How to remove rows that contains only NaN values in all columns of dataframe? [duplicate]

Question

I have dataframe like below.

Input

df A B C 1 2 1 NaN 4 2 3 NaN NaN NaN NaN NaN 4 2 NaN NaN NaN NaN

Output

 A B C 1 2 1 NaN 4 2 3 NaN NaN 4 2 NaN

How can this be done in python

Sai · Accepted Answer · 2020-08-03 09:05:54Z

6

df.dropna(axis = 0, how = 'all')

answered Aug 3, 2020 at 9:05

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Comments

Tasnuva Leeya · Accepted Answer · 2020-08-03 09:06:30Z

you can use:

df.dropna(how='all')

Jonas Palačionis · Accepted Answer · 2020-08-03 10:02:13Z

You can select the df which is not NaN rather than dropping it:

df = df[~((df['A'].isna()) & (df['B'].isna()) & (df['C'].isna()))]

This gives a bit more capability if you want to filter your df by certain values of each column.

A B C 1 2 1 NaN 4 2 3 NaN NaN 4 2 NaN

You can use df.dropna?? to get the information about the dropna functionality.