drop a column from dataframe
#To delete the column without having to reassign df
df.drop('column_name', axis=1, inplace=True)
drop a column from dataframe
#To delete the column without having to reassign df
df.drop('column_name', 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 columns
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
drop a column from dataframe
#working with "text" syntax for the columns:
df.drop(['column_nameA', 'column_nameB'], axis=1, inplace=True)
drop unamed columns in pandas
df = df.loc[:, ~df.columns.str.contains('^Unnamed')]
In [162]: df
Out[162]:
colA ColB colC colD colE colF colG
0 44 45 26 26 40 26 46
1 47 16 38 47 48 22 37
2 19 28 36 18 40 18 46
3 50 14 12 33 12 44 23
4 39 47 16 42 33 48 38
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