How to delete a column from a data frame with pandas?

Question

I read my data

import pandas as pd df = pd.read_csv('/path/file.tsv', header=0, delimiter='\t') print df 

and get:

          id    text 0    361.273    text1... 1    374.350    text2... 2    374.350    text3... 

How can I delete the id column from the above data frame?. I tried the following:

import pandas as pd df = pd.read_csv('/path/file.tsv', header=0, delimiter='\t') print df.drop('id', 1) 

But it raises this exception:

ValueError: labels ['id'] not contained in axis 

Answer 1

df.drop(colname, axis=1) (or del df[colname]) is the correct method to use to delete a column.

If a ValueError is raised, it means the column name is not exactly what you think it is.

Check df.columns to see what Pandas thinks are the names of the columns.

Answer 2

The best way to delete a column in pandas is to use drop:

df = df.drop('column_name', axis=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, e.g. the 1st, 2nd and 4th columns:

df.drop(df.columns[[0, 1, 3]], axis=1)  # df.columns is zero-based pd.Index  

Exceptions:

If a wrong column number or label is requested an error will be thrown. To check the number of columns use df.shape[1] or len(df.columns.values) and to check the column labels use df.columns.values.

An exception would be raised answer was based on @LondonRob's answer and left here to help future visitors of this page.