Join two columns in Pandas, even both of them are null

Question

I have dataset with routing list:

| order | point | city | boxes | pallets |
|--| -- | -- | -- | -- |
| o12345 | 1 | X |b0|p0,p1|
|o12345|2|Y|-|p2,p3,p4|
|o12345|3|Z|b1|-|
|o34567|1|Q|-|-|
|o34567|2|W|b2,b3|p5,p6|
|o34567|3|E|-|p7|
|o34567|4|R|b4,b5|p8,p9,p10|

How to join the columns "boxes" and "pallets" to get "cargo" with list both of boxes and pallets inside and the to explode this column to get each value in separate row

import pandas as pd
df=pd.read_excel('example.xlsx')
df['cargo'] = df['pallets']+','+ df['boxes']
print(df)

But not works with null values:(

Firstly expect to get:

And then to explode only for cargo:

Asked By: bluekit46

||

Source

Answer 1

Here is an approach using df.explode()

df['cargo'] = (df[['boxes', 'pallets']]
                .apply(lambda x: ','.join([i for i in x if i]), axis=1))
df = df.drop(['boxes', 'pallets'], axis=1)
print(df)

    order  point city            cargo
0  o12345      1    X         b0,p0,p1
1  o12345      2    Y         p2,p3,p4
2  o12345      3    Z               b1
3  o34567      1    Q                 
4  o34567      2    W      b2,b3,p5,p6
5  o34567      3    E               p7
6  o34567      4    R  b4,b5,p8,p9,p10


df['cargo'] = df['cargo'].str.split(',')
df = (df.explode('cargo').sort_values(by=['order', 'point']))
print(df)

    order  point city cargo
0  o12345      1    X    b0
0  o12345      1    X    p0
0  o12345      1    X    p1
1  o12345      2    Y    p2
1  o12345      2    Y    p3
1  o12345      2    Y    p4
2  o12345      3    Z    b1
3  o34567      1    Q      
4  o34567      2    W    b2
4  o34567      2    W    b3
4  o34567      2    W    p5
4  o34567      2    W    p6
5  o34567      3    E    p7
6  o34567      4    R    b4
6  o34567      4    R    b5
6  o34567      4    R    p8
6  o34567      4    R    p9
6  o34567      4    R   p10

Answered By: Jamiu S.

Join two columns in Pandas, even both of them are null

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