Explode multiple list columns with not same value length

I’m trying to explode dataframe that have multiple columns as list and list of length is different. Below is my dataframe:

import pandas as pd
import numpy as np
df = pd.DataFrame({'Name': ['Name1','Name2'], 
                    'Time': [[0.0, 5.0, 10.0, 15.0],[0.0, 4.0, 28.0, 48.0]],
                    'Values': [[0.0, 5.0, 10.0],[0.0, 4.0, 48.0]]})

df

    Name    Time    Values
0   Name1   [0.0, 5.0, 10.0, 15.0]  [0.0, 5.0, 10.0]
1   Name2   [0.0, 4.0, 28.0, 48.0]  [0.0, 4.0, 48.0]

I tried with df2 = df.explode(['Time','Values']) but it raised error that said ValueError: columns must have matching element counts.

Below is my expected Output:

df2 = pd.DataFrame({'Name': ['Name1','Name1','Name1','Name1','Name2','Name2' ,'Name2' ,'Name2'], 
                    'Time': [0.0, 5.0, 10.0, 15.0,0.0, 5.0, 10.0, np.nan],
                    'Values': [0.0, 4.0, 28.0, 48.0, 0.0, 4.0, 48.0, np.nan]})

df2

Name    Time    Values
0   Name1   0.0 0.0
1   Name1   5.0 4.0
2   Name1   10.0    28.0
3   Name1   15.0    48.0
4   Name2   0.0 0.0
5   Name2   5.0 4.0
6   Name2   10.0    48.0
7   Name2   NaN NaN

Thank and best regards

>Solution :

Here is trick with GroupBy.cumcount for create unique MultiIndex for exploded values:

cols = ['Time','Values']

df1 = pd.concat([df[x].explode().to_frame()
                      .assign(g=lambda x: x.groupby(level=0).cumcount())
                      .set_index('g', append=True) 
                for x in cols], axis=1)

df = df.drop(cols, axis=1).join(df1.droplevel(1))
print (df)
    Name  Time Values
0  Name1   0.0    0.0
0  Name1   5.0    5.0
0  Name1  10.0   10.0
0  Name1  15.0    NaN
1  Name2   0.0    0.0
1  Name2   4.0    4.0
1  Name2  28.0   48.0
1  Name2  48.0    NaN