Delete column from pandas DataFrame using del df.column
When deleting a column in a DataFrame I use:
del df['column_name']
and this works great. Why can't I use:
del df.column_name
As you can access the column/Series as df.column_name , I expect this to work.
It's difficult to make del df.column_name work simply as the result of syntactic limitations in Python. del df[name] gets translated to df.__delitem__(name) under the covers by Python.
The best way to do this in pandas is to use drop :
df = df.drop('column_name', 1)
where 1 is the axis number ( 0 for rows and 1 for columns.)
To delete the column without having to reassign df you can do:
df.drop('column_name', axis=1, inplace=True)
Finally, to drop by column number instead of by column label, try this to delete, eg the 1st, 2nd and 4th columns:
df.drop(df.columns[[0, 1, 3]], axis=1) # df.columns is zero-based pd.Index
columns = ['Col1', 'Col2', ...]
df.drop(columns, inplace=True, axis=1)
This will delete one or more columns in-place. Note that inplace=True was added in pandas v0.13 and won't work on older versions, do you'd have to do assign the result back in that case:
df = df.drop(columns, axis=1)