PANDAS split dataframe to multiple by unique values rows

Question

I have a DataFrame in Pandas

      PRICE   Name     PER   CATEGORY   STORENAME
0      9.99    MF      gram  Indica     Store1
1      9.99    HY      gram  Herb       Store2
2      9.99    FF      gram  Herb       Store2

What I want to do is split these into multiple data frames to have unique names, then in those split to category.

Current code:

names = df['STORENAME'].unique().tolist()   #find unique values
store1 = df[df['STORENAME']==names[0]]        
store2 = df[df['STORENAME']==names[1]]

This code works perfectly but I am wondering if there is a Pythonic way since the number of stores may change.

This is needed to plot the difference in prices in categories in stores.

Thanks!

Answer 1

I think you can create dictionary of DataFrames:

dfs = dict(tuple(df.groupby('STORENAME')))

And then select by STORENAME:

store1 = dfs['Store1']
store2 = dfs['Store2']

print (store1)
   PRICE Name   PER CATEGORY STORENAME
0   9.99   MF  gram   Indica    Store1

print (store2)
   PRICE Name   PER CATEGORY STORENAME
1   9.99   HY  gram     Herb    Store2
2   9.99   FF  gram     Herb    Store2