Grouping data by a particular column then splitting row value into different columns

Asked Jun 22 '20 at 08:55

Active Jun 22 '20 at 08:57

Viewed 15 times

#My input dataframe(df) looks like this:

+----------+--------------------------+
| order_id |  product_category_name   |
+----------+--------------------------+
| 47585339 | Beverages                |
| 47585339 | Snacks & Branded Foods   |
| 47585339 | Foodgrains, Oil & Masala |
| 31076491 | Baby Care                |
| 78258104 | Breakfast Cereals        |
| 78258104 | Snacks & Namkeen         |
| 78258104 | Pickles & Chutney        |
+----------+--------------------------+

Desired output Dataframe:

|  order_id   |     0                    |         1             |          2 
|             |                          |                       |
| 47585339    | Beverages                |Snacks & Branded Foods |Foodgrains, Oil & Masala
| 31076491    | Baby Care                |nan                    | nan
| 78258104    | Breakfast Cereals        |Snacks & Namkeen       |Pickles & Chutney

#I tried this by doing Group by:

groups = df.groupby('order_id')
df_result= pd.DataFrame(groups['product_category_name'])

#But the output is not coming in the desired manner. Any approach is acceptable even apart from using group by.

edited Jun 22 '20 at 08:57

asked Jun 22 '20 at 08:55

Karan_009

1

check question no 10 – jezrael Jun 22 '20 at 08:57
Question 10 is a good solution but to achieve that I desire I have to transpose the results obtained from question 10. Please open my question as it will be helpful for other beginners also. – Karan_009 Jun 22 '20 at 09:15
Can you add solution from No 10 and explain why not working? – jezrael Jun 22 '20 at 09:16
It's working with a slight modification of transposing the rows and columns. – Karan_009 Jun 22 '20 at 09:18
hmmm, can you edit question with this modification? – jezrael Jun 22 '20 at 09:19
I can, but it's better to have it in this form. If a beginner wants the results in this form it will be helpful. – Karan_009 Jun 22 '20 at 09:22
Not understand, I am curious about modifications. – jezrael Jun 22 '20 at 09:23
Modification is just interchanging the rows and columns in my desired output. – Karan_009 Jun 22 '20 at 09:28
But if pd.Dataframe.Transpose() is used then I will get above mentioned desired df. – Karan_009 Jun 22 '20 at 09:29
1

swap values in pivot for index and columns, then transpose is not necessary – jezrael Jun 22 '20 at 09:30

Grouping data by a particular column then splitting row value into different columns

0 Answers0