CODEWITHSUNDEEP
pythonpandas
Richard
Richard

Reputation: 65530

How can I retrieve a row by index value from a Pandas DataFrame?

I have created a dataframe and set an index:

df = pd.DataFrame(np.random.randn(8, 4),columns=['A', 'B', 'C', 'D'])
df = df.set_index('A')

The dataframe looks like this:

                  B         C         D
A
 0.687263 -1.700568  0.140175  1.420394
-0.212621 -0.700442 -0.041497 -1.034021
-0.614214 -0.437313 -0.464493 -1.182492
-0.885062  0.203892 -0.412400 -0.578346
-1.222661  2.014908 -0.463674 -0.378910
 0.132472 -0.389512  0.623531 -0.788556
-1.083620  1.167158 -0.558217 -0.222078
 1.066270 -0.215586 -0.884757 -0.878557

How do I get the value of B in the row for which A is 0.687263?

I've tried:

e = df.loc(0.687263)

This gives me a LocIndexer object, rather than the row I'd expect (also I'd like to specify that it should be a single row if possible):

<pandas.core.indexing._LocIndexer object at 0x10385e210>

And if I now try e['B'] I get an error.

How do I get the value of B?

Upvotes: 25

Views: 43982

Answers (1)

sorpha
sorpha

Reputation: 433

pandas rounds values when it prints a dataframe. The actual value you are trying to index on is:

1.764052345967664

import pandas as pd
import numpy as np

np.random.seed(0)
df = pd.DataFrame(np.random.randn(8, 4),columns=['A', 'B', 'C', 'D'])

df = df.set_index('A')
print df


                  B         C         D
A                                      
 1.764052  0.400157  0.978738  2.240893
 1.867558 -0.977278  0.950088 -0.151357
-0.103219  0.410599  0.144044  1.454274
 0.761038  0.121675  0.443863  0.333674
 1.494079 -0.205158  0.313068 -0.854096
-2.552990  0.653619  0.864436 -0.742165
 2.269755 -1.454366  0.045759 -0.187184
 1.532779  1.469359  0.154947  0.378163


df.loc[1.764052345967664]
Out[32]: 
B    0.400157
C    0.978738
D    2.240893
Name: 1.76405234597, dtype: float64

Upvotes: 30

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