Fillna in multiple columns in place in Python Pandas

Question

I have a pandas dataFrame of mixed types, some are strings and some are numbers. I would like to replace the NAN values in string columns by \'.\', and the NAN values in flo

Answer 1

Came across this page while looking for an answer to this problem, but didn't like the existing answers. I ended up finding something better in the DataFrame.fillna documentation, and figured I'd contribute for anyone else that happens upon this.

If you have multiple columns, but only want to replace the NaN in a subset of them, you can use:

df.fillna({'Name':'.', 'City':'.'}, inplace=True)

This also allows you to specify different replacements for each column. And if you want to go ahead and fill all remaining NaN values, you can just throw another fillna on the end:

df.fillna({'Name':'.', 'City':'.'}, inplace=True).fillna(0, inplace=True)