drop columns pandas
df.drop(columns=['B', 'C'])
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 11
df.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 11
drop values based on type pandas
df[df.columns[n]] = df[df.columns[n]].apply(pd.to_numeric, errors='coerce').fillna(0).astype(float).dropna()
drop variable pandas
# pandas drop a column with drop function
gapminder_ocean.drop(['pop'], axis=1)
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