Question

我想在不使用分割符的情况下分割等长的字符串，并扩展数据框。

这是我正在使用的测试数据框：

sample1 = pd.DataFrame({
        'TST': {1: 1535840000000, 2: 1535840000000}, 
        'RCV': {1: 1535840000000, 2: 1535850000000}, 
        'TCU': {1: 358272000000000, 2: 358272000000000}, 
        'SPD': {1: '0', 2: '00000000000000710000007D007C00E2'}
        })

如您所见，SPD列包含各种长度的字符串，没有任何分隔符。

我想每4个字符将SPD列拆分为新行，然后将其扩展到数据框。

             TST            RCV              TCU   SPD
0  1535840000000  1535840000000  358272000000000  0000
1  1535840000000  1535840000000  358272000000000  0000
2  1535840000000  1535840000000  358272000000000  0000
3  1535840000000  1535840000000  358272000000000  0071
4  1535840000000  1535840000000  358272000000000  0000
5  1535840000000  1535840000000  358272000000000  007D
6  1535840000000  1535840000000  358272000000000  007C
7  1535840000000  1535840000000  358272000000000  00E2

我尝试首先使用以下方法生成系列：

pd.concat([pd.Series(re.findall('....', row['SPD'])) for _, row in sample1.iterrows()]).reset_index()

给出

   index     0
0      0  0000
1      1  0000
2      2  0000
3      3  0071
4      4  0000
5      5  007D
6      6  007C
7      7  00E2

但是我无法将其扩展回sample1

Answer 1

您可以使用str.findall，然后根据来自SPD的4个字符切片的数量，使用repeat行。

from itertools import chain

spd4 = df.pop('SPD').str.findall(r'.{4}') 

(pd.DataFrame(df.values.repeat(spd4.str.len(), axis=0), columns=df.columns)
   .assign(SPD=list(chain.from_iterable(spd4))))

             TST            RCV              TCU   SPD
0  1535840000000  1535850000000  358272000000000  0000
1  1535840000000  1535850000000  358272000000000  0000
2  1535840000000  1535850000000  358272000000000  0000
3  1535840000000  1535850000000  358272000000000  0071
4  1535840000000  1535850000000  358272000000000  0000
5  1535840000000  1535850000000  358272000000000  007D
6  1535840000000  1535850000000  358272000000000  007C
7  1535840000000  1535850000000  358272000000000  00E2

Answer 2

您可以使用str.findall每SPD个字符将4中的字符串分割，然后从链接的解决方案中将unnesting嵌套到结果数据框中：

sample1['SPD'] = sample1.SPD.str.ljust(4, '0').str.findall(r'.{4}?')
unnesting(sample1, ['SPD'])

   SPD            TST            RCV              TCU
1  0000  1535840000000  1535840000000  358272000000000
2  0000  1535840000000  1535850000000  358272000000000
2  0000  1535840000000  1535850000000  358272000000000
2  0000  1535840000000  1535850000000  358272000000000
2  0071  1535840000000  1535850000000  358272000000000
2  0000  1535840000000  1535850000000  358272000000000
2  007D  1535840000000  1535850000000  358272000000000
2  007C  1535840000000  1535850000000  358272000000000
2  00E2  1535840000000  1535850000000  358272000000000

Answer 3

使用Series.str.extractall，然后加入原始df。

sample1.filter(regex='^(?!SPD)').join(
    sample1.SPD.str.extractall('(?P<SPD>.{4})').reset_index(level=1, drop=True)
) 

#             TST            RCV              TCU   SPD
#1  1535840000000  1535840000000  358272000000000   NaN
#2  1535840000000  1535850000000  358272000000000  0000
#2  1535840000000  1535850000000  358272000000000  0000
#2  1535840000000  1535850000000  358272000000000  0000
#2  1535840000000  1535850000000  358272000000000  0071
#2  1535840000000  1535850000000  358272000000000  0000
#2  1535840000000  1535850000000  358272000000000  007D
#2  1535840000000  1535850000000  358272000000000  007C
#2  1535840000000  1535850000000  358272000000000  00E2

如果要排除行数少于4个字符SPD的行，请使用inner join（... how ='inner'）。

如何在不使用分割线的情况下分割等长字符串并扩展数据框

3 个答案: