split dataframe into multiple dataframes by generating possible combinations based on a condition

Question

I have a below dataframe

        df = 
        city         value
        hyderabad     1
        chennai       1
        mumbai        2
        pune          2
        delhi         3
        nodia         3

I want to split the dataframe into multiple dataframes to generate one combination for each dataframe, excluding the rows which has same value in a loop. The result sets would look like below.

df =  city         value
      hyderabad     1
      mumbai        2
      delhi         3
      
df =  city         value
      hyderabad     1
      mumbai        2
      nodia         3
      
      
df =  city         value
      hyderabad     1
      pune          2
      delhi         3
      
df =  city         value
      hyderabad     1
      pune          2
      nodia         3

      
df =  city         value
      chennai        1
      mumbai         2
      delhi          3
      
df =  city         value
      chennai        1
      mumbai         2
      nodia          3

df =  city         value
      chennai        1
      pune           2
      nodia          3

df =  city         value
      chennai        1
      pune           2
      delhi          3

What is the simplest way to get this done, as i dont know how many rows of data I will have in advance.

What do you mean by 'into multiple dataframes'. You want a variable df1, df2, ..., dfN or a dict with a key for each combination? — Corralien
– Corralien, Commented Jul 6, 2021 at 21:38

Andrej Kesely · Accepted Answer · 2021-07-06 21:41:13Z

1

Try:

from itertools import product

for c in product(*[g.index.tolist() for _, g in df.groupby("value")]):
    print(df.loc[c, :])
    print()

Prints:

        city  value
0  hyderabad      1
2     mumbai      2
4      delhi      3

        city  value
0  hyderabad      1
2     mumbai      2
5      nodia      3

        city  value
0  hyderabad      1
3       pune      2
4      delhi      3

        city  value
0  hyderabad      1
3       pune      2
5      nodia      3

      city  value
1  chennai      1
2   mumbai      2
4    delhi      3

      city  value
1  chennai      1
2   mumbai      2
5    nodia      3

      city  value
1  chennai      1
3     pune      2
4    delhi      3

      city  value
1  chennai      1
3     pune      2
5    nodia      3

answered Jul 6, 2021 at 21:41

Andrej Kesely

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