I am trying to assign all the three unique groups from the group
column in df
to different variables (see my code) using Python. How do I incorporate this inside a for loop? Obviously var + i
does not work.
import pandas as pd data = { 'group': ['a', 'a', 'a', 'b', 'b', 'c', 'c'], 'num': list(range(7)) } df = pd.DataFrame(data) unique_groups = df['group'].unique() # How do I incorporate this logic inside a for loop?? var1 = df[df['group'] == unique_groups[0]] var2 = df[df['group'] == unique_groups[1]] var3 = df[df['group'] == unique_groups[2]] # My approach: for i in range(len(unique_groups)): var + i = df[df['group'] == unique_groups[i]] # obviously "var + i" does not work
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Answer
From your comment it seems it is okay for all_vars
to be a list so that all_vars[0]
is the first group, all_vars[1]
the second, etc. In that case, consider using groupby
instead:
all_vars = [group for name, group in df.groupby("group")]