迭代csv / xlsx文件python 3中的行和列
我是Stack Overflow的新手，有一个我无法解决的问题。 我有一个CSV文件或Excel（基本上是一个表），并希望在Python 3中执行以下操作：
Column Header,"r269_d","r295_A","r295_R","r299_A","r325_D","r326_A" id1,"0.0","2.29","0.0","1.3","0.0","188.4" id2,"0.0","1.0","0.0","0.6","0.0","0.0" 对于这个CSV文件，我想：
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进入第一行（id1）
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检查第1栏（r269_d）
2.1如果col1 = 0的值将0写入新的result_string
2.2如果col1！= 0的值将1写入新的result_string
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检查第2栏（r295_A）
3.1如果col2 = 0的值如2.1所述将0写入相同的result_string
3.2如果col2！= 0的值如2.1所述，将1写入相同的result_string
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为所有专栏做这个
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转到下一行，并执行相同的操作。
最后我想看到这样的东西：
Column Header,"r269_d","r295_A","r295_R","r299_A","r325_D","r326_A", "result_string" id1,"0.0","2.29","0.0","1.3","0.0","188.4","010101" id2,"0.0","1.0","0.0","0.6","0.0","0.0","010100"
pandas解决scheme：
import pandas as pd import numpy as np df = pd.read_csv(r'/path/to/file.csv') df['result_string'] = (df.filter(regex='r\d+') .ne(0).astype(np.int8).astype(str) .apply(''.join, axis=1)) df.to_csv(r'/path/to/result.csv', index=False)
来源CSV文件：
col,r269_d,r295_A,r295_R,r299_A,r325_D,r326_A id1,0.0,2.29,0.0,1.3,0.0,188.4 id2,0.0,1.0,0.0,0.6,0.0,0.0
parsingDF：
In [169]: df Out[169]: col r269_d r295_A r295_R r299_A r325_D r326_A 0 id1 0.0 2.29 0.0 1.3 0.0 188.4 1 id2 0.0 1.00 0.0 0.6 0.0 0.0
结果：
In [170]: df['result_string'] = (df.filter(regex='r\d+') ...: .ne(0).astype(np.int8).astype(str) ...: .apply(''.join, axis=1)) ...: In [171]: df Out[171]: col r269_d r295_A r295_R r299_A r325_D r326_A result_string 0 id1 0.0 2.29 0.0 1.3 0.0 188.4 010101 1 id2 0.0 1.00 0.0 0.6 0.0 0.0 010100 In [172]: df.to_csv(r'c:/temp/result.csv', index=False)
结果CSV：
col,r269_d,r295_A,r295_R,r299_A,r325_D,r326_A,result_string id1,0.0,2.29,0.0,1.3,0.0,188.4,010101 id2,0.0,1.0,0.0,0.6,0.0,0.0,010100