Conditional replace in pandas dataframe

Question

new_df['year'].describe()

count    10866.000000
mean      2004.009939
std         14.958790
min       1968.000000
25%       1996.000000
50%       2006.000000
75%       2012.000000
max       2067.000000
Name: year, dtype: float64

It seems like the erroneous year values are +100 years off (ie, 2067 should probably be 1967). Therefore, for values above 2018, how do I [year - 100] while leaving the rest of the values untouched?

Did an answer below help? Feel free to accept an answer (green tick on left), or ask for clarification. — jpp
– jpp, Commented May 8, 2018 at 11:13

jpp · Accepted Answer · 2018-04-27 22:47:28Z

1

You can use pd.DataFrame.loc:

new_df.loc[new_df['year'] > 2018, 'year'] -= 100

answered Apr 27, 2018 at 22:47

jpp

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