大熊貓樞軸，並創建額外的列重複

Question

所以我有一些重複索引的數據和我想要的列。示例

df = pd.DataFrame({ 
       "id":[1,1,1,2,2,3,3,3], 
       "contact_type":["email","phone","phone","email","mobile","email","phone","mobile"], 
       "contact":["a@a.ca","123","456","b@b.com","78432","c@c.ca","12","12"] 
       }) 

我想要做的就是讓每個ID都是單行。我的理想輸出將是

ID email  phone  phone.1 mobile 
1  a@a.ca  123  456  NaN 
2  b@b.com NaN  NaN  78432 
3  c@c.ca  12   NaN  12 

嘗試使用df.pivot（「ID」，「CONTACT_TYPE」，「接觸」）給我一個錯誤「索引包含重複的條目，不能重塑」。問題是，ID 1在contact_type中有2個電話，似乎並不如此。那麼還有另一種方法可以將數據轉換爲這種格式嗎？

Answer 1

我想你必須一塊一塊地組裝最終的數據框（pd.concat），因爲你事先並不知道ID最多可能有多少個不同的電話號碼。假設每個ID最多隻有1個電子郵件或手機號碼：

In [130]: 

df_mail = df.ix[df.contact_type=='email', ['contact', 'id']].set_index('id') 
In [131]: 

df_mobile = df.ix[df.contact_type=='mobile', ['contact', 'id']].set_index('id') 
In [132]: 

df_phone = df.ix[df.contact_type=='phone', ['contact', 'id']] 
In [133]: 
# make a columns stores 'phone0', 'phone1' and so on: 
df_phone['field'] = 'Phone' + df_phone.groupby('id').transform(lambda x: range(len(x))).contact.map(str) 
In [134]: 

df_phone = df_phone.pivot('id', 'field', 'contact') 
In [135]: 

df_mail.columns = ['Email'] 
df_mobile.columns = ['Mobile'] 
In [136]: 

print pd.concat((df_mail, df_phone, df_mobile), axis=1) 
     Email Phone0 Phone1 Mobile 
id        
1 a@a.ca 123 456 NaN 
2 b@b.com NaN NaN 78432 
3 c@c.ca  12 NaN  12