CODEWITHSUNDEEP
pythonnumpyhistogram
DurgaDatta
DurgaDatta

Reputation: 4170

Binning frequency distribution in Python

I have data in the two lists value and freq like this:

value freq
1      2
2      1
3      3
6      2
7      3
8      3
....

and I want the output to be 

bin freq
1-3   6
4-6   2
7-9   6
...

I can write few lines of code to do this. However, I am looking if there are builitin functions in standard python or Numpy? I found the solution when you are given data in array/list with repetition i.e. they are not already grouped into frequency table(eg. d= [1,1,2,3,3,3,6,6,7,7,7,8,8,8,...]. However, in this case I could not find the answers. I do not want to convert my data into single expanded list like d first and use histogram function.

Upvotes: 7

Views: 14262

Answers (3)

shx2
shx2

Reputation: 64298

I found the solution when you are given data in array/list with repetition

You didn't say what the solution was, but if it supports taking an iterator, you can generate it, instead of creating the entire list:

import itertools

values = [1,2,3,6]
freqs =  [2,1,3,2]

v_iter = itertools.chain(*[ itertools.repeat(v,f) for v, f in zip(values, freqs) ])

#for x in v_iter:
#    print x

your_solution(v_iter)

Upvotes: 0

HYRY
HYRY

Reputation: 97261

import numpy as np
values = [1,2,3,6,7,8]
freqs = [2,1,3,2,3,3]

hist, _ = np.histogram(values, bins=[1, 4, 7, 10], weights=freqs)
print hist

output:

[6 2 6]

Upvotes: 15

MIE
MIE

Reputation: 454

you can try this:

import collections
d=[1,1,2,3,3,3,6,6,7,7,7,8,8,8]
collections.Counter([i-i%3+3 for i in d])

it would generate a dictionary with what you want.

Upvotes: 0

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