Return the changed values after using fillna() python's pandas-CodePudding

I am using fillna() in a dataframe to change the null values from one column for another ones from another column, but I don't seem to find the way to print the changed values. I've tried to iterate over fillna() but that doesn't do the trick.

df.column_with_nan.fillna(column_to_use_as_nan_replacement, inplace=True)

I was thinking maybe I could run the new changed column against the old unchanged column, but I'd like to know whether there's a simpler way.

Any piece of advice?

Thanks!

CodePudding user response：

I don't know of any non-hacky way to straight print the changed values, but you can use pandas.Series.compare() to get the changed values. Just do

tmp = pd.Series(df1.column_with_nan.copy())
df.row_with_nan.fillna(column_to_use_as_nan_replacement, inplace=True)
print(tmp.compare(df.column_with_nan))

You can also run df.compare for full dataframes.

CodePudding user response：

You could create a mask before replacing the values:

mask = df["col_with_nan"].isna()

After replacing the nan values, you can then access the changed rows like this:

df[mask]

Example:

import pandas as pd
import numpy as np

df = pd.DataFrame(
    {
        "col_with_nan": [np.nan, 1, 1, 1, np.nan, 1, 1, 1, np.nan],
        "column_to_use_as_nan_replacement": [11, 22, 33, 44, 55, 66, 77, 88, 99],
    }
)
print(df)
mask = df["col_with_nan"].isna()
df.col_with_nan.fillna(df.column_to_use_as_nan_replacement, inplace=True)
print(df)
print(df[mask])