My goal in to split python dataframe by multiple columns. In the case of one column, data frame can be splitted by column 'X1' as below, using the groupby method. However, how to split dataframe according to columns X1 and X2?
df = pd.DataFrame({'X1': ['Falcon', 'Falcon', 'Parrot', 'Parrot'],
'X2': ['Captive', 'Wild', 'Captive', 'Wild'],
'X3': ['BIG', 'SMALL', 'BIG', 'SMALL']})
dfs= dict(tuple(df.groupby('X1')))
dfs
CodePudding user response:
If pass another column name is necessary select dfs
by tuples:
dfs= dict(tuple(df.groupby(['X1', 'X2'])))
print (dfs[('Falcon','Captive')])
X1 X2 X3
0 Falcon Captive BIG
If want select by string
s is possible use join
in dict comprehension:
dfs={f'{"_".join(k)}' : v for k, v in df.groupby(['X1', 'X2'])}
print (dfs['Falcon_Captive'])
X1 X2 X3
0 Falcon Captive BIG