如何在右侧数据框中获取不在左侧数据框中的数据 [英] How to get data in the right dataframe that isn't in the left dataframe

问题描述

我有两个数据帧，我试图输出其中一个而不是另一个的数据.

I have two data frames and I am trying to output the data that is in one but not the other.

我可以使用第一个数据帧获取数据，而不能使用第二个数据帧

I can get the data in the first dataframe but not the second using

only_new = old.merge(
new, 'outer', on=['Employee ID', 'Benefit Plan Type'],
suffixes=['','_'], indicator=True
).query('_merge == "left_only"').reindex_axis(old.columns, axis=1)

这就是我用来获取仅在第二个数据帧中的数据的东西

Here is what I'm using to get the data that's only in my second dataframe

only_new =new.merge(
old, 'outer', on=['Employee ID', 'Benefit Plan Type'],
suffixes=['','_'], indicator=True
).query('_merge == "left only"').reindex_axis(new.columns, axis=1)

但是它不返回任何数据，但是使用Excel我可以看到应该有几行.

But it doesn't return any data, but using Excel I can see that there should be a couple of rows.

看来这应该可行

only_new = old.merge(new, on='Employee ID', indicator=True, how='outer',
       only_new[only_new['_merge'] == 'right_only'])

但是我明白了

SyntaxError: non-keyword arg after keyword arg

推荐答案

考虑数据帧old和new

old = pd.DataFrame(dict(
        ID=[1, 2, 3, 4, 5],
        Type=list('AAABB'),
        Total=[9 for _ in range(5)],
        ArbitraryColumn=['blah' for _ in range(5)]
    ))

new = pd.DataFrame(dict(
        ID=[3, 4, 5, 6, 7],
        Type=list('ABBCC'),
        Total=[9 for _ in range(5)],
        ArbitraryColumn=['blah' for _ in range(5)]
    ))

然后采取对称相同的解决方案

Then to take the symmetrically identical solution

old.merge(
    new, 'outer', on=['ID', 'Type'],
    suffixes=['_', ''], indicator=True  # changed order of suffixes
).query('_merge == "right_only"').reindex_axis(new.columns, axis=1)
#                   \......../                 \./
#   changed from `left` to `right`      reindex with `new`

  ArbitraryColumn  ID  Total Type
5            blah   6    9.0    C
6            blah   7    9.0    C

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