Python 如何使用熊猫分割文本文件中的键、值？

我有这样的输入文本文件：

Input.txt-

1=88|2=1438|3=KKK|4=7.7|5=00|7=66|8=a
1=13|2=1388|3=DDD|4=157.73|6=00|7=08|8=b|9=k

index[0]
1     88
2     1438
3     kkk
4     7.7
5     00
6     
7     66
8     a
9    

index[1]
1     13
2     1438
3     DDD
4     157.73
5    
6     00
7     08
8     b
9     k

df = pd.read_csv(inputfile, index_col=None, names=['text'])

    #spliting two times with respect to (= & |) and saving into stack
    s = df.text.str.split('|', expand=True).stack().str.split('=', expand=True)

    #giving index's as empty string ('') i.e. for removing
    s.columns = ['idx','']

    #rename_axis(None) for excluding index values  
    dfs = [g.set_index('idx').rename_axis(None) for i, g in s.groupby(level=0)]

    #length for iterating through list
    dfs_length = len(dfs)


    #opening output file
    with open(outputfile + 'output.txt','w') as file_obj:
        i = 0
        while i < dfs_length:
            #index of each column
            s = '\nindex[%d]\n'%i
            #writing index to file
            file_obj.write(str(s))
            #print '\nindex[%d]'%i
            #print dfs[i]
            #wriring actual contents to file
            file_obj.write(str(dfs[i])+'\n')
            i = i + 1

index[0]
1     88
2     1438
3     kkk
4     7.7
5     00
7     66
8     a

index[1]
1     13
2     1438
3     DDD
4     157.73
6     00
7     08
8     b
9     k

我想拆分此键和值对，并以如下格式显示：

Output.txt-

1=88|2=1438|3=KKK|4=7.7|5=00|7=66|8=a
1=13|2=1388|3=DDD|4=157.73|6=00|7=08|8=b|9=k

index[0]
1     88
2     1438
3     kkk
4     7.7
5     00
6     
7     66
8     a
9    

index[1]
1     13
2     1438
3     DDD
4     157.73
5    
6     00
7     08
8     b
9     k

df = pd.read_csv(inputfile, index_col=None, names=['text'])

    #spliting two times with respect to (= & |) and saving into stack
    s = df.text.str.split('|', expand=True).stack().str.split('=', expand=True)

    #giving index's as empty string ('') i.e. for removing
    s.columns = ['idx','']

    #rename_axis(None) for excluding index values  
    dfs = [g.set_index('idx').rename_axis(None) for i, g in s.groupby(level=0)]

    #length for iterating through list
    dfs_length = len(dfs)


    #opening output file
    with open(outputfile + 'output.txt','w') as file_obj:
        i = 0
        while i < dfs_length:
            #index of each column
            s = '\nindex[%d]\n'%i
            #writing index to file
            file_obj.write(str(s))
            #print '\nindex[%d]'%i
            #print dfs[i]
            #wriring actual contents to file
            file_obj.write(str(dfs[i])+'\n')
            i = i + 1

index[0]
1     88
2     1438
3     kkk
4     7.7
5     00
7     66
8     a

index[1]
1     13
2     1438
3     DDD
4     157.73
6     00
7     08
8     b
9     k

参见索引[0]中的第6条和第9条记录的值为空，因为第6条在另一列中可用，但在本列中不可用。像索引[1]中这样，第5条记录是空白的

程序代码-

1=88|2=1438|3=KKK|4=7.7|5=00|7=66|8=a
1=13|2=1388|3=DDD|4=157.73|6=00|7=08|8=b|9=k

index[0]
1     88
2     1438
3     kkk
4     7.7
5     00
6     
7     66
8     a
9    

index[1]
1     13
2     1438
3     DDD
4     157.73
5    
6     00
7     08
8     b
9     k

df = pd.read_csv(inputfile, index_col=None, names=['text'])

    #spliting two times with respect to (= & |) and saving into stack
    s = df.text.str.split('|', expand=True).stack().str.split('=', expand=True)

    #giving index's as empty string ('') i.e. for removing
    s.columns = ['idx','']

    #rename_axis(None) for excluding index values  
    dfs = [g.set_index('idx').rename_axis(None) for i, g in s.groupby(level=0)]

    #length for iterating through list
    dfs_length = len(dfs)


    #opening output file
    with open(outputfile + 'output.txt','w') as file_obj:
        i = 0
        while i < dfs_length:
            #index of each column
            s = '\nindex[%d]\n'%i
            #writing index to file
            file_obj.write(str(s))
            #print '\nindex[%d]'%i
            #print dfs[i]
            #wriring actual contents to file
            file_obj.write(str(dfs[i])+'\n')
            i = i + 1

index[0]
1     88
2     1438
3     kkk
4     7.7
5     00
7     66
8     a

index[1]
1     13
2     1438
3     DDD
4     157.73
6     00
7     08
8     b
9     k

---

我只得到输入文本文件中可用的记录。如何将记录值保留为空白？

您可以使用

.str.extract（）

函数和生成的正则表达式来执行此操作：

pat = r'(?:1=)?(?P<a1>[^\|]*)?'

# you may want to adjust the right bound of the range interval
for i in range(2, 12):
    pat += r'(?:\|{0}=)?(?P<a{0}>[^\|]*)?'.format(i)

new = df.val.str.extract(pat, expand=True)

---

您可以将

.str.extract（）

函数与生成的正则表达式结合使用：

pat = r'(?:1=)?(?P<a1>[^\|]*)?'

# you may want to adjust the right bound of the range interval
for i in range(2, 12):
    pat += r'(?:\|{0}=)?(?P<a{0}>[^\|]*)?'.format(i)

new = df.val.str.extract(pat, expand=True)

---

看起来像是家庭作业。@Ernesten，不，不是。依我看，这是一个有趣的问题…@kitty，你有固定数量的属性吗（

1=…

，…，

9=…

）？@MaxU-不，这不是固定的。我必须保持空白或空白。看起来像是家庭作业。@ernesten，不，没有。依我看，这是一个有趣的问题…@kitty，你有固定数量的属性吗（

1=…

，…，

9=…

）？@MaxU-不，这不是固定的。我必须保持空白或保留它们。