python – 合并两个数据帧而不重复pandas
作者:互联网
我正在尝试合并两个数据框,一个包含列:customerId,全名和电子邮件,另一个数据框包含列:customerId,amount和date.我想让第一个数据帧成为主数据帧,并包含其他数据帧信息,但仅限于customerIds匹配时;我试过做:
merge = pd.merge(df, df2, on='customerId', how='left')
但是生成的数据框包含大量重复并且看起来不对:
customerId full name emails amount date
0 002963338 Star shine star.shine@cdw.com $2,910.94 2016-06-14
1 002963338 Star shine star.shine@cdw.com $9,067.70 2016-05-27
2 002963338 Star shine star.shine@cdw.com $6,507.24 2016-04-12
3 002963338 Star shine star.shine@cdw.com $1,457.99 2016-02-24
4 986423367 palm tree tree.palm@snapchat.com,tree@.com $4,604.83 2016-07-16
这不行,请帮忙!
解决方法:
在customerId列中存在重复的问题.
因此解决方案是删除它们,例如到drop_duplicates
:
df2 = df2.drop_duplicates('customerId')
样品:
df = pd.DataFrame({'customerId':[1,2,1,1,2], 'full name':list('abcde')})
print (df)
customerId full name
0 1 a
1 2 b
2 1 c
3 1 d
4 2 e
df2 = pd.DataFrame({'customerId':[1,2,1,2,1,1], 'full name':list('ABCDEF')})
print (df2)
customerId full name
0 1 A
1 2 B
2 1 C
3 2 D
4 1 E
5 1 F
merge = pd.merge(df, df2, on='customerId', how='left')
print (merge)
customerId full name_x full name_y
0 1 a A
1 1 a C
2 1 a E
3 1 a F
4 2 b B
5 2 b D
6 1 c A
7 1 c C
8 1 c E
9 1 c F
10 1 d A
11 1 d C
12 1 d E
13 1 d F
14 2 e B
15 2 e D
df2 = df2.drop_duplicates('customerId')
merge = pd.merge(df, df2, on='customerId', how='left')
print (merge)
customerId full name_x full name_y
0 1 a A
1 2 b B
2 1 c A
3 1 d A
4 2 e B
标签:python,pandas,ipython,ipython-notebook,merge 来源: https://codeday.me/bug/20191002/1845206.html