python - Pandas 数据框唯一值

Question

需要一些帮助来从 pandas dataframe 中获取唯一值

我有:

    >>> df1
     source    target metric
0  acc1.yyy  acx1.xxx  10000
1  acx1.xxx  acc1.yyy  10000

目标是删除基于源+目标或目标+源的唯一值。但我不能用 drop_duplicates 得到这个。

>>> df2 = df1.drop_duplicates(subset=['source','target'])
>>> df2
     source    target metric
0  acc1.yyy  acx1.xxx  10000
1  acx1.xxx  acc1.yyy  10000

[更新]

也许重复在这里不是正确的词所以让我进一步解释

id  source  target
0   bng1.xxx.00 bdr2.xxx.00
1   bng1.xxx.00 bdr1.xxx.00
2   bdr3.yyy.00 bdr3.xxx.00
3   bdr3.xxx.00 bdr3.yyy.00
4   bdr2.xxx.00 bng1.xxx.00
5   bdr1.xxx.00 bng1.xxx.00

在上面，我想删除具有例如 source=target 和 target=source 的条目。

0 and 4 = same pair
1 and 5 = same pair
2 and 3 = same pair

end goal will be to keep 0 1 2 or 4 5 3 .

Answer 1

您需要先对两列进行排序:

df1[['source','target']] = df1[['source','target']].apply(sorted,axis=1)
print (df1)
     source    target  metric
0  acc1.yyy  acx1.xxx   10000
1  acc1.yyy  acx1.xxx   10000

df2 = df1.drop_duplicates(subset=['source','target'])
print (df2)
     source    target  metric
0  acc1.yyy  acx1.xxx   10000

编辑:

source 列似乎需要更改 - 删除最后 3 个字符:

df1['source1'] = df1.source.str[:-3]
df1[['source1','target']] = df1[['source1','target']].apply(sorted,axis=1)
print (df1)
   id          source       target      source1
0   0  bng1.xxx.00-00  bng1.xxx.00  bdr2.xxx.00
1   1  bng1.xxx.00-00  bng1.xxx.00  bdr1.xxx.00
2   2  bdr3.yyy.00-00  bdr3.yyy.00  bdr3.xxx.00
3   3  bdr3.xxx.00-00  bdr3.yyy.00  bdr3.xxx.00
4   4  bdr2.xxx.00-00  bng1.xxx.00  bdr2.xxx.00
5   5  bdr1.xxx.00-00  bng1.xxx.00  bdr1.xxx.00

df2 = df1.drop_duplicates(subset=['source1','target'])
df2 = df2.drop('source1', axis=1)
print (df2)
   id          source       target
0   0  bng1.xxx.00-00  bng1.xxx.00
1   1  bng1.xxx.00-00  bng1.xxx.00
2   2  bdr3.yyy.00-00  bdr3.yyy.00