Delete column from pandas DataFrame

Question

When deleting a column in a DataFrame I use:

del df[\'column_name\']

And this works great. Why can\'t I use the following?

Answer 1

As you've guessed, the right syntax is

del df['column_name']

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.

Answer 2

Deleting a column using iloc function of dataframe and slicing, when we have a typical column name with unwanted values.

df = df.iloc[:,1:] # removing an unnamed index column

Here 0 is the default row and 1 is 1st column so ,1 where starts and stepping is taking default values, hence :,1: is our parameter for deleting the first column.

Answer 3

The dot syntax works in JavaScript, but not in Python.

• Python: del df['column_name']
• JavaScript: del df['column_name'] or del df.column_name

Answer 4

Use:

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. You'd have to assign the result back in that case:

df = df.drop(columns, axis=1)

Answer 5

from version 0.16.1 you can do

df.drop(['column_name'], axis = 1, inplace = True, errors = 'ignore')

Answer 6

In pandas 0.16.1+ you can drop columns only if they exist per the solution posted by @eiTanLaVi. Prior to that version, you can achieve the same result via a conditional list comprehension:

df.drop([col for col in ['col_name_1','col_name_2',...,'col_name_N'] if col in df], 
        axis=1, inplace=True)