Richard Richard - 3 months ago 35
Python Question

Basic pandas: retrieve row by index value?

Apologies for this basic question, but 10 minutes of Googling and I'm still stuck.

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?

Answer

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