Question

我有：

$ cat file1.csv (tab delimited)
R923E06 273911 2990492 2970203 F Resistant 
R923F06 273910 2990492 2970203 F Resistant 
R923H02 273894 2970600 2990171 M Resistant

和：

$ cat file2.txt (space delimited and it's a large file)
R923E06 CC GG TT AA ...
R923F06 GG TT AA CC ...
R923H02 TT GG CC AA ...

如何将file2.txt中的第一列替换为file1.csv中的6列？

Answer 1

使用join，您可以这样做：

join   <(sed -e 's/\t/ /g' file1.csv) <(cat file2.txt)

sed将制表符更改为空格

join到公共字段中两个文件的连接行。

输出：

R923E06 273911 2990492 2970203 F Resistant  CC GG TT AA ...
R923F06 273910 2990492 2970203 F Resistant  GG TT AA CC ...
R923H02 273894 2970600 2990171 M Resistant TT GG CC AA ...

Answer 2

看看这个AWK示例：

awk 'FNR == NR { d[$1] = $0; next } { $1 = d[$1] } 1' file1.csv file2.txt

在这里，我将file2.txt中的第一列替换为file1.csv的相应行（6列）。

输出：

R923E06 273911 2990492 2970203 F Resistant  CC GG TT AA ...
R923F06 273910 2990492 2970203 F Resistant  GG TT AA CC ...
R923H02 273894 2970600 2990171 M Resistant  TT GG CC AA ...

如果要在结果中用制表符分隔所有内容，则可以添加gsub(/[[:space:]]/,"\t")以用制表符替换任何空格或制表符：

awk 'FNR == NR { d[$1] = $0; next } { $1 = d[$1]; gsub(/[[:space:]]/,"\t") } 1' file1.csv file2.txt

Answer 3

#import pandas
import pandas as pd

#read file1.csv
#set index_col as false if file has delimiters at the end
file1 = pd.read_csv( 'file1.csv', ' ', index_col = False, names = 
['1','2','3','4','5','6']);

#read file2.txt, read_csv can read txt files as well
#set index_col as false if file has delimiters at the end
file2 = pd.read_csv( 'file2.csv', ' ', index_col = False, names = 
['1','2','3','4','5']);

#drop first column
file2.drop( '1', axis = 1, inplace = True )

#concat both frames
final = pd.concat([file1, file2], axis = 1)
#you might end up with mixed column names you can change it by using 
final.columns = ['col1', 'col2', ....]


#save as csv
final.to_csv('out.csv',sep='\t')

如何将多列从一个文本文件替换为另一文本文件中的列？

3 个答案: