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fake-orcid-analysis
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adding preprocessing with make

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Andrea Mannocci 2021-03-23 19:03:37 +01:00
parent 4e30d743d8
commit b5e99701b1
2 changed files with 4259 additions and 4175 deletions
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8393
notebooks/01-Exploration.ipynb
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41
src/data/make_dataset.py
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@ -3,7 +3,9 @@ import click
import logging import logging
from pathlib import Path from pathlib import Path
from dotenv import find_dotenv, load_dotenv from dotenv import find_dotenv, load_dotenv
import pandas as pd
import ast
import os
@click.command() @click.command()
@click.argument('input_filepath', type=click.Path(exists=True)) @click.argument('input_filepath', type=click.Path(exists=True))
@ -13,8 +15,41 @@ def main(input_filepath, output_filepath):
cleaned data ready to be analyzed (saved in ../processed). cleaned data ready to be analyzed (saved in ../processed).
""" """
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
logger.info('making final data set from raw data') logger.info('Making final data set from raw data')
logger.info('Loading the zipped dataset')
df = pd.read_csv(os.path.join(input_filepath, 'initial_info_whole_20210322.tsv.gz'), compression='gzip', sep='\t', header=0,
names=['orcid', 'claimed','verified_email', 'verified_primary_email',
'given_names', 'family_name', 'biography', 'other_names', 'urls',
'primary_email', 'other_emails', 'keywords', 'external_ids', 'education',
'employment', 'n_works', 'works_source', 'activation_date', 'last_update_date',
'n_doi', 'n_arxiv', 'n_pmc', 'n_other_pids'])
logger.info('Loading list columns')
logger.info('... other_names')
df['other_names'] = df[df.other_names.notna()]['other_names'].apply(lambda x: ast.literal_eval(x))
logger.info('... keywords')
df['keywords'] = df[df.keywords.notna()]['keywords'].apply(lambda x: ast.literal_eval(x))
logger.info('... urls')
df['urls'] = df[df.urls.notna()]['urls'].apply(lambda x: ast.literal_eval(x))
logger.info('... other_emails')
df['other_emails'] = df[df.other_emails.notna()]['other_emails'].apply(lambda x: ast.literal_eval(x))
logger.info('... education')
df['education'] = df[df.education.notna()]['education'].apply(lambda x: ast.literal_eval(x))
logger.info('... employment')
df['employment'] = df[df.employment.notna()]['employment'].apply(lambda x: ast.literal_eval(x))
logger.info('... external_ids')
df['external_ids'] = df[df.external_ids.notna()]['external_ids'].apply(lambda x: ast.literal_eval(x))
logger.info('... works_source')
df['works_source'] = df[df.works_source.notna()]['works_source'].apply(lambda x: ast.literal_eval(x))
openaire_orcid = pd.read_csv(os.path.join(input_filepath, 'orcid_openaire.txt'), header=None, names=['orcid'])
df['label'] = df.orcid.isin(openaire_orcid['orcid'])
df['label'] = df['label'].astype(int)
logger.info('Serializing the dataset in ../processed')
df.to_pickle(os.path.join(output_filepath, 'dataset.pkl'))
if __name__ == '__main__': if __name__ == '__main__':
log_fmt = '%(asctime)s - %(name)s - %(levelname)s - %(message)s' log_fmt = '%(asctime)s - %(name)s - %(levelname)s - %(message)s'