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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
de
modifier
les
donn
é
es
extraites
des
differentes
sources
et
les
exporter
dans
les
tables
de
l
'
application
OACCT
.
Auteur
:
**
Pablo
Iriarte
**,
Universit
é
de
Gen
è
ve
(
pablo
.
iriarte
@
unige
.
ch
)
Date
de
derni
è
re
mise
à
jour
:
08.09.2021
```
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
)
#
definir
le
debut
des
ids
id_start
=
1
```
##
Ajout
des
rabais
pour
les
revues
des
licences
Read
&
Publish
Journals
list
by
publisher
:
*
https
:
//consortium.ch/elsevier_titlelist_publication
*
https
:
//consortium.ch/springer_titlelist_publication
*
https
:
//consortium.ch/wiley_titlelist_publish
*
https
:
//consortium.ch/tandf_titlelist_publish
*
https
:
//consortium.ch/sage_titlelist_publish
*
https
:
//consortium.ch/cup_titlelist_publish
Licence
term
:
*
Elsevier
:
2020
-
2023
*
Springer
Nature
:
2020
-
2022
*
Wiley
:
2021
-
2024
*
Taylor
&
Francis
:
2021
-
2023
*
Cambridge
University
Press
(
CUP
)
:
2021
-
2023
CC
licences
:
*
Elsevier
:
CC
-
BY
,
CC
-
BY
-
NC
-
ND
*
Springer
Nature
:
CC
-
BY
,
CC
-
BY
-
NC
*
Wiley
:
CC
-
BY
,
CC
-
BY
-
NC
,
CC
-
BY
-
NC
-
ND
*
Taylor
&
Francis
:
CC
-
BY
*
Cambridge
University
Press
(
CUP
)
:
CC
-
BY
,
CC
-
BY
-
NC
,
CC
-
BY
-
NC
-
ND
,
CC
-
BY
-
NC
-
SA
Special
conditions
:
*
Cambridge
University
Press
(
CUP
)
:
Only
the
following
article
types
are
covered
:
Research
Articles
,
Review
Articles
,
Rapid
Communication
,
Brief
Reports
and
Case
Reports
##
Import
du
fichier
des
issns
```
python
issn
=
pd
.
read_csv
(
'
sample
/
issn
.
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
>
id
</
th
>
<
th
>
issn
</
th
>
<
th
>
journal
</
th
>
<
th
>
issn_type
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0001
-
2815
</
td
>
<
td
>
532
</
td
>
<
td
>
1
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
2
</
td
>
<
td
>
1399
-
0039
</
td
>
<
td
>
532
</
td
>
<
td
>
2
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
3
</
td
>
<
td
>
0001
-
4842
</
td
>
<
td
>
498
</
td
>
<
td
>
1
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
4
</
td
>
<
td
>
1520
-
4898
</
td
>
<
td
>
498
</
td
>
<
td
>
2
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
5
</
td
>
<
td
>
0001
-
4966
</
td
>
<
td
>
789
</
td
>
<
td
>
1
</
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
>
533
</
td
>
<
td
>
3
</
td
>
</
tr
>
<
tr
>
<
td
>
1756
</
td
>
<
td
>
1757
</
td
>
<
td
>
2470
-
0053
</
td
>
<
td
>
533
</
td
>
<
td
>
2
</
td
>
</
tr
>
<
tr
>
<
td
>
1757
</
td
>
<
td
>
1758
</
td
>
<
td
>
2475
-
9953
</
td
>
<
td
>
608
</
td
>
<
td
>
2
</
td
>
</
tr
>
<
tr
>
<
td
>
1758
</
td
>
<
td
>
1759
</
td
>
<
td
>
2504
-
4427
</
td
>
<
td
>
994
</
td
>
<
td
>
1
</
td
>
</
tr
>
<
tr
>
<
td
>
1759
</
td
>
<
td
>
1760
</
td
>
<
td
>
2504
-
4435
</
td
>
<
td
>
994
</
td
>
<
td
>
3
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
1760
rows
×
4
columns
</
p
>
</
div
>
```
python
#
open
publishers
publisher
=
pd
.
read_csv
(
'
sample
/
publisher
.
tsv
'
,
encoding
=
'
utf
-
8
'
,
header
=
0
,
sep
=
'\t'
)
publisher
```
<
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
>
name
</
th
>
<
th
>
country
</
th
>
<
th
>
city
</
th
>
<
th
>
state
</
th
>
<
th
>
starting_year
</
th
>
<
th
>
website
</
th
>
<
th
>
oa_policies
</
th
>
<
th
>
id
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
Revue
M
é
dicale
Suisse
</
td
>
<
td
>
999999
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
American
Physical
Society
</
td
>
<
td
>
236
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0
</
td
>
<
td
>
http
:
//www.aps.org/</td>
<
td
>
NaN
</
td
>
<
td
>
2
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
Public
Library
of
Science
</
td
>
<
td
>
236
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0
</
td
>
<
td
>
http
:
//www.plos.org/</td>
<
td
>
NaN
</
td
>
<
td
>
3
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
The
Global
Studies
Institute
de
l
’
Universit
é
d
...</
td
>
<
td
>
999999
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
4
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
Universitat
de
Val
è
ncia
,
Departamento
de
Teor
í
...</
td
>
<
td
>
999999
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
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
>
</
tr
>
<
tr
>
<
td
>
191
</
td
>
<
td
>[
American
Medical
Association
]</
td
>
<
td
>
999999
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0
</
td
>
<
td
>
http
:
//archneur.jamanetwork.com/issues.aspx</td>
<
td
>
NaN
</
td
>
<
td
>
192
</
td
>
</
tr
>
<
tr
>
<
td
>
192
</
td
>
<
td
>
Soci
é
t
é
botanique
de
Gen
è
ve
</
td
>
<
td
>
999999
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
193
</
td
>
</
tr
>
<
tr
>
<
td
>
193
</
td
>
<
td
>
Red
.:
Prof
.
Dr
.
F
.
Cavalli
,
Istituto
oncologic
...</
td
>
<
td
>
999999
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
194
</
td
>
</
tr
>
<
tr
>
<
td
>
194
</
td
>
<
td
>
Generative
Grammar
Group
of
the
Department
of
...</
td
>
<
td
>
999999
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
195
</
td
>
</
tr
>
<
tr
>
<
td
>
195
</
td
>
<
td
>
UNKNOWN
</
td
>
<
td
>
999999
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
196
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
196
rows
×
8
columns
</
p
>
</
div
>
```
python
publisher
.
loc
[
publisher
[
'
name
'
]
==
'
Elsevier
'
]
```
<
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
>
name
</
th
>
<
th
>
country
</
th
>
<
th
>
city
</
th
>
<
th
>
state
</
th
>
<
th
>
starting_year
</
th
>
<
th
>
website
</
th
>
<
th
>
oa_policies
</
th
>
<
th
>
id
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
10
</
td
>
<
td
>
Elsevier
</
td
>
<
td
>
236
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0
</
td
>
<
td
>
http
:
//www.elsevier.com/</td>
<
td
>
NaN
</
td
>
<
td
>
11
</
td
>
</
tr
>
</
tbody
>
</
table
>
</
div
>
```
python
publisher
.
loc
[(
publisher
[
'
name
'
]
==
'
Springer
Verlag
'
)
|
(
publisher
[
'
name
'
]
==
'
Nature
Research
'
)]
```
<
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
>
name
</
th
>
<
th
>
country
</
th
>
<
th
>
city
</
th
>
<
th
>
state
</
th
>
<
th
>
starting_year
</
th
>
<
th
>
website
</
th
>
<
th
>
oa_policies
</
th
>
<
th
>
id
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
8
</
td
>
<
td
>
Nature
Research
</
td
>
<
td
>
234
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0
</
td
>
<
td
>
http
:
//www.nature.com/</td>
<
td
>
NaN
</
td
>
<
td
>
9
</
td
>
</
tr
>
<
tr
>
<
td
>
28
</
td
>
<
td
>
Springer
Verlag
</
td
>
<
td
>
83
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0
</
td
>
<
td
>
http
:
//www.springerlink.com/?MUD=MP</td>
<
td
>
NaN
</
td
>
<
td
>
29
</
td
>
</
tr
>
</
tbody
>
</
table
>
</
div
>
```
python
publisher
.
loc
[
publisher
[
'
name
'
]
==
'
Wiley
'
]
```
<
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
>
name
</
th
>
<
th
>
country
</
th
>
<
th
>
city
</
th
>
<
th
>
state
</
th
>
<
th
>
starting_year
</
th
>
<
th
>
website
</
th
>
<
th
>
oa_policies
</
th
>
<
th
>
id
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
11
</
td
>
<
td
>
Wiley
</
td
>
<
td
>
236
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0
</
td
>
<
td
>
https
:
//www.wiley.com/en-gb</td>
<
td
>
NaN
</
td
>
<
td
>
12
</
td
>
</
tr
>
</
tbody
>
</
table
>
</
div
>
```
python
publisher
.
loc
[
publisher
[
'
name
'
]
==
'
Taylor
and
Francis
'
]
```
<
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
>
name
</
th
>
<
th
>
country
</
th
>
<
th
>
city
</
th
>
<
th
>
state
</
th
>
<
th
>
starting_year
</
th
>
<
th
>
website
</
th
>
<
th
>
oa_policies
</
th
>
<
th
>
id
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
23
</
td
>
<
td
>
Taylor
and
Francis
</
td
>
<
td
>
234
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0
</
td
>
<
td
>
http
:
//www.tandf.co.uk/journals/default.asp</td>
<
td
>
NaN
</
td
>
<
td
>
24
</
td
>
</
tr
>
</
tbody
>
</
table
>
</
div
>
```
python
publisher
.
loc
[
publisher
[
'
name
'
]
==
'
Cambridge
University
Press
'
]
```
<
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
>
name
</
th
>
<
th
>
country
</
th
>
<
th
>
city
</
th
>
<
th
>
state
</
th
>
<
th
>
starting_year
</
th
>
<
th
>
website
</
th
>
<
th
>
oa_policies
</
th
>
<
th
>
id
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
60
</
td
>
<
td
>
Cambridge
University
Press
</
td
>
<
td
>
234
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
0
</
td
>
<
td
>
http
:
//www.cambridge.org/uk/</td>
<
td
>
NaN
</
td
>
<
td
>
61
</
td
>
</
tr
>
</
tbody
>
</
table
>
</
div
>
```
python
#
ouvrir
la
liste
d
'
organisations
participants
=
pd
.
read_csv
(
'
agreements
/
consortium_institutions_participation_read_and_publish
.
csv
'
,
encoding
=
'
utf
-
8
'
,
header
=
0
,
sep
=
'\t'
)
participants
```
<
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
>
Institution
</
th
>
<
th
>
Elsevier
</
th
>
<
th
>
Springer
Nature
</
th
>
<
th
>
Wiley
</
th
>
<
th
>
ROR
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
Agroscope
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/04d8ztx87</td>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
Berner
Fachhochschule
BFH
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/02bnkt322</td>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
CERN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/01ggx4157</td>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
Eidgen
ö
ssisches
Hochschulinstitut
f
ü
r
Berufsbi
...</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/00zg4za48</td>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
EPF
Lausanne
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/02s376052</td>
</
tr
>
<
tr
>
<
td
>
5
</
td
>
<
td
>
ETH
Z
ü
rich
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/05a28rw58</td>
</
tr
>
<
tr
>
<
td
>
6
</
td
>
<
td
>
Fachhochschule
Graub
ü
nden
FHGR
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/032ymzc07</td>
</
tr
>
<
tr
>
<
td
>
7
</
td
>
<
td
>
Fachhochschule
Nordwestschweiz
FHNW
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/04mq2g308</td>
</
tr
>
<
tr
>
<
td
>
8
</
td
>
<
td
>
Forschungsinstitut
f
ü
r
biologischen
Landbau
FibL
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/0210tb741</td>
</
tr
>
<
tr
>
<
td
>
9
</
td
>
<
td
>
Graduate
Institute
(
IHEID
)
–
since
2021
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/007ygn379</td>
</
tr
>
<
tr
>
<
td
>
10
</
td
>
<
td
>
Haute
é
cole
sp
é
cialis
é
e
de
Suisse
occidentale
...</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/01xkakk17</td>
</
tr
>
<
tr
>
<
td
>
11
</
td
>
<
td
>
HEP
Berne
,
Jura
,
Neuch
â
tel
(
HEP
-
BEJUNE
)</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/015pmkr43</td>
</
tr
>
<
tr
>
<
td
>
12
</
td
>
<
td
>
HEP
Fribourg
(
PHFR
)</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/048gre751</td>
</
tr
>
<
tr
>
<
td
>
13
</
td
>
<
td
>
HEP
Vaud
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/01bvm0h13</td>
</
tr
>
<
tr
>
<
td
>
14
</
td
>
<
td
>
Hochschule
f
ü
r
Wirtschaft
Z
ü
rich
HWZ
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/02ejkey04</td>
</
tr
>
<
tr
>
<
td
>
15
</
td
>
<
td
>
Hochschule
Luzern
HSLU
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/04nd0xd48</td>
</
tr
>
<
tr
>
<
td
>
16
</
td
>
<
td
>
Interkantonale
Hochschule
f
ü
r
Heilp
ä
dagogik
(
HfH
)</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/00w9q2c06</td>
</
tr
>
<
tr
>
<
td
>
17
</
td
>
<
td
>
Kalaidos
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/049c2kr37</td>
</
tr
>
<
tr
>
<
td
>
18
</
td
>
<
td
>
Lib4RI
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/021f7p178</td>
</
tr
>
<
tr
>
<
td
>
19
</
td
>
<
td
>
Medi
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
20
</
td
>
<
td
>
MMV
-
Medicine
for
Malaria
Ventures
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/00p9jf779</td>
</
tr
>
<
tr
>
<
td
>
21
</
td
>
<
td
>
Ostschweizer
Fachhochschulen
OST
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/038mj2660</td>
</
tr
>
<
tr
>
<
td
>
22
</
td
>
<
td
>
P
ä
dagogische
Hochschule
Z
ü
rich
PHZH
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/01awgk221</td>
</
tr
>
<
tr
>
<
td
>
23
</
td
>
<
td
>
PH
Bern
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/05jf1ma54</td>
</
tr
>
<
tr
>
<
td
>
24
</
td
>
<
td
>
PH
Graub
ü
nden
(
PHGR
)</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/02fjgft97</td>
</
tr
>
<
tr
>
<
td
>
25
</
td
>
<
td
>
PH
Luzern
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/0235ynq74</td>
</
tr
>
<
tr
>
<
td
>
26
</
td
>
<
td
>
PH
Schaffhausen
(
PHSH
)</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/03fs41j10</td>
</
tr
>
<
tr
>
<
td
>
27
</
td
>
<
td
>
PH
Schwyz
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/00rqdn375</td>
</
tr
>
<
tr
>
<
td
>
28
</
td
>
<
td
>
PH
St
.
Gallen
(
PHSG
)</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/05m37v666</td>
</
tr
>
<
tr
>
<
td
>
29
</
td
>
<
td
>
PH
Thurgau
(
PHTG
)</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/04bf6dq94</td>
</
tr
>
<
tr
>
<
td
>
30
</
td
>
<
td
>
PH
Wallis
/
HEP
Valais
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/040gs8e06</td>
</
tr
>
<
tr
>
<
td
>
31
</
td
>
<
td
>
PH
Zug
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/05ghhx264</td>
</
tr
>
<
tr
>
<
td
>
32
</
td
>
<
td
>
Schweizerische
Vogelwarte
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/03mcsbr76</td>
</
tr
>
<
tr
>
<
td
>
33
</
td
>
<
td
>
Scuola
universitaria
professionale
della
Svizz
...</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/05ep8g269</td>
</
tr
>
<
tr
>
<
td
>
34
</
td
>
<
td
>
Universit
à
della
Svizzera
italiana
USI
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/03c4atk17</td>
</
tr
>
<
tr
>
<
td
>
35
</
td
>
<
td
>
Universit
ä
t
Basel
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/02s6k3f65</td>
</
tr
>
<
tr
>
<
td
>
36
</
td
>
<
td
>
Universit
ä
t
Bern
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/02k7v4d05</td>
</
tr
>
<
tr
>
<
td
>
37
</
td
>
<
td
>
Universit
ä
t
Liechtenstein
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/01qjrx392</td>
</
tr
>
<
tr
>
<
td
>
38
</
td
>
<
td
>
Universit
ä
t
Luzern
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/00kgrkn83</td>
</
tr
>
<
tr
>
<
td
>
39
</
td
>
<
td
>
Universit
ä
t
St
.
Gallen
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/0561a3s31</td>
</
tr
>
<
tr
>
<
td
>
40
</
td
>
<
td
>
Universit
ä
t
Z
ü
rich
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/02crff812</td>
</
tr
>
<
tr
>
<
td
>
41
</
td
>
<
td
>
Universit
é
de
Fribourg
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/022fs9h90</td>
</
tr
>
<
tr
>
<
td
>
42
</
td
>
<
td
>
Universit
é
de
Gen
è
ve
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/01swzsf04</td>
</
tr
>
<
tr
>
<
td
>
43
</
td
>
<
td
>
Universit
é
de
Lausanne
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/019whta54</td>
</
tr
>
<
tr
>
<
td
>
44
</
td
>
<
td
>
Universit
é
de
Neuch
â
tel
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/00vasag41</td>
</
tr
>
<
tr
>
<
td
>
45
</
td
>
<
td
>
Z
ü
rcher
Hochschule
der
K
ü
nste
ZHdK
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/05r0ap620</td>
</
tr
>
<
tr
>
<
td
>
46
</
td
>
<
td
>
Z
ü
rcher
Hochschule
f
ü
r
Angewandte
Wissenschaft
...</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/05pmsvm27</td>
</
tr
>
</
tbody
>
</
table
>
</
div
>
```
python
#
suppression
de
Lib4RI
qui
est
une
biblioth
è
que
participants
=
participants
.
loc
[
participants
[
'
Institution
'
]
!=
'
Lib4RI
'
]
participants
```
<
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
>
Institution
</
th
>
<
th
>
Elsevier
</
th
>
<
th
>
Springer
Nature
</
th
>
<
th
>
Wiley
</
th
>
<
th
>
ROR
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
Agroscope
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/04d8ztx87</td>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
Berner
Fachhochschule
BFH
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/02bnkt322</td>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
CERN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/01ggx4157</td>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
Eidgen
ö
ssisches
Hochschulinstitut
f
ü
r
Berufsbi
...</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/00zg4za48</td>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
EPF
Lausanne
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/02s376052</td>
</
tr
>
<
tr
>
<
td
>
5
</
td
>
<
td
>
ETH
Z
ü
rich
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/05a28rw58</td>
</
tr
>
<
tr
>
<
td
>
6
</
td
>
<
td
>
Fachhochschule
Graub
ü
nden
FHGR
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/032ymzc07</td>
</
tr
>
<
tr
>
<
td
>
7
</
td
>
<
td
>
Fachhochschule
Nordwestschweiz
FHNW
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/04mq2g308</td>
</
tr
>
<
tr
>
<
td
>
8
</
td
>
<
td
>
Forschungsinstitut
f
ü
r
biologischen
Landbau
FibL
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/0210tb741</td>
</
tr
>
<
tr
>
<
td
>
9
</
td
>
<
td
>
Graduate
Institute
(
IHEID
)
–
since
2021
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/007ygn379</td>
</
tr
>
<
tr
>
<
td
>
10
</
td
>
<
td
>
Haute
é
cole
sp
é
cialis
é
e
de
Suisse
occidentale
...</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/01xkakk17</td>
</
tr
>
<
tr
>
<
td
>
11
</
td
>
<
td
>
HEP
Berne
,
Jura
,
Neuch
â
tel
(
HEP
-
BEJUNE
)</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/015pmkr43</td>
</
tr
>
<
tr
>
<
td
>
12
</
td
>
<
td
>
HEP
Fribourg
(
PHFR
)</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/048gre751</td>
</
tr
>
<
tr
>
<
td
>
13
</
td
>
<
td
>
HEP
Vaud
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/01bvm0h13</td>
</
tr
>
<
tr
>
<
td
>
14
</
td
>
<
td
>
Hochschule
f
ü
r
Wirtschaft
Z
ü
rich
HWZ
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/02ejkey04</td>
</
tr
>
<
tr
>
<
td
>
15
</
td
>
<
td
>
Hochschule
Luzern
HSLU
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/04nd0xd48</td>
</
tr
>
<
tr
>
<
td
>
16
</
td
>
<
td
>
Interkantonale
Hochschule
f
ü
r
Heilp
ä
dagogik
(
HfH
)</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/00w9q2c06</td>
</
tr
>
<
tr
>
<
td
>
17
</
td
>
<
td
>
Kalaidos
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/049c2kr37</td>
</
tr
>
<
tr
>
<
td
>
19
</
td
>
<
td
>
Medi
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
20
</
td
>
<
td
>
MMV
-
Medicine
for
Malaria
Ventures
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/00p9jf779</td>
</
tr
>
<
tr
>
<
td
>
21
</
td
>
<
td
>
Ostschweizer
Fachhochschulen
OST
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/038mj2660</td>
</
tr
>
<
tr
>
<
td
>
22
</
td
>
<
td
>
P
ä
dagogische
Hochschule
Z
ü
rich
PHZH
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/01awgk221</td>
</
tr
>
<
tr
>
<
td
>
23
</
td
>
<
td
>
PH
Bern
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/05jf1ma54</td>
</
tr
>
<
tr
>
<
td
>
24
</
td
>
<
td
>
PH
Graub
ü
nden
(
PHGR
)</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/02fjgft97</td>
</
tr
>
<
tr
>
<
td
>
25
</
td
>
<
td
>
PH
Luzern
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/0235ynq74</td>
</
tr
>
<
tr
>
<
td
>
26
</
td
>
<
td
>
PH
Schaffhausen
(
PHSH
)</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/03fs41j10</td>
</
tr
>
<
tr
>
<
td
>
27
</
td
>
<
td
>
PH
Schwyz
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/00rqdn375</td>
</
tr
>
<
tr
>
<
td
>
28
</
td
>
<
td
>
PH
St
.
Gallen
(
PHSG
)</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/05m37v666</td>
</
tr
>
<
tr
>
<
td
>
29
</
td
>
<
td
>
PH
Thurgau
(
PHTG
)</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/04bf6dq94</td>
</
tr
>
<
tr
>
<
td
>
30
</
td
>
<
td
>
PH
Wallis
/
HEP
Valais
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/040gs8e06</td>
</
tr
>
<
tr
>
<
td
>
31
</
td
>
<
td
>
PH
Zug
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/05ghhx264</td>
</
tr
>
<
tr
>
<
td
>
32
</
td
>
<
td
>
Schweizerische
Vogelwarte
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/03mcsbr76</td>
</
tr
>
<
tr
>
<
td
>
33
</
td
>
<
td
>
Scuola
universitaria
professionale
della
Svizz
...</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/05ep8g269</td>
</
tr
>
<
tr
>
<
td
>
34
</
td
>
<
td
>
Universit
à
della
Svizzera
italiana
USI
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/03c4atk17</td>
</
tr
>
<
tr
>
<
td
>
35
</
td
>
<
td
>
Universit
ä
t
Basel
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/02s6k3f65</td>
</
tr
>
<
tr
>
<
td
>
36
</
td
>
<
td
>
Universit
ä
t
Bern
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/02k7v4d05</td>
</
tr
>
<
tr
>
<
td
>
37
</
td
>
<
td
>
Universit
ä
t
Liechtenstein
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/01qjrx392</td>
</
tr
>
<
tr
>
<
td
>
38
</
td
>
<
td
>
Universit
ä
t
Luzern
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/00kgrkn83</td>
</
tr
>
<
tr
>
<
td
>
39
</
td
>
<
td
>
Universit
ä
t
St
.
Gallen
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/0561a3s31</td>
</
tr
>
<
tr
>
<
td
>
40
</
td
>
<
td
>
Universit
ä
t
Z
ü
rich
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/02crff812</td>
</
tr
>
<
tr
>
<
td
>
41
</
td
>
<
td
>
Universit
é
de
Fribourg
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/022fs9h90</td>
</
tr
>
<
tr
>
<
td
>
42
</
td
>
<
td
>
Universit
é
de
Gen
è
ve
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/01swzsf04</td>
</
tr
>
<
tr
>
<
td
>
43
</
td
>
<
td
>
Universit
é
de
Lausanne
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/019whta54</td>
</
tr
>
<
tr
>
<
td
>
44
</
td
>
<
td
>
Universit
é
de
Neuch
â
tel
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/00vasag41</td>
</
tr
>
<
tr
>
<
td
>
45
</
td
>
<
td
>
Z
ü
rcher
Hochschule
der
K
ü
nste
ZHdK
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/05r0ap620</td>
</
tr
>
<
tr
>
<
td
>
46
</
td
>
<
td
>
Z
ü
rcher
Hochschule
f
ü
r
Angewandte
Wissenschaft
...</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/05pmsvm27</td>
</
tr
>
</
tbody
>
</
table
>
</
div
>
```
python
#
ajout
de
TF
et
CUP
pour
tous
(
TODO
:
obtenir
la
liste
des
biblioth
è
ques
pour
ces
deux
licences
)
participants
[
'
TF
'
]
=
'x'
participants
[
'
CUP
'
]
=
'x'
participants
```
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
C
:\
Users
\
iriarte
\
AppData
\
Local
\
Continuum
\
anaconda3
\
lib
\
site
-
packages
\
ipykernel_launcher
.
py
:
3
:
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
This
is
separate
from
the
ipykernel
package
so
we
can
avoid
doing
imports
until
<
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
>
Institution
</
th
>
<
th
>
Elsevier
</
th
>
<
th
>
Springer
Nature
</
th
>
<
th
>
Wiley
</
th
>
<
th
>
ROR
</
th
>
<
th
>
TF
</
th
>
<
th
>
CUP
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
Agroscope
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/04d8ztx87</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
Berner
Fachhochschule
BFH
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/02bnkt322</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
CERN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/01ggx4157</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
Eidgen
ö
ssisches
Hochschulinstitut
f
ü
r
Berufsbi
...</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/00zg4za48</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
EPF
Lausanne
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/02s376052</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
5
</
td
>
<
td
>
ETH
Z
ü
rich
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/05a28rw58</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
6
</
td
>
<
td
>
Fachhochschule
Graub
ü
nden
FHGR
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/032ymzc07</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
7
</
td
>
<
td
>
Fachhochschule
Nordwestschweiz
FHNW
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/04mq2g308</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
8
</
td
>
<
td
>
Forschungsinstitut
f
ü
r
biologischen
Landbau
FibL
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/0210tb741</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
9
</
td
>
<
td
>
Graduate
Institute
(
IHEID
)
–
since
2021
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/007ygn379</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
10
</
td
>
<
td
>
Haute
é
cole
sp
é
cialis
é
e
de
Suisse
occidentale
...</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/01xkakk17</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
11
</
td
>
<
td
>
HEP
Berne
,
Jura
,
Neuch
â
tel
(
HEP
-
BEJUNE
)</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/015pmkr43</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
12
</
td
>
<
td
>
HEP
Fribourg
(
PHFR
)</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/048gre751</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
13
</
td
>
<
td
>
HEP
Vaud
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/01bvm0h13</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
14
</
td
>
<
td
>
Hochschule
f
ü
r
Wirtschaft
Z
ü
rich
HWZ
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/02ejkey04</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
15
</
td
>
<
td
>
Hochschule
Luzern
HSLU
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/04nd0xd48</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
16
</
td
>
<
td
>
Interkantonale
Hochschule
f
ü
r
Heilp
ä
dagogik
(
HfH
)</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/00w9q2c06</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
17
</
td
>
<
td
>
Kalaidos
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/049c2kr37</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
19
</
td
>
<
td
>
Medi
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
20
</
td
>
<
td
>
MMV
-
Medicine
for
Malaria
Ventures
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/00p9jf779</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
21
</
td
>
<
td
>
Ostschweizer
Fachhochschulen
OST
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/038mj2660</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
22
</
td
>
<
td
>
P
ä
dagogische
Hochschule
Z
ü
rich
PHZH
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/01awgk221</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
23
</
td
>
<
td
>
PH
Bern
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/05jf1ma54</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
24
</
td
>
<
td
>
PH
Graub
ü
nden
(
PHGR
)</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/02fjgft97</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
25
</
td
>
<
td
>
PH
Luzern
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/0235ynq74</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
26
</
td
>
<
td
>
PH
Schaffhausen
(
PHSH
)</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/03fs41j10</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
27
</
td
>
<
td
>
PH
Schwyz
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/00rqdn375</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
28
</
td
>
<
td
>
PH
St
.
Gallen
(
PHSG
)</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/05m37v666</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
29
</
td
>
<
td
>
PH
Thurgau
(
PHTG
)</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/04bf6dq94</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
30
</
td
>
<
td
>
PH
Wallis
/
HEP
Valais
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/040gs8e06</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
31
</
td
>
<
td
>
PH
Zug
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/05ghhx264</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
32
</
td
>
<
td
>
Schweizerische
Vogelwarte
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/03mcsbr76</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
33
</
td
>
<
td
>
Scuola
universitaria
professionale
della
Svizz
...</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/05ep8g269</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
34
</
td
>
<
td
>
Universit
à
della
Svizzera
italiana
USI
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/03c4atk17</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
35
</
td
>
<
td
>
Universit
ä
t
Basel
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/02s6k3f65</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
36
</
td
>
<
td
>
Universit
ä
t
Bern
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/02k7v4d05</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
37
</
td
>
<
td
>
Universit
ä
t
Liechtenstein
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/01qjrx392</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
38
</
td
>
<
td
>
Universit
ä
t
Luzern
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/00kgrkn83</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
39
</
td
>
<
td
>
Universit
ä
t
St
.
Gallen
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/0561a3s31</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
40
</
td
>
<
td
>
Universit
ä
t
Z
ü
rich
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/02crff812</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
41
</
td
>
<
td
>
Universit
é
de
Fribourg
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/022fs9h90</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
42
</
td
>
<
td
>
Universit
é
de
Gen
è
ve
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/01swzsf04</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
43
</
td
>
<
td
>
Universit
é
de
Lausanne
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/019whta54</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
44
</
td
>
<
td
>
Universit
é
de
Neuch
â
tel
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/00vasag41</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
45
</
td
>
<
td
>
Z
ü
rcher
Hochschule
der
K
ü
nste
ZHdK
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/05r0ap620</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
46
</
td
>
<
td
>
Z
ü
rcher
Hochschule
f
ü
r
Angewandte
Wissenschaft
...</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/05pmsvm27</td>
<
td
>
x
</
td
>
<
td
>
x
</
td
>
</
tr
>
</
tbody
>
</
table
>
</
div
>
```
python
#
ouvrir
la
liste
des
journaux
Elsevier
elsevier
=
pd
.
read_excel
(
'
agreements
/
Elsevier_titlelist_publication
.
xlsx
'
,
skiprows
=
7
)
elsevier
```
<
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
>
Title
</
th
>
<
th
>
ISSN
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
Academic
Pediatrics
</
td
>
<
td
>
1876
-
2859
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
Accident
Analysis
and
Prevention
</
td
>
<
td
>
0001
-
4575
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
Accounting
,
Organizations
and
Society
</
td
>
<
td
>
0361
-
3682
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
Acta
Astronautica
</
td
>
<
td
>
0094
-
5765
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
Acta
Biomaterialia
</
td
>
<
td
>
1742
-
7061
</
td
>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
2240
</
td
>
<
td
>
Wound
Medicine
</
td
>
<
td
>
2213
-
9095
</
td
>
</
tr
>
<
tr
>
<
td
>
2241
</
td
>
<
td
>
Zeitschrift
fuer
Evidenz
,
Fortbildung
und
Qual
...</
td
>
<
td
>
1865
-
9217
</
td
>
</
tr
>
<
tr
>
<
td
>
2242
</
td
>
<
td
>
Zeitschrift
fuer
Medizinische
Physik
</
td
>
<
td
>
0939
-
3889
</
td
>
</
tr
>
<
tr
>
<
td
>
2243
</
td
>
<
td
>
Zoologischer
Anzeiger
</
td
>
<
td
>
0044
-
5231
</
td
>
</
tr
>
<
tr
>
<
td
>
2244
</
td
>
<
td
>
Zoology
</
td
>
<
td
>
0944
-
2006
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
2245
rows
×
2
columns
</
p
>
</
div
>
```
python
#
ajout
du
champ
version
elsevier
[
'
article_version
'
]
=
'
published
'
elsevier
```
<
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
>
Title
</
th
>
<
th
>
ISSN
</
th
>
<
th
>
article_version
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
Academic
Pediatrics
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
published
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
Accident
Analysis
and
Prevention
</
td
>
<
td
>
0001
-
4575
</
td
>
<
td
>
published
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
Accounting
,
Organizations
and
Society
</
td
>
<
td
>
0361
-
3682
</
td
>
<
td
>
published
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
Acta
Astronautica
</
td
>
<
td
>
0094
-
5765
</
td
>
<
td
>
published
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
Acta
Biomaterialia
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
published
</
td
>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
2240
</
td
>
<
td
>
Wound
Medicine
</
td
>
<
td
>
2213
-
9095
</
td
>
<
td
>
published
</
td
>
</
tr
>
<
tr
>
<
td
>
2241
</
td
>
<
td
>
Zeitschrift
fuer
Evidenz
,
Fortbildung
und
Qual
...</
td
>
<
td
>
1865
-
9217
</
td
>
<
td
>
published
</
td
>
</
tr
>
<
tr
>
<
td
>
2242
</
td
>
<
td
>
Zeitschrift
fuer
Medizinische
Physik
</
td
>
<
td
>
0939
-
3889
</
td
>
<
td
>
published
</
td
>
</
tr
>
<
tr
>
<
td
>
2243
</
td
>
<
td
>
Zoologischer
Anzeiger
</
td
>
<
td
>
0044
-
5231
</
td
>
<
td
>
published
</
td
>
</
tr
>
<
tr
>
<
td
>
2244
</
td
>
<
td
>
Zoology
</
td
>
<
td
>
0944
-
2006
</
td
>
<
td
>
published
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
2245
rows
×
3
columns
</
p
>
</
div
>
```
python
#
ajout
des
dates
elsevier
[
'
valid_from
'
]
=
'
2020
-
01
-
01
'
elsevier
[
'
valid_until
'
]
=
'
2023
-
12
-
31
'
elsevier
```
<
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
>
Title
</
th
>
<
th
>
ISSN
</
th
>
<
th
>
article_version
</
th
>
<
th
>
valid_from
</
th
>
<
th
>
valid_until
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
Academic
Pediatrics
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
published
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
Accident
Analysis
and
Prevention
</
td
>
<
td
>
0001
-
4575
</
td
>
<
td
>
published
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
Accounting
,
Organizations
and
Society
</
td
>
<
td
>
0361
-
3682
</
td
>
<
td
>
published
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
Acta
Astronautica
</
td
>
<
td
>
0094
-
5765
</
td
>
<
td
>
published
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
Acta
Biomaterialia
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
published
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
2240
</
td
>
<
td
>
Wound
Medicine
</
td
>
<
td
>
2213
-
9095
</
td
>
<
td
>
published
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>
2241
</
td
>
<
td
>
Zeitschrift
fuer
Evidenz
,
Fortbildung
und
Qual
...</
td
>
<
td
>
1865
-
9217
</
td
>
<
td
>
published
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>
2242
</
td
>
<
td
>
Zeitschrift
fuer
Medizinische
Physik
</
td
>
<
td
>
0939
-
3889
</
td
>
<
td
>
published
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>
2243
</
td
>
<
td
>
Zoologischer
Anzeiger
</
td
>
<
td
>
0044
-
5231
</
td
>
<
td
>
published
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>
2244
</
td
>
<
td
>
Zoology
</
td
>
<
td
>
0944
-
2006
</
td
>
<
td
>
published
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
2245
rows
×
5
columns
</
p
>
</
div
>
```
python
#
ajout
du
embargo
et
archiving
elsevier
[
'
embargo_months
'
]
=
0
elsevier
[
'
archiving
'
]
=
True
elsevier
```
<
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
>
Title
</
th
>
<
th
>
ISSN
</
th
>
<
th
>
article_version
</
th
>
<
th
>
valid_from
</
th
>
<
th
>
valid_until
</
th
>
<
th
>
embargo_months
</
th
>
<
th
>
archiving
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
Academic
Pediatrics
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
published
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0
</
td
>
<
td
>
True
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
Accident
Analysis
and
Prevention
</
td
>
<
td
>
0001
-
4575
</
td
>
<
td
>
published
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0
</
td
>
<
td
>
True
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
Accounting
,
Organizations
and
Society
</
td
>
<
td
>
0361
-
3682
</
td
>
<
td
>
published
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0
</
td
>
<
td
>
True
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
Acta
Astronautica
</
td
>
<
td
>
0094
-
5765
</
td
>
<
td
>
published
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0
</
td
>
<
td
>
True
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
Acta
Biomaterialia
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
published
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0
</
td
>
<
td
>
True
</
td
>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
2240
</
td
>
<
td
>
Wound
Medicine
</
td
>
<
td
>
2213
-
9095
</
td
>
<
td
>
published
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0
</
td
>
<
td
>
True
</
td
>
</
tr
>
<
tr
>
<
td
>
2241
</
td
>
<
td
>
Zeitschrift
fuer
Evidenz
,
Fortbildung
und
Qual
...</
td
>
<
td
>
1865
-
9217
</
td
>
<
td
>
published
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0
</
td
>
<
td
>
True
</
td
>
</
tr
>
<
tr
>
<
td
>
2242
</
td
>
<
td
>
Zeitschrift
fuer
Medizinische
Physik
</
td
>
<
td
>
0939
-
3889
</
td
>
<
td
>
published
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0
</
td
>
<
td
>
True
</
td
>
</
tr
>
<
tr
>
<
td
>
2243
</
td
>
<
td
>
Zoologischer
Anzeiger
</
td
>
<
td
>
0044
-
5231
</
td
>
<
td
>
published
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0
</
td
>
<
td
>
True
</
td
>
</
tr
>
<
tr
>
<
td
>
2244
</
td
>
<
td
>
Zoology
</
td
>
<
td
>
0944
-
2006
</
td
>
<
td
>
published
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0
</
td
>
<
td
>
True
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
2245
rows
×
7
columns
</
p
>
</
div
>
```
python
elsevier
.
iloc
[
elsevier
.
shape
[
0
]-
1
]
```
Title
Zoology
ISSN
0944
-
2006
article_version
published
valid_from
2020
-
01
-
01
valid_until
2023
-
12
-
31
embargo_months
0
archiving
True
Name
:
2244
,
dtype
:
object
```
python
#
ajout
du
champ
license
#
cc_by
,
cc_by_nc_nd
rp
=
pd
.
DataFrame
()
elsevier
[
'
article_version
'
]
=
'
published
'
elsevier
[
'
license
'
]
=
'
cc_by
'
elsevier
[
'
Elsevier
'
]
=
'x'
rp
=
rp
.
append
(
elsevier
,
ignore_index
=
True
)
elsevier
[
'
license
'
]
=
'
cc_by_nc_nd
'
rp
=
rp
.
append
(
elsevier
,
ignore_index
=
True
)
rp
```
<
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
>
Title
</
th
>
<
th
>
ISSN
</
th
>
<
th
>
article_version
</
th
>
<
th
>
valid_from
</
th
>
<
th
>
valid_until
</
th
>
<
th
>
embargo_months
</
th
>
<
th
>
archiving
</
th
>
<
th
>
license
</
th
>
<
th
>
Elsevier
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
Academic
Pediatrics
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
published
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0
</
td
>
<
td
>
True
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
Accident
Analysis
and
Prevention
</
td
>
<
td
>
0001
-
4575
</
td
>
<
td
>
published
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0
</
td
>
<
td
>
True
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
Accounting
,
Organizations
and
Society
</
td
>
<
td
>
0361
-
3682
</
td
>
<
td
>
published
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0
</
td
>
<
td
>
True
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
Acta
Astronautica
</
td
>
<
td
>
0094
-
5765
</
td
>
<
td
>
published
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0
</
td
>
<
td
>
True
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
Acta
Biomaterialia
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
published
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0
</
td
>
<
td
>
True
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
4485
</
td
>
<
td
>
Wound
Medicine
</
td
>
<
td
>
2213
-
9095
</
td
>
<
td
>
published
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0
</
td
>
<
td
>
True
</
td
>
<
td
>
cc_by_nc_nd
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
4486
</
td
>
<
td
>
Zeitschrift
fuer
Evidenz
,
Fortbildung
und
Qual
...</
td
>
<
td
>
1865
-
9217
</
td
>
<
td
>
published
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0
</
td
>
<
td
>
True
</
td
>
<
td
>
cc_by_nc_nd
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
4487
</
td
>
<
td
>
Zeitschrift
fuer
Medizinische
Physik
</
td
>
<
td
>
0939
-
3889
</
td
>
<
td
>
published
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0
</
td
>
<
td
>
True
</
td
>
<
td
>
cc_by_nc_nd
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
4488
</
td
>
<
td
>
Zoologischer
Anzeiger
</
td
>
<
td
>
0044
-
5231
</
td
>
<
td
>
published
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0
</
td
>
<
td
>
True
</
td
>
<
td
>
cc_by_nc_nd
</
td
>
<
td
>
x
</
td
>
</
tr
>
<
tr
>
<
td
>
4489
</
td
>
<
td
>
Zoology
</
td
>
<
td
>
0944
-
2006
</
td
>
<
td
>
published
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0
</
td
>
<
td
>
True
</
td
>
<
td
>
cc_by_nc_nd
</
td
>
<
td
>
x
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
4490
rows
×
9
columns
</
p
>
</
div
>
```
python
#
ouvrir
la
liste
des
journaux
Springer
Nature
springer
=
pd
.
read_excel
(
'
agreements
/
Springer_titlelist_publication
.
xlsx
'
,
skiprows
=
7
)
springer
```
<
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
>
Title
</
th
>
<
th
>
ISSN
</
th
>
<
th
>
URL
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
3
Biotech
</
td
>
<
td
>
2190
-
5738
</
td
>
<
td
>
https
:
//www.springer.com/journal/13205</td>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
4
OR
</
td
>
<
td
>
1614
-
2411
</
td
>
<
td
>
https
:
//www.springer.com/journal/10288</td>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
AAPS
PharmSciTech
</
td
>
<
td
>
1530
-
9932
</
td
>
<
td
>
https
:
//www.springer.com/journal/12249</td>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
Abdominal
Radiology
</
td
>
<
td
>
2366
-
0058
</
td
>
<
td
>
https
:
//www.springer.com/journal/261</td>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
Abhandlungen
aus
dem
Mathematischen
Seminar
de
...</
td
>
<
td
>
1865
-
8784
</
td
>
<
td
>
https
:
//www.springer.com/journal/12188</td>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
2035
</
td
>
<
td
>
Zeitschrift
f
ü
r
Religion
,
Gesellschaft
und
Pol
...</
td
>
<
td
>
2510
-
1226
</
td
>
<
td
>
https
:
//www.springer.com/journal/41682</td>
</
tr
>
<
tr
>
<
td
>
2036
</
td
>
<
td
>
Zeitschrift
f
ü
r
Rheumatologie
</
td
>
<
td
>
1435
-
1250
</
td
>
<
td
>
https
:
//www.springer.com/journal/393</td>
</
tr
>
<
tr
>
<
td
>
2037
</
td
>
<
td
>
Zeitschrift
f
ü
r
Vergleichende
Politikwissenschaft
</
td
>
<
td
>
1865
-
2654
</
td
>
<
td
>
https
:
//www.springer.com/journal/12286</td>
</
tr
>
<
tr
>
<
td
>
2038
</
td
>
<
td
>
Zentralblatt
f
ü
r
Arbeitsmedizin
,
Arbeitsschutz
...</
td
>
<
td
>
2198
-
0713
</
td
>
<
td
>
https
:
//www.springer.com/journal/40664</td>
</
tr
>
<
tr
>
<
td
>
2039
</
td
>
<
td
>
Zoomorphology
</
td
>
<
td
>
1432
-
234
X
</
td
>
<
td
>
https
:
//www.springer.com/journal/435</td>
</
tr
>
</
tbody
>
</
table
>
<
p
>
2040
rows
×
3
columns
</
p
>
</
div
>
```
python
#
ajout
du
champ
license
#
cc_by
,
cc_by_nc
springer
[
'
article_version
'
]
=
'
published
'
springer
[
'
license
'
]
=
'
cc_by
'
springer
[
'
Springer
Nature
'
]
=
'x'
#
ajout
des
dates
springer
[
'
valid_from
'
]
=
'
2020
-
01
-
01
'
springer
[
'
valid_until
'
]
=
'
2022
-
12
-
31
'
#
ajout
du
embargo
et
archiving
springer
[
'
embargo_months
'
]
=
0
springer
[
'
archiving
'
]
=
True
```
```
python
#
append
rp
=
rp
.
append
(
springer
,
ignore_index
=
True
)
springer
[
'
license
'
]
=
'
cc_by_nc
'
rp
=
rp
.
append
(
springer
,
ignore_index
=
True
)
rp
```
C
:\
Users
\
iriarte
\
AppData
\
Local
\
Continuum
\
anaconda3
\
lib
\
site
-
packages
\
pandas
\
core
\
frame
.
py
:
7123
:
FutureWarning
:
Sorting
because
non
-
concatenation
axis
is
not
aligned
.
A
future
version
of
pandas
will
change
to
not
sort
by
default
.
To
accept
the
future
behavior
,
pass
'
sort
=
False
'
.
To
retain
the
current
behavior
and
silence
the
warning
,
pass
'
sort
=
True
'
.
sort
=
sort
,
<
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
>
Elsevier
</
th
>
<
th
>
ISSN
</
th
>
<
th
>
Springer
Nature
</
th
>
<
th
>
Title
</
th
>
<
th
>
URL
</
th
>
<
th
>
archiving
</
th
>
<
th
>
article_version
</
th
>
<
th
>
embargo_months
</
th
>
<
th
>
license
</
th
>
<
th
>
valid_from
</
th
>
<
th
>
valid_until
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
x
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Academic
Pediatrics
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
x
</
td
>
<
td
>
0001
-
4575
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Accident
Analysis
and
Prevention
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
x
</
td
>
<
td
>
0361
-
3682
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Accounting
,
Organizations
and
Society
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
x
</
td
>
<
td
>
0094
-
5765
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Acta
Astronautica
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
x
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Acta
Biomaterialia
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
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
>
</
tr
>
<
tr
>
<
td
>
8565
</
td
>
<
td
>
NaN
</
td
>
<
td
>
2510
-
1226
</
td
>
<
td
>
x
</
td
>
<
td
>
Zeitschrift
f
ü
r
Religion
,
Gesellschaft
und
Pol
...</
td
>
<
td
>
https
:
//www.springer.com/journal/41682</td>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by_nc
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2022
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>
8566
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1435
-
1250
</
td
>
<
td
>
x
</
td
>
<
td
>
Zeitschrift
f
ü
r
Rheumatologie
</
td
>
<
td
>
https
:
//www.springer.com/journal/393</td>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by_nc
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2022
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>
8567
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1865
-
2654
</
td
>
<
td
>
x
</
td
>
<
td
>
Zeitschrift
f
ü
r
Vergleichende
Politikwissenschaft
</
td
>
<
td
>
https
:
//www.springer.com/journal/12286</td>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by_nc
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2022
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>
8568
</
td
>
<
td
>
NaN
</
td
>
<
td
>
2198
-
0713
</
td
>
<
td
>
x
</
td
>
<
td
>
Zentralblatt
f
ü
r
Arbeitsmedizin
,
Arbeitsschutz
...</
td
>
<
td
>
https
:
//www.springer.com/journal/40664</td>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by_nc
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2022
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>
8569
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1432
-
234
X
</
td
>
<
td
>
x
</
td
>
<
td
>
Zoomorphology
</
td
>
<
td
>
https
:
//www.springer.com/journal/435</td>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by_nc
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2022
-
12
-
31
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
8570
rows
×
11
columns
</
p
>
</
div
>
```
python
#
ouvrir
la
liste
des
journaux
Wiley
wiley
=
pd
.
read_excel
(
'
agreements
/
Wiley_titlelist_publish
.
xlsx
'
,
skiprows
=
7
)
wiley
```
<
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
>
Title
</
th
>
<
th
>
ISSN
</
th
>
<
th
>
URL
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
ABACUS
</
td
>
<
td
>
1467
-
6281
</
td
>
<
td
>
https
:
//onlinelibrary.wiley.com/journal/14676281</td>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
ACADEMIC
EMERGENCY
MEDICINE
</
td
>
<
td
>
1553
-
2712
</
td
>
<
td
>
https
:
//onlinelibrary.wiley.com/journal/15532712</td>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
ACCOUNTING
&
amp
;
FINANCE
</
td
>
<
td
>
1467
-
629
X
</
td
>
<
td
>
https
:
//onlinelibrary.wiley.com/journal/1467629X</td>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
ACCOUNTING
PERSPECTIVES
</
td
>
<
td
>
1911
-
3838
</
td
>
<
td
>
https
:
//onlinelibrary.wiley.com/journal/19113838</td>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
ACTA
ANAESTHESIOLOGICA
SCANDINAVICA
</
td
>
<
td
>
1399
-
6576
</
td
>
<
td
>
https
:
//onlinelibrary.wiley.com/journal/13996576</td>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
1391
</
td
>
<
td
>
ZEITSCHRIFT
F
ü
R
ANORGANISCHE
UND
ALLGEMEINE
CH
...</
td
>
<
td
>
1521
-
3749
</
td
>
<
td
>
https
:
//onlinelibrary.wiley.com/journal/15213749</td>
</
tr
>
<
tr
>
<
td
>
1392
</
td
>
<
td
>
ZOO
BIOLOGY
</
td
>
<
td
>
1098
-
2361
</
td
>
<
td
>
https
:
//onlinelibrary.wiley.com/journal/10982361</td>
</
tr
>
<
tr
>
<
td
>
1393
</
td
>
<
td
>
ZOOLOGICA
SCRIPTA
</
td
>
<
td
>
1463
-
6409
</
td
>
<
td
>
https
:
//onlinelibrary.wiley.com/journal/14636409</td>
</
tr
>
<
tr
>
<
td
>
1394
</
td
>
<
td
>
ZOONOSES
AND
PUBLIC
HEALTH
</
td
>
<
td
>
1863
-
2378
</
td
>
<
td
>
https
:
//onlinelibrary.wiley.com/journal/18632378</td>
</
tr
>
<
tr
>
<
td
>
1395
</
td
>
<
td
>
ZYGON
®
JOURNAL
OF
RELIGION
AND
SCIENCE
</
td
>
<
td
>
1467
-
9744
</
td
>
<
td
>
https
:
//onlinelibrary.wiley.com/journal/14679744</td>
</
tr
>
</
tbody
>
</
table
>
<
p
>
1396
rows
×
3
columns
</
p
>
</
div
>
```
python
#
ajout
du
champ
license
#
cc_by
,
cc_by_nc
,
cc_by_nc_nd
wiley
[
'
article_version
'
]
=
'
published
'
wiley
[
'
license
'
]
=
'
cc_by
'
wiley
[
'
Wiley
'
]
=
'x'
#
ajout
des
dates
wiley
[
'
valid_from
'
]
=
'
2021
-
01
-
01
'
wiley
[
'
valid_until
'
]
=
'
2024
-
12
-
31
'
#
ajout
du
embargo
et
archiving
wiley
[
'
embargo_months
'
]
=
0
wiley
[
'
archiving
'
]
=
True
rp
=
rp
.
append
(
wiley
,
ignore_index
=
True
)
#
append
avec
une
autre
licence
wiley
[
'
license
'
]
=
'
cc_by_nc
'
rp
=
rp
.
append
(
wiley
,
ignore_index
=
True
)
#
append
avec
une
autre
licence
wiley
[
'
license
'
]
=
'
cc_by_nc_nd
'
rp
=
rp
.
append
(
wiley
,
ignore_index
=
True
)
rp
```
<
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
>
Elsevier
</
th
>
<
th
>
ISSN
</
th
>
<
th
>
Springer
Nature
</
th
>
<
th
>
Title
</
th
>
<
th
>
URL
</
th
>
<
th
>
Wiley
</
th
>
<
th
>
archiving
</
th
>
<
th
>
article_version
</
th
>
<
th
>
embargo_months
</
th
>
<
th
>
license
</
th
>
<
th
>
valid_from
</
th
>
<
th
>
valid_until
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
x
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Academic
Pediatrics
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
x
</
td
>
<
td
>
0001
-
4575
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Accident
Analysis
and
Prevention
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
x
</
td
>
<
td
>
0361
-
3682
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Accounting
,
Organizations
and
Society
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
x
</
td
>
<
td
>
0094
-
5765
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Acta
Astronautica
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
x
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Acta
Biomaterialia
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
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
>
</
tr
>
<
tr
>
<
td
>
12753
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1521
-
3749
</
td
>
<
td
>
NaN
</
td
>
<
td
>
ZEITSCHRIFT
F
ü
R
ANORGANISCHE
UND
ALLGEMEINE
CH
...</
td
>
<
td
>
https
:
//onlinelibrary.wiley.com/journal/15213749</td>
<
td
>
x
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by_nc_nd
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2024
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>
12754
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1098
-
2361
</
td
>
<
td
>
NaN
</
td
>
<
td
>
ZOO
BIOLOGY
</
td
>
<
td
>
https
:
//onlinelibrary.wiley.com/journal/10982361</td>
<
td
>
x
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by_nc_nd
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2024
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>
12755
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1463
-
6409
</
td
>
<
td
>
NaN
</
td
>
<
td
>
ZOOLOGICA
SCRIPTA
</
td
>
<
td
>
https
:
//onlinelibrary.wiley.com/journal/14636409</td>
<
td
>
x
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by_nc_nd
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2024
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>
12756
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1863
-
2378
</
td
>
<
td
>
NaN
</
td
>
<
td
>
ZOONOSES
AND
PUBLIC
HEALTH
</
td
>
<
td
>
https
:
//onlinelibrary.wiley.com/journal/18632378</td>
<
td
>
x
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by_nc_nd
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2024
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>
12757
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1467
-
9744
</
td
>
<
td
>
NaN
</
td
>
<
td
>
ZYGON
®
JOURNAL
OF
RELIGION
AND
SCIENCE
</
td
>
<
td
>
https
:
//onlinelibrary.wiley.com/journal/14679744</td>
<
td
>
x
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by_nc_nd
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2024
-
12
-
31
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
12758
rows
×
12
columns
</
p
>
</
div
>
```
python
#
ouvrir
la
liste
des
journaux
TF
tf
=
pd
.
read_excel
(
'
agreements
/
TandF_titlelist_publish
.
xlsx
'
,
skiprows
=
7
)
tf
```
<
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
>
Title
</
th
>
<
th
>
ISSN
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
a
/
b
:
Auto
/
Biography
Studies
</
td
>
<
td
>
2151
-
7290
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
Accountability
in
Research
</
td
>
<
td
>
1545
-
5815
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
Accounting
and
Business
Research
</
td
>
<
td
>
2159
-
4260
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
Accounting
Education
</
td
>
<
td
>
1468
-
4489
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
Accounting
Forum
</
td
>
<
td
>
1467
-
6303
</
td
>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
2401
</
td
>
<
td
>
Writing
Systems
Research
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
2402
</
td
>
<
td
>
Xenobiotica
</
td
>
<
td
>
1366
-
5928
</
td
>
</
tr
>
<
tr
>
<
td
>
2403
</
td
>
<
td
>
Yorkshire
Archaeological
Journal
</
td
>
<
td
>
2045
-
0664
</
td
>
</
tr
>
<
tr
>
<
td
>
2404
</
td
>
<
td
>
Youth
Theatre
Journal
</
td
>
<
td
>
1948
-
4798
</
td
>
</
tr
>
<
tr
>
<
td
>
2405
</
td
>
<
td
>
Zoology
in
the
Middle
East
</
td
>
<
td
>
2326
-
2680
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
2406
rows
×
2
columns
</
p
>
</
div
>
```
python
#
ajout
du
champ
license
#
cc_by
,
cc_by_nc
,
cc_by_nc_nd
tf
[
'
article_version
'
]
=
'
published
'
tf
[
'
license
'
]
=
'
cc_by
'
tf
[
'
TF
'
]
=
'x'
#
ajout
des
dates
tf
[
'
valid_from
'
]
=
'
2021
-
01
-
01
'
tf
[
'
valid_until
'
]
=
'
2023
-
12
-
31
'
#
ajout
du
embargo
et
archiving
tf
[
'
embargo_months
'
]
=
0
tf
[
'
archiving
'
]
=
True
```
```
python
#
append
rp
=
rp
.
append
(
tf
,
ignore_index
=
True
)
rp
```
<
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
>
Elsevier
</
th
>
<
th
>
ISSN
</
th
>
<
th
>
Springer
Nature
</
th
>
<
th
>
TF
</
th
>
<
th
>
Title
</
th
>
<
th
>
URL
</
th
>
<
th
>
Wiley
</
th
>
<
th
>
archiving
</
th
>
<
th
>
article_version
</
th
>
<
th
>
embargo_months
</
th
>
<
th
>
license
</
th
>
<
th
>
valid_from
</
th
>
<
th
>
valid_until
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
x
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Academic
Pediatrics
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
x
</
td
>
<
td
>
0001
-
4575
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Accident
Analysis
and
Prevention
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
x
</
td
>
<
td
>
0361
-
3682
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Accounting
,
Organizations
and
Society
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
x
</
td
>
<
td
>
0094
-
5765
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Acta
Astronautica
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
x
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Acta
Biomaterialia
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
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
>
</
tr
>
<
tr
>
<
td
>
15159
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
Writing
Systems
Research
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>
15160
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1366
-
5928
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
Xenobiotica
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>
15161
</
td
>
<
td
>
NaN
</
td
>
<
td
>
2045
-
0664
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
Yorkshire
Archaeological
Journal
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>
15162
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1948
-
4798
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
Youth
Theatre
Journal
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>
15163
</
td
>
<
td
>
NaN
</
td
>
<
td
>
2326
-
2680
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
Zoology
in
the
Middle
East
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
15164
rows
×
13
columns
</
p
>
</
div
>
```
python
#
ouvrir
la
liste
des
journaux
CUP
cup
=
pd
.
read_excel
(
'
agreements
/
CUP_Journals_titlelist_publish
.
xlsx
'
,
skiprows
=
7
)
cup
```
<
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
>
Title
</
th
>
<
th
>
e
-
ISSN
</
th
>
<
th
>
URL
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
Agricultural
and
Resource
Economics
Review
</
td
>
<
td
>
2372
-
2614
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
AJIL
Unbound
</
td
>
<
td
>
2398
-
7723
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
Annals
of
Glaciology
</
td
>
<
td
>
1727
-
5644
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
APSIPA
Transactions
on
Signal
and
Information
...</
td
>
<
td
>
2048
-
7703
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
Biological
Imaging
</
td
>
<
td
>
2633
-
903
X
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
366
</
td
>
<
td
>
Visual
Neuroscience
</
td
>
<
td
>
1469
-
8714
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
</
tr
>
<
tr
>
<
td
>
367
</
td
>
<
td
>
Weed
Science
</
td
>
<
td
>
1550
-
2759
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
</
tr
>
<
tr
>
<
td
>
368
</
td
>
<
td
>
Weed
Technology
</
td
>
<
td
>
1550
-
2740
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
</
tr
>
<
tr
>
<
td
>
369
</
td
>
<
td
>
World
Trade
Review
</
td
>
<
td
>
1475
-
3138
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
</
tr
>
<
tr
>
<
td
>
370
</
td
>
<
td
>
Zygote
</
td
>
<
td
>
1469
-
8730
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
</
tr
>
</
tbody
>
</
table
>
<
p
>
371
rows
×
3
columns
</
p
>
</
div
>
```
python
#
renommer
l
'
ISSN
cup
=
cup
.
rename
(
columns
=
{
'
e
-
ISSN
'
:
'
ISSN
'
})
cup
```
<
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
>
Title
</
th
>
<
th
>
ISSN
</
th
>
<
th
>
URL
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
Agricultural
and
Resource
Economics
Review
</
td
>
<
td
>
2372
-
2614
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
AJIL
Unbound
</
td
>
<
td
>
2398
-
7723
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
Annals
of
Glaciology
</
td
>
<
td
>
1727
-
5644
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
APSIPA
Transactions
on
Signal
and
Information
...</
td
>
<
td
>
2048
-
7703
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
Biological
Imaging
</
td
>
<
td
>
2633
-
903
X
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
366
</
td
>
<
td
>
Visual
Neuroscience
</
td
>
<
td
>
1469
-
8714
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
</
tr
>
<
tr
>
<
td
>
367
</
td
>
<
td
>
Weed
Science
</
td
>
<
td
>
1550
-
2759
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
</
tr
>
<
tr
>
<
td
>
368
</
td
>
<
td
>
Weed
Technology
</
td
>
<
td
>
1550
-
2740
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
</
tr
>
<
tr
>
<
td
>
369
</
td
>
<
td
>
World
Trade
Review
</
td
>
<
td
>
1475
-
3138
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
</
tr
>
<
tr
>
<
td
>
370
</
td
>
<
td
>
Zygote
</
td
>
<
td
>
1469
-
8730
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
</
tr
>
</
tbody
>
</
table
>
<
p
>
371
rows
×
3
columns
</
p
>
</
div
>
```
python
#
ajout
du
champ
license
#
cc_by
,
cc_by_nc
,
cc_by_nc_nd
,
cc_by_nc_sa
cup
[
'
article_version
'
]
=
'
published
'
cup
[
'
license
'
]
=
'
cc_by
'
cup
[
'
CUP
'
]
=
'x'
#
ajout
des
dates
cup
[
'
valid_from
'
]
=
'
2021
-
01
-
01
'
cup
[
'
valid_until
'
]
=
'
2023
-
12
-
31
'
#
ajout
du
embargo
et
archiving
cup
[
'
embargo_months
'
]
=
60
cup
[
'
archiving
'
]
=
True
```
```
python
#
append
rp
=
rp
.
append
(
cup
,
ignore_index
=
True
)
cup
[
'
license
'
]
=
'
cc_by_nc
'
rp
=
rp
.
append
(
cup
,
ignore_index
=
True
)
cup
[
'
license
'
]
=
'
cc_by_nc_nd
'
rp
=
rp
.
append
(
cup
,
ignore_index
=
True
)
cup
[
'
license
'
]
=
'
cc_by_nc_sa
'
rp
=
rp
.
append
(
cup
,
ignore_index
=
True
)
rp
```
<
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
>
CUP
</
th
>
<
th
>
Elsevier
</
th
>
<
th
>
ISSN
</
th
>
<
th
>
Springer
Nature
</
th
>
<
th
>
TF
</
th
>
<
th
>
Title
</
th
>
<
th
>
URL
</
th
>
<
th
>
Wiley
</
th
>
<
th
>
archiving
</
th
>
<
th
>
article_version
</
th
>
<
th
>
embargo_months
</
th
>
<
th
>
license
</
th
>
<
th
>
valid_from
</
th
>
<
th
>
valid_until
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Academic
Pediatrics
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
0001
-
4575
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Accident
Analysis
and
Prevention
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
0361
-
3682
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Accounting
,
Organizations
and
Society
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
0094
-
5765
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Acta
Astronautica
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Acta
Biomaterialia
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
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
>
</
tr
>
<
tr
>
<
td
>
16643
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1469
-
8714
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Visual
Neuroscience
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>
16644
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1550
-
2759
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Weed
Science
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>
16645
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1550
-
2740
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Weed
Technology
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>
16646
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1475
-
3138
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
World
Trade
Review
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
</
tr
>
<
tr
>
<
td
>
16647
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1469
-
8730
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zygote
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
16648
rows
×
14
columns
</
p
>
</
div
>
```
python
#
test
des
lignes
sans
embargo
rp
.
loc
[
rp
[
'
embargo_months
'
].
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
>
CUP
</
th
>
<
th
>
Elsevier
</
th
>
<
th
>
ISSN
</
th
>
<
th
>
Springer
Nature
</
th
>
<
th
>
TF
</
th
>
<
th
>
Title
</
th
>
<
th
>
URL
</
th
>
<
th
>
Wiley
</
th
>
<
th
>
archiving
</
th
>
<
th
>
article_version
</
th
>
<
th
>
embargo_months
</
th
>
<
th
>
license
</
th
>
<
th
>
valid_from
</
th
>
<
th
>
valid_until
</
th
>
</
tr
>
</
thead
>
<
tbody
>
</
tbody
>
</
table
>
</
div
>
```
python
#
ajout
des
ISSN
-
L
issnl
=
pd
.
read_csv
(
'
issn
/
20171102
.
ISSN
-
to
-
ISSN
-
L
.
txt
'
,
encoding
=
'
utf
-
8
'
,
header
=
0
,
sep
=
'\t'
)
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
>
ISSN
</
th
>
<
th
>
ISSN
-
L
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
0000
-
0019
</
td
>
<
td
>
0000
-
0019
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
0000
-
0027
</
td
>
<
td
>
0000
-
0027
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
0000
-
0043
</
td
>
<
td
>
0000
-
0043
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
0000
-
0051
</
td
>
<
td
>
0000
-
0051
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
0000
-
006
X
</
td
>
<
td
>
0000
-
006
X
</
td
>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
1995913
</
td
>
<
td
>
8756
-
9957
</
td
>
<
td
>
8756
-
9957
</
td
>
</
tr
>
<
tr
>
<
td
>
1995914
</
td
>
<
td
>
8756
-
9965
</
td
>
<
td
>
8756
-
9965
</
td
>
</
tr
>
<
tr
>
<
td
>
1995915
</
td
>
<
td
>
8756
-
9973
</
td
>
<
td
>
8756
-
9973
</
td
>
</
tr
>
<
tr
>
<
td
>
1995916
</
td
>
<
td
>
8756
-
9981
</
td
>
<
td
>
8756
-
9981
</
td
>
</
tr
>
<
tr
>
<
td
>
1995917
</
td
>
<
td
>
8756
-
999
X
</
td
>
<
td
>
8756
-
999
X
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
1995918
rows
×
2
columns
</
p
>
</
div
>
```
python
#
renommer
les
colonnes
issnl
=
issnl
.
rename
(
columns
={
'
ISSN
'
:
'
issn
'
,
'
ISSN
-
L
'
:
'
issnl
'
})
rp
=
rp
.
rename
(
columns
={
'
ISSN
'
:
'
issn
'
})
```
```
python
#
merge
rp
=
pd
.
merge
(
rp
,
issnl
,
on
=
'
issn
'
,
how
=
'
left
'
)
rp
```
<
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
>
CUP
</
th
>
<
th
>
Elsevier
</
th
>
<
th
>
issn
</
th
>
<
th
>
Springer
Nature
</
th
>
<
th
>
TF
</
th
>
<
th
>
Title
</
th
>
<
th
>
URL
</
th
>
<
th
>
Wiley
</
th
>
<
th
>
archiving
</
th
>
<
th
>
article_version
</
th
>
<
th
>
embargo_months
</
th
>
<
th
>
license
</
th
>
<
th
>
valid_from
</
th
>
<
th
>
valid_until
</
th
>
<
th
>
issnl
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Academic
Pediatrics
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1876
-
2859
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
0001
-
4575
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Accident
Analysis
and
Prevention
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0001
-
4575
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
0361
-
3682
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Accounting
,
Organizations
and
Society
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0361
-
3682
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
0094
-
5765
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Acta
Astronautica
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0094
-
5765
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Acta
Biomaterialia
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1742
-
7061
</
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
>
</
tr
>
<
tr
>
<
td
>
16643
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1469
-
8714
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Visual
Neuroscience
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0952
-
5238
</
td
>
</
tr
>
<
tr
>
<
td
>
16644
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1550
-
2759
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Weed
Science
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0043
-
1745
</
td
>
</
tr
>
<
tr
>
<
td
>
16645
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1550
-
2740
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Weed
Technology
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0890
-
037
X
</
td
>
</
tr
>
<
tr
>
<
td
>
16646
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1475
-
3138
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
World
Trade
Review
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1474
-
7456
</
td
>
</
tr
>
<
tr
>
<
td
>
16647
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1469
-
8730
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zygote
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0967
-
1994
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
16648
rows
×
15
columns
</
p
>
</
div
>
```
python
#
cummuler
les
issns
pour
le
merge
#
rp_1
=
rp
.
loc
[
rp
[
'
issnl
'
].
notna
()][[
'
issnl
'
,
'
article_version
'
,
'
license
'
,
'
Elsevier
'
,
'
Springer
Nature
'
,
'
Wiley
'
,
'
TF
'
,
'
CUP
'
]]
#
rp_1
=
rp_1
.
rename
(
columns
=
{
'
issnl
'
:
'
issn
'
})
#
rp_2
=
rp
.
loc
[
rp
[
'
issn
'
].
notna
()][[
'
issn
'
,
'
article_version
'
,
'
license
'
,
'
Elsevier
'
,
'
Springer
Nature
'
,
'
Wiley
'
,
'
TF
'
,
'
CUP
'
]]
#
rp_all
=
rp_1
.
append
(
rp_2
,
ignore_index
=
True
)
rp_all
=
rp
```
```
python
#
ajouter
les
champs
manquants
#
valeur
discount
(
id
2
)
à
100
%
pour
les
licences
read
&
publish
#
elsevier
[
'
amount
'
]
=
100
#
elsevier
[
'
symbol
'
]
=
'%'
#
elsevier
[
'
cost_factor_type
'
]
=
2
#
elsevier
[
'
comment
'
]
=
'
Source
:
swissuniversities
'
#
elsevier
```
```
python
#
merge
avec
les
organisations
#
'
Elsevier
'
,
'
Springer
Nature
'
,
'
Wiley
'
,
'
TF
'
,
'
CUP
'
participants_elsevier
=
participants
.
loc
[
participants
[
'
Elsevier
'
].
notna
()][[
'
Elsevier
'
,
'
ROR
'
]]
rp_elsevier
=
rp_all
.
loc
[
rp_all
[
'
Elsevier
'
].
notna
()]
rp_1
=
pd
.
merge
(
rp_elsevier
,
participants_elsevier
,
on
=
'
Elsevier
'
,
how
=
'
outer
'
)
rp_1
```
<
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
>
CUP
</
th
>
<
th
>
Elsevier
</
th
>
<
th
>
issn
</
th
>
<
th
>
Springer
Nature
</
th
>
<
th
>
TF
</
th
>
<
th
>
Title
</
th
>
<
th
>
URL
</
th
>
<
th
>
Wiley
</
th
>
<
th
>
archiving
</
th
>
<
th
>
article_version
</
th
>
<
th
>
embargo_months
</
th
>
<
th
>
license
</
th
>
<
th
>
valid_from
</
th
>
<
th
>
valid_until
</
th
>
<
th
>
issnl
</
th
>
<
th
>
ROR
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Academic
Pediatrics
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
https
:
//ror.org/04d8ztx87</td>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Academic
Pediatrics
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
https
:
//ror.org/02bnkt322</td>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Academic
Pediatrics
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
https
:
//ror.org/00zg4za48</td>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Academic
Pediatrics
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
https
:
//ror.org/02s376052</td>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Academic
Pediatrics
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
https
:
//ror.org/05a28rw58</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
>
197555
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
0944
-
2006
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zoology
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by_nc_nd
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0944
-
2006
</
td
>
<
td
>
https
:
//ror.org/01swzsf04</td>
</
tr
>
<
tr
>
<
td
>
197556
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
0944
-
2006
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zoology
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by_nc_nd
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0944
-
2006
</
td
>
<
td
>
https
:
//ror.org/019whta54</td>
</
tr
>
<
tr
>
<
td
>
197557
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
0944
-
2006
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zoology
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by_nc_nd
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0944
-
2006
</
td
>
<
td
>
https
:
//ror.org/00vasag41</td>
</
tr
>
<
tr
>
<
td
>
197558
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
0944
-
2006
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zoology
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by_nc_nd
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0944
-
2006
</
td
>
<
td
>
https
:
//ror.org/05r0ap620</td>
</
tr
>
<
tr
>
<
td
>
197559
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
0944
-
2006
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zoology
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by_nc_nd
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0944
-
2006
</
td
>
<
td
>
https
:
//ror.org/05pmsvm27</td>
</
tr
>
</
tbody
>
</
table
>
<
p
>
197560
rows
×
16
columns
</
p
>
</
div
>
```
python
rp_elsevier
```
<
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
>
CUP
</
th
>
<
th
>
Elsevier
</
th
>
<
th
>
issn
</
th
>
<
th
>
Springer
Nature
</
th
>
<
th
>
TF
</
th
>
<
th
>
Title
</
th
>
<
th
>
URL
</
th
>
<
th
>
Wiley
</
th
>
<
th
>
archiving
</
th
>
<
th
>
article_version
</
th
>
<
th
>
embargo_months
</
th
>
<
th
>
license
</
th
>
<
th
>
valid_from
</
th
>
<
th
>
valid_until
</
th
>
<
th
>
issnl
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Academic
Pediatrics
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1876
-
2859
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
0001
-
4575
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Accident
Analysis
and
Prevention
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0001
-
4575
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
0361
-
3682
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Accounting
,
Organizations
and
Society
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0361
-
3682
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
0094
-
5765
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Acta
Astronautica
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0094
-
5765
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Acta
Biomaterialia
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1742
-
7061
</
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
>
</
tr
>
<
tr
>
<
td
>
4485
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
2213
-
9095
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Wound
Medicine
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by_nc_nd
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
2213
-
9095
</
td
>
</
tr
>
<
tr
>
<
td
>
4486
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1865
-
9217
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zeitschrift
fuer
Evidenz
,
Fortbildung
und
Qual
...</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by_nc_nd
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1865
-
9217
</
td
>
</
tr
>
<
tr
>
<
td
>
4487
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
0939
-
3889
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zeitschrift
fuer
Medizinische
Physik
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by_nc_nd
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0939
-
3889
</
td
>
</
tr
>
<
tr
>
<
td
>
4488
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
0044
-
5231
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zoologischer
Anzeiger
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by_nc_nd
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0044
-
5231
</
td
>
</
tr
>
<
tr
>
<
td
>
4489
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
0944
-
2006
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zoology
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by_nc_nd
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0944
-
2006
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
4490
rows
×
15
columns
</
p
>
</
div
>
```
python
participants_elsevier
```
<
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
>
Elsevier
</
th
>
<
th
>
ROR
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/04d8ztx87</td>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/02bnkt322</td>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/00zg4za48</td>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/02s376052</td>
</
tr
>
<
tr
>
<
td
>
5
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/05a28rw58</td>
</
tr
>
<
tr
>
<
td
>
6
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/032ymzc07</td>
</
tr
>
<
tr
>
<
td
>
7
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/04mq2g308</td>
</
tr
>
<
tr
>
<
td
>
8
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/0210tb741</td>
</
tr
>
<
tr
>
<
td
>
9
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/007ygn379</td>
</
tr
>
<
tr
>
<
td
>
10
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/01xkakk17</td>
</
tr
>
<
tr
>
<
td
>
11
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/015pmkr43</td>
</
tr
>
<
tr
>
<
td
>
12
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/048gre751</td>
</
tr
>
<
tr
>
<
td
>
13
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/01bvm0h13</td>
</
tr
>
<
tr
>
<
td
>
14
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/02ejkey04</td>
</
tr
>
<
tr
>
<
td
>
15
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/04nd0xd48</td>
</
tr
>
<
tr
>
<
td
>
16
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/00w9q2c06</td>
</
tr
>
<
tr
>
<
td
>
17
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/049c2kr37</td>
</
tr
>
<
tr
>
<
td
>
20
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/00p9jf779</td>
</
tr
>
<
tr
>
<
td
>
21
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/038mj2660</td>
</
tr
>
<
tr
>
<
td
>
22
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/01awgk221</td>
</
tr
>
<
tr
>
<
td
>
23
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/05jf1ma54</td>
</
tr
>
<
tr
>
<
td
>
24
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/02fjgft97</td>
</
tr
>
<
tr
>
<
td
>
25
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/0235ynq74</td>
</
tr
>
<
tr
>
<
td
>
26
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/03fs41j10</td>
</
tr
>
<
tr
>
<
td
>
27
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/00rqdn375</td>
</
tr
>
<
tr
>
<
td
>
28
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/05m37v666</td>
</
tr
>
<
tr
>
<
td
>
29
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/04bf6dq94</td>
</
tr
>
<
tr
>
<
td
>
30
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/040gs8e06</td>
</
tr
>
<
tr
>
<
td
>
31
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/05ghhx264</td>
</
tr
>
<
tr
>
<
td
>
32
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/03mcsbr76</td>
</
tr
>
<
tr
>
<
td
>
33
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/05ep8g269</td>
</
tr
>
<
tr
>
<
td
>
34
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/03c4atk17</td>
</
tr
>
<
tr
>
<
td
>
35
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/02s6k3f65</td>
</
tr
>
<
tr
>
<
td
>
36
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/02k7v4d05</td>
</
tr
>
<
tr
>
<
td
>
37
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/01qjrx392</td>
</
tr
>
<
tr
>
<
td
>
38
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/00kgrkn83</td>
</
tr
>
<
tr
>
<
td
>
39
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/0561a3s31</td>
</
tr
>
<
tr
>
<
td
>
40
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/02crff812</td>
</
tr
>
<
tr
>
<
td
>
41
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/022fs9h90</td>
</
tr
>
<
tr
>
<
td
>
42
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/01swzsf04</td>
</
tr
>
<
tr
>
<
td
>
43
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/019whta54</td>
</
tr
>
<
tr
>
<
td
>
44
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/00vasag41</td>
</
tr
>
<
tr
>
<
td
>
45
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/05r0ap620</td>
</
tr
>
<
tr
>
<
td
>
46
</
td
>
<
td
>
x
</
td
>
<
td
>
https
:
//ror.org/05pmsvm27</td>
</
tr
>
</
tbody
>
</
table
>
</
div
>
```
python
#
merge
avec
les
organisations
#
'
Elsevier
'
,
'
Springer
Nature
'
,
'
Wiley
'
,
'
TF
'
,
'
CUP
'
participants_springer
=
participants
.
loc
[
participants
[
'
Springer
Nature
'
].
notna
()][[
'
Springer
Nature
'
,
'
ROR
'
]]
rp_springer
=
rp_all
.
loc
[
rp_all
[
'
Springer
Nature
'
].
notna
()]
rp_2
=
pd
.
merge
(
rp_springer
,
participants_springer
,
on
=
'
Springer
Nature
'
,
how
=
'
outer
'
)
rp_2
```
<
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
>
CUP
</
th
>
<
th
>
Elsevier
</
th
>
<
th
>
issn
</
th
>
<
th
>
Springer
Nature
</
th
>
<
th
>
TF
</
th
>
<
th
>
Title
</
th
>
<
th
>
URL
</
th
>
<
th
>
Wiley
</
th
>
<
th
>
archiving
</
th
>
<
th
>
article_version
</
th
>
<
th
>
embargo_months
</
th
>
<
th
>
license
</
th
>
<
th
>
valid_from
</
th
>
<
th
>
valid_until
</
th
>
<
th
>
issnl
</
th
>
<
th
>
ROR
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
2190
-
5738
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
3
Biotech
</
td
>
<
td
>
https
:
//www.springer.com/journal/13205</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2022
-
12
-
31
</
td
>
<
td
>
2190
-
5738
</
td
>
<
td
>
https
:
//ror.org/04d8ztx87</td>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
2190
-
5738
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
3
Biotech
</
td
>
<
td
>
https
:
//www.springer.com/journal/13205</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2022
-
12
-
31
</
td
>
<
td
>
2190
-
5738
</
td
>
<
td
>
https
:
//ror.org/02bnkt322</td>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
2190
-
5738
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
3
Biotech
</
td
>
<
td
>
https
:
//www.springer.com/journal/13205</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2022
-
12
-
31
</
td
>
<
td
>
2190
-
5738
</
td
>
<
td
>
https
:
//ror.org/01ggx4157</td>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
2190
-
5738
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
3
Biotech
</
td
>
<
td
>
https
:
//www.springer.com/journal/13205</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2022
-
12
-
31
</
td
>
<
td
>
2190
-
5738
</
td
>
<
td
>
https
:
//ror.org/00zg4za48</td>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
2190
-
5738
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
3
Biotech
</
td
>
<
td
>
https
:
//www.springer.com/journal/13205</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2022
-
12
-
31
</
td
>
<
td
>
2190
-
5738
</
td
>
<
td
>
https
:
//ror.org/02s376052</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
>
187675
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1432
-
234
X
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zoomorphology
</
td
>
<
td
>
https
:
//www.springer.com/journal/435</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by_nc
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2022
-
12
-
31
</
td
>
<
td
>
0720
-
213
X
</
td
>
<
td
>
https
:
//ror.org/01swzsf04</td>
</
tr
>
<
tr
>
<
td
>
187676
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1432
-
234
X
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zoomorphology
</
td
>
<
td
>
https
:
//www.springer.com/journal/435</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by_nc
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2022
-
12
-
31
</
td
>
<
td
>
0720
-
213
X
</
td
>
<
td
>
https
:
//ror.org/019whta54</td>
</
tr
>
<
tr
>
<
td
>
187677
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1432
-
234
X
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zoomorphology
</
td
>
<
td
>
https
:
//www.springer.com/journal/435</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by_nc
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2022
-
12
-
31
</
td
>
<
td
>
0720
-
213
X
</
td
>
<
td
>
https
:
//ror.org/00vasag41</td>
</
tr
>
<
tr
>
<
td
>
187678
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1432
-
234
X
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zoomorphology
</
td
>
<
td
>
https
:
//www.springer.com/journal/435</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by_nc
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2022
-
12
-
31
</
td
>
<
td
>
0720
-
213
X
</
td
>
<
td
>
https
:
//ror.org/05r0ap620</td>
</
tr
>
<
tr
>
<
td
>
187679
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1432
-
234
X
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zoomorphology
</
td
>
<
td
>
https
:
//www.springer.com/journal/435</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by_nc
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2022
-
12
-
31
</
td
>
<
td
>
0720
-
213
X
</
td
>
<
td
>
https
:
//ror.org/05pmsvm27</td>
</
tr
>
</
tbody
>
</
table
>
<
p
>
187680
rows
×
16
columns
</
p
>
</
div
>
```
python
#
merge
avec
les
organisations
#
'
Elsevier
'
,
'
Springer
Nature
'
,
'
Wiley
'
,
'
TF
'
,
'
CUP
'
participants_wiley
=
participants
.
loc
[
participants
[
'
Wiley
'
].
notna
()][[
'
Wiley
'
,
'
ROR
'
]]
rp_wiley
=
rp_all
.
loc
[
rp_all
[
'
Wiley
'
].
notna
()]
rp_3
=
pd
.
merge
(
rp_wiley
,
participants_wiley
,
on
=
'
Wiley
'
,
how
=
'
outer
'
)
rp_3
```
<
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
>
CUP
</
th
>
<
th
>
Elsevier
</
th
>
<
th
>
issn
</
th
>
<
th
>
Springer
Nature
</
th
>
<
th
>
TF
</
th
>
<
th
>
Title
</
th
>
<
th
>
URL
</
th
>
<
th
>
Wiley
</
th
>
<
th
>
archiving
</
th
>
<
th
>
article_version
</
th
>
<
th
>
embargo_months
</
th
>
<
th
>
license
</
th
>
<
th
>
valid_from
</
th
>
<
th
>
valid_until
</
th
>
<
th
>
issnl
</
th
>
<
th
>
ROR
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1467
-
6281
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
ABACUS
</
td
>
<
td
>
https
:
//onlinelibrary.wiley.com/journal/14676281</td>
<
td
>
x
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2024
-
12
-
31
</
td
>
<
td
>
0001
-
3072
</
td
>
<
td
>
https
:
//ror.org/04d8ztx87</td>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1467
-
6281
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
ABACUS
</
td
>
<
td
>
https
:
//onlinelibrary.wiley.com/journal/14676281</td>
<
td
>
x
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2024
-
12
-
31
</
td
>
<
td
>
0001
-
3072
</
td
>
<
td
>
https
:
//ror.org/02bnkt322</td>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1467
-
6281
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
ABACUS
</
td
>
<
td
>
https
:
//onlinelibrary.wiley.com/journal/14676281</td>
<
td
>
x
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2024
-
12
-
31
</
td
>
<
td
>
0001
-
3072
</
td
>
<
td
>
https
:
//ror.org/01ggx4157</td>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1467
-
6281
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
ABACUS
</
td
>
<
td
>
https
:
//onlinelibrary.wiley.com/journal/14676281</td>
<
td
>
x
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2024
-
12
-
31
</
td
>
<
td
>
0001
-
3072
</
td
>
<
td
>
https
:
//ror.org/00zg4za48</td>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1467
-
6281
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
ABACUS
</
td
>
<
td
>
https
:
//onlinelibrary.wiley.com/journal/14676281</td>
<
td
>
x
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2024
-
12
-
31
</
td
>
<
td
>
0001
-
3072
</
td
>
<
td
>
https
:
//ror.org/02s376052</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
>
188455
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1467
-
9744
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
ZYGON
®
JOURNAL
OF
RELIGION
AND
SCIENCE
</
td
>
<
td
>
https
:
//onlinelibrary.wiley.com/journal/14679744</td>
<
td
>
x
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by_nc_nd
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2024
-
12
-
31
</
td
>
<
td
>
0591
-
2385
</
td
>
<
td
>
https
:
//ror.org/01swzsf04</td>
</
tr
>
<
tr
>
<
td
>
188456
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1467
-
9744
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
ZYGON
®
JOURNAL
OF
RELIGION
AND
SCIENCE
</
td
>
<
td
>
https
:
//onlinelibrary.wiley.com/journal/14679744</td>
<
td
>
x
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by_nc_nd
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2024
-
12
-
31
</
td
>
<
td
>
0591
-
2385
</
td
>
<
td
>
https
:
//ror.org/019whta54</td>
</
tr
>
<
tr
>
<
td
>
188457
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1467
-
9744
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
ZYGON
®
JOURNAL
OF
RELIGION
AND
SCIENCE
</
td
>
<
td
>
https
:
//onlinelibrary.wiley.com/journal/14679744</td>
<
td
>
x
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by_nc_nd
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2024
-
12
-
31
</
td
>
<
td
>
0591
-
2385
</
td
>
<
td
>
https
:
//ror.org/00vasag41</td>
</
tr
>
<
tr
>
<
td
>
188458
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1467
-
9744
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
ZYGON
®
JOURNAL
OF
RELIGION
AND
SCIENCE
</
td
>
<
td
>
https
:
//onlinelibrary.wiley.com/journal/14679744</td>
<
td
>
x
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by_nc_nd
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2024
-
12
-
31
</
td
>
<
td
>
0591
-
2385
</
td
>
<
td
>
https
:
//ror.org/05r0ap620</td>
</
tr
>
<
tr
>
<
td
>
188459
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1467
-
9744
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
ZYGON
®
JOURNAL
OF
RELIGION
AND
SCIENCE
</
td
>
<
td
>
https
:
//onlinelibrary.wiley.com/journal/14679744</td>
<
td
>
x
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by_nc_nd
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2024
-
12
-
31
</
td
>
<
td
>
0591
-
2385
</
td
>
<
td
>
https
:
//ror.org/05pmsvm27</td>
</
tr
>
</
tbody
>
</
table
>
<
p
>
188460
rows
×
16
columns
</
p
>
</
div
>
```
python
rp_wiley
```
<
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
>
CUP
</
th
>
<
th
>
Elsevier
</
th
>
<
th
>
issn
</
th
>
<
th
>
Springer
Nature
</
th
>
<
th
>
TF
</
th
>
<
th
>
Title
</
th
>
<
th
>
URL
</
th
>
<
th
>
Wiley
</
th
>
<
th
>
archiving
</
th
>
<
th
>
article_version
</
th
>
<
th
>
embargo_months
</
th
>
<
th
>
license
</
th
>
<
th
>
valid_from
</
th
>
<
th
>
valid_until
</
th
>
<
th
>
issnl
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
8570
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1467
-
6281
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
ABACUS
</
td
>
<
td
>
https
:
//onlinelibrary.wiley.com/journal/14676281</td>
<
td
>
x
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2024
-
12
-
31
</
td
>
<
td
>
0001
-
3072
</
td
>
</
tr
>
<
tr
>
<
td
>
8571
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1553
-
2712
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
ACADEMIC
EMERGENCY
MEDICINE
</
td
>
<
td
>
https
:
//onlinelibrary.wiley.com/journal/15532712</td>
<
td
>
x
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2024
-
12
-
31
</
td
>
<
td
>
1069
-
6563
</
td
>
</
tr
>
<
tr
>
<
td
>
8572
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1467
-
629
X
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
ACCOUNTING
&
amp
;
FINANCE
</
td
>
<
td
>
https
:
//onlinelibrary.wiley.com/journal/1467629X</td>
<
td
>
x
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2024
-
12
-
31
</
td
>
<
td
>
0810
-
5391
</
td
>
</
tr
>
<
tr
>
<
td
>
8573
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1911
-
3838
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
ACCOUNTING
PERSPECTIVES
</
td
>
<
td
>
https
:
//onlinelibrary.wiley.com/journal/19113838</td>
<
td
>
x
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2024
-
12
-
31
</
td
>
<
td
>
1911
-
382
X
</
td
>
</
tr
>
<
tr
>
<
td
>
8574
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1399
-
6576
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
ACTA
ANAESTHESIOLOGICA
SCANDINAVICA
</
td
>
<
td
>
https
:
//onlinelibrary.wiley.com/journal/13996576</td>
<
td
>
x
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2024
-
12
-
31
</
td
>
<
td
>
0001
-
5172
</
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
>
</
tr
>
<
tr
>
<
td
>
12753
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1521
-
3749
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
ZEITSCHRIFT
F
ü
R
ANORGANISCHE
UND
ALLGEMEINE
CH
...</
td
>
<
td
>
https
:
//onlinelibrary.wiley.com/journal/15213749</td>
<
td
>
x
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by_nc_nd
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2024
-
12
-
31
</
td
>
<
td
>
0044
-
2313
</
td
>
</
tr
>
<
tr
>
<
td
>
12754
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1098
-
2361
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
ZOO
BIOLOGY
</
td
>
<
td
>
https
:
//onlinelibrary.wiley.com/journal/10982361</td>
<
td
>
x
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by_nc_nd
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2024
-
12
-
31
</
td
>
<
td
>
0733
-
3188
</
td
>
</
tr
>
<
tr
>
<
td
>
12755
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1463
-
6409
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
ZOOLOGICA
SCRIPTA
</
td
>
<
td
>
https
:
//onlinelibrary.wiley.com/journal/14636409</td>
<
td
>
x
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by_nc_nd
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2024
-
12
-
31
</
td
>
<
td
>
0300
-
3256
</
td
>
</
tr
>
<
tr
>
<
td
>
12756
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1863
-
2378
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
ZOONOSES
AND
PUBLIC
HEALTH
</
td
>
<
td
>
https
:
//onlinelibrary.wiley.com/journal/18632378</td>
<
td
>
x
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by_nc_nd
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2024
-
12
-
31
</
td
>
<
td
>
1863
-
1959
</
td
>
</
tr
>
<
tr
>
<
td
>
12757
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1467
-
9744
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
ZYGON
®
JOURNAL
OF
RELIGION
AND
SCIENCE
</
td
>
<
td
>
https
:
//onlinelibrary.wiley.com/journal/14679744</td>
<
td
>
x
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by_nc_nd
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2024
-
12
-
31
</
td
>
<
td
>
0591
-
2385
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
4188
rows
×
15
columns
</
p
>
</
div
>
```
python
#
merge
avec
les
organisations
#
'
Elsevier
'
,
'
Springer
Nature
'
,
'
Wiley
'
,
'
TF
'
,
'
CUP
'
participants_tf
=
participants
.
loc
[
participants
[
'
TF
'
].
notna
()][[
'
TF
'
,
'
ROR
'
]]
rp_tf
=
rp_all
.
loc
[
rp_all
[
'
TF
'
].
notna
()]
rp_4
=
pd
.
merge
(
rp_tf
,
participants_tf
,
on
=
'
TF
'
,
how
=
'
outer
'
)
rp_4
```
<
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
>
CUP
</
th
>
<
th
>
Elsevier
</
th
>
<
th
>
issn
</
th
>
<
th
>
Springer
Nature
</
th
>
<
th
>
TF
</
th
>
<
th
>
Title
</
th
>
<
th
>
URL
</
th
>
<
th
>
Wiley
</
th
>
<
th
>
archiving
</
th
>
<
th
>
article_version
</
th
>
<
th
>
embargo_months
</
th
>
<
th
>
license
</
th
>
<
th
>
valid_from
</
th
>
<
th
>
valid_until
</
th
>
<
th
>
issnl
</
th
>
<
th
>
ROR
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
2151
-
7290
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
a
/
b
:
Auto
/
Biography
Studies
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0898
-
9575
</
td
>
<
td
>
https
:
//ror.org/04d8ztx87</td>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
2151
-
7290
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
a
/
b
:
Auto
/
Biography
Studies
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0898
-
9575
</
td
>
<
td
>
https
:
//ror.org/02bnkt322</td>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
2151
-
7290
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
a
/
b
:
Auto
/
Biography
Studies
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0898
-
9575
</
td
>
<
td
>
https
:
//ror.org/01ggx4157</td>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
2151
-
7290
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
a
/
b
:
Auto
/
Biography
Studies
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0898
-
9575
</
td
>
<
td
>
https
:
//ror.org/00zg4za48</td>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
2151
-
7290
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
a
/
b
:
Auto
/
Biography
Studies
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0898
-
9575
</
td
>
<
td
>
https
:
//ror.org/02s376052</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
>
110671
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
2326
-
2680
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
Zoology
in
the
Middle
East
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0939
-
7140
</
td
>
<
td
>
https
:
//ror.org/01swzsf04</td>
</
tr
>
<
tr
>
<
td
>
110672
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
2326
-
2680
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
Zoology
in
the
Middle
East
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0939
-
7140
</
td
>
<
td
>
https
:
//ror.org/019whta54</td>
</
tr
>
<
tr
>
<
td
>
110673
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
2326
-
2680
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
Zoology
in
the
Middle
East
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0939
-
7140
</
td
>
<
td
>
https
:
//ror.org/00vasag41</td>
</
tr
>
<
tr
>
<
td
>
110674
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
2326
-
2680
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
Zoology
in
the
Middle
East
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0939
-
7140
</
td
>
<
td
>
https
:
//ror.org/05r0ap620</td>
</
tr
>
<
tr
>
<
td
>
110675
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
2326
-
2680
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
Zoology
in
the
Middle
East
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0939
-
7140
</
td
>
<
td
>
https
:
//ror.org/05pmsvm27</td>
</
tr
>
</
tbody
>
</
table
>
<
p
>
110676
rows
×
16
columns
</
p
>
</
div
>
```
python
#
merge
avec
les
organisations
#
'
Elsevier
'
,
'
Springer
Nature
'
,
'
Wiley
'
,
'
TF
'
,
'
CUP
'
participants_cup
=
participants
.
loc
[
participants
[
'
CUP
'
].
notna
()][[
'
CUP
'
,
'
ROR
'
]]
rp_cup
=
rp_all
.
loc
[
rp_all
[
'
CUP
'
].
notna
()]
rp_5
=
pd
.
merge
(
rp_cup
,
participants_cup
,
on
=
'
CUP
'
,
how
=
'
outer
'
)
rp_5
```
<
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
>
CUP
</
th
>
<
th
>
Elsevier
</
th
>
<
th
>
issn
</
th
>
<
th
>
Springer
Nature
</
th
>
<
th
>
TF
</
th
>
<
th
>
Title
</
th
>
<
th
>
URL
</
th
>
<
th
>
Wiley
</
th
>
<
th
>
archiving
</
th
>
<
th
>
article_version
</
th
>
<
th
>
embargo_months
</
th
>
<
th
>
license
</
th
>
<
th
>
valid_from
</
th
>
<
th
>
valid_until
</
th
>
<
th
>
issnl
</
th
>
<
th
>
ROR
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
2372
-
2614
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Agricultural
and
Resource
Economics
Review
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1068
-
2805
</
td
>
<
td
>
https
:
//ror.org/04d8ztx87</td>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
2372
-
2614
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Agricultural
and
Resource
Economics
Review
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1068
-
2805
</
td
>
<
td
>
https
:
//ror.org/02bnkt322</td>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
2372
-
2614
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Agricultural
and
Resource
Economics
Review
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1068
-
2805
</
td
>
<
td
>
https
:
//ror.org/01ggx4157</td>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
2372
-
2614
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Agricultural
and
Resource
Economics
Review
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1068
-
2805
</
td
>
<
td
>
https
:
//ror.org/00zg4za48</td>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
2372
-
2614
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Agricultural
and
Resource
Economics
Review
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1068
-
2805
</
td
>
<
td
>
https
:
//ror.org/02s376052</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
>
68259
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1469
-
8730
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zygote
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0967
-
1994
</
td
>
<
td
>
https
:
//ror.org/01swzsf04</td>
</
tr
>
<
tr
>
<
td
>
68260
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1469
-
8730
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zygote
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0967
-
1994
</
td
>
<
td
>
https
:
//ror.org/019whta54</td>
</
tr
>
<
tr
>
<
td
>
68261
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1469
-
8730
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zygote
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0967
-
1994
</
td
>
<
td
>
https
:
//ror.org/00vasag41</td>
</
tr
>
<
tr
>
<
td
>
68262
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1469
-
8730
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zygote
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0967
-
1994
</
td
>
<
td
>
https
:
//ror.org/05r0ap620</td>
</
tr
>
<
tr
>
<
td
>
68263
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1469
-
8730
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zygote
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0967
-
1994
</
td
>
<
td
>
https
:
//ror.org/05pmsvm27</td>
</
tr
>
</
tbody
>
</
table
>
<
p
>
68264
rows
×
16
columns
</
p
>
</
div
>
```
python
#
concat
des
5
rp_fin
=
rp_1
.
append
(
rp_2
,
ignore_index
=
True
)
rp_fin
=
rp_fin
.
append
(
rp_3
,
ignore_index
=
True
)
rp_fin
=
rp_fin
.
append
(
rp_4
,
ignore_index
=
True
)
rp_fin
=
rp_fin
.
append
(
rp_5
,
ignore_index
=
True
)
rp_fin
```
<
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
>
CUP
</
th
>
<
th
>
Elsevier
</
th
>
<
th
>
issn
</
th
>
<
th
>
Springer
Nature
</
th
>
<
th
>
TF
</
th
>
<
th
>
Title
</
th
>
<
th
>
URL
</
th
>
<
th
>
Wiley
</
th
>
<
th
>
archiving
</
th
>
<
th
>
article_version
</
th
>
<
th
>
embargo_months
</
th
>
<
th
>
license
</
th
>
<
th
>
valid_from
</
th
>
<
th
>
valid_until
</
th
>
<
th
>
issnl
</
th
>
<
th
>
ROR
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Academic
Pediatrics
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
https
:
//ror.org/04d8ztx87</td>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Academic
Pediatrics
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
https
:
//ror.org/02bnkt322</td>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Academic
Pediatrics
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
https
:
//ror.org/00zg4za48</td>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Academic
Pediatrics
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
https
:
//ror.org/02s376052</td>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Academic
Pediatrics
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
https
:
//ror.org/05a28rw58</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
>
752635
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1469
-
8730
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zygote
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0967
-
1994
</
td
>
<
td
>
https
:
//ror.org/01swzsf04</td>
</
tr
>
<
tr
>
<
td
>
752636
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1469
-
8730
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zygote
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0967
-
1994
</
td
>
<
td
>
https
:
//ror.org/019whta54</td>
</
tr
>
<
tr
>
<
td
>
752637
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1469
-
8730
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zygote
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0967
-
1994
</
td
>
<
td
>
https
:
//ror.org/00vasag41</td>
</
tr
>
<
tr
>
<
td
>
752638
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1469
-
8730
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zygote
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0967
-
1994
</
td
>
<
td
>
https
:
//ror.org/05r0ap620</td>
</
tr
>
<
tr
>
<
td
>
752639
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1469
-
8730
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zygote
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0967
-
1994
</
td
>
<
td
>
https
:
//ror.org/05pmsvm27</td>
</
tr
>
</
tbody
>
</
table
>
<
p
>
752640
rows
×
16
columns
</
p
>
</
div
>
```
python
#
supprimer
les
doublons
et
les
vides
rp_fin
=
rp_fin
.
dropna
(
subset
=[
'
issn
'
])
rp_fin
=
rp_fin
.
drop_duplicates
(
subset
=[
'
issn
'
,
'
license
'
,
'
ROR
'
])
rp_fin
```
<
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
>
CUP
</
th
>
<
th
>
Elsevier
</
th
>
<
th
>
issn
</
th
>
<
th
>
Springer
Nature
</
th
>
<
th
>
TF
</
th
>
<
th
>
Title
</
th
>
<
th
>
URL
</
th
>
<
th
>
Wiley
</
th
>
<
th
>
archiving
</
th
>
<
th
>
article_version
</
th
>
<
th
>
embargo_months
</
th
>
<
th
>
license
</
th
>
<
th
>
valid_from
</
th
>
<
th
>
valid_until
</
th
>
<
th
>
issnl
</
th
>
<
th
>
ROR
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Academic
Pediatrics
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
https
:
//ror.org/04d8ztx87</td>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Academic
Pediatrics
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
https
:
//ror.org/02bnkt322</td>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Academic
Pediatrics
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
https
:
//ror.org/00zg4za48</td>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Academic
Pediatrics
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
https
:
//ror.org/02s376052</td>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Academic
Pediatrics
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
https
:
//ror.org/05a28rw58</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
>
752635
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1469
-
8730
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zygote
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0967
-
1994
</
td
>
<
td
>
https
:
//ror.org/01swzsf04</td>
</
tr
>
<
tr
>
<
td
>
752636
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1469
-
8730
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zygote
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0967
-
1994
</
td
>
<
td
>
https
:
//ror.org/019whta54</td>
</
tr
>
<
tr
>
<
td
>
752637
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1469
-
8730
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zygote
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0967
-
1994
</
td
>
<
td
>
https
:
//ror.org/00vasag41</td>
</
tr
>
<
tr
>
<
td
>
752638
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1469
-
8730
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zygote
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0967
-
1994
</
td
>
<
td
>
https
:
//ror.org/05r0ap620</td>
</
tr
>
<
tr
>
<
td
>
752639
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1469
-
8730
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zygote
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0967
-
1994
</
td
>
<
td
>
https
:
//ror.org/05pmsvm27</td>
</
tr
>
</
tbody
>
</
table
>
<
p
>
751628
rows
×
16
columns
</
p
>
</
div
>
```
python
#
reindex
et
ajout
de
l
'
id
avec
l
'
index
+
1
rp_fin
=
rp_fin
.
reset_index
()
del
rp_fin
[
'
index
'
]
rp_fin
=
rp_fin
.
reset_index
()
rp_fin
[
'
rp_id
'
]
=
rp_fin
.
index
+
1
rp_fin
```
<
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
>
index
</
th
>
<
th
>
CUP
</
th
>
<
th
>
Elsevier
</
th
>
<
th
>
issn
</
th
>
<
th
>
Springer
Nature
</
th
>
<
th
>
TF
</
th
>
<
th
>
Title
</
th
>
<
th
>
URL
</
th
>
<
th
>
Wiley
</
th
>
<
th
>
archiving
</
th
>
<
th
>
article_version
</
th
>
<
th
>
embargo_months
</
th
>
<
th
>
license
</
th
>
<
th
>
valid_from
</
th
>
<
th
>
valid_until
</
th
>
<
th
>
issnl
</
th
>
<
th
>
ROR
</
th
>
<
th
>
rp_id
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Academic
Pediatrics
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
https
:
//ror.org/04d8ztx87</td>
<
td
>
1
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Academic
Pediatrics
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
https
:
//ror.org/02bnkt322</td>
<
td
>
2
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
2
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Academic
Pediatrics
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
https
:
//ror.org/00zg4za48</td>
<
td
>
3
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
3
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Academic
Pediatrics
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
https
:
//ror.org/02s376052</td>
<
td
>
4
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
4
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Academic
Pediatrics
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
https
:
//ror.org/05a28rw58</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
>
</
tr
>
<
tr
>
<
td
>
751623
</
td
>
<
td
>
751623
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1469
-
8730
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zygote
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0967
-
1994
</
td
>
<
td
>
https
:
//ror.org/01swzsf04</td>
<
td
>
751624
</
td
>
</
tr
>
<
tr
>
<
td
>
751624
</
td
>
<
td
>
751624
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1469
-
8730
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zygote
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0967
-
1994
</
td
>
<
td
>
https
:
//ror.org/019whta54</td>
<
td
>
751625
</
td
>
</
tr
>
<
tr
>
<
td
>
751625
</
td
>
<
td
>
751625
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1469
-
8730
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zygote
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0967
-
1994
</
td
>
<
td
>
https
:
//ror.org/00vasag41</td>
<
td
>
751626
</
td
>
</
tr
>
<
tr
>
<
td
>
751626
</
td
>
<
td
>
751626
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1469
-
8730
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zygote
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0967
-
1994
</
td
>
<
td
>
https
:
//ror.org/05r0ap620</td>
<
td
>
751627
</
td
>
</
tr
>
<
tr
>
<
td
>
751627
</
td
>
<
td
>
751627
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1469
-
8730
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zygote
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0967
-
1994
</
td
>
<
td
>
https
:
//ror.org/05pmsvm27</td>
<
td
>
751628
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
751628
rows
×
18
columns
</
p
>
</
div
>
```
python
rp_fin
[
'
embargo_months
'
].
value_counts
()
```
0
683364
60
68264
Name
:
embargo_months
,
dtype
:
int64
```
python
#
test
des
lignes
sans
embargo
rp_fin
.
loc
[
rp_fin
[
'
embargo_months
'
].
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
>
index
</
th
>
<
th
>
CUP
</
th
>
<
th
>
Elsevier
</
th
>
<
th
>
issn
</
th
>
<
th
>
Springer
Nature
</
th
>
<
th
>
TF
</
th
>
<
th
>
Title
</
th
>
<
th
>
URL
</
th
>
<
th
>
Wiley
</
th
>
<
th
>
archiving
</
th
>
<
th
>
article_version
</
th
>
<
th
>
embargo_months
</
th
>
<
th
>
license
</
th
>
<
th
>
valid_from
</
th
>
<
th
>
valid_until
</
th
>
<
th
>
issnl
</
th
>
<
th
>
ROR
</
th
>
<
th
>
rp_id
</
th
>
</
tr
>
</
thead
>
<
tbody
>
</
tbody
>
</
table
>
</
div
>
```
python
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
>
id
</
th
>
<
th
>
issn
</
th
>
<
th
>
journal
</
th
>
<
th
>
issn_type
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0001
-
2815
</
td
>
<
td
>
532
</
td
>
<
td
>
1
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
2
</
td
>
<
td
>
1399
-
0039
</
td
>
<
td
>
532
</
td
>
<
td
>
2
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
3
</
td
>
<
td
>
0001
-
4842
</
td
>
<
td
>
498
</
td
>
<
td
>
1
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
4
</
td
>
<
td
>
1520
-
4898
</
td
>
<
td
>
498
</
td
>
<
td
>
2
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
5
</
td
>
<
td
>
0001
-
4966
</
td
>
<
td
>
789
</
td
>
<
td
>
1
</
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
>
533
</
td
>
<
td
>
3
</
td
>
</
tr
>
<
tr
>
<
td
>
1756
</
td
>
<
td
>
1757
</
td
>
<
td
>
2470
-
0053
</
td
>
<
td
>
533
</
td
>
<
td
>
2
</
td
>
</
tr
>
<
tr
>
<
td
>
1757
</
td
>
<
td
>
1758
</
td
>
<
td
>
2475
-
9953
</
td
>
<
td
>
608
</
td
>
<
td
>
2
</
td
>
</
tr
>
<
tr
>
<
td
>
1758
</
td
>
<
td
>
1759
</
td
>
<
td
>
2504
-
4427
</
td
>
<
td
>
994
</
td
>
<
td
>
1
</
td
>
</
tr
>
<
tr
>
<
td
>
1759
</
td
>
<
td
>
1760
</
td
>
<
td
>
2504
-
4435
</
td
>
<
td
>
994
</
td
>
<
td
>
3
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
1760
rows
×
4
columns
</
p
>
</
div
>
```
python
#
merge
pour
avoir
l
'
issnl
issn
=
pd
.
merge
(
issn
,
issnl
,
on
=
'
issn
'
,
how
=
'
left
'
)
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
>
id
</
th
>
<
th
>
issn
</
th
>
<
th
>
journal
</
th
>
<
th
>
issn_type
</
th
>
<
th
>
issnl
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
1
</
td
>
<
td
>
0001
-
2815
</
td
>
<
td
>
532
</
td
>
<
td
>
1
</
td
>
<
td
>
0001
-
2815
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
2
</
td
>
<
td
>
1399
-
0039
</
td
>
<
td
>
532
</
td
>
<
td
>
2
</
td
>
<
td
>
0001
-
2815
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
3
</
td
>
<
td
>
0001
-
4842
</
td
>
<
td
>
498
</
td
>
<
td
>
1
</
td
>
<
td
>
0001
-
4842
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
4
</
td
>
<
td
>
1520
-
4898
</
td
>
<
td
>
498
</
td
>
<
td
>
2
</
td
>
<
td
>
0001
-
4842
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
5
</
td
>
<
td
>
0001
-
4966
</
td
>
<
td
>
789
</
td
>
<
td
>
1
</
td
>
<
td
>
0001
-
4966
</
td
>
</
tr
>
<
tr
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
1755
</
td
>
<
td
>
1756
</
td
>
<
td
>
2470
-
0045
</
td
>
<
td
>
533
</
td
>
<
td
>
3
</
td
>
<
td
>
2470
-
0045
</
td
>
</
tr
>
<
tr
>
<
td
>
1756
</
td
>
<
td
>
1757
</
td
>
<
td
>
2470
-
0053
</
td
>
<
td
>
533
</
td
>
<
td
>
2
</
td
>
<
td
>
2470
-
0045
</
td
>
</
tr
>
<
tr
>
<
td
>
1757
</
td
>
<
td
>
1758
</
td
>
<
td
>
2475
-
9953
</
td
>
<
td
>
608
</
td
>
<
td
>
2
</
td
>
<
td
>
2475
-
9953
</
td
>
</
tr
>
<
tr
>
<
td
>
1758
</
td
>
<
td
>
1759
</
td
>
<
td
>
2504
-
4427
</
td
>
<
td
>
994
</
td
>
<
td
>
1
</
td
>
<
td
>
2504
-
4427
</
td
>
</
tr
>
<
tr
>
<
td
>
1759
</
td
>
<
td
>
1760
</
td
>
<
td
>
2504
-
4435
</
td
>
<
td
>
994
</
td
>
<
td
>
3
</
td
>
<
td
>
2504
-
4427
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
1760
rows
×
5
columns
</
p
>
</
div
>
```
python
issn
.
loc
[
issn
[
'
issnl
'
].
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
>
issn
</
th
>
<
th
>
journal
</
th
>
<
th
>
issn_type
</
th
>
<
th
>
issnl
</
th
>
</
tr
>
</
thead
>
<
tbody
>
</
tbody
>
</
table
>
</
div
>
```
python
#
merge
dans
l
'
autre
sens
pour
garder
que
les
lignes
du
fichier
rp_fin
=
pd
.
merge
(
rp_fin
,
issn
[[
'
id
'
,
'
journal
'
,
'
issnl
'
]],
on
=
'
issnl
'
,
how
=
'
left
'
)
rp_fin
```
<
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
>
index
</
th
>
<
th
>
CUP
</
th
>
<
th
>
Elsevier
</
th
>
<
th
>
issn
</
th
>
<
th
>
Springer
Nature
</
th
>
<
th
>
TF
</
th
>
<
th
>
Title
</
th
>
<
th
>
URL
</
th
>
<
th
>
Wiley
</
th
>
<
th
>
archiving
</
th
>
<
th
>
article_version
</
th
>
<
th
>
embargo_months
</
th
>
<
th
>
license
</
th
>
<
th
>
valid_from
</
th
>
<
th
>
valid_until
</
th
>
<
th
>
issnl
</
th
>
<
th
>
ROR
</
th
>
<
th
>
rp_id
</
th
>
<
th
>
id
</
th
>
<
th
>
journal
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Academic
Pediatrics
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
https
:
//ror.org/04d8ztx87</td>
<
td
>
1
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
1
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Academic
Pediatrics
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
https
:
//ror.org/02bnkt322</td>
<
td
>
2
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
2
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Academic
Pediatrics
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
https
:
//ror.org/00zg4za48</td>
<
td
>
3
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
3
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Academic
Pediatrics
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
https
:
//ror.org/02s376052</td>
<
td
>
4
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
4
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Academic
Pediatrics
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1876
-
2859
</
td
>
<
td
>
https
:
//ror.org/05a28rw58</td>
<
td
>
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
>
</
tr
>
<
tr
>
<
td
>
792211
</
td
>
<
td
>
751623
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1469
-
8730
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zygote
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0967
-
1994
</
td
>
<
td
>
https
:
//ror.org/01swzsf04</td>
<
td
>
751624
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
792212
</
td
>
<
td
>
751624
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1469
-
8730
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zygote
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0967
-
1994
</
td
>
<
td
>
https
:
//ror.org/019whta54</td>
<
td
>
751625
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
792213
</
td
>
<
td
>
751625
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1469
-
8730
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zygote
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0967
-
1994
</
td
>
<
td
>
https
:
//ror.org/00vasag41</td>
<
td
>
751626
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
792214
</
td
>
<
td
>
751626
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1469
-
8730
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zygote
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0967
-
1994
</
td
>
<
td
>
https
:
//ror.org/05r0ap620</td>
<
td
>
751627
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
<
tr
>
<
td
>
792215
</
td
>
<
td
>
751627
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1469
-
8730
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Zygote
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
0967
-
1994
</
td
>
<
td
>
https
:
//ror.org/05pmsvm27</td>
<
td
>
751628
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
792216
rows
×
20
columns
</
p
>
</
div
>
```
python
#
test
des
lignes
sans
embargo
rp_fin
.
loc
[
rp_fin
[
'
embargo_months
'
].
isna
()
&
rp_fin
[
'
id
'
].
notna
()]
```
<
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
>
index
</
th
>
<
th
>
CUP
</
th
>
<
th
>
Elsevier
</
th
>
<
th
>
issn
</
th
>
<
th
>
Springer
Nature
</
th
>
<
th
>
TF
</
th
>
<
th
>
Title
</
th
>
<
th
>
URL
</
th
>
<
th
>
Wiley
</
th
>
<
th
>
archiving
</
th
>
<
th
>
article_version
</
th
>
<
th
>
embargo_months
</
th
>
<
th
>
license
</
th
>
<
th
>
valid_from
</
th
>
<
th
>
valid_until
</
th
>
<
th
>
issnl
</
th
>
<
th
>
ROR
</
th
>
<
th
>
rp_id
</
th
>
<
th
>
id
</
th
>
<
th
>
journal
</
th
>
</
tr
>
</
thead
>
<
tbody
>
</
tbody
>
</
table
>
</
div
>
```
python
#
garder
les
lignes
avec
merge
rp_fin_merge
=
rp_fin
.
loc
[
rp_fin
[
'
id
'
].
notna
()]
rp_fin_merge
```
<
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
>
index
</
th
>
<
th
>
CUP
</
th
>
<
th
>
Elsevier
</
th
>
<
th
>
issn
</
th
>
<
th
>
Springer
Nature
</
th
>
<
th
>
TF
</
th
>
<
th
>
Title
</
th
>
<
th
>
URL
</
th
>
<
th
>
Wiley
</
th
>
<
th
>
archiving
</
th
>
<
th
>
article_version
</
th
>
<
th
>
embargo_months
</
th
>
<
th
>
license
</
th
>
<
th
>
valid_from
</
th
>
<
th
>
valid_until
</
th
>
<
th
>
issnl
</
th
>
<
th
>
ROR
</
th
>
<
th
>
rp_id
</
th
>
<
th
>
id
</
th
>
<
th
>
journal
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
176
</
td
>
<
td
>
176
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Acta
Biomaterialia
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
https
:
//ror.org/04d8ztx87</td>
<
td
>
177
</
td
>
<
td
>
1623.0
</
td
>
<
td
>
899.0
</
td
>
</
tr
>
<
tr
>
<
td
>
177
</
td
>
<
td
>
176
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Acta
Biomaterialia
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
https
:
//ror.org/04d8ztx87</td>
<
td
>
177
</
td
>
<
td
>
1624.0
</
td
>
<
td
>
899.0
</
td
>
</
tr
>
<
tr
>
<
td
>
178
</
td
>
<
td
>
177
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Acta
Biomaterialia
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
https
:
//ror.org/02bnkt322</td>
<
td
>
178
</
td
>
<
td
>
1623.0
</
td
>
<
td
>
899.0
</
td
>
</
tr
>
<
tr
>
<
td
>
179
</
td
>
<
td
>
177
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Acta
Biomaterialia
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
https
:
//ror.org/02bnkt322</td>
<
td
>
178
</
td
>
<
td
>
1624.0
</
td
>
<
td
>
899.0
</
td
>
</
tr
>
<
tr
>
<
td
>
180
</
td
>
<
td
>
178
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Acta
Biomaterialia
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
https
:
//ror.org/00zg4za48</td>
<
td
>
179
</
td
>
<
td
>
1623.0
</
td
>
<
td
>
899.0
</
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
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
788071
</
td
>
<
td
>
747485
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1435
-
8115
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Microscopy
and
Microanalysis
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1431
-
9276
</
td
>
<
td
>
https
:
//ror.org/00vasag41</td>
<
td
>
747486
</
td
>
<
td
>
1419.0
</
td
>
<
td
>
592.0
</
td
>
</
tr
>
<
tr
>
<
td
>
788072
</
td
>
<
td
>
747486
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1435
-
8115
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Microscopy
and
Microanalysis
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1431
-
9276
</
td
>
<
td
>
https
:
//ror.org/05r0ap620</td>
<
td
>
747487
</
td
>
<
td
>
1418.0
</
td
>
<
td
>
592.0
</
td
>
</
tr
>
<
tr
>
<
td
>
788073
</
td
>
<
td
>
747486
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1435
-
8115
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Microscopy
and
Microanalysis
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1431
-
9276
</
td
>
<
td
>
https
:
//ror.org/05r0ap620</td>
<
td
>
747487
</
td
>
<
td
>
1419.0
</
td
>
<
td
>
592.0
</
td
>
</
tr
>
<
tr
>
<
td
>
788074
</
td
>
<
td
>
747487
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1435
-
8115
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Microscopy
and
Microanalysis
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1431
-
9276
</
td
>
<
td
>
https
:
//ror.org/05pmsvm27</td>
<
td
>
747488
</
td
>
<
td
>
1418.0
</
td
>
<
td
>
592.0
</
td
>
</
tr
>
<
tr
>
<
td
>
788075
</
td
>
<
td
>
747487
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1435
-
8115
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Microscopy
and
Microanalysis
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1431
-
9276
</
td
>
<
td
>
https
:
//ror.org/05pmsvm27</td>
<
td
>
747488
</
td
>
<
td
>
1419.0
</
td
>
<
td
>
592.0
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
80671
rows
×
20
columns
</
p
>
</
div
>
```
python
#
supprimer
les
doublons
et
les
vides
rp_fin_merge
=
rp_fin_merge
.
drop_duplicates
(
subset
=[
'
rp_id
'
])
rp_fin_merge
```
<
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
>
index
</
th
>
<
th
>
CUP
</
th
>
<
th
>
Elsevier
</
th
>
<
th
>
issn
</
th
>
<
th
>
Springer
Nature
</
th
>
<
th
>
TF
</
th
>
<
th
>
Title
</
th
>
<
th
>
URL
</
th
>
<
th
>
Wiley
</
th
>
<
th
>
archiving
</
th
>
<
th
>
article_version
</
th
>
<
th
>
embargo_months
</
th
>
<
th
>
license
</
th
>
<
th
>
valid_from
</
th
>
<
th
>
valid_until
</
th
>
<
th
>
issnl
</
th
>
<
th
>
ROR
</
th
>
<
th
>
rp_id
</
th
>
<
th
>
id
</
th
>
<
th
>
journal
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
176
</
td
>
<
td
>
176
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Acta
Biomaterialia
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
https
:
//ror.org/04d8ztx87</td>
<
td
>
177
</
td
>
<
td
>
1623.0
</
td
>
<
td
>
899.0
</
td
>
</
tr
>
<
tr
>
<
td
>
178
</
td
>
<
td
>
177
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Acta
Biomaterialia
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
https
:
//ror.org/02bnkt322</td>
<
td
>
178
</
td
>
<
td
>
1623.0
</
td
>
<
td
>
899.0
</
td
>
</
tr
>
<
tr
>
<
td
>
180
</
td
>
<
td
>
178
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Acta
Biomaterialia
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
https
:
//ror.org/00zg4za48</td>
<
td
>
179
</
td
>
<
td
>
1623.0
</
td
>
<
td
>
899.0
</
td
>
</
tr
>
<
tr
>
<
td
>
182
</
td
>
<
td
>
179
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Acta
Biomaterialia
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
https
:
//ror.org/02s376052</td>
<
td
>
180
</
td
>
<
td
>
1623.0
</
td
>
<
td
>
899.0
</
td
>
</
tr
>
<
tr
>
<
td
>
184
</
td
>
<
td
>
180
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Acta
Biomaterialia
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
https
:
//ror.org/05a28rw58</td>
<
td
>
181
</
td
>
<
td
>
1623.0
</
td
>
<
td
>
899.0
</
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
>
<
td
>...</
td
>
</
tr
>
<
tr
>
<
td
>
788066
</
td
>
<
td
>
747483
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1435
-
8115
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Microscopy
and
Microanalysis
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1431
-
9276
</
td
>
<
td
>
https
:
//ror.org/01swzsf04</td>
<
td
>
747484
</
td
>
<
td
>
1418.0
</
td
>
<
td
>
592.0
</
td
>
</
tr
>
<
tr
>
<
td
>
788068
</
td
>
<
td
>
747484
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1435
-
8115
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Microscopy
and
Microanalysis
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1431
-
9276
</
td
>
<
td
>
https
:
//ror.org/019whta54</td>
<
td
>
747485
</
td
>
<
td
>
1418.0
</
td
>
<
td
>
592.0
</
td
>
</
tr
>
<
tr
>
<
td
>
788070
</
td
>
<
td
>
747485
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1435
-
8115
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Microscopy
and
Microanalysis
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1431
-
9276
</
td
>
<
td
>
https
:
//ror.org/00vasag41</td>
<
td
>
747486
</
td
>
<
td
>
1418.0
</
td
>
<
td
>
592.0
</
td
>
</
tr
>
<
tr
>
<
td
>
788072
</
td
>
<
td
>
747486
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1435
-
8115
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Microscopy
and
Microanalysis
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1431
-
9276
</
td
>
<
td
>
https
:
//ror.org/05r0ap620</td>
<
td
>
747487
</
td
>
<
td
>
1418.0
</
td
>
<
td
>
592.0
</
td
>
</
tr
>
<
tr
>
<
td
>
788074
</
td
>
<
td
>
747487
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1435
-
8115
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Microscopy
and
Microanalysis
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1431
-
9276
</
td
>
<
td
>
https
:
//ror.org/05pmsvm27</td>
<
td
>
747488
</
td
>
<
td
>
1418.0
</
td
>
<
td
>
592.0
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
40083
rows
×
20
columns
</
p
>
</
div
>
```
python
#
test
des
lignes
sans
journal
rp_fin_merge
.
loc
[
rp_fin_merge
[
'
journal
'
].
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
>
index
</
th
>
<
th
>
CUP
</
th
>
<
th
>
Elsevier
</
th
>
<
th
>
issn
</
th
>
<
th
>
Springer
Nature
</
th
>
<
th
>
TF
</
th
>
<
th
>
Title
</
th
>
<
th
>
URL
</
th
>
<
th
>
Wiley
</
th
>
<
th
>
archiving
</
th
>
<
th
>
article_version
</
th
>
<
th
>
embargo_months
</
th
>
<
th
>
license
</
th
>
<
th
>
valid_from
</
th
>
<
th
>
valid_until
</
th
>
<
th
>
issnl
</
th
>
<
th
>
ROR
</
th
>
<
th
>
rp_id
</
th
>
<
th
>
id
</
th
>
<
th
>
journal
</
th
>
</
tr
>
</
thead
>
<
tbody
>
</
tbody
>
</
table
>
</
div
>
```
python
#
convertir
l
'
index
en
id
del
rp_fin_merge
[
'
id
'
]
del
rp_fin_merge
[
'
index
'
]
del
rp_fin_merge
[
'
rp_id
'
]
rp_fin_merge
=
rp_fin_merge
.
reset_index
()
#
ajout
de
l
'
id
avec
l
'
index
+
1
rp_fin_merge
[
'
rp_id
'
]
=
rp_fin_merge
[
'
index
'
]
+
1
del
rp_fin_merge
[
'
index
'
]
rp_fin_merge
```
<
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
>
CUP
</
th
>
<
th
>
Elsevier
</
th
>
<
th
>
issn
</
th
>
<
th
>
Springer
Nature
</
th
>
<
th
>
TF
</
th
>
<
th
>
Title
</
th
>
<
th
>
URL
</
th
>
<
th
>
Wiley
</
th
>
<
th
>
archiving
</
th
>
<
th
>
article_version
</
th
>
<
th
>
embargo_months
</
th
>
<
th
>
license
</
th
>
<
th
>
valid_from
</
th
>
<
th
>
valid_until
</
th
>
<
th
>
issnl
</
th
>
<
th
>
ROR
</
th
>
<
th
>
journal
</
th
>
<
th
>
rp_id
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Acta
Biomaterialia
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
https
:
//ror.org/04d8ztx87</td>
<
td
>
899.0
</
td
>
<
td
>
177
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Acta
Biomaterialia
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
https
:
//ror.org/02bnkt322</td>
<
td
>
899.0
</
td
>
<
td
>
179
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Acta
Biomaterialia
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
https
:
//ror.org/00zg4za48</td>
<
td
>
899.0
</
td
>
<
td
>
181
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Acta
Biomaterialia
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
https
:
//ror.org/02s376052</td>
<
td
>
899.0
</
td
>
<
td
>
183
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Acta
Biomaterialia
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
https
:
//ror.org/05a28rw58</td>
<
td
>
899.0
</
td
>
<
td
>
185
</
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
>
40078
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1435
-
8115
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Microscopy
and
Microanalysis
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1431
-
9276
</
td
>
<
td
>
https
:
//ror.org/01swzsf04</td>
<
td
>
592.0
</
td
>
<
td
>
788067
</
td
>
</
tr
>
<
tr
>
<
td
>
40079
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1435
-
8115
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Microscopy
and
Microanalysis
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1431
-
9276
</
td
>
<
td
>
https
:
//ror.org/019whta54</td>
<
td
>
592.0
</
td
>
<
td
>
788069
</
td
>
</
tr
>
<
tr
>
<
td
>
40080
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1435
-
8115
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Microscopy
and
Microanalysis
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1431
-
9276
</
td
>
<
td
>
https
:
//ror.org/00vasag41</td>
<
td
>
592.0
</
td
>
<
td
>
788071
</
td
>
</
tr
>
<
tr
>
<
td
>
40081
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1435
-
8115
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Microscopy
and
Microanalysis
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1431
-
9276
</
td
>
<
td
>
https
:
//ror.org/05r0ap620</td>
<
td
>
592.0
</
td
>
<
td
>
788073
</
td
>
</
tr
>
<
tr
>
<
td
>
40082
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1435
-
8115
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Microscopy
and
Microanalysis
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1431
-
9276
</
td
>
<
td
>
https
:
//ror.org/05pmsvm27</td>
<
td
>
592.0
</
td
>
<
td
>
788075
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
40083
rows
×
18
columns
</
p
>
</
div
>
```
python
#
convertir
l
'
index
en
id
del
rp_fin_merge
[
'
rp_id
'
]
rp_fin_merge
=
rp_fin_merge
.
reset_index
()
#
ajout
de
l
'
id
avec
l
'
index
+
1
rp_fin_merge
[
'
rp_id
'
]
=
rp_fin_merge
[
'
index
'
]
+
1
del
rp_fin_merge
[
'
index
'
]
rp_fin_merge
```
<
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
>
CUP
</
th
>
<
th
>
Elsevier
</
th
>
<
th
>
issn
</
th
>
<
th
>
Springer
Nature
</
th
>
<
th
>
TF
</
th
>
<
th
>
Title
</
th
>
<
th
>
URL
</
th
>
<
th
>
Wiley
</
th
>
<
th
>
archiving
</
th
>
<
th
>
article_version
</
th
>
<
th
>
embargo_months
</
th
>
<
th
>
license
</
th
>
<
th
>
valid_from
</
th
>
<
th
>
valid_until
</
th
>
<
th
>
issnl
</
th
>
<
th
>
ROR
</
th
>
<
th
>
journal
</
th
>
<
th
>
rp_id
</
th
>
</
tr
>
</
thead
>
<
tbody
>
<
tr
>
<
td
>
0
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Acta
Biomaterialia
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
https
:
//ror.org/04d8ztx87</td>
<
td
>
899.0
</
td
>
<
td
>
1
</
td
>
</
tr
>
<
tr
>
<
td
>
1
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Acta
Biomaterialia
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
https
:
//ror.org/02bnkt322</td>
<
td
>
899.0
</
td
>
<
td
>
2
</
td
>
</
tr
>
<
tr
>
<
td
>
2
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Acta
Biomaterialia
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
https
:
//ror.org/00zg4za48</td>
<
td
>
899.0
</
td
>
<
td
>
3
</
td
>
</
tr
>
<
tr
>
<
td
>
3
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Acta
Biomaterialia
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
https
:
//ror.org/02s376052</td>
<
td
>
899.0
</
td
>
<
td
>
4
</
td
>
</
tr
>
<
tr
>
<
td
>
4
</
td
>
<
td
>
NaN
</
td
>
<
td
>
x
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Acta
Biomaterialia
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
0
</
td
>
<
td
>
cc_by
</
td
>
<
td
>
2020
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1742
-
7061
</
td
>
<
td
>
https
:
//ror.org/05a28rw58</td>
<
td
>
899.0
</
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
>
</
tr
>
<
tr
>
<
td
>
40078
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1435
-
8115
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Microscopy
and
Microanalysis
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1431
-
9276
</
td
>
<
td
>
https
:
//ror.org/01swzsf04</td>
<
td
>
592.0
</
td
>
<
td
>
40079
</
td
>
</
tr
>
<
tr
>
<
td
>
40079
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1435
-
8115
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Microscopy
and
Microanalysis
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1431
-
9276
</
td
>
<
td
>
https
:
//ror.org/019whta54</td>
<
td
>
592.0
</
td
>
<
td
>
40080
</
td
>
</
tr
>
<
tr
>
<
td
>
40080
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1435
-
8115
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Microscopy
and
Microanalysis
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1431
-
9276
</
td
>
<
td
>
https
:
//ror.org/00vasag41</td>
<
td
>
592.0
</
td
>
<
td
>
40081
</
td
>
</
tr
>
<
tr
>
<
td
>
40081
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1435
-
8115
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Microscopy
and
Microanalysis
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1431
-
9276
</
td
>
<
td
>
https
:
//ror.org/05r0ap620</td>
<
td
>
592.0
</
td
>
<
td
>
40082
</
td
>
</
tr
>
<
tr
>
<
td
>
40082
</
td
>
<
td
>
x
</
td
>
<
td
>
NaN
</
td
>
<
td
>
1435
-
8115
</
td
>
<
td
>
NaN
</
td
>
<
td
>
NaN
</
td
>
<
td
>
Microscopy
and
Microanalysis
</
td
>
<
td
>
http
:
//www.cambridge.org/core/product/identifi...</td>
<
td
>
NaN
</
td
>
<
td
>
True
</
td
>
<
td
>
published
</
td
>
<
td
>
60
</
td
>
<
td
>
cc_by_nc_sa
</
td
>
<
td
>
2021
-
01
-
01
</
td
>
<
td
>
2023
-
12
-
31
</
td
>
<
td
>
1431
-
9276
</
td
>
<
td
>
https
:
//ror.org/05pmsvm27</td>
<
td
>
592.0
</
td
>
<
td
>
40083
</
td
>
</
tr
>
</
tbody
>
</
table
>
<
p
>
40083
rows
×
18
columns
</
p
>
</
div
>
```
python
rp_fin_merge
[
'
embargo_months
'
].
value_counts
()
```
0
39163
60
920
Name
:
embargo_months
,
dtype
:
int64
```
python
#
test
des
lignes
sans
embargo
rp_fin_merge
.
loc
[
rp_fin_merge
[
'
embargo_months
'
].
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
>
CUP
</
th
>
<
th
>
Elsevier
</
th
>
<
th
>
issn
</
th
>
<
th
>
Springer
Nature
</
th
>
<
th
>
TF
</
th
>
<
th
>
Title
</
th
>
<
th
>
URL
</
th
>
<
th
>
Wiley
</
th
>
<
th
>
archiving
</
th
>
<
th
>
article_version
</
th
>
<
th
>
embargo_months
</
th
>
<
th
>
license
</
th
>
<
th
>
valid_from
</
th
>
<
th
>
valid_until
</
th
>
<
th
>
issnl
</
th
>
<
th
>
ROR
</
th
>
<
th
>
journal
</
th
>
<
th
>
rp_id
</
th
>
</
tr
>
</
thead
>
<
tbody
>
</
tbody
>
</
table
>
</
div
>
```
python
#
export
excel
rp_fin_merge
.
to_excel
(
'
sample
/
read_publish_brut_merge
.
xlsx
'
,
index
=
False
)
```
```
python
#
export
csv
rp_fin_merge
.
to_csv
(
'
sample
/
read_publish_brut_merge
.
tsv
'
,
sep
=
'\t'
,
index
=
False
)
```
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