drop a column pandas
df.drop(['column_1', 'Column_2'], axis = 1, inplace = True)drop a column pandas
df.drop(['column_1', 'Column_2'], axis = 1, inplace = True)python pandas drop
df = pd.DataFrame(np.arange(12).reshape(3, 4),
... columns=['A', 'B', 'C', 'D'])
>>> df
A B C D
0 0 1 2 3
1 4 5 6 7
2 8 9 10 11
Drop columns
>>> df.drop(['B', 'C'], axis=1)
A D
0 0 3
1 4 7
2 8 11
>>> df.drop(columns=['B', 'C'])
A D
0 0 3
1 4 7
2 8 11df.drop
>>>df = pd.DataFrame(np.arange(12).reshape(3, 4),
columns=['A', 'B', 'C', 'D'])
>>>df
A B C D
0 0 1 2 3
1 4 5 6 7
2 8 9 10 11
>>> df.drop(['B', 'C'], axis=1)
A D
0 0 3
1 4 7
2 8 11
OR
>>> df.drop(columns=['B', 'C'])
A D
0 0 3
1 4 7
2 8 11drop a column from dataframe
#to drop by column number instead of by column label, try this to delete, e.g. the 1st, 2nd and 4th columns
df = df.drop(df.columns[[0, 1, 3]], axis=1) # df.columns is zero-based pd.IndexCopyright © 2021 Codeinu
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