Below is the Dataframe i'm working. I want to replace NaN values in 'Score' columns using values from column 'Country' and 'Sectors'
Country Sectors Score
0 USA MECH NaN
1 IND ELEC 10.0
2 USA CHEM NaN
3 RUS ENT 34.0
4 PAK MATH 45.0
5 SL LAN 23.0
6 USA CHEM 56.0
7 IND ELEC 32.0
8 USA CHEM NaN
9 RUS ENT 45.0
10 PAK MATH 45.0
Below is the code which I've tried
import pandas as pd
import numpy as np
df = pd.read_csv('../Data/Data.csv')
df['Score'] = df[(df['Country'] == 'USA') & (df['Sectors'] == 'CHEM') & (df['Score'].isnull())]['Score'].fillna(10)
print(df)
```but I am getting below result```
Country Sectors Score
0 USA MECH NaN
1 IND ELEC NaN
2 USA CHEM 10.0
3 RUS ENT NaN
4 PAK MATH NaN
5 SL LAN NaN
6 USA CHEM NaN
7 IND ELEC NaN
8 USA CHEM 10.0
9 RUS ENT NaN
10 PAK MATH NaN
I want to replace only NaN values specific to country == 'USA' and Sectors == 'CHEM' and keep all values as it is. Could anyone please help?```
You can use np.where
:
>>> df = pd.DataFrame({'Country':['USA', 'IND','USA'], 'Sectors':['MECH', 'ELEC','CHEM'], 'Score':[45.0, 30.0, np.NaN]})
>>> df["Score"] = np.where((df["Country"]=='USA') & (df['Sectors'] == 'CHEM'), 10, df["Score"])
>>> df
Country Sectors Score
0 USA MECH 45.0
1 IND ELEC 30.0
2 USA CHEM 10.0
If df["Country"]=='USA'
and df['Sectors'] == 'CHEM'
, the df['Score']
is set to 10
, else, the original value in df['Score']
is set.
The technical post webpages of this site follow the CC BY-SA 4.0 protocol. If you need to reprint, please indicate the site URL or the original address.Any question please contact:yoyou2525@163.com.