我有兩個數(shù)據(jù)框df1： col2 col3 deptdate 2020-05-06 29 21 A2020-05-07 56 12 B2020-05-08 82 15 C2020-05-09 13 9 D2020-05-10 35 13 E2020-05-11 53 87 F2020-05-12 25 9 G2020-05-13 23 63 Hdf2: col2 deptdate 2020-05-06 64 A2020-05-07 41 B2020-05-08 95 C2020-05-09 58 D2020-05-10 89 E2020-05-11 37 F2020-05-12 24 G2020-05-13 67 H我想用列col2中df1的值更新列col2，df2所以我的輸出如下所示： col2 col3 deptdate 2020-05-06 64 21 A2020-05-07 41 12 B2020-05-08 95 15 C2020-05-09 58 9 D2020-05-10 89 13 E2020-05-11 37 87 F2020-05-12 24 9 G2020-05-13 67 63 H我寫了一些看起來像這樣的代碼：df1=df1.set_index('dept')df1.update(df2.set_index('dept'))df1=df1.reset_index()但是它將索引重置df1為整數(shù)而不是日期，因此我得到的輸出如下所示： dept col2 col30 A 64 211 B 41 122 C 95 153 D 58 94 E 89 135 F 37 876 G 24 97 H 67 63我的完整代碼如下：import pandas as pdimport numpy as npfrom datetime import datetime, timedeltaimport datetimedept=['A','B','C','D','E','F','G','H']date_today = datetime.date.today()days = pd.date_range(date_today, date_today + timedelta(7), freq='D')np.random.seed(seed=1111)data1 = np.random.randint(1, high=100, size=len(days))data2 = np.random.randint(1, high=100, size=len(days))df1 = pd.DataFrame({'date': days, 'dept':dept,'col2': data1, 'col3': data2})df1 = df1.set_index('date')print(df1)dept=['A','B','C','D','E','F','G','H']date_today = datetime.date.today()days = pd.date_range(date_today, date_today + timedelta(7), freq='D')np.random.seed(seed=1331)data3 = np.random.randint(1, high=100, size=len(days))df2 = pd.DataFrame({'date': days, 'dept':dept,'col2': data3})df2 = df2.set_index('date')如何更新df1并df2保持索引日期格式df1？
3 回答
心有法竹
TA貢獻1866條經(jīng)驗 獲得超5個贊
正如我對您的示例所了解的那樣，您df1從index 和 column的df2基礎(chǔ)上進行更新。您需要添加到索引并調(diào)用datedeptdeptupdate
df1 = df1.set_index('dept', append=True)
df1 = df1.update(df2.set_index('dept', append=True))
df1 = df1.reset_index('dept')
Out[35]:
dept col2 col3
date
2020-05-06 A 64 21
2020-05-07 B 41 12
2020-05-08 C 95 15
2020-05-09 D 58 9
2020-05-10 E 89 13
2020-05-11 F 37 87
2020-05-12 G 24 9
2020-05-13 H 67 63
猛跑小豬
TA貢獻1858條經(jīng)驗 獲得超8個贊
concat那時你可以使用groupby
df_out=pd.concat([df1,df2],sort=False).groupby(level=0).last()
Out[261]:
col2 col3 dept
date
2020-05-06 64 21.0 A
2020-05-07 41 12.0 B
2020-05-08 95 15.0 C
2020-05-09 58 9.0 D
2020-05-10 89 13.0 E
2020-05-11 37 87.0 F
2020-05-12 24 9.0 G
2020-05-13 67 63.0 H
一只甜甜圈
TA貢獻1836條經(jīng)驗 獲得超5個贊
您可以使用以下方法執(zhí)行此操作df.update：
In [2162]: df1['col2'].update(df2['col2'])
In [2163]: df1
Out[2163]:
col2 col3 dept
date
2020-05-06 64 21 A
2020-05-07 41 12 B
2020-05-08 95 15 C
2020-05-09 58 9 D
2020-05-10 89 13 E
2020-05-11 37 87 F
2020-05-12 24 9 G
2020-05-13 67 63 H
添加回答
舉報
0/150
提交
取消