33 lines
1.1 KiB
Python
33 lines
1.1 KiB
Python
import csv_metadata_quality.check as check
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import csv_metadata_quality.fix as fix
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import pandas as pd
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import re
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def main():
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# Read all fields as strings so dates don't get converted from 1998 to 1998.0
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#df = pd.read_csv('/home/aorth/Downloads/2019-07-26-Bioversity-Migration.csv', dtype=str)
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#df = pd.read_csv('/tmp/quality.csv', dtype=str)
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df = pd.read_csv('data/test.csv', dtype=str)
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# Fix whitespace in all columns
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for column in df.columns.values.tolist():
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# Run whitespace fix on all columns
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df[column] = df[column].apply(fix.whitespace)
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# Run invalid multi-value separator check on all columns
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df[column] = df[column].apply(check.separators)
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if column == 'dc.identifier.issn':
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df[column] = df[column].apply(check.issn)
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if column == 'dc.identifier.isbn':
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df[column] = df[column].apply(check.isbn)
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# check if column is a date column like dc.date.issued
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match = re.match(r'^.*?date.*$', column)
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if match is not None:
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df[column] = df[column].apply(check.date)
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# Write
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df.to_csv('/tmp/test.fixed.csv', index=False)
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