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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?

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1 Answer 1

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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')
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