如何将数据框列转换为二维数组？

Question

I've the below dataset:

Sample Dataset

My objective is to create a 2D array of the column 'Products' for this dataset.

Now, if I do the following code:

prodarr = Order_Details[['Product']].to_numpy()

It returns me the result as follows:

 [['PRODUCT_75'],
       ['PRODUCT_75'],
       ['PRODUCT_63'],
       ['PRODUCT_63'],
       ['PRODUCT_34,PRODUCT_86,PRODUCT_57,PRODUCT_89'],
       ['PRODUCT_34,PRODUCT_66,PRODUCT_58,PRODUCT_83'],
       ['PRODUCT_75'],
       ['PRODUCT_63,PRODUCT_90,PRODUCT_27,PRODUCT_5'],
       ['PRODUCT_26'],
       ['PRODUCT_63'],
       ['PRODUCT_63'],
       ['PRODUCT_5,PRODUCT_34'],
       ['PRODUCT_84,PRODUCT_27'],
       ['PRODUCT_27'], ...]

Now, this is an undesirable situation for me, as I wanted all the distinct products as different elements in a given row. What I mean is that the output should instead be like this:

[['PRODUCT_75'],['PRODUCT_63'],['PRODUCT_63'],['PRODUCT_34','PRODUCT_86','PRODUCT_57','PRODUCT_89'], ['PRODUCT_34','PRODUCT_66','PRODUCT_58','PRODUCT_83'], ['PRODUCT_75'], ['PRODUCT_63','PRODUCT_90','PRODUCT_27','PRODUCT_5'], ...]

This means that it is that on each row there are multiple columns of strings and not just one.

How should I approach this conundrum? Will have to segregate the strings based on commas and make use of df.iterrows ?

Answer 1

here is one way to do it

df = df['product'].str.split(',', expand=True)

    0   1   2   3
0   PRODUCT_75  None    None    None
1   PRODUCT_75  None    None    None
2   PRODUCT_63  None    None    None
3   PRODUCT_63  None    None    None
4   PRODUCT_34  PRODUCT_86  PRODUCT_57  PRODUCT_89
5   PRODUCT_34  PRODUCT_66  PRODUCT_58  PRODUCT_83
6   PRODUCT_75  None    None    None
7   PRODUCT_63  PRODUCT_90  PRODUCT_27  PRODUCT_5
8   PRODUCT_26  None    None    None
9   PRODUCT_63  None    None    None
10  PRODUCT_63  None    None    None
11  PRODUCT_5   PRODUCT_34  None    None
12  PRODUCT_84  PRODUCT_27  None    None
13  PRODUCT_27  None    None    None