Unpivot data with delimiters (v1)

unpivot_delimited_data.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(
    target_series: pd.Series,
    delimiter: str
) -> pd.DataFrame:
    unpivoted_data = target_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,
    index_column: str,
    delimiter: str
) -> pd.DataFrame:
    unpivoted_data = 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_data,
        source_data_to_merge,
        how="inner",
        on=index_column
    )

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

    merged_data = merged_data[ source_df_other_columns + [target_column] ]

    return merged_data


if __name__ == "__main__":
    # Load the data and set the first column as the index column
    data = pd.read_csv(
        "sample_data.csv", 
        index_col=0
    )

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

    print(data)
    print(final_data)