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 code to drop columns from dataframe
# Let df be a dataframe
# Let new_df be a dataframe after dropping a column
new_df = df.drop(labels='column_name', axis=1)
# Or if you don't want to change the name of the dataframe
df = df.drop(labels='column_name', axis=1)
# Or to remove several columns
df = df.drop(['list_of_column_names'], axis=1)
# axis=0 for 'rows' and axis=1 for columnsdelete columns pandas
df = df.drop(df.columns[[0, 1, 3]], axis=1) # df.columns is zero-based pd.Index
df.drop(['column_nameA', 'column_nameB'], axis=1, inplace=True)how to drop a column by name in pandas
>>> midx = pd.MultiIndex(levels=[['lama', 'cow', 'falcon'],
... ['speed', 'weight', 'length']],
... codes=[[0, 0, 0, 1, 1, 1, 2, 2, 2],
... [0, 1, 2, 0, 1, 2, 0, 1, 2]])
>>> df = pd.DataFrame(index=midx, columns=['big', 'small'],
... data=[[45, 30], [200, 100], [1.5, 1], [30, 20],
... [250, 150], [1.5, 0.8], [320, 250],
... [1, 0.8], [0.3, 0.2]])
>>> df
big small
lama speed 45.0 30.0
weight 200.0 100.0
length 1.5 1.0
cow speed 30.0 20.0
weight 250.0 150.0
length 1.5 0.8
falcon speed 320.0 250.0
weight 1.0 0.8
length 0.3 0.2remove a columns in pandas
DataFrame.drop(self, labels=None, axis=0, index=None, columns=None, level=None, inplace=False, errors='raise')[source]Copyright © 2021 Codeinu
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