如何从一个大 pandas 数据帧的行中减去另一行? [英] How to subtract rows of one pandas data frame from another?

问题描述

我要执行的操作类似于合并.例如，通过inner合并，我们得到一个数据帧，其中包含第一个AND第二个数据帧中存在的行.通过outer合并，我们得到一个数据帧，该数据帧出现在第二个数据帧的第一个或"中.

The operation that I want to do is similar to merger. For example, with the inner merger we get a data frame that contains rows that are present in the first AND second data frame. With the outer merger we get a data frame that are present EITHER in the first OR in the second data frame.

我需要的是一个数据帧，其中包含第一个数据帧中存在的行而第二个数据帧中不存在的行?有快速而优雅的方法吗?

What I need is a data frame that contains rows that are present in the first data frame AND NOT present in the second one? Is there a fast and elegant way to do it?

推荐答案

类似以下内容如何?

print df1

    Team  Year  foo
0   Hawks  2001    5
1   Hawks  2004    4
2    Nets  1987    3
3    Nets  1988    6
4    Nets  2001    8
5    Nets  2000   10
6    Heat  2004    6
7  Pacers  2003   12

print df2

    Team  Year  foo
0  Pacers  2003   12
1    Heat  2004    6
2    Nets  1988    6

只要有一个非关键的通用命名列，就可以让在sufffexes上执行的工作(如果没有非关键的通用列，则可以创建一个临时使用的列... df1['common'] = 1和df2['common'] = 1):

As long as there is a non-key commonly named column, you can let the added on sufffexes do the work (if there is no non-key common column then you could create one to use temporarily ... df1['common'] = 1 and df2['common'] = 1):

new = df1.merge(df2,on=['Team','Year'],how='left')
print new[new.foo_y.isnull()]

     Team  Year  foo_x  foo_y
0  Hawks  2001      5    NaN
1  Hawks  2004      4    NaN
2   Nets  1987      3    NaN
4   Nets  2001      8    NaN
5   Nets  2000     10    NaN

或者您可以使用isin，但是您必须创建一个密钥:

Or you can use isin but you would have to create a single key:

df1['key'] = df1['Team'] + df1['Year'].astype(str)
df2['key'] = df1['Team'] + df2['Year'].astype(str)
print df1[~df1.key.isin(df2.key)]

     Team  Year  foo         key
0   Hawks  2001    5   Hawks2001
2    Nets  1987    3    Nets1987
4    Nets  2001    8    Nets2001
5    Nets  2000   10    Nets2000
6    Heat  2004    6    Heat2004
7  Pacers  2003   12  Pacers2003

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