I have a dataset that has many columns, I want to extract the numeric columns and replace with the mean of the columns and then these modified columns replacing the ones in the original dataframe.
df1 = df.select_dtypes(include = ["number"]).apply(lambda x: x.fillna(x.mean()),axis=0)
df.loc[df.select_dtypes(include = ["number"])] = df1
I managed to extract the numeric columns but I couldn't replace them, the idea is not to manually indicate which are those numeric columns.
It's probably easier to assign a new/changed DataFrame. This will only change the columns you altered.
new_df = df.assign(**df.select_dtypes('number').apply(lambda x: x.fillna(x.mean())))
If you want to preserve the original DataFrame, you can do it in steps:
cols = df.select_dtypes('number').columns
df[cols] = df[cols].apply(lambda x: x.fillna(x.mean()))