CODEWITHSUNDEEP
pythonpandasdataframemulti-index
alanjo
alanjo

Reputation: 45

multiple row selection in multi indexed dataframe

Suppose I write this code in pandas to create a dataframe:

pd.DataFrame({'x':random.sample(range(1,100), 4),
         'y':random.sample(range(1,100), 4),
         'z':random.sample(range(1,100), 4)},
          index = [['a1', 'b1', 'c1','d1'], ['a2', 'b2', 'c2', 'd2']])

This results in the following dataframe:

            x   y   z
    a1  a2  8   2   85
    b1  b2  43  93  58
    c1  c2  1   46  24
    d1  d2  60  37  62

I want to select the multi indexed rows by passing a list like:

[[a1, a2], [b1, b2], [c1, c2]]

to return:

            x   y   z
    a1  a2  8   2   85
    b1  b2  43  93  58
    c1  c2  1   46  24

Is there a function in pandas that does it?

Upvotes: 3

Views: 91

Answers (2)

Cleb
Cleb

Reputation: 26039

You were very close: you need to define the indexes as a list of tuples and not as a list of lists:

target_index = [('a1', 'a2'), ('b1', 'b2'), ('c1', 'c2')]

Then 

df.loc[target_index]

gives you the desired output:

       x  y  z
a1 a2  0  2  3
b1 b2  1  3  4
c1 c2  2  4  5

Upvotes: 3

dubbbdan
dubbbdan

Reputation: 2740

You can select by index using df.iloc

import pandas as pd
import random
df = pd.DataFrame({'x':random.sample(range(1,100), 4),
         'y':random.sample(range(1,100), 4),
         'z':random.sample(range(1,100), 4)},
          index = [['a1', 'b1', 'c1','d1'], ['a2', 'b2', 'c2', 'd2']])

df.iloc[0:3]

returns

        x   y   z
a1 a2  51  36  70
b1 b2  37  45  63
c1 c2  96  16  64

Upvotes: 0

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