根据python中另一个标签文件中的条件从标签文件中删除行 [英] Remove lines from a tab file according to conditions in another tab file in python

问题描述

嘿，我有两个标签文件，例如: file1.txt

He llo I have two tab file such as : file1.txt

Clustername Seqname1 Seqname2
Cluster1 Seq1(+) SeqA
Cluster1 Seq2(-) SeqA
Cluster1 Seq3(+) SeqB
Cluster1 Seq300(+) SeqB
Cluster1 Seq90(+) SeqL
Cluster1 Seq90(+) SeqO
Cluster1 Seq2(-) SeqC
Cluster2 Seq8(-) SeqY
Cluster2 Seq8(-) SeqH
Cluster2 Seq8(-) SeqP
Cluster2 Seq79(-) SeqY
Cluster3 Seq10(+) SeqK
Cluster3 Seq10(+) SeqS
Cluster3 Seq10(+) SeqT
Cluster4 Seq300(+) SeqB

file2.txt

Clustername Names
Cluster1    SeqA
Cluster1    Seq1(+)
Cluster1    SeqC
Cluster1    Seq2(-)
Cluster1    SeqO
Cluster1    Seq3(+)
Cluster1    Seq90(+)
Cluster1    SeqB
Cluster1    SeqG
Cluster2    Seq8(-)
Cluster2    SeqY
Cluster2    SeqH
Cluster3    Seq10(+)
Cluster3    SeqK
Cluster4    SeqB
Cluster4    Seq300(+)

正如您在file2.txt中看到的

SeqL 在Cluster1中不存在，那么我想删除该行: Cluster1 Seq90(+) SeqL来自 file1.txt

as you can see in file2.txt SeqL is not present in the Cluster1, then I want to remove the line : Cluster1 Seq90(+) SeqL from the file1.txt

Seq300(+)在Cluster1中也不存在，然后我删除了该行:

Seq300(+) is not present either in Cluster1, then I remove the line:

Cluster1 Seq300(+) SeqB

来自 file1.txt

相同于:

Cluster2 Seq8(-) SeqP
Cluster2 Seq79(-) SeqY

在 file2.txt 中的CLuster2中也没有SeqP，在Cluster2中也没有Seq79(-)，然后我删除了以下行:

there is no SeqP in CLuster2 nor Seq79(-) in Cluster2 in file2.txt, then I remove lines:

Cluster2 Seq8(-) SeqP
Cluster2 Seq79(-) SeqY

来自 file1.txt

相同于:

Cluster3 Seq10(+) SeqS
Cluster3 Seq10(+) SeqT

因为SeqS和SeqT不在 file2.txt 的Cluster2中，所以我从 file1.txt 中删除了以下两行: /p>

because SeqS and SeqT are not in Cluster2 in file2.txt, then I remove the two following lines from the file1.txt:

 Cluster3 Seq10(+) SeqS
 Cluster3 Seq10(+) SeqT

最后我应该得到一个ex file1.txt，例如:

at the end I should get an ex file1.txt such as:

Clustername Seqname1 Seqname2
Cluster1 Seq1(+) SeqA
Cluster1 Seq2(-) SeqA
Cluster1 Seq3(+) SeqB
Cluster1 Seq90(+) SeqO
Cluster1 Seq2(-) SeqC
Cluster2 Seq8(-) SeqY
Cluster2 Seq8(-) SeqH
Cluster3 Seq10(+) SeqK
Cluster4 Seq300(+) SeqB

推荐答案

使用 DataFrame.reindex 以获得原始列:

Use DataFrame.merge + DataFrame.reindex to get the original columns:

new_df=( df1.merge(df2,left_on=['Clustername','Seqname1'],right_on=['Clustername','Names'])
            .merge(df2,left_on=['Clustername','Seqname2'],right_on=['Clustername','Names'])
            .reindex(columns=df1.columns))
print(new_df)

输出

  Clustername   Seqname1 Seqname2
0    Cluster1    Seq1(+)     SeqA
1    Cluster1    Seq2(-)     SeqA
2    Cluster1    Seq2(-)     SeqC
3    Cluster1    Seq3(+)     SeqB
4    Cluster1   Seq90(+)     SeqO
5    Cluster2    Seq8(-)     SeqY
6    Cluster2    Seq8(-)     SeqH
7    Cluster3   Seq10(+)     SeqK
8    Cluster4  Seq300(+)     SeqB

---

n个seqnames列的解决方案:

df1['aux']=df1.groupby('Clustername').cumcount()

new_df= ( df1.melt(['Clustername','aux'],var_name='Seq')
             .merge(df2,left_on=['Clustername','value'],right_on=['Clustername','Names'])
             .groupby(['Clustername','aux'])
             .filter(lambda x: x.value.size>=(len(df1.columns)-2))
             .pivot_table(index=['Clustername','aux'],columns='Seq',values='value',aggfunc=''.join)
             .reset_index()
             .drop('aux',axis=1)
             .rename_axis(columns=None) )

print(new_df)

输出

  Clustername   Seqname1 Seqname2
0    Cluster1    Seq1(+)     SeqA
1    Cluster1    Seq2(-)     SeqA
2    Cluster1    Seq3(+)     SeqB
3    Cluster1   Seq90(+)     SeqO
4    Cluster1    Seq2(-)     SeqC
5    Cluster2    Seq8(-)     SeqY
6    Cluster2    Seq8(-)     SeqH
7    Cluster3   Seq10(+)     SeqK
8    Cluster4  Seq300(+)     SeqB

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