Replace the NaNs in pandas dataframe with empty_rows in pandas

Question

I have the following table (df):

Col1	Col2	Col3
A1	finished	1234
A2	ongoing	1235
A3	NaN	1236
A4	finished	1237
A5	started	1238
A6	NaN	1239

I would like to replace the NaNs in the dataframe with empty_row. How do I do that?

Desired output:

Col1	Col2	Col3
A1	finished	1234
A2	ongoing	1235
A3	empty_row	1236
A4	finished	1237
A5	started	1238
A6	empty_row	1239

What I tried so far?

if df['col2'] == 'NaN':
   df['col2'] = 'empty_row'

I get the following error: ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

How do I solve this?

Answer 1

You should use the fillna method https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.fillna.html

df['col2'] = df['col2'].fillna('empty_row')