get the most frequent group of values with pandas in python

I have an ascii file as following

1   306.0416667
2   286.1666667
3   207.5
4   226.4166667
5   304.2083333
6   336.1666667
7   255.5416667
8   224.5833333
9   190.1666667
10  163.5
11  231.125
12  167.3333333
13  193.5416667
14  165
15  166
16  172.173913
17  158.9166667
18  196.8333333
19  154.875
20  303.4166667

I want to found the most frequent group of values. The groups are 0-90, 90-180, 180-270, 270-360.

I tried to use .value_counts() but with no success (even though without grouping the values).

import pandas as pd
col_names=['id','val']
df = pd.read_csv(i,names=col_names,header=None)
df['val'].value_counts().[:1].index.tolist()

Solution

You can use pd.cut, groupby(), count() like below:

>>> df = pd.DataFrame({
    'freq': [306.0416667, 286.1666667, 207.5 , 226.4166667 , 304.2083333 , 
             336.1666667 , 255.5416667, 224.5833333 , 190.1666667, 163.5 , 
             231.125, 167.3333333 , 193.5416667 , 165 , 154.875 , 303.4166667]})

>>> ranges = [0,90,180,270, 360]
>>> df.groupby(pd.cut(df['freq'], ranges)).count()

           freq
freq    
(0, 90]     0
(90, 180]   4
(180, 270]  7
(270, 360]  5

>>> df.groupby(pd.cut(df['freq'], ranges)).count().idxmax()
freq    (180, 270]
dtype: interval