I want to transform the below example dataframe, which could be described as Col1 having duplicated values, with relevant values in other columns. Then I want to flatten out as Col1 only has distinct values remain, then the other relevant value will be mapped into other extended columns.
Current DataFrame:
| Col1 | Col2 | Col3 | Col4 |
|---|---|---|---|
| A | 12 | dafd | 104rd |
| A | 100 | dafa | 134fdd |
| A | 45 | adrrqq | 1345h |
| B | 85 | adf | 3145gfr |
| C | 101 | dafv | 134daf |
| C | 118 | aerqeq | 314dflk |
| D | 1344 | dafad | 098daf |
| E | 151 | dava | 214dfafd |
| E | 167 | qewrrq | 0897fdaf |
Transform to:
| Col1 | Col2_1 | Col2_2 | Col2_3 | Col3_1 | Col3_2 | Col3_3 | Col4_1 | Col4_2 | Col4_3 |
|---|---|---|---|---|---|---|---|---|---|
| A | 12 | 100 | 45 | dafd | dafa | adrrqq | 104rd | 134fdd | 1345h |
| B | 85 | adf | 3145gfr | ||||||
| C | 101 | 118 | dafv | aerqeq | 134daf | 314dflk | |||
| D | 1344 | dafad | 098daf | ||||||
| E | 151 | 167 | dava | qewrrq | 214dfafd | 0897fdaf |
I have tried it in python and pandas, and googling but it seems difficult when it led to other results.
