CODEWITHSUNDEEP
pythonarraysnumpy
user12298516
user12298516

Reputation:

How to split an array into bins of equal length in python?

I want to divide an array, which has 1000 data points into the bins of 100 data points each. Then, I want to calculate the mean of these bins separately.

Can someone suggest how to divide the data which is in a numpy array into the bins? This is what I've tried.

import numpy as np

f = np.random.random((1000))
bin_1 = f[0:100]
mean_1= bin_1.mean()
print(bin_1, mean_1)

Upvotes: 1

Views: 3087

Answers (2)

snaipeberry
snaipeberry

Reputation: 1059

If your list has always a constant size of 1000 data points, you can simply write a for loop from 0 to 1000. This loop will increment the main index of 100 at every iteration. You can compute the mean result of a your list[i-100:i].

For instance:

f = np.loadtxt('ising_T2.dat',usecols=(0))

for (i = 100; i < 1000; i += 100) {
    // mean = f[i - 100:i].mean()
}

Something like this. The trick is that you can crop a list using variables.

Upvotes: 0

Alexander Santos
Alexander Santos

Reputation: 1691

import numpy as np

f = np.loadtxt('ising_T2.dat',usecols=(0))
chunk_begin, chunk_end = 0, 100
splitted_bins = []
splitted_means = []
for _ in range(9):
    bin = f[chunk_begin:chunk_end]
    mean = bin.mean()
    splitted_bins.append(bin)
    splitted_means.append(mean)
    chunk_begin, chunk_end = chunk_begin + 100, chunk_end + 100
print(splitted_bins, splitted_means)

Not sure if that is what you want

Upvotes: 2

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