How do I make bins of equal number of observations in a pandas dataframe?

Question

I'm trying to make a column in a dataframe depicting a group or bin that observation belongs to. The idea is to sort the dataframe according to some column, then develop another column denoting which bin that observation belongs to. If I want deciles, then I should be able to tell a function I want 10 equal (or close to equal) groups.

I tried the pandas qcut but that just gives a tuples of the the upper and lower limits of the bins. I would like just 1,2,3,4....etc. Take the following for example

import numpy as np
import pandas as pd

x = [1,2,3,4,5,6,7,8,5,45,64545,65,6456,564]
y = np.random.rand(len(x))

df_dict = {'x': x, 'y': y}
df = pd.DataFrame(df_dict)

This gives a df of 14 observations. How could I get groups of 5 equal bins?

The desired result would be the following:

        x         y  group
0       1  0.926273      1
1       2  0.678101      1
2       3  0.636875      1
3       4  0.802590      2
4       5  0.494553      2
5       6  0.874876      2
6       7  0.607902      3
7       8  0.028737      3
8       5  0.493545      3
9      45  0.498140      4
10  64545  0.938377      4
11     65  0.613015      4
12   6456  0.288266      5
13    564  0.917817      5

Answer 1

Group by N rows, and find ngroup

df['group']=df.groupby(np.arange(len(df.index))//3,axis=0).ngroup()+1



     x      y        group
0       1  0.548801      1
1       2  0.096620      1
2       3  0.713771      1
3       4  0.922987      2
4       5  0.283689      2
5       6  0.807755      2
6       7  0.592864      3
7       8  0.670315      3
8       5  0.034549      3
9      45  0.355274      4
10  64545  0.239373      4
11     65  0.156208      4
12   6456  0.419990      5
13    564  0.248278      5