Matplotlib

This is the most popular graphing and data visualization library of Python. We can install by using pip
conda install -c conda-forge matplotlib
Simple graphs Metplotlib Graph
import matplotlib.pyplot as plt
x=[1,2,3,4,5]
y=[2,1,5,7,3]
plt.plot(x,y)    
plt.show()

Adding more features to graph

xlable() : Add Lable to X axis
ylable() : Add Lable to Y axis
title() : Add a title to your graph
grid() : Add grid to graph , plt.grid(True,color='#f1f1f1')
legend(): Show legend on graph Metplotlib Graph example
from matplotlib import pyplot as plt
x = [2,5,7]
y = [2,16,4]
plt.plot(x,y,label='my data')
plt.title('plus2net Info')
plt.ylabel('Y axis')
plt.xlabel('X axis')
plt.legend()
plt.grid(True,color='#f1f1f1')
plt.show()
Note : To show legend , you must add label to your plot()
One of the important method is plot(), here are different parameters can be used with plot()
plt.plot(x,y,'g',label='my data', linewidth=4)

Pie Chart

Metplotlib pie chart example
import matplotlib.pyplot as plt

classes = 'Four', 'Five', 'Six', 'Seven'
sizes = [30, 50, 40, 60]
explode = (0, 0, 0.1, 0)  
# only "explode" the 3rd slice (i.e. 'Six')

plt.pie(sizes, explode=explode, autopct='%1.1f%%',
        labels=classes,shadow=True, startangle=90)

plt.title("Distribution of Classes")
plt.show()

Bar Chart

Metplotlib single bar chart example
import matplotlib.pyplot as plt

classes = 'Four', 'Five', 'Six', 'Seven'
sizes = [30, 50, 40, 60]

plt.bar([.5,1.5,2.5,3.5], sizes,width=.5)
plt.title("Distribution of Classes")
plt.show()
Metplotlib double bar chart example
import matplotlib.pyplot as plt

classes = 'Four', 'Five', 'Six', 'Seven'
sizes = [30, 50, 40, 60]
marks=[50,70,65,50]

plt.bar([.5,1.5,2.5,3.5], sizes,width=.25,
        label='size')
plt.bar([.75,1.75,2.75,3.75], marks,
        width=.25,label='mark',color='r')

plt.legend()
plt.title("Distribution of Classes")
plt.show()

Histogram

Shows the frequency of distribution of data. Here we will see how marks are obtained at different rages . Here we can see more marks are obtained by the students in the range 50 to 60. Metplotlib histogram chart example
import matplotlib.pyplot as plt
range = [30,40,50,60,70,80,90,100]
marks = [35,55,78,46,48,55,79,95,55,58,65]
plt.hist(marks,range,label='mark',
    color='r', histtype='bar', rwidth=0.8)

plt.legend()
plt.title("Distribution of Classes")
plt.show()


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