pandas:将一系列字母数字文本拆分并转换为列和行

Question

当前数据框架：我有一个panda数据框架，每个员工都有一个文本代码(所有代码都以T开头(和代码旁边的相关频率。所有文本代码都有8个字符。

+----------+-------------------------------------------------------------+
|  emp_id  |   text                                                      |
+----------+-------------------------------------------------------------+
|   E0001  | [T0431516,-8,T0401531,-12,T0517519,12]                      |
|   E0002  | [T0701540,-1,T0431516,-2]                                   |
|   E0003  | [T0517519,-1,T0421531,-7,T0516319,9,T0500371,-6,T0309711,-3]|
|   E0004  | [T0516319,-3]                                               |
|   E0005  | [T0431516,2]                                                |
+----------+-------------------------------------------------------------+

预期的数据框架：我正在尝试将文本代码作为单独的列出现在数据框架中，如果员工有该代码的频率，则填充频率为0。

+----------+----------------------------------------------------------------------------------------+
|  emp_id  | T0431516 | T0401531 | T0517519 | T0701540 | T0421531 |  T0516319 | T0500371 | T0309711 |                                      
+----------+----------------------------------------------------------------------------------------+
|   E0001  | -8       | -12      | 12       | 0        | 0        | 0         | 0        | 0        |
|   E0002  | -2       | 0        | 0        | -1       | 0        | 0         | 0        | 0        |
|   E0003  | 0        | 0        | -1       | 0        | -7       | 9         | -6       | -3       |
|   E0004  | 0        | 0        | 0        | 0        | 0        | -3        | 0        | 0        |
|   E0005  | 2        | 0        | 0        | 0        | 0        | 0         | 0        | 0        |
+----------+----------------------------------------------------------------------------------------+

样本数据：

pd.DataFrame({'emp_id' : {0: 'E0001', 1: 'E0002', 2: 'E0003', 3: 'E0004', 4: 'E0005'},
'text' :  {0: '[T0431516,-8,T0401531,-12,T0517519,12]', 1: '[T0701540,-1,T0431516,-2]', 2: '[T0517519,-1,T0421531,-7,T0516319,9,T0500371,-6,T0309711,-3]', 3: '[T0516319,-3]', 4: '[T0431516,2]'}
})

到目前为止，我的尝试都没有成功。如有任何建议/帮助，不胜感激！

Answer 1

您可以explode数据帧，然后创建pivot_table:

df = pd.DataFrame({'emp_id' : ['E0001', 'E0002', 'E0003', 'E0004', 'E0005'],
'text' : [['T0431516',-8,'T0401531',-12,'T0517519',12],
['T0701540',-1,'T0431516',-2],['T0517519',-1,'T0421531',-7,'T0516319',9,'T0500371',-6,'T0309711',-3],
['T0516319',-3], ['T0431516',2]]})
df = df.explode('text')
df['freq'] = df['text'].shift(-1)
df = df[df['text'].str[0] == 'T']
df['freq'] = df['freq'].astype(int)
df = pd.pivot_table(df, index='emp_id', columns='text', values='freq',aggfunc = 'sum').fillna(0).astype(int)
df
Out[1]: 
text    T0309711  T0401531  T0421531  T0431516  T0500371  T0516319  T0517519  
emp_id                                                                         
E0001          0       -12         0        -8         0         0        12   
E0002          0         0         0        -2         0         0         0   
E0003         -3         0        -7         0        -6         9        -1   
E0004          0         0         0         0         0        -3         0   
E0005          0         0         0         2         0         0         0   
text    T0701540  
emp_id            
E0001          0  
E0002         -1  
E0003          0  
E0004          0  
E0005          0