How to replace NaN values by Zeroes in a column of a Pandas Dataframe?

Question

I have a Pandas Dataframe as below:

      itm Date                  Amount 
67    420 2012-09-30 00:00:00   65211
68    421 2012-09-09 00:00:00   29424
69             


        

Answer 1

Easy way to fill the missing values:-

filling string columns: when string columns have missing values and NaN values.

df['string column name'].fillna(df['string column name'].mode().values[0], inplace = True)

filling numeric columns: when the numeric columns have missing values and NaN values.

df['numeric column name'].fillna(df['numeric column name'].mean(), inplace = True)

filling NaN with zero:

df['column name'].fillna(0, inplace = True)