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Simple pseudonymization of a column with name values in a pandas dataframe
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#!/usr/bin/python3 | |
# -*- coding: utf-8 -*- | |
# Requires pandas and numpy | |
# pip3 install pandas numpy | |
# and the Faker package: | |
# pip3 install Faker | |
from faker import Faker | |
import numpy as np | |
import pandas as pd | |
# example dataframe | |
df = pd.DataFrame({'name': {0: 'foo', 1: 'bar', 2: 'foo', 3: 'foobar', 4: 'foobar', 5: np.nan, 6: ''}}) | |
print(df) | |
# name | |
# 0 foo | |
# 1 bar | |
# 2 foo | |
# 3 foobar | |
# 4 foobar | |
# 5 NaN | |
# 6 | |
# pseudonymization of the name column using Faker | |
fake = Faker() | |
# empty string values as nan | |
df.replace('', np.nan, inplace=True) | |
# name replacement dictionary | |
name_replacements = {name: fake.name().lower().replace(" ", "") for name in df['name'].unique() if name is not np.nan} | |
# apply replacement | |
df.replace({"name": name_replacements}, inplace=True) | |
print(df) | |
# name | |
# 0 traceymata | |
# 1 susansmithmd | |
# 2 traceymata | |
# 3 charlesrogers | |
# 4 charlesrogers | |
# 5 NaN | |
# 6 NaN |
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