NumPy has a numpy.histogram() function that is a graphical
representation of the frequency distribution of data. Rectangles of
equal horizontal size corresponding to class interval called bin and variable height corresponding to frequency.
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numpy.histogram()
The numpy.histogram() function takes the input array and bins as two parameters. The successive elements in bin array act as the boundary of each bin.import numpy as np a = np.array([22,87,5,43,56,73,55,54,11,20,51,5,79,31,27]) np.histogram(a,bins = [0,20,40,60,80,100]) hist,bins = np.histogram(a,bins = [0,20,40,60,80,100]) print hist print binsIt will produce the following output −
[3 4 5 2 1] [0 20 40 60 80 100]
plt()
Matplotlib can convert this numeric representation of histogram into a graph. The plt() function of pyplot submodule takes the array containing the data and bin array as parameters and converts into a histogram.from matplotlib import pyplot as plt import numpy as np a = np.array([22,87,5,43,56,73,55,54,11,20,51,5,79,31,27]) plt.hist(a, bins = [0,20,40,60,80,100]) plt.title("histogram") plt.show()It should produce the following output −
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