How to fill missing value in a few columns at the same time

Question

I need to drop missing values in a few columns. I wrote this to do it one by one:

df2['A'].fillna(df1['A'].mean(), inplace=True)
df2['B'].fillna(df1['B'].mean(), inplace=True)
df2['C'].fillna(df1['C'].mean(), inplace=True)

Any other ways I can fill them all in one line of code?

Answer 1

You can use a single instructions:

cols = ['A', 'B', 'C']
df[cols] = df[cols].fillna(df[cols].mean())

Or for apply on all numeric columns, use select_dtypes:

cols = df.select_dtypes('number').columns
df[cols] = df[cols].fillna(df[cols].mean())

Note: I strongly discourage you to use inplace parameter. It will probably disappear in Pandas 2