當前數據框架：我有一個 pandas 數據框架，其中每個員工都有一個文本代碼（所有代碼以 T 開頭）以及代碼旁邊的相關頻率。所有文本代碼都有 8 個字符。+----------+-------------------------------------------------------------+| 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] |+----------+-------------------------------------------------------------+預期數據框：我試圖將數據框中的文本代碼作為單獨的列顯示，如果員工具有該代碼的頻率，則填充頻率，否則為 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 |+----------+----------------------------------------------------------------------------------------+所以，到目前為止我的嘗試都沒有成功。非常感謝任何指示/幫助！
1 回答
狐的傳說
TA貢獻1804條經驗 獲得超3個贊
您可以explode數據框，然后創建一個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
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