I'd like to 'anonymize' or 'recode' a column in a pandas DataFrame. What's the most efficient way to do so? I wrote the following, but it seems likely there's a built-in function or better way.
dataset = dataset.sample(frac=1).reset_index(drop=False) # reorders dataframe randomly (helps anonymization, since order could have some meaning)
# make dictionary of old and new values
value_replacer = 1
values_dict = {}
for unique_val in dataset[var].unique():
values_dict[unique_val] = value_replacer
value_replacer += 1
# replace old values with new
for k, v in values_dict.items():
dataset[var].replace(to_replace=k, value=v, inplace=True)
IIUC you want to factorize your values:
dataset[var] = pd.factorize(dataset[var])[0] + 1
Demo:
In [2]: df
Out[2]:
col
0 aaa
1 aaa
2 bbb
3 ccc
4 ddd
5 bbb
In [3]: df['col'] = pd.factorize(df['col'])[0] + 1
In [4]: df
Out[4]:
col
0 1
1 1
2 2
3 3
4 4
5 2