英文:
Transform dataframe Python
问题
| UUid | page XY opened | shopcart filled | purchase made |
|---|---|---|---|
| B32E7AA5B11A40AE | 121 | 92 | 23 |
| 2AEFB3AEA64140BE | 221 | 21 | 0 |
| A0DFAACDEB4D40C1 | 1345 | 1323 | 1321 |
英文:
I have data in one format (summing up events' occurrences by UUID, events in separate rows) but would need it in a different format (events' occurrences in separate columns for each event).
How to, by using Python, transform it from:
| UUid | Event | sum |
|---|---|---|
| B32E7AA5B11A40AE | page XY opened | 121 |
| B32E7AA5B11A40AE | shopcart filled | 92 |
| B32E7AA5B11A40AE | purchase made | 23 |
| 2AEFB3AEA64140BE | page XY opened | 221 |
| 2AEFB3AEA64140BE | shopcart filled | 21 |
| A0DFAACDEB4D40C1 | page XY opened | 1345 |
| A0DFAACDEB4D40C1 | shopcart filled | 1323 |
| A0DFAACDEB4D40C1 | purchase made | 1321 |
To this:
| UUid | page XY opened | shopcart filled | purchase made |
|---|---|---|---|
| B32E7AA5B11A40AE | 121 | 92 | 23 |
| 2AEFB3AEA64140BE | 221 | 23 | 0 |
| A0DFAACDEB4D40C1 | 1345 | 1323 | 1321 |
I don't know where to start.
答案1
得分: 2
尝试使用pivot()和fillna()：
df_pivot = df.pivot(index='UUid', columns='Event', values='sum').fillna(0)
df_pivot = df_pivot.reset_index()
df_pivot
输出：
| UUid | page XY opened | purchase made | shopcart filled | |
|---|---|---|---|---|
| 0 | 2AEFB3AEA64140BE | 221 | 0 | 21 |
| 1 | A0DFAACDEB4D40C1 | 1345 | 1321 | 1323 |
| 2 | B32E7AA5B11A40AE | 121 | 23 | 92 |
英文:
Try using pivot() and fillna()
df_pivot = df.pivot(index='UUid', columns='Event', values='sum').fillna(0)
df_pivot = df_pivot.reset_index()
df_pivot
Output:
| UUid | page XY opened | purchase made | shopcart filled | |
|---|---|---|---|---|
| 0 | 2AEFB3AEA64140BE | 221 | 0 | 21 |
| 1 | A0DFAACDEB4D40C1 | 1345 | 1321 | 1323 |
| 2 | B32E7AA5B11A40AE | 121 | 23 | 92 |
答案2
得分: 1
df = pd.pivot_table(df, values='sum', index='UUid', columns='Event', fill_value=0)
df = df.reset_index()
英文:
df = pd.pivot_table(df, values='sum', index='UUid', columns='Event', fill_value=0)
df = df.reset_index()
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