Groupby fillna ffill

df['three'] = df.groupby(['one','two'], sort=False)['three']
                .apply(lambda x: x.ffill().bfill())
print (df)
   one  two  three
0    1    1   10.0
1    1    1   10.0
2    1    1   10.0
3    1    2   20.0
4    1    2   20.0
5    1    2   20.0
6    1    3    NaN
7    1    3    NaN

Source: stackoverflow.com

Groupby fillna ffill

print (df)
   one  two  three
0    1    1   10.0
1    1    1   40.0
2    1    1    NaN
3    1    2    NaN
4    1    2   20.0
5    1    2    NaN
6    1    3    NaN
7    1    3    NaN

df['three'] = df.groupby(['one','two'], sort=False)['three']
                .apply(lambda x: x.fillna(x.mean()))
print (df)
   one  two  three
0    1    1   10.0
1    1    1   40.0
2    1    1   25.0
3    1    2   20.0
4    1    2   20.0
5    1    2   20.0
6    1    3    NaN
7    1    3    NaN

Source: stackoverflow.com

Similar codes

0 vote131 views1 answer
Import csv import re data = [] with open('customerData.csv') as csvfile: reader = csv.DictReader(csvfile) for row in reader: data.append(row) print(data[0]) print(data[1]["Name"]) print(data[2]["Spent Past 30 Days"])
Python
0 vote140 views1 answer
Method for format age in python
Python
0 vote188 views2 answers
The readlines() method returns
Python
0 vote127 views1 answer
Pytho ntoday as string
Python
1 vote129 views1 answer
Python dynamic object
Python
0 vote131 views1 answer
No module named googlesearch
Python
2 votes121 views6 answers
Variable python
Python
0 vote153 views1 answer
SparkSession pyspark
Python
34 votes149 views6 answers
Logging python
Python
0 vote131 views1 answer
How to import sin and cos in python
Python