Grouped Forward Fill & Back Fill with Pandas

Python

In this snippet all NAs in the latest_value column are filled but filling only happens within each category i.e. a latest value from one category won't be used to fill an NA from a different category

 1|  #Forward fill
 2|  df['latest_value_ffill'] = df.groupby('category')['latest_value'].transform(lambda x: x.fillna(method='ffill'))
 3|  
 4|  #Back fill
 5|  df['latest_value_bfill'] = df.groupby('category')['latest_value'].transform(lambda x: x.fillna(method='bfill'))
detro
Groupby | Fillna
Did you find this snippet useful?

Sign up for free to to add this to your code library

Remove Stop Words from Text in DataFrame Column
Python

Pandas | Nltk | Nlp

133
LightGBM Custom Loss Function
Python

LightGBM | Loss function

121
Tuning XGBoost Hyperparameters with Grid Search
Python

XGBoost | Tuning

116
How to Convert DataFrame Values Into Percentages
Python

Lambda | Percentages | Pipe

109
How to Scale Data Using Standard Scaler But Keep Column Names
Python

Scaler | Standard

78
Calculating Root Mean Squared Error (RMSE) with Sklearn and Python
Python

Rmse

77
LightGBM Hyperparameter Tuning with GridSearch
Python

Python | LightGBM | Hyperparameter tuning | Gridsearch

77
Dynamically Create Columns in Pandas Dataframe
Python

Pandas | Columns

61
How to Train a Catboost Classifier with GridSearch Hyperparameter Tuning
Python

Catboost | Hyperparameter tuning

60
Overwriting a Python Logging File Instead of Appending
Python

Logging

55