I have a database where I query for this kind of result with panda read_sql (millions results by query), Id is linked to an other table .
| ID | Date | Value |
|---|---|---|
| 369 | 2021-06-15 13:06:54 | 0.33 |
| 370 | 2021-06-15 13:06:54 | 0.02 |
| 377 | 2021-06-15 13:06:54 | 0.30 |
| 378 | 2021-06-15 13:06:54 | 0.36 |
| 390 | 2021-06-15 13:06:54 | 535.27 |
| 391 | 2021-06-15 13:06:54 | 35.55 |
| 264 | 2021-06-15 13:06:55 | 3.29 |
| 265 | 2021-06-15 13:06:55 | 5.70 |
| 266 | 2021-06-15 13:06:55 | 6.37 |
| 267 | 2021-06-15 13:06:55 | 23.36 |
| 268 | 2021-06-15 13:06:55 | 25.44 |
| 269 | 2021-06-15 13:06:55 | 23.80 |
| 270 | 2021-06-15 13:06:55 | 26.86 |
| 271 | 2021-06-15 13:06:55 | 22.54 |
| 272 | 2021-06-15 13:06:55 | 25.24 |
Is there a way to create a column by Id with the Date as unique Index in a pandas dataframe with value = None if there is no entry for this date like :
| Date | 369 | 370 | 377 | ... | 272 |
|---|---|---|---|---|---|
| 2021-06-15 13:06:54 | 0.33 | 0.02 | 0.30 | ... | None |
| 2021-06-15 13:06:55 | None | None | None | ... | 25.24 |
CodePudding user response：
Use pivot_table:
df.pivot_table('Value', 'Date', 'ID')