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)
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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