ForwardFill

class geoanalytics.imputation.ForwardFill.ForwardFill(dataframe)

Bases: object

About this algorithm

Description:

Forward Fill imputes missing values using the previous valid entry, with backward fill as a fallback for trailing NaNs.

Parameters:

• dataframe (pd.DataFrame): Input dataset where the first two columns are assumed to be spatial (‘x’, ‘y’) and all remaining columns are treated as features to be imputed.

Attributes:

• df (pd.DataFrame): Copy of the input data, with the first two columns renamed to ‘x’, ‘y’.

• imputedDF (pd.DataFrame): Output DataFrame after missing value imputation.

Execution methods

import pandas as pd

from geoanalytics.imputation import ForwardFill

df = pd.read_csv("input.csv")

ff = ForwardFill(df)

imputed_df = ff.impute()

ff.save("ForwardFilled.csv")

Credits

This implementation was created and revised under the guidance of Professor Rage Uday Kiran.

getMemoryRSS()

Prints the memory usage (RSS) of the process in kilobytes.

getMemoryUSS()

Prints the memory usage (USS) of the process in kilobytes.

getRuntime()

Prints the total runtime of the algorithm.

run()

Applies forward fill imputation followed by backward fill as fallback.

Returns:

A pandas DataFrame with the original spatial coordinates and imputed feature values.

save(outputFile='ForwardFilled.csv')

Saves the imputed DataFrame to a CSV file.

Parameters:

outputFile – The filename for saving the DataFrame. Defaults to ‘ForwardFilled.csv’.