Question

我想将数据框中的数据排列成多个数据帧或组。输入数据是

id  channel path
15  direct  a1
15  direct  a2
15  direct  a3
15  direct  a4
213 paid    b2
213 paid    b1
2222    direct  as25
2222    direct  dw46
2222    direct  32q
3111    paid    d32a
3111    paid    23ff
3111    paid    www32
3111    paid    2d2

所需的输出应该是

id  channel p1  p2      
213 paid    b2  b2      

id  channel p1  p2  p3  
2222    direct  as25    dw46    dw46    

id  channel p1  p2  p3  p4
15  direct  a1  a2  a3  a4
3111    paid    d32a    23ff    www32   2d2

请说明我能实现的方式。感谢

Answer 1

我认为您可以先cumcount然后pivot_table创建帮助列cols。然后你需要找到notnull列的长度（减去前2）和这length groupby。每组中的最后dropna列：

df['cols'] = 'p' + (df.groupby('id')['id'].cumcount() + 1).astype(str)

df1 = df.pivot_table(index=['id', 'channel'], 
                    columns='cols', 
                    values='path', 
                    aggfunc='first').reset_index().rename_axis(None, axis=1)

print df1
     id channel    p1    p2     p3    p4
0    15  direct    a1    a2     a3    a4
1   213    paid    b2    b1   None  None
2  2222  direct  as25  dw46    32q  None
3  3111    paid  d32a  23ff  www32   2d2

print df1.apply(lambda x: x.notnull().sum() - 2 , axis=1)
0    4
1    2
2    3
3    4
dtype: int64

for i, g in df1.groupby(df1.apply(lambda x: x.notnull().sum() - 2 , axis=1)):
    print i
    print g.dropna(axis=1)
2
    id channel  p1  p2
1  213    paid  b2  b1
3
     id channel    p1    p2   p3
2  2222  direct  as25  dw46  32q
4
     id channel    p1    p2     p3   p4
0    15  direct    a1    a2     a3   a4
3  3111    paid  d32a  23ff  www32  2d2

要进行存储，您可以使用dictionary的{{1}}：

DataFrames

在pandas中切片和排列数据帧

1 个答案: