Forward and backward filling of missing values of DataFrame columns in Pandas?
Forward and backward filling of missing values:
import pandas as pd df = pd.DataFrame([[10, 30, 40], [], [15, 8, 12], [15, 14, 1, 8], [7, 8], [5, 4, 1]], columns=['Apple', 'Orange', 'Banana', 'Pear'], index=['Basket1', 'Basket2', 'Basket3', 'Basket4', 'Basket5', 'Basket6']) print("\n------ DataFrame with NaN -----\n") print(df) print("\n------ DataFrame with Forward Filling -----\n") print(df.ffill()) print("\n------ DataFrame with Forward Filling -----\n") print(df.bfill())
C:\pandas>python example.py ------ DataFrame with NaN ----- Apple Orange Banana Pear Basket1 10.0 30.0 40.0 NaN Basket2 NaN NaN NaN NaN Basket3 15.0 8.0 12.0 NaN Basket4 15.0 14.0 1.0 8.0 Basket5 7.0 8.0 NaN NaN Basket6 5.0 4.0 1.0 NaN ------ DataFrame with Forward Filling ----- Apple Orange Banana Pear Basket1 10.0 30.0 40.0 NaN Basket2 10.0 30.0 40.0 NaN Basket3 15.0 8.0 12.0 NaN Basket4 15.0 14.0 1.0 8.0 Basket5 7.0 8.0 1.0 8.0 Basket6 5.0 4.0 1.0 8.0 ------ DataFrame with Forward Filling ----- Apple Orange Banana Pear Basket1 10.0 30.0 40.0 8.0 Basket2 15.0 8.0 12.0 8.0 Basket3 15.0 8.0 12.0 8.0 Basket4 15.0 14.0 1.0 8.0 Basket5 7.0 8.0 1.0 NaN Basket6 5.0 4.0 1.0 NaN C:\pandas>
2018-10-24T14:15:31+05:30
2018-10-24T14:15:31+05:30
Amit Arora
Amit Arora
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