split_row_pandas.py

df = pd.DataFrame({
        "col_1": ["Movie1", "Movie2", "Movie3"],
        "films": ["film1, film1.1", "film2", "film3"],
        "books": ["book1, book1.1", "book2", "book3, book3.1"]
    })

def split_values(row, row_accumulator):
    """
    Split the rows into multiple Rows based on Books array.
    Extends Films by repeating the last value to the length of Books list.
    Based on SO Post - http://stackoverflow.com/questions/12680754/split-pandas-dataframe-string-entry-to-separate-rows
    """
    books = row["books"].split(",")
    films = row["films"].split(",")
    if len(films) < len(books):
        # Extend films by copying the last value
        films.extend([films[-1] for idx in range(len(books) - len(films))])
    for book, film in zip(books[::-1], films[::-1]):  # Traverse in Reverse
        new_row = row.to_dict()
        new_row["books"] = book
        new_row["films"] = film
        row_accumulator.append(new_row) 

new_rows = []
df.apply(split_values, axis="columns", args=(new_rows,))
new_df = pd.DataFrame(new_rows)
new_df