I have a number of dfs stored in a list (df\_list). Some dfs share an identical column ('b'). dfs with this identical column should be extracted from the list and stored into a new list of dataframes. Is there a way to 'groupby' dfs in a list programmatically, to handle more cases where this will happen?

Example data and the expected output is shown below. all comments welcome. thanks so much

**example data**

```
df1 = pd.DataFrame(data={'id': [1, 2, 3], 'a': [1,2,3], 'b': ['t1','t1','t1']})
df2 = pd.DataFrame(data={'id': [10, 11, 12], 'a': [2,3,4], 'b': ['t1','t1','t1']})
df3 = pd.DataFrame(data={'id': [1, 2, 3], 'a': [1,2,3], 'b': ['t2','t2','t2']})
df4 = pd.DataFrame(data={'id': [1, 2, 3], 'a': [1,2,3], 'b': ['t3','t3','t3']})
df5 = pd.DataFrame(data={'id': [10, 11, 12], 'a': [2,3,4], 'b': ['t1','t1','t1']})

df_list = (df1, df2, df3, df4, df5)

```

**expected output** : grouped lists

```
df_list_t1 = (df1, df2, df5)
df_list_t2 = (df3)
df_list_t3 = (df4)

```