重映射值快譯通到列大熊貓

Question

我有一個數據幀，其中features -column的值是字典般如下：字典的

http://screencast.com/t/0Ko0NIBLwo

features     name    price rating read reviews 
9 {'Cooking...': '- S...', } Master Chef... $279.99 None None  {} 

例如：

{u'Cooking Type': u'- Specialty Cooking', u'Cooking Area': u'- Backyard', u'Brand Name': u'- Pizzacraft', u'Fuel Type': u'- Propane', u'Product Type': u'- BBQ', u'Size': u'- Medium Size'} 

是否有可能將這些值轉換爲新列？

features     Cooking Type  Specialty Cooking ... name    price rating read reviews 
9 {'Cooking...': '- S...', } Specialty Cooking Backyard   ... Master Chef... $279.99 None None  {} 

Answer 1

我認爲你可以使用replace和strip和concat：

print df 
              features   name price \ 
0 {u'Cooking Type': u'- Specialty Cooking', u'Co... Master Chef1 $279.99 
1 {u'Cooking Type': u'- Specialty Cooking', u'Co... Master Chef3 $279.99 

    rating read reviews 
0 None None  {} 
1 None None  {} 

df1 = pd.DataFrame([x for x in df['features']], index=df.index) 

for col in df1.columns: 
    df1[col] = df1[col].str.replace(r'-','').str.strip() 

print df1 
    Brand Name Cooking Area  Cooking Type Fuel Type Product Type \ 
0 Pizzacraft  Backyard Specialty Cooking Propane   BBQ 
1 Pizzacraft  Backyard Specialty Cooking Propane   BBQ 

      Size 
0 Medium Size 
1 Medium Size 

df = pd.concat([df1, df[['name','price','rating','read','reviews']]], axis=1) 
print df 
    Brand Name Cooking Area  Cooking Type Fuel Type Product Type \ 
0 Pizzacraft  Backyard Specialty Cooking Propane   BBQ 
1 Pizzacraft  Backyard Specialty Cooking Propane   BBQ 

      Size   name price rating read reviews 
0 Medium Size Master Chef1 $279.99 None None  {} 
1 Medium Size Master Chef3 $279.99 None None  {}