
<
td
>
47
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
2
</
td
>
</
tr
>
<
tr
>
<
td
>
907
</
td
>
<
td
>
998
</
td
>
<
td
>
Journal
of
Pediatric
Surgery
</
td
>
<
td
>
J
.
pediatr
.
surg
.
(
Print
)</
td
>
<
td
>
1966
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.jpedsurg.org/</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
75
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
2
</
td
>
</
tr
>
<
tr
>
<
td
>
908
</
td
>
<
td
>
999
</
td
>
<
td
>
Probability
Theory
and
Related
Fields
</
td
>
<
td
>
Probab
.
theory
relat
.
fields
(
Internet
)</
td
>
<
td
>
uuuu
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.springerlink.com/content/100451/?p=...</td>
<
td
>
83
</
td
>
<
td
>
124
</
td
>
<
td
>
8
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
NaN
</
td
>
<
td
>
2
</
td
>
</
tr
>
<
tr
>
<
td
>
909
</
td
>
<
td
>
1000
</
td
>
<
td
>
Renewable
Energy
</
td
>
<
td
>
Renew
.
energy
</
td
>
<
td
>
1991
</
td
>
<
td
>
9999
</
td
>
<
td
>
http
:
//www.elsevier.com/wps/product/cws_home/9...</td>
<
td
>
234
</
td
>
<
td
>
124
</
td
>
<
td
>
119
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
2
</
td
>
</
tr
>
<
tr
>
<
td
>
910
</
td
>
<
td
>
1001
</
td
>
<
td
>
Journal
of
applied
physiology
:
respiratory
,
en
...</
td
>
<
td
>
J
.
appl
.
physiol
.:
respir
.,
environ
.
exercise
...</
td
>
<
td
>
1977
</
td
>
<
td
>
1984
</
td
>
<
td
>
https
:
//www.physiology.org/journal/jappl</td>
<
td
>
236
</
td
>
<
td
>
124
</
td
>
<
td
>
217
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
911
rows
×
16
columns
</
p
>
</
div
>
```
python
#
export
csv
journals_export
.
to_csv
(
'
sample
/
journal_fin_sherpa
.
tsv
'
,
sep
=
'\t'
,
encoding
=
'
utf
-
8
'
,
index
=
False
)
```
```
python
#
export
excel
journals_export
.
to_excel
(
'
sample
/
journal_fin_sherpa
.
xlsx
'
,
index
=
False
)
```
```
python
#
export
csv
sherpa_policies_ir_dedup
.
to_csv
(
'
sample
/
journal_ir
.
tsv
'
,
sep
=
'\t'
,
encoding
=
'
utf
-
8
'
,
index
=
False
)
```
```
python
#
export
excel
sherpa_policies_ir_dedup
.
to_excel
(
'
sample
/
journal_ir
.
xlsx
'
,
index
=
False
)
```
```
python
```
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