# df pivot

- [[df json]]

<code>
df = pd.DataFrame(data)
df.head()
</code>

^    ^ id    | brand        | brand\_id  | date        | property        | data              | count  |
| 0  | 5276  | 펜디         | 68        | 2021-03-15  | MENU\_MAX\_LEVEL  | {'max\_level': 3}  | 3      |
| 1  | 5286  | 발렌시아가   | 925       | 2021-03-15  | MENU\_MAX\_LEVEL  | {'max\_level': 3}  | 3      |
| 2  | 5294  | 지컷         | 19672     | 2021-03-15  | MENU\_MAX\_LEVEL  | {'max\_level': 3}  | 3      |
| 3  | 5278  | 랑방 컬렉션  | 19735     | 2021-03-15  | MENU\_MAX\_LEVEL  | {'max\_level': 3}  | 3      |
| 4  | 5285  | 모조에스핀   | 826       | 2021-03-15  | MENU\_MAX\_LEVEL  | {'max\_level': 3}  | 3      |


<code>
pv = df.pivot(index="brand", columns="property", values="count")
</code>

^ property  ^ DUPLICATED\_IMAGE  | DUPLICATED\_LINK  | MENU_MAX\_LEVEL  | NEW\_PRODUCT\_COUNT  | PRICE\_DOWN\_PRODUCT\_COUNT  | TOTAL\_PRODUCT\_COUNT  |
| brand     |                   |                  |                 |                    |                           |                      |
| 골든구스  | NaN               | 1.0              | 3.0             | 0.0                | 0.0                       | 1048.0               |
| 구찌      | 46.0              | 0.0              | 3.0             | 0.0                | 0.0                       | 2133.0               |
| 구호      | NaN               | 0.0              | 4.0             | 0.0                | 0.0                       | 1512.0               |
| 까르띠에  | 88.0              | 0.0              | 2.0             | 0.0                | 0.0                       | 1440.0               |
| 듀엘      | NaN               | 0.0              | 3.0             | 0.0                | 0.0                       | 775.0                |