Pandas columns of lists, create multiple columns by iterate (select) each list element of three columns as new columns and rows

Question

I have a dataframe of five columns where three of these columns contain lists of multiple values, which are ("Long", "Lat", Time_stamp"). Note that all ("Long", "Lat", Time_stamp") columns as object data-type. Rather than storing multiple values in a cell, I'd like to split these values of the three columns into new three columns with including each lists element, so that each item in these lists gets its own rows (with the same values in all other columns( index and car_id). So the output I am looking for is as follows :

index	car_id	Long	Lat	Time_stamp
0	8919	108.99553	34.27859	1539041301
0	8919	108.99552	34.27822	1539041304
0	8919	108.99552	34.27786	1539041307
0	8919	108.99552	34.27748	1539041310
1	19785	108.9665	34.20515	1539014039
1	19785	108.9665	34.20543	1539014042
1	19785	108.9665	34.20572	1539014046
1	19785	108.9665	34.20602	1539014049

And so on.....

Thank you for your help....

Answer 1

Assumption

The following code assumes only a fixed number of columns need to be normalized.

Implementation

import pandas as pd

df = pd.DataFrame({'car_id': [[1], [2]], 'longitudes': [[108.99553, 108.99552], [108.9665]], 'latitudes': [[34.27859, 34.27822, 34.27786], [34.20543, 34.20572]]})

print(df)

pd.DataFrame([car_id, longitude, latitude] for car_id, longitudes, latitudes in df.values for car_id in car_id for longitude in longitudes for latitude in latitudes)

Answer 2

If the values in a column are in a list you can use explode to distribute each of the values of the list into its own row.

please try

              df2.explode('Long').explode('Lat').explode('Time_stamp')