python中实现指定列筛选数据——利用python的Pandas模块

 

001、

root@PC1:/home/test2# ls
outcome.map  test.map
root@PC1:/home/test2# cat outcome.map       ## 测试数据
1       snp1    0       55910
1       snp2    0       85204
1       snp3    0       122948
1       snp4    0       203750
1       snp5    0       312707
1       snp6    0       356863
1       snp7    0       400518
1       snp8    0       487423
1       snp9    0       578716
1       snp10   0       639876
root@PC1:/home/test2# cat test.map
snp6    7       107059
snp4    7       61125
snp9    7       173615
snp3    7       36884.4

 

002、

root@PC1:/home/test2# ls
outcome.map  test.map
root@PC1:/home/test2# python          ## 启动python shell
Python 3.7.0 (default, Jun 28 2018, 13:15:42)
[GCC 7.2.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import pandas as pd                    ## 导入panda模块
>>> outcome=pd.read_table('outcome.map', header = -1)     ## 读取数据
>>> test=pd.read_table('test.map', header = -1)
>>> outcome.head()
   0     1  2       3
0  1  snp1  0   55910
1  1  snp2  0   85204
2  1  snp3  0  122948
3  1  snp4  0  203750
4  1  snp5  0  312707
>>> test.head()
      0  1         2
0  snp6  7  107059.0
1  snp4  7   61125.0
2  snp9  7  173615.0
3  snp3  7   36884.4
>>> result=outcome[outcome[1].isin(test[0])]           ## 依据snp列筛选数据
>>> result.head()
   0     1  2       3
2  1  snp3  0  122948
3  1  snp4  0  203750
5  1  snp6  0  356863
8  1  snp9  0  578716
>>> result.to_csv('xxx.txt', sep='\t')                ## 写出数据
>>> quit()
root@PC1:/home/test2# ls
outcome.map  test.map  xxx.txt
root@PC1:/home/test2# cat xxx.txt                     ## 筛选结果
        0       1       2       3
2       1       snp3    0       122948
3       1       snp4    0       203750
5       1       snp6    0       356863
8       1       snp9    0       578716

 

参考：https://mp.weixin.qq.com/s?__biz=MzIxNzc1Mzk3NQ==&mid=2247492546&idx=1&sn=fe174e559474a95a7fb5b7e87b26af0a&chksm=97f653daa081dacce91c47786854cea073bcffeaa1b621f34e2d7aadebe84cfe266da63264df&mpshare=1&scene=23&srcid=0803H31kgVMVVI4fknb1DnRE&sharer_sharetime=1659470423020&sharer_shareid=50b75c6a886e09824b582fb782a7678b#rd