Python：如何解析文件并查找每列缺少的数据？

我会尽力解释我的问题：

我正在编写一个python脚本，我在某个点上进行了堆叠。我有以下表格/矩阵：

Data xx_a_xx xx_a_xx xx_b_xx xx_b_xx xx_rd_xx xx_rd_xx xx_c_xx xx_c_xx
Data xx_a_xx xx_a_xx xx_b_xx xx_b_xx xx_rd_xx xx_rd_xx xx_c_xx xx_c_xx
Data xx_a_xx xx_a_xx xx_b_xx xx_rd_xx xx_rd_xx xx_c_xx xx_c_xx
Data xx_a_xx xx_a_xx xx_b_xx xx_b_xx xx_rd_xx xx_rd_xx xx_c_xx xx_c_xx
Data xx_a_xx xx_a_xx xx_b_xx xx_b_xx xx_rd_xx xx_c_xx xx_c_xx

数据遵循以下模式；“x”是一个变化的数字，但每个列中的字母顺序相同且成对不变。我想做的是在缺少数据的地方引入一个函数，得到以下输出：

Data xx_a_xx xx_a_xx xx_b_xx xx_b_xx xx_rd_xx xx_rd_xx xx_c_xx xx_c_xx
Data xx_a_xx xx_a_xx xx_b_xx xx_b_xx xx_rd_xx xx_rd_xx xx_c_xx xx_c_xx
Data xx_a_xx xx_a_xx **<NA>**    xx_b_xx xx_rd_xx xx_rd_xx xx_c_xx xx_c_xx
Data xx_a_xx xx_a_xx xx_b_xx xx_b_xx xx_rd_xx xx_rd_xx xx_c_xx xx_c_xx
Data xx_a_xx xx_a_xx xx_b_xx xx_b_xx **<NA>**     xx_rd_xx xx_c_xx xx_c_xx

数据xx_a_xx_a_xx_b_xx_b_xx_xx_rd_xx_xx_c_xx
数据xx_a_xx_a_xx_b_xx_b_xx_rd_xx_rd_xx_c_xx_c_xx_xx
数据xx_a_xx_a_xx****xx_b_xx_rd_xx_rd_xx_c_xx_xx_c_xx
数据xx_a_xx_a_xx_b_xx_b_xx_rd_xx_rd_xx_c_xx_c_xx_xx
数据xx_a_xx_a_xx_b_xx_b_xx****xx_rd_xx_c_xx_c_xx

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有什么建议吗？谢谢

您将首先

按空格字符拆分

行字符串； 然后你会扔掉“数据”这个词

然后，您可以将“xx_a_xx”类型的字符串转换为元组，比如您编写了一个函数

string_to_key

，该函数将“99_a_72”映射为“a”；将该函数映射到列表

之后，您只需检查事情是否按正确的顺序排列，如果不按正确的顺序排列，则填充N/A值

....
def string_to_key(string):
    return string.split("_")[1] #will produce an exception on malformed lines!
....
reference = ("a","a","b","b","rd","rd","c","c")

for row in rows: #assuming rows is the result of reading all lines
    items = row.split(" ")[1:] #throwing away "Data"
    keys = [string_to_key(string) for string in items]
    result = []
    for num, ref_key in enumerate(reference):
         if keys[num] == ref_key:
              result.append(items[num])
         else:
              result.append("**NA**")
              keys.insert("")
    print "Data "+" ".join(result)

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我认为我的回答很简洁，问题也没问题，所以请@jornsharpe和其他持有者重新考虑这个问题。