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# Projet Open Access Compliance Check Tool (OACCT)
Projet P5 de la bibliothèque de l'EPFL en collaboration avec les bibliothèques des Universités de Genève, Lausanne et Berne : https://www.swissuniversities.ch/themen/digitalisierung/p-5-wissenschaftliche-information/projekte/swiss-mooc-service-1-1-1-1
Ce notebook permet d'extraire les données choisis parmis les sources obtenues par API et les traiter pour les rendre exploitables dans l'application OACCT.
Auteur : **Pablo Iriarte**, Université de Genève (pablo.iriarte@unige.ch)
Date de dernière mise à jour : 16.07.2021
## Table ISSNs
```python
import pandas as pd
import csv
import json
import numpy as np
import os
```
```python
# ajout des ISSN-L
issns = pd.read_csv('issn/20171102.ISSN-to-ISSN-L.txt', encoding='utf-8', header=0, sep='\t')
issns
```
<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>0000-006X</td>
<td>0000-006X</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>8756-999X</td>
<td>8756-999X</td>
</tr>
</tbody>
</table>
<p>1995918 rows × 2 columns</p>
</div>
```python
# renommer les colonnes
issns = issns.rename(columns={'ISSN' : 'issn', 'ISSN-L' : 'issnl'})
issns
```
<div>
<style scoped>
.dataframe tbody tr th:only-of-type {
vertical-align: middle;
}
.dataframe tbody tr th {
vertical-align: top;
}
.dataframe thead th {
text-align: right;
}
</style>
<table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>issn</th>
<th>issnl</th>
</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>0000-006X</td>
<td>0000-006X</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>8756-999X</td>
<td>8756-999X</td>
</tr>
</tbody>
</table>
<p>1995918 rows × 2 columns</p>
</div>
```python
journals = pd.read_csv('sample/journals_brut.tsv', encoding='utf-8', sep='\t', usecols=(['id', 'issn', 'issnl']))
journals
```
<div>
<style scoped>
.dataframe tbody tr th:only-of-type {
vertical-align: middle;
}
.dataframe tbody tr th {
vertical-align: top;
}
.dataframe thead th {
text-align: right;
}
</style>
<table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>id</th>
<th>issn</th>
<th>issnl</th>
</tr>
</thead>
<tbody>
<tr>
<td>0</td>
<td>1</td>
<td>1660-9379</td>
<td>1660-9379</td>
</tr>
<tr>
<td>1</td>
<td>2</td>
<td>0031-9007</td>
<td>0031-9007</td>
</tr>
<tr>
<td>2</td>
<td>3</td>
<td>1932-6203</td>
<td>1932-6203</td>
</tr>
<tr>
<td>3</td>
<td>4</td>
<td>2174-8454</td>
<td>2174-8454</td>
</tr>
<tr>
<td>4</td>
<td>5</td>
<td>1098-0121</td>
<td>1098-0121</td>
</tr>
<tr>
<td>...</td>
<td>...</td>
<td>...</td>
<td>...</td>
</tr>
<tr>
<td>906</td>
<td>997</td>
<td>0964-1726</td>
<td>0964-1726</td>
</tr>
<tr>
<td>907</td>
<td>998</td>
<td>0022-3468</td>
<td>0022-3468</td>
</tr>
<tr>
<td>908</td>
<td>999</td>
<td>1432-2064</td>
<td>0178-8051</td>
</tr>
<tr>
<td>909</td>
<td>1000</td>
<td>0960-1481</td>
<td>0960-1481</td>
</tr>
<tr>
<td>910</td>
<td>1001</td>
<td>0161-7567</td>
<td>0161-7567</td>
</tr>
</tbody>
</table>
<p>911 rows × 3 columns</p>
</div>
```python
# renomer les colonnes id
journals = journals.rename(columns = {'id' : 'journal'})
journals
```
<div>
<style scoped>
.dataframe tbody tr th:only-of-type {
vertical-align: middle;
}
.dataframe tbody tr th {
vertical-align: top;
}
.dataframe thead th {
text-align: right;
}
</style>
<table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>journal</th>
<th>issn</th>
<th>issnl</th>
</tr>
</thead>
<tbody>
<tr>
<td>0</td>
<td>1</td>
<td>1660-9379</td>
<td>1660-9379</td>
</tr>
<tr>
<td>1</td>
<td>2</td>
<td>0031-9007</td>
<td>0031-9007</td>
</tr>
<tr>
<td>2</td>
<td>3</td>
<td>1932-6203</td>
<td>1932-6203</td>
</tr>
<tr>
<td>3</td>
<td>4</td>
<td>2174-8454</td>
<td>2174-8454</td>
</tr>
<tr>
<td>4</td>
<td>5</td>
<td>1098-0121</td>
<td>1098-0121</td>
</tr>
<tr>
<td>...</td>
<td>...</td>
<td>...</td>
<td>...</td>
</tr>
<tr>
<td>906</td>
<td>997</td>
<td>0964-1726</td>
<td>0964-1726</td>
</tr>
<tr>
<td>907</td>
<td>998</td>
<td>0022-3468</td>
<td>0022-3468</td>
</tr>
<tr>
<td>908</td>
<td>999</td>
<td>1432-2064</td>
<td>0178-8051</td>
</tr>
<tr>
<td>909</td>
<td>1000</td>
<td>0960-1481</td>
<td>0960-1481</td>
</tr>
<tr>
<td>910</td>
<td>1001</td>
<td>0161-7567</td>
<td>0161-7567</td>
</tr>
</tbody>
</table>
<p>911 rows × 3 columns</p>
</div>
```python
# test journals sans issn
journals.loc[journals['issn'].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>journal</th>
<th>issn</th>
<th>issnl</th>
</tr>
</thead>
<tbody>
</tbody>
</table>
</div>
```python
journals.loc[journals['journal'] == 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>journal</th>
<th>issn</th>
<th>issnl</th>
</tr>
</thead>
<tbody>
<tr>
<td>4</td>
<td>5</td>
<td>1098-0121</td>
<td>1098-0121</td>
</tr>
</tbody>
</table>
</div>
## Extraction du format
```python
# creation du DF
col_names = ['issn',
'format'
]
journals_format = pd.DataFrame(columns = col_names)
journals_format
```
<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>format</th>
</tr>
</thead>
<tbody>
</tbody>
</table>
</div>
```python
# extraction des informations à partir des données ISSN.org
for index, row in journals.iterrows():
# myid = row['journal']
myissn = row['issn']
# myissnl = row['issnl']
if (((index/10) - int(index/10)) == 0) :
print(index)
# initialisation des variables à extraire
myformat = np.nan
# export en json
if os.path.exists('issn/data/' + myissn + '.json'):
with open('issn/data/' + myissn + '.json', 'r', encoding='utf-8') as f:
data = json.load(f)
for x in data['@graph']:
if ('@id' in x):
if (x['@id'] == 'resource/ISSN/' + myissn):
if ('format' in x):
myformats = x['format']
if type(myformats) is list:
myformat = myformats[0].replace('vocabularies/medium#', '')
else :
myformat = myformats.replace('vocabularies/medium#', '')
# journals_format.at[index,'journal'] = myid
journals_format.at[index,'issn'] = myissn
# journals2.at[index,'issnl'] = myissnl
journals_format.at[index,'format'] = myformat
else :
print(row['issn'] + ' - pas trouvé')
```
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```python
journals_format
```
<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>format</th>
</tr>
</thead>
<tbody>
<tr>
<td>0</td>
<td>1660-9379</td>
<td>Print</td>
</tr>
<tr>
<td>1</td>
<td>0031-9007</td>
<td>Print</td>
</tr>
<tr>
<td>2</td>
<td>1932-6203</td>
<td>Online</td>
</tr>
<tr>
<td>3</td>
<td>2174-8454</td>
<td>Print</td>
</tr>
<tr>
<td>4</td>
<td>1098-0121</td>
<td>Print</td>
</tr>
<tr>
<td>...</td>
<td>...</td>
<td>...</td>
</tr>
<tr>
<td>906</td>
<td>0964-1726</td>
<td>Print</td>
</tr>
<tr>
<td>907</td>
<td>0022-3468</td>
<td>Print</td>
</tr>
<tr>
<td>908</td>
<td>1432-2064</td>
<td>Online</td>
</tr>
<tr>
<td>909</td>
<td>0960-1481</td>
<td>Print</td>
</tr>
<tr>
<td>910</td>
<td>0161-7567</td>
<td>Print</td>
</tr>
</tbody>
</table>
<p>911 rows × 2 columns</p>
</div>
```python
# test
journals_format.loc[journals_format['format'].isnull()]
```
<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>format</th>
</tr>
</thead>
<tbody>
</tbody>
</table>
</div>
```python
journals_format['format'].value_counts()
```
Print 817
Online 92
Other 2
Name: format, dtype: int64
```python
del journals['issn']
```
```python
issns = pd.merge(issns, journals, on='issnl', how='outer')
issns
```
<div>
<style scoped>
.dataframe tbody tr th:only-of-type {
vertical-align: middle;
}
.dataframe tbody tr th {
vertical-align: top;
}
.dataframe thead th {
text-align: right;
}
</style>
<table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>issn</th>
<th>issnl</th>
<th>journal</th>
</tr>
</thead>
<tbody>
<tr>
<td>0</td>
<td>0000-0019</td>
<td>0000-0019</td>
<td>NaN</td>
</tr>
<tr>
<td>1</td>
<td>2150-4008</td>
<td>0000-0019</td>
<td>NaN</td>
</tr>
<tr>
<td>2</td>
<td>0000-0027</td>
<td>0000-0027</td>
<td>NaN</td>
</tr>
<tr>
<td>3</td>
<td>0000-0043</td>
<td>0000-0043</td>
<td>NaN</td>
</tr>
<tr>
<td>4</td>
<td>0000-0051</td>
<td>0000-0051</td>
<td>NaN</td>
</tr>
<tr>
<td>...</td>
<td>...</td>
<td>...</td>
<td>...</td>
</tr>
<tr>
<td>1995915</td>
<td>8756-9973</td>
<td>8756-9973</td>
<td>NaN</td>
</tr>
<tr>
<td>1995916</td>
<td>8756-9981</td>
<td>8756-9981</td>
<td>NaN</td>
</tr>
<tr>
<td>1995917</td>
<td>8756-999X</td>
<td>8756-999X</td>
<td>NaN</td>
</tr>
<tr>
<td>1995918</td>
<td>NaN</td>
<td>2624-8557</td>
<td>120.0</td>
</tr>
<tr>
<td>1995919</td>
<td>NaN</td>
<td>0032-1052</td>
<td>936.0</td>
</tr>
</tbody>
</table>
<p>1995920 rows × 3 columns</p>
</div>
```python
# tester les lignes sans issn
issns.loc[issns['issn'].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>issn</th>
<th>issnl</th>
<th>journal</th>
</tr>
</thead>
<tbody>
<tr>
<td>1995918</td>
<td>NaN</td>
<td>2624-8557</td>
<td>120.0</td>
</tr>
<tr>
<td>1995919</td>
<td>NaN</td>
<td>0032-1052</td>
<td>936.0</td>
</tr>
</tbody>
</table>
</div>
```python
# garder les lilgnes non null
issns = issns.loc[issns['issn'].notna()]
```
```python
# isoler les lignes avec marge
issns2 = issns.loc[issns['journal'].notna()]
issns2
```
<div>
<style scoped>
.dataframe tbody tr th:only-of-type {
vertical-align: middle;
}
.dataframe tbody tr th {
vertical-align: top;
}
.dataframe thead th {
text-align: right;
}
</style>
<table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>issn</th>
<th>issnl</th>
<th>journal</th>
</tr>
</thead>
<tbody>
<tr>
<td>334</td>
<td>0001-2815</td>
<td>0001-2815</td>
<td>532.0</td>
</tr>
<tr>
<td>335</td>
<td>1399-0039</td>
<td>0001-2815</td>
<td>532.0</td>
</tr>
<tr>
<td>493</td>
<td>0001-4842</td>
<td>0001-4842</td>
<td>498.0</td>
</tr>
<tr>
<td>494</td>
<td>1520-4898</td>
<td>0001-4842</td>
<td>498.0</td>
</tr>
<tr>
<td>505</td>
<td>0001-4966</td>
<td>0001-4966</td>
<td>789.0</td>
</tr>
<tr>
<td>...</td>
<td>...</td>
<td>...</td>
<td>...</td>
</tr>
<tr>
<td>1921352</td>
<td>2470-0045</td>
<td>2470-0045</td>
<td>533.0</td>
</tr>
<tr>
<td>1921353</td>
<td>2470-0053</td>
<td>2470-0045</td>
<td>533.0</td>
</tr>
<tr>
<td>1925740</td>
<td>2475-9953</td>
<td>2475-9953</td>
<td>608.0</td>
</tr>
<tr>
<td>1951854</td>
<td>2504-4427</td>
<td>2504-4427</td>
<td>994.0</td>
</tr>
<tr>
<td>1951855</td>
<td>2504-4435</td>
<td>2504-4427</td>
<td>994.0</td>
</tr>
</tbody>
</table>
<p>1760 rows × 3 columns</p>
</div>
```python
# ajout du format par ISSN
issns2 = pd.merge(issns2, journals_format, on='issn', how='outer')
issns2
```
<div>
<style scoped>
.dataframe tbody tr th:only-of-type {
vertical-align: middle;
}
.dataframe tbody tr th {
vertical-align: top;
}
.dataframe thead th {
text-align: right;
}
</style>
<table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>issn</th>
<th>issnl</th>
<th>journal</th>
<th>format</th>
</tr>
</thead>
<tbody>
<tr>
<td>0</td>
<td>0001-2815</td>
<td>0001-2815</td>
<td>532.0</td>
<td>Print</td>
</tr>
<tr>
<td>1</td>
<td>1399-0039</td>
<td>0001-2815</td>
<td>532.0</td>
<td>NaN</td>
</tr>
<tr>
<td>2</td>
<td>0001-4842</td>
<td>0001-4842</td>
<td>498.0</td>
<td>Print</td>
</tr>
<tr>
<td>3</td>
<td>1520-4898</td>
<td>0001-4842</td>
<td>498.0</td>
<td>NaN</td>
</tr>
<tr>
<td>4</td>
<td>0001-4966</td>
<td>0001-4966</td>
<td>789.0</td>
<td>Print</td>
</tr>
<tr>
<td>...</td>
<td>...</td>
<td>...</td>
<td>...</td>
<td>...</td>
</tr>
<tr>
<td>1758</td>
<td>2504-4427</td>
<td>2504-4427</td>
<td>994.0</td>
<td>Print</td>
</tr>
<tr>
<td>1759</td>
<td>2504-4435</td>
<td>2504-4427</td>
<td>994.0</td>
<td>NaN</td>
</tr>
<tr>
<td>1760</td>
<td>2624-8557</td>
<td>NaN</td>
<td>NaN</td>
<td>Online</td>
</tr>
<tr>
<td>1761</td>
<td>2469-9926</td>
<td>NaN</td>
<td>NaN</td>
<td>Print</td>
</tr>
<tr>
<td>1762</td>
<td>1529-4242</td>
<td>NaN</td>
<td>NaN</td>
<td>Online</td>
</tr>
</tbody>
</table>
<p>1763 rows × 4 columns</p>
</div>
```python
# isoler les lignes avec marge
issns2 = issns2.loc[issns2['journal'].notna()]
issns2
```
<div>
<style scoped>
.dataframe tbody tr th:only-of-type {
vertical-align: middle;
}
.dataframe tbody tr th {
vertical-align: top;
}
.dataframe thead th {
text-align: right;
}
</style>
<table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>issn</th>
<th>issnl</th>
<th>journal</th>
<th>format</th>
</tr>
</thead>
<tbody>
<tr>
<td>0</td>
<td>0001-2815</td>
<td>0001-2815</td>
<td>532.0</td>
<td>Print</td>
</tr>
<tr>
<td>1</td>
<td>1399-0039</td>
<td>0001-2815</td>
<td>532.0</td>
<td>NaN</td>
</tr>
<tr>
<td>2</td>
<td>0001-4842</td>
<td>0001-4842</td>
<td>498.0</td>
<td>Print</td>
</tr>
<tr>
<td>3</td>
<td>1520-4898</td>
<td>0001-4842</td>
<td>498.0</td>
<td>NaN</td>
</tr>
<tr>
<td>4</td>
<td>0001-4966</td>
<td>0001-4966</td>
<td>789.0</td>
<td>Print</td>
</tr>
<tr>
<td>...</td>
<td>...</td>
<td>...</td>
<td>...</td>
<td>...</td>
</tr>
<tr>
<td>1755</td>
<td>2470-0045</td>
<td>2470-0045</td>
<td>533.0</td>
<td>Other</td>
</tr>
<tr>
<td>1756</td>
<td>2470-0053</td>
<td>2470-0045</td>
<td>533.0</td>
<td>NaN</td>
</tr>
<tr>
<td>1757</td>
<td>2475-9953</td>
<td>2475-9953</td>
<td>608.0</td>
<td>Online</td>
</tr>
<tr>
<td>1758</td>
<td>2504-4427</td>
<td>2504-4427</td>
<td>994.0</td>
<td>Print</td>
</tr>
<tr>
<td>1759</td>
<td>2504-4435</td>
<td>2504-4427</td>
<td>994.0</td>
<td>NaN</td>
</tr>
</tbody>
</table>
<p>1760 rows × 4 columns</p>
</div>
```python
issns2['format'] = issns2['format'].str.upper()
issns2['format'] = issns2['format'].str.replace('ONLINE', 'ELECTRONIC')
# DigitalCarrier
issns2['format'] = issns2['format'].str.replace('DIGITALCARRIER', 'ELECTRONIC')
issns2
```
C:\Users\iriarte\AppData\Local\Continuum\anaconda3\lib\site-packages\ipykernel_launcher.py:1: 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
"""Entry point for launching an IPython kernel.
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:4: 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
after removing the cwd from sys.path.
<div>
<style scoped>
.dataframe tbody tr th:only-of-type {
vertical-align: middle;
}
.dataframe tbody tr th {
vertical-align: top;
}
.dataframe thead th {
text-align: right;
}
</style>
<table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>issn</th>
<th>issnl</th>
<th>journal</th>
<th>format</th>
</tr>
</thead>
<tbody>
<tr>
<td>0</td>
<td>0001-2815</td>
<td>0001-2815</td>
<td>532.0</td>
<td>PRINT</td>
</tr>
<tr>
<td>1</td>
<td>1399-0039</td>
<td>0001-2815</td>
<td>532.0</td>
<td>NaN</td>
</tr>
<tr>
<td>2</td>
<td>0001-4842</td>
<td>0001-4842</td>
<td>498.0</td>
<td>PRINT</td>
</tr>
<tr>
<td>3</td>
<td>1520-4898</td>
<td>0001-4842</td>
<td>498.0</td>
<td>NaN</td>
</tr>
<tr>
<td>4</td>
<td>0001-4966</td>
<td>0001-4966</td>
<td>789.0</td>
<td>PRINT</td>
</tr>
<tr>
<td>...</td>
<td>...</td>
<td>...</td>
<td>...</td>
<td>...</td>
</tr>
<tr>
<td>1755</td>
<td>2470-0045</td>
<td>2470-0045</td>
<td>533.0</td>
<td>OTHER</td>
</tr>
<tr>
<td>1756</td>
<td>2470-0053</td>
<td>2470-0045</td>
<td>533.0</td>
<td>NaN</td>
</tr>
<tr>
<td>1757</td>
<td>2475-9953</td>
<td>2475-9953</td>
<td>608.0</td>
<td>ELECTRONIC</td>
</tr>
<tr>
<td>1758</td>
<td>2504-4427</td>
<td>2504-4427</td>
<td>994.0</td>
<td>PRINT</td>
</tr>
<tr>
<td>1759</td>
<td>2504-4435</td>
<td>2504-4427</td>
<td>994.0</td>
<td>NaN</td>
</tr>
</tbody>
</table>
<p>1760 rows × 4 columns</p>
</div>
```python
issns2['format'].value_counts()
```
PRINT 816
ELECTRONIC 90
OTHER 2
Name: format, dtype: int64
```python
# tester les lignes sans issn
issns2.loc[issns2['format'].isnull()]
```
<div>
<style scoped>
.dataframe tbody tr th:only-of-type {
vertical-align: middle;
}
.dataframe tbody tr th {
vertical-align: top;
}
.dataframe thead th {
text-align: right;
}
</style>
<table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>issn</th>
<th>issnl</th>
<th>journal</th>
<th>format</th>
</tr>
</thead>
<tbody>
<tr>
<td>1</td>
<td>1399-0039</td>
<td>0001-2815</td>
<td>532.0</td>
<td>NaN</td>
</tr>
<tr>
<td>3</td>
<td>1520-4898</td>
<td>0001-4842</td>
<td>498.0</td>
<td>NaN</td>
</tr>
<tr>
<td>5</td>
<td>1520-8524</td>
<td>0001-4966</td>
<td>789.0</td>
<td>NaN</td>
</tr>
<tr>
<td>6</td>
<td>1520-9024</td>
<td>0001-4966</td>
<td>789.0</td>
<td>NaN</td>
</tr>
<tr>
<td>8</td>
<td>0942-0940</td>
<td>0001-6268</td>
<td>166.0</td>
<td>NaN</td>
</tr>
<tr>
<td>...</td>
<td>...</td>
<td>...</td>
<td>...</td>
<td>...</td>
</tr>
<tr>
<td>1750</td>
<td>2469-9934</td>
<td>2469-9926</td>
<td>870.0</td>
<td>NaN</td>
</tr>
<tr>
<td>1752</td>
<td>2469-9969</td>
<td>2469-9950</td>
<td>41.0</td>
<td>NaN</td>
</tr>
<tr>
<td>1754</td>
<td>2470-0029</td>
<td>2470-0010</td>
<td>80.0</td>
<td>NaN</td>
</tr>
<tr>
<td>1756</td>
<td>2470-0053</td>
<td>2470-0045</td>
<td>533.0</td>
<td>NaN</td>
</tr>
<tr>
<td>1759</td>
<td>2504-4435</td>
<td>2504-4427</td>
<td>994.0</td>
<td>NaN</td>
</tr>
</tbody>
</table>
<p>852 rows × 4 columns</p>
</div>
```python
# attribution de l'id du type
# PRINT = 1
# ELECTRONIC = 2
# OTHER = 3
issns2['issn_type'] = issns2['format']
issns2['issn_type'] = issns2['issn_type'].str.replace('PRINT', '1')
issns2['issn_type'] = issns2['issn_type'].str.replace('ELECTRONIC', '2')
issns2['issn_type'] = issns2['issn_type'].str.replace('OTHER', '3')
issns2['issn_type'] = issns2['issn_type'].fillna(3)
issns2
```
C:\Users\iriarte\AppData\Local\Continuum\anaconda3\lib\site-packages\ipykernel_launcher.py:5: 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:6: 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:7: 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
import sys
C:\Users\iriarte\AppData\Local\Continuum\anaconda3\lib\site-packages\ipykernel_launcher.py:8: 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:9: 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
if __name__ == '__main__':
<div>
<style scoped>
.dataframe tbody tr th:only-of-type {
vertical-align: middle;
}
.dataframe tbody tr th {
vertical-align: top;
}
.dataframe thead th {
text-align: right;
}
</style>
<table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>issn</th>
<th>issnl</th>
<th>journal</th>
<th>format</th>
<th>issn_type</th>
</tr>
</thead>
<tbody>
<tr>
<td>0</td>
<td>0001-2815</td>
<td>0001-2815</td>
<td>532.0</td>
<td>PRINT</td>
<td>1</td>
</tr>
<tr>
<td>1</td>
<td>1399-0039</td>
<td>0001-2815</td>
<td>532.0</td>
<td>NaN</td>
<td>3</td>
</tr>
<tr>
<td>2</td>
<td>0001-4842</td>
<td>0001-4842</td>
<td>498.0</td>
<td>PRINT</td>
<td>1</td>
</tr>
<tr>
<td>3</td>
<td>1520-4898</td>
<td>0001-4842</td>
<td>498.0</td>
<td>NaN</td>
<td>3</td>
</tr>
<tr>
<td>4</td>
<td>0001-4966</td>
<td>0001-4966</td>
<td>789.0</td>
<td>PRINT</td>
<td>1</td>
</tr>
<tr>
<td>...</td>
<td>...</td>
<td>...</td>
<td>...</td>
<td>...</td>
<td>...</td>
</tr>
<tr>
<td>1755</td>
<td>2470-0045</td>
<td>2470-0045</td>
<td>533.0</td>
<td>OTHER</td>
<td>3</td>
</tr>
<tr>
<td>1756</td>
<td>2470-0053</td>
<td>2470-0045</td>
<td>533.0</td>
<td>NaN</td>
<td>3</td>
</tr>
<tr>
<td>1757</td>
<td>2475-9953</td>
<td>2475-9953</td>
<td>608.0</td>
<td>ELECTRONIC</td>
<td>2</td>
</tr>
<tr>
<td>1758</td>
<td>2504-4427</td>
<td>2504-4427</td>
<td>994.0</td>
<td>PRINT</td>
<td>1</td>
</tr>
<tr>
<td>1759</td>
<td>2504-4435</td>
<td>2504-4427</td>
<td>994.0</td>
<td>NaN</td>
<td>3</td>
</tr>
</tbody>
</table>
<p>1760 rows × 5 columns</p>
</div>
```python
# convertir journal en int
issns2['journal'] = issns2['journal'].astype(int)
```
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
```python
# convertir l'index en id
issns2 = issns2.reset_index()
issns2['id'] = issns2['index'] + 1
del issns2['index']
issns2
```
<div>
<style scoped>
.dataframe tbody tr th:only-of-type {
vertical-align: middle;
}
.dataframe tbody tr th {
vertical-align: top;
}
.dataframe thead th {
text-align: right;
}
</style>
<table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>issn</th>
<th>issnl</th>
<th>journal</th>
<th>format</th>
<th>issn_type</th>
<th>id</th>
</tr>
</thead>
<tbody>
<tr>
<td>0</td>
<td>0001-2815</td>
<td>0001-2815</td>
<td>532</td>
<td>PRINT</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<td>1</td>
<td>1399-0039</td>
<td>0001-2815</td>
<td>532</td>
<td>NaN</td>
<td>3</td>
<td>2</td>
</tr>
<tr>
<td>2</td>
<td>0001-4842</td>
<td>0001-4842</td>
<td>498</td>
<td>PRINT</td>
<td>1</td>
<td>3</td>
</tr>
<tr>
<td>3</td>
<td>1520-4898</td>
<td>0001-4842</td>
<td>498</td>
<td>NaN</td>
<td>3</td>
<td>4</td>
</tr>
<tr>
<td>4</td>
<td>0001-4966</td>
<td>0001-4966</td>
<td>789</td>
<td>PRINT</td>
<td>1</td>
<td>5</td>
</tr>
<tr>
<td>...</td>
<td>...</td>
<td>...</td>
<td>...</td>
<td>...</td>
<td>...</td>
<td>...</td>
</tr>
<tr>
<td>1755</td>
<td>2470-0045</td>
<td>2470-0045</td>
<td>533</td>
<td>OTHER</td>
<td>3</td>
<td>1756</td>
</tr>
<tr>
<td>1756</td>
<td>2470-0053</td>
<td>2470-0045</td>
<td>533</td>
<td>NaN</td>
<td>3</td>
<td>1757</td>
</tr>
<tr>
<td>1757</td>
<td>2475-9953</td>
<td>2475-9953</td>
<td>608</td>
<td>ELECTRONIC</td>
<td>2</td>
<td>1758</td>
</tr>
<tr>
<td>1758</td>
<td>2504-4427</td>
<td>2504-4427</td>
<td>994</td>
<td>PRINT</td>
<td>1</td>
<td>1759</td>
</tr>
<tr>
<td>1759</td>
<td>2504-4435</td>
<td>2504-4427</td>
<td>994</td>
<td>NaN</td>
<td>3</td>
<td>1760</td>
</tr>
</tbody>
</table>
<p>1760 rows × 6 columns</p>
</div>
```python
issns2['issn_type'] = issns2['issn_type'].astype(int)
```
```python
# supprimer les doublons par ISSN
issns2 = issns2.drop_duplicates(subset='issn')
issns2
```
<div>
<style scoped>
.dataframe tbody tr th:only-of-type {
vertical-align: middle;
}
.dataframe tbody tr th {
vertical-align: top;
}
.dataframe thead th {
text-align: right;
}
</style>
<table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>issn</th>
<th>issnl</th>
<th>journal</th>
<th>format</th>
<th>issn_type</th>
<th>id</th>
</tr>
</thead>
<tbody>
<tr>
<td>0</td>
<td>0001-2815</td>
<td>0001-2815</td>
<td>532</td>
<td>PRINT</td>
<td>1</td>
<td>1</td>
</tr>
<tr>
<td>1</td>
<td>1399-0039</td>
<td>0001-2815</td>
<td>532</td>
<td>NaN</td>
<td>3</td>
<td>2</td>
</tr>
<tr>
<td>2</td>
<td>0001-4842</td>
<td>0001-4842</td>
<td>498</td>
<td>PRINT</td>
<td>1</td>
<td>3</td>
</tr>
<tr>
<td>3</td>
<td>1520-4898</td>
<td>0001-4842</td>
<td>498</td>
<td>NaN</td>
<td>3</td>
<td>4</td>
</tr>
<tr>
<td>4</td>
<td>0001-4966</td>
<td>0001-4966</td>
<td>789</td>
<td>PRINT</td>
<td>1</td>
<td>5</td>
</tr>
<tr>
<td>...</td>
<td>...</td>
<td>...</td>
<td>...</td>
<td>...</td>
<td>...</td>
<td>...</td>
</tr>
<tr>
<td>1755</td>
<td>2470-0045</td>
<td>2470-0045</td>
<td>533</td>
<td>OTHER</td>
<td>3</td>
<td>1756</td>
</tr>
<tr>
<td>1756</td>
<td>2470-0053</td>
<td>2470-0045</td>
<td>533</td>
<td>NaN</td>
<td>3</td>
<td>1757</td>
</tr>
<tr>
<td>1757</td>
<td>2475-9953</td>
<td>2475-9953</td>
<td>608</td>
<td>ELECTRONIC</td>
<td>2</td>
<td>1758</td>
</tr>
<tr>
<td>1758</td>
<td>2504-4427</td>
<td>2504-4427</td>
<td>994</td>
<td>PRINT</td>
<td>1</td>
<td>1759</td>
</tr>
<tr>
<td>1759</td>
<td>2504-4435</td>
<td>2504-4427</td>
<td>994</td>
<td>NaN</td>
<td>3</td>
<td>1760</td>
</tr>
</tbody>
</table>
<p>1760 rows × 6 columns</p>
</div>
```python
# export csv
issns2.to_csv('sample/issn_brut.tsv', sep='\t', encoding='utf-8', index=False)
```
```python
# export excel
issns2.to_excel('sample/issn_brut.xlsx', index=False)
```
```python
# export CSV des IDs
issns2[['id', 'issn', 'issnl', 'journal']].to_csv('sample/issn_ids.tsv', sep='\t', encoding='utf-8', index=False)
```
```python
# export excel des IDs
issns2[['id', 'issn', 'issnl', 'journal']].to_excel('sample/issn_ids.xlsx', index=False)
```

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