stats_visualizing_histogram.py

#!/usr/bin/env python
# coding: utf-8

# # COURSE: Master statistics and machine learning: Intuition, Math, code
# ##### COURSE URL: udemy.com/course/statsml_x/?couponCode=202006 
# ## SECTION: Visualizing data
# ### VIDEO: Histograms
# #### TEACHER: Mike X Cohen, sincxpress.com
# 

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# import libraries
import matplotlib.pyplot as plt
import numpy as np


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## create data for the histogram

# number of data points
n = 1000

# generate data - log-normal distribution
data = np.exp( np.random.randn(n)/2 )


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# show as a histogram

# number of histogram bins
k = 40

plt.hist(data,bins=k)
plt.show()


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# another option
y,x = np.histogram(data,bins=k)

# bin centers
xx = (x[1:]+x[:-1])/2

plt.plot(xx,y)
plt.show()


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