How to have logarithmic bins in a Python histogram

Question

As far as I know the option Log=True in the histogram function only refers to the y-axis.

P.hist(d,bins=50,log=True,alpha=0.5,color='b',histtype='step')

I need the bins to be equally spaced in log10. Is there something that can do this?

You must divide the count in each bin by the bin width if you do so! — Peaceful, Jan 28 '16 at 19:38

score 156 · Accepted Answer · edited Jan 10 '18 at 02:15

156

use logspace() to create a geometric sequence, and pass it to bins parameter. And set the scale of xaxis to log scale.

import pylab as pl
import numpy as np

data = np.random.normal(size=10000)
pl.hist(data, bins=np.logspace(np.log10(0.1),np.log10(1.0), 50))
pl.gca().set_xscale("log")
pl.show()

enter image description here

edited Jan 10 '18 at 02:15

Kedar Grr

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answered Jul 28 '11 at 08:37

HYRY

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note that `np.logspace(0.1,1.0,...)` will create a range from `10**0.1` to `10**1.0`, not from `0.1` to `1.0` – Andre Holzner Sep 09 '15 at 08:30
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should be `np.logspace(np.log10(0.1),np.log10(1.0),50)` – JoseOrtiz3 May 04 '16 at 19:14
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See my answer for how to use bins='auto' – N. McA. Apr 21 '18 at 11:41
@AndreHolzner @OrangeSherbet One can use [`np.geomspace`](https://numpy.org/doc/stable/reference/generated/numpy.geomspace.html) to specify endpoints directly. – Nicolai Weitkemper May 29 '21 at 15:10
Note that the photo doesn't match the code. The limits on the x-axis should be from 10**-1 to 10**0. – Jvinniec Oct 14 '21 at 14:53

Nimar · Answer 2 · 2018-07-24T22:54:29.013

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The most direct way is to just compute the log10 of the limits, compute linearly spaced bins, and then convert back by raising to the power of 10, as below:

import pylab as pl
import numpy as np

data = np.random.normal(size=10000)

MIN, MAX = .01, 10.0

pl.figure()
pl.hist(data, bins = 10 ** np.linspace(np.log10(MIN), np.log10(MAX), 50))
pl.gca().set_xscale("log")
pl.show()

edited Jul 24 '18 at 22:54

answered Aug 04 '14 at 00:52

Nimar

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score 17 · Answer 3 · edited Apr 11 '19 at 18:34

17

The following code indicates how you can use bins='auto' with the log scale.

import numpy as np
import matplotlib.pyplot as plt

data = 10**np.random.normal(size=500)

_, bins = np.histogram(np.log10(data + 1), bins='auto')
plt.hist(data, bins=10**bins);
plt.gca().set_xscale("log")

edited Apr 11 '19 at 18:34

Max Ghenis

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answered Apr 21 '18 at 11:45

N. McA.

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why did you add "+1" (in np.log10(data + 1))? I see that it regularize the case of log(0), but does this not create proble mo represent with the binning the data <1? – user1172131 Nov 08 '22 at 18:34

score 1 · Answer 4 · edited Aug 16 '17 at 10:29

In addition to what was stated, performing this on pandas dataframes works as well:

some_column_hist = dataframe['some_column'].plot(bins=np.logspace(-2, np.log10(max_value), 100), kind='hist', loglog=True, xlim=(0,max_value))

I would caution, that there may be an issue with normalizing the bins. Each bin is larger than the previous one, and therefore must be divided by it's size to normalize the frequencies before plotting, and it seems that neither my solution, nor HYRY's solution accounts for this.

Source: https://arxiv.org/pdf/cond-mat/0412004.pdf

How to have logarithmic bins in a Python histogram

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