Nov-12-2019, 01:33 PM (This post was last modified: Nov-12-2019, 01:33 PM by bobopt. Edited 1 time in total.)

Hello everybody, I'm new in python and I would ask you a question that is making me crazy.

I think I've not well understood some things, so please help me.

The question is: I want to fill NaN value of a column in a dataframe but based on a value of another column.

The example of 2 dataframe:

- if M then 99.9

- if B then 66.6

Here's the problem...

I try:

Where I'm wrong?

Thank you for answers.

I think I've not well understood some things, so please help me.

The question is: I want to fill NaN value of a column in a dataframe but based on a value of another column.

The example of 2 dataframe:

import pandas as pd import numpy as np df = pd.DataFrame([{'a':'A', 'b': 'B', 'c': 15.2}, \ {'a':'Z', 'b': 'M', 'c': 1.7}, \ {'a':'A', 'b': 'B', 'c': np.nan},\ {'a':'Z', 'b': 'B', 'c': 16.8}, \ {'a':'Z', 'b': 'M', 'c': np.nan},\ {'a':'A', 'b': 'M', 'c': np.nan},\ {'a':'Z', 'b': 'B', 'c': np.nan}]) sw = pd.DataFrame([{'x': 'B', 'v': 66.6}, \ {'x': 'M', 'v': 99.9},])Now I want to fill Nan value of column named c in dataframe df depending on the value of the column b of the dataframe df and take the value from another dataframe sw, that is:

- if M then 99.9

- if B then 66.6

Here's the problem...

I try:

df.loc[(df['b'] == 'M') & (df['c'].isnull()), 'c'] = sw.loc[(sw['x']=='M'), 'v'] df.loc[(df['b'] == 'B') & (df['c'].isnull()), 'c'] = sw.loc[(sw['x']=='B'), 'v']But the dataframe df doesn't change, Nan value still remain...

Where I'm wrong?

Thank you for answers.