Accessing Another Column By Value ,Pandas

Question

I have a dataframe as follows:

    Type      Name           Category              
    Bird      Flappy Bird    Air      
    Bird      Pigeon         Air    
    Pokemon   Jerry          Aquatic      
    Pokemon   Mudkip         Aquatic
    Animal    Lion           Terrestrial
    Bird      Pigeon         Air2  

For the given name like say "Pigeon", I need to access the corresponding value in the category Column i.e it should give me the string "Air" .
I have 2 values of Pigeon but i need to return "Air" for 2nd observation.

Please note that I am not using indexing at all so having something like 2nd observation with iloc would'nt do. I need to access it by value in the other column.

Or something like obtaining the index of "Pigeon" and using that to get the corresponding column value will do.

Answer 1

use loc

So for you example:

df.loc[df.Name == 'Pigeon', 'Category'] 

would give you what you want

Example:

In [17]:

import io
import pandas as pd
temp = """Type      Name           Category              
Bird      Flappy_Bird    Air      
Bird      Pigeon         Air    
Pokemon   Jerry          Aquatic      
Pokemon   Mudkip         Aquatic
Animal    Lion           Terrestrial"""

df = pd.read_csv(io.StringIO(temp), sep='\s+')
df
Out[17]:
      Type         Name     Category
0     Bird  Flappy_Bird          Air
1     Bird       Pigeon          Air
2  Pokemon        Jerry      Aquatic
3  Pokemon       Mudkip      Aquatic
4   Animal         Lion  Terrestrial

[5 rows x 3 columns]
In [19]:

df.loc[df.Name == 'Pigeon','Category']
Out[19]:
1    Air
Name: Category, dtype: object

If you have multiple values and just want the first then use idxmin:

In [24]:

df.ix[(df.Name == 'Pigeon').idxmin(),'Category']
Out[24]:
'Air'

EDIT

So for the case where we have multiple values and you want to access the individual values, you can either check the index values and directly access them:

In [23]:

df.loc[df.Name=='Pigeon','Category'].index.values
Out[23]:
array([1, 5], dtype=int64)
In [26]:

df.loc[df.Name=='Pigeon','Category'][5]
Out[26]:
'Air2'

OR if you want to loop over them then series has a iteritems() method:

In [28]:

df.loc[df.Name=='Pigeon','Category'].iteritems()
Out[28]:
[(1, 'Air'), (5, 'Air2')]

either of these should satisfy your requirements