使用 Pandas 从另一个数据帧中删除一个数据帧

2022-01-25 00:00:00 python pandas dataframe compare difference

问题描述

我有两个不同大小的数据框(df1 nad df2).我想从 df1 中删除所有存储在 df2 中的行.

I have two dataframes of different size (df1 nad df2). I would like to remove from df1 all the rows which are stored within df2.

所以如果我有 df2 等于:

So if I have df2 equals to:

     A  B
0  wer  6
1  tyu  7

而df1等于:

     A  B  C
0  qwe  5  a
1  wer  6  s
2  wer  6  d
3  rty  9  f
4  tyu  7  g
5  tyu  7  h
6  tyu  7  j
7  iop  1  k

最终的结果应该是这样的:

The final result should be like so:

     A  B  C
0  qwe  5  a
1  rty  9  f
2  iop  1  k

我能够通过使用 for 循环来实现我的目标，但我想知道是否有更好、更优雅、更高效的方式来执行此类操作.

I was able to achieve my goal by using a for loop but I would like to know if there is a better and more elegant and efficient way to perform such operation.

这是我编写的代码，以备您需要时使用:将熊猫导入为 pd

Here is the code I wrote in case you need it: import pandas as pd

df1 = pd.DataFrame({'A' : ['qwe', 'wer', 'wer', 'rty', 'tyu', 'tyu', 'tyu', 'iop'],
                    'B' : [    5,     6,     6,     9,     7,     7,     7,     1],
                    'C' : ['a'  ,   's',   'd',   'f',   'g',   'h',   'j',   'k']})

df2 = pd.DataFrame({'A' : ['wer', 'tyu'],
                    'B' : [    6,     7]})

for i, row in df2.iterrows():
    df1 = df1[(df1['A']!=row['A']) & (df1['B']!=row['B'])].reset_index(drop=True)

解决方案

使用merge 使用 query，最后通过 drop:

df = pd.merge(df1, df2, on=['A','B'], how='outer', indicator=True)
       .query("_merge != 'both'")
       .drop('_merge', axis=1)
       .reset_index(drop=True)
print (df)
     A  B  C
0  qwe  5  a
1  rty  9  f
2  iop  1  k

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