Unpivot data with delimiters (v2)

unpivot_delimited_data_v2.py

import pandas as pd
from typing import List
# Base clode for splitting and unpivoting a Series
# https://stackoverflow.com/questions/19482970/get-list-from-pandas-dataframe-column-headers


def unpivot_delimited_series(
    series: pd.Series,
    delimiter: str
) -> pd.DataFrame:
    unpivoted_data = series\
        .apply( lambda series_row: pd.Series(series_row.split(delimiter)) )\
        .stack()

    unpivoted_data = unpivoted_data.reset_index()

    return unpivoted_data


def get_other_colum_names(
    source_df: pd.DataFrame,
    unpivoted_column: str
) -> List[str]:
    other_columns = list(source_df.columns.values)

    other_columns.remove(unpivoted_column)
    
    return other_columns


def unpivot_delimited_data(
    source_df: pd.DataFrame,
    target_column: str,
    delimiter: str
) -> pd.DataFrame:
    unpivoted_series = unpivot_delimited_series(
        source_df[target_column], 
        ";"
    )

    source_df = source_df.reset_index()

    source_df_other_columns = get_other_colum_names(
        source_df, 
        target_column
    )

    source_data_to_merge = source_df[source_df_other_columns]

    merged_data = pd.merge(
        unpivoted_series,
        source_data_to_merge,
        how="inner",
        left_on="level_0",
        right_on="index"
    )

    merged_data.rename(
        columns={0: target_column},
        inplace=True
    )

    # List with the names of the columns to keep (the only index kept is the\
    # post-reset index of the source DataFrame)
    columns_to_keep = source_df_other_columns + [target_column]
    columns_to_keep.remove("index")

    merged_data = merged_data[columns_to_keep]

    return merged_data


if __name__ == "__main__":
    # Load the original dataset
    data = pd.read_csv("sample_data.csv")

    # Split and unpivot the column with delimited data, keeping the\
    # complete DataFrame
    final_data = unpivot_delimited_data(
        data,
        "Used Social Networks",
        ";"
    )

    print(data)
    print(final_data)