Remap Values-dict To Columns In Pandas

I have a dataframe where values of features-column are dict-like as here: http://screencast.com/t/0Ko0NIBLwo features name price rating read rev

Solution 1:

I think you can use replace and strip and 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      {}