How does numpy histogram work

Question

While reading up on numpy  I encountered the function numpy histogram     What is it for and how does it work  In the docs they mention bins  What are they   Some googling led me to the definition of Histograms in general  I get that  But unfortunately I can t link this knowledge to the examples given in the docs

User · Accepted Answer

A bin is range that represents the width of a single bar of the histogram along the X-axis. You could also call this the interval. (Wikipedia defines them more formally as "disjoint categories".)

The Numpy histogram function doesn't draw the histogram, but it computes the occurrences of input data that fall within each bin, which in turns determines the area (not necessarily the height if the bins aren't of equal width) of each bar.

In this example:

 np.histogram([1, 2, 1], bins=[0, 1, 2, 3])

There are 3 bins, for values ranging from 0 to 1 (excl 1.), 1 to 2 (excl. 2) and 2 to 3 (incl. 3), respectively. The way Numpy defines these bins if by giving a list of delimiters ([0, 1, 2, 3]) in this example, although it also returns the bins in the results, since it can choose them automatically from the input, if none are specified. If bins=5, for example, it will use 5 bins of equal width spread between the minimum input value and the maximum input value.

The input values are 1, 2 and 1. Therefore, bin "1 to 2" contains two occurrences (the two 1 values), and bin "2 to 3" contains one occurrence (the 2). These results are in the first item in the returned tuple: array([0, 2, 1]).

Since the bins here are of equal width, you can use the number of occurrences for the height of each bar. When drawn, you would have:

a bar of height 0 for range/bin [0,1] on the X-axis,
a bar of height 2 for range/bin [1,2],
a bar of height 1 for range/bin [2,3].

You can plot this directly with Matplotlib (its hist function also returns the bins and the values):

>>> import matplotlib.pyplot as plt
>>> plt.hist([1, 2, 1], bins=[0, 1, 2, 3])
(array([0, 2, 1]), array([0, 1, 2, 3]), <a list of 3 Patch objects>)
>>> plt.show()

enter image description here

User · Answer

import numpy as np     hist  bin edges   np histogram  1  1  2  2  2  2  3   bins   range 5     Below  hist indicates that there are 0 items in bin  0  2 in bin  1  4 in bin  3  1 in bin  4   print hist    array  0  2  4  1        bin edges indicates that bin  0 is the interval  0 1   bin  1 is  1 2        bin  3 is  3 4    print  bin edges    array  0  1  2  3  4        Play with the above code  change the input to np histogram and see how it works     But a picture is worth a thousand words   import matplotlib pyplot as plt plt bar bin edges  -1   hist  width   1  plt xlim min bin edges   max bin edges   plt show

User · Answer

Another useful thing to do with numpy histogram is to plot the output as the x and y coordinates on a linegraph  For example   arr   np random randint 1  51  500  y  x   np histogram arr  bins np arange 51   fig  ax   plt subplots   ax plot x  -1   y  fig show       This can be a useful way to visualize histograms where you would like a higher level of granularity without bars everywhere  Very useful in image histograms for identifying extreme pixel values

[python] How does numpy.histogram() work?

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