.fillna(), when is it appropriate?

When is it appropriate to use .fillna() instead of removing Nan values?

Hi, welcome to the forums.

I guess it depends on how you want to use your data. Personally, I wouldn’t use dropna().

In this case you’re just adding a “0” in that column, score rather than get rid of the entire row for that particular student. (Even though when calculating the .mean() NAs are ignored anyway.

Also:
To count the number of nulls in each col:

df.isnull.sum()

To count the total number of nulls in a df:
df.isnull.sum().sum()

1 Like