Want to learn Data Visualization using Matplotlib?
 Hello friends, in the previous blog post we have to see basic pandas library Numpy and pandas so it’s time to see Data viasualization in python using Matplotlib. so first upon what is matplotlib ? let’s start. Matplotlib is the grandfathers library of data visualizations with Python. It was created by the John Hunter. He created it to try to replicate MatLab(another programming language) plotting capabilities in Pythons. So if you happen to be familiar with matlab, matplotlibs will feel natural to you.

Also read : scope in python

 

 

conda install matplotlib

or pip install matplotlib



5.1 example:

 

import matplotlib.pyplot as plt

# plot a lines, implicitly creating a subplot(111)

plt.plot([1,2,3])

# now create a subplots which represents the top plot of a grid with 2 rows and 1 column.

#Since this subplots will overlap the first, the plot (and its axes) previously

created, will be removed

plt.subplot(211)

plt.plot(range(12))

plt.subplot(212, facecolor=’y’) # create 2nd subplots with yellow background

plt.plot(range(12))

5.2 Example:

from matplotlib import pyplot as plt

import numpy as np

fig,ax = plt.subplots(1,1)

a = np.array([22,87,5,43,56,73,55,54,11,20,51,5,79,31,27])

ax.hist(a, bins = [0,25,50,75,100])

ax.set_title(“histogram of result”)

ax.set_xticks([0,25,50,75,100])

ax.set_xlabel(‘marks’)

ax.set_ylabel(‘no. of students’)

plt.show()