dataframe
df.columns=['ipo_date','l2y_gg_date','l1k_kk_date']
Purpose
- extract dataframe with columns titled
_dateexcludingipo_date.
Solution
df.filter(regex='_date&^ipo_date')
df.columns=['ipo_date','l2y_gg_date','l1k_kk_date']
_date excluding ipo_date.df.filter(regex='_date&^ipo_date')Take advantage of a negative lookbehind pattern:
import numpy as np
import pandas as pd
df = pd.DataFrame(np.arange(1, 21).reshape((5, 4)),
columns=['ipo_date', 'l2y_gg_date', 'l1k_kk_date', 'other'])
filtered = df.filter(regex=r'(?<!ipo)_date')
print(filtered)
Here is a sample df:
ipo_date l2y_gg_date l1k_kk_date other
0 1 2 3 4
1 5 6 7 8
2 9 10 11 12
3 13 14 15 16
4 17 18 19 20
The resulting filtered dataframe:
l2y_gg_date l1k_kk_date
0 2 3
1 6 7
2 10 11
3 14 15
4 18 19
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