/Python/Impute data by using groupby and transform

Impute data by using groupby and transform

import pandas as pd
from datetime import datetime

def generate_data():
    ...

t = datetime.now()
df = generate_data()
df['value'] = df.groupby(['category', 'name'])['value']\
    .transform(lambda x: x.fillna(x.mean()))
print(datetime.now()-t)

# 0:00:00.016012

t = datetime.now()
df = generate_data()
df["value"] = df.groupby(['category', 'name'])\
    .transform(lambda x: x.fillna(x.mean()))['value']
print(datetime.now()-t)

# 0:00:00.030022

Source: stackoverflow.com

Impute data by using groupby and transform

df['value'] = df.groupby(['category', 'name'])['value']\
    .transform(lambda x: x.fillna(x.mean()))

Source: stackoverflow.com

Similar codes

1 vote182 views1 answer
Series to numpy array
Python
0 vote227 views1 answer
Python on_mouse_down/collidepoint
Python
1 vote231 views1 answer
Django query multiple conditions
Python Django
6 votes242 views5 answers
Django logout
Python
0 vote215 views1 answer
Python Key Gen
Python
-2 votes195 views1 answer
Start django project in windows
Python
0 vote175 views1 answer
Matplotlib show two distinct plots
Python
0 vote210 views1 answer
Torch print floating precision
Python
0 vote180 views4 answers
Insert blank row in data frame
Python
0 vote183 views1 answer
ValueError: expected sparse matrix with integer values, found float values
Python