pandas select rows by index level

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Maximiliano
23 Aug 2020
1#for single row
2df.loc[ index , : ]
3
4# for multiple rows
5indices = [1, 20, 33, 47, 52 ]
6new_df= df.iloc[indices, :]
source
Andrea
19 Oct 2020
1rowData = dfObj.loc[ 'b' , : ]
2
Francesca
21 Jan 2020
1### w3sources ###
2d = {'num_legs': [4, 4, 4, 2, 2],
3     'num_wings': [0, 0, 0, 2, 2],
4     'class': ['mammal', 'mammal', 'mammal', 'bird', 'bird'],
5     'animal': ['tiger', 'lion', 'fox', 'eagle', 'penguin'],
6     'locomotion': ['walks', 'walks', 'walks', 'flies', 'walks']}
7
8df = pd.DataFrame(data=d)
9df = df.set_index(['class', 'animal', 'locomotion'])
10
11#							num_legs	num_wings
12# class	animal	locomotion		
13# mammal| tiger	walks		4			0
14#	    | lion	walks		4			0
15#	    | fox	walks		4			0
16# __________________________________________
17# bird  | eagle		flies	2			2
18#	    | penguin	walks	2			2
19  
20df.xs('mammal')
21df.xs(('mammal', 'fox'))
22df.xs('lion', level=1)
23df.xs(('bird', 'walks'),level=[0, 'locomotion'])
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