Pandas - groupby 索引作为列

Question

使用这些数据

    DATETIME_ADDED  ACTION_ID   USECASE_WIDGET_ID   QUERY_ORDER_BY  BROWSER_IP  REQUEST_IP  QUERY_RAW_PHRASE    LOG_TIME    ITEM_COUNT
0   2020-02-06 13:15:02 /search katalog/lista_produktow 1000011 x.x.x.x x.x.x.x kabel   533 67908
1   2020-02-06 13:00:02 /search katalog/lista_produktow 1000011 x.x.x.x x.x.x.x kabel   521 67908
2   2020-02-06 12:45:02 /search katalog/lista_produktow 1000011 x.x.x.x x.x.x.x kabel   488 67908
3   2020-02-06 12:30:02 /search katalog/lista_produktow 1000011 x.x.x.x x.x.x.x kabel   506 67908
4   2020-02-06 12:15:02 /search katalog/lista_produktow 1000011 x.x.x.x x.x.x.x kabel   499 67907
... ... ... ... ... ... ... ... ... ...
5552    2019-12-10 17:14:02 /search katalog/lista_produktow 1000011 x.x.x.x x.x.x.x kabel   470 66935
5553    2019-12-10 17:08:02 /search katalog/lista_produktow 1000011 x.x.x.x x.x.x.x kabel   493 66935
5554    2019-12-10 17:01:55 /search katalog/lista_produktow 1000011 x.x.x.x x.x.x.x kabel   443 66935
5555    2019-12-10 16:58:15 /search katalog/lista_produktow 1000011 x.x.x.x x.x.x.x kabel   465 66935
5556    2019-12-10 16:56:45 /search katalog/lista_produktow 1000011 x.x.x.x x.x.x.x kabel   423 66935

从 csv 文件导入我已经创建了这个。

df = pd.read_csv("/mnt/c/_KOD_/github/jupyter/Czasy_wyszukiwarki.csv", delimiter=";", encoding="UTF-8")
raw_data = pd.read_csv("/mnt/c/_KOD_/github/jupyter/Czasy_wyszukiwarki.csv", delimiter=";", encoding="UTF-8")
df = df.drop(columns=['ACTION_ID','USECASE_WIDGET_ID','QUERY_ORDER_BY','BROWSER_IP','REQUEST_IP','QUERY_RAW_PHRASE'])
new = df["DATETIME_ADDED"].str.split(' ',n=1, expand=True)
df['DATE']= new[0]
df['TIME']= new[1]
df2 = df.drop(columns=['DATETIME_ADDED'])
df3 = df2.groupby(['DATE']).agg(
        min_logtime=('LOG_TIME',min),
        max_logtime=('LOG_TIME',max),
        mean_logtime=('LOG_TIME',"mean")        
    )
fig = px.line(df3, x="DATE", y='min_logtime', title='Search time')
fig.show()

df3 中的数据如下所示

    min_logtime max_logtime mean_logtime
DATE            
2019-12-10  406 493 453.419355
2019-12-11  392 547 463.265306
2019-12-12  411 570 468.583333

现在我遇到了如何将索引数据转换为普通列的问题，以便我可以将其用作 X 轴。

Answer 1

@Zaraki Kenpachi 提供的答案解决了我的问题

df3.reset_index()