Example 1: how to plot a graph using matplotlib
from matplotlib import pyplot as plt
plt.plot([0, 1, 2, 3, 4, 5], [0, 1, 4, 9, 16, 25])
plt.show()
Example 2: python 2d graph
names = ['group_a', 'group_b', 'group_c']
values = [1, 10, 100]
plt.figure(figsize=(9, 3))
plt.subplot(131)
plt.bar(names, values)
plt.subplot(132)
plt.scatter(names, values)
plt.subplot(133)
plt.plot(names, values)
plt.suptitle('Categorical Plotting')
plt.show()
Example 3: plot function in numpy
import numpy as np
from matplotlib import pyplot as plt
x = np.arange(1,11)
y = 2 * x + 5
plt.title("Matplotlib demo")
plt.xlabel("x axis caption")
plt.ylabel("y axis caption")
plt.plot(x,y)
plt.show()
Example 4: matplotlib plot
import matplotlib.pyplot as plt
fig = plt.figure(1) #identifies the figure
plt.title("Y vs X", fontsize='16') #title
plt.plot([1, 2, 3, 4], [6,2,8,4]) #plot the points
plt.xlabel("X",fontsize='13') #adds a label in the x axis
plt.ylabel("Y",fontsize='13') #adds a label in the y axis
plt.legend(('YvsX'),loc='best') #creates a legend to identify the plot
plt.savefig('Y_X.png') #saves the figure in the present directory
plt.grid() #shows a grid under the plot
plt.show()
Example 5: matplotlib line plot
from matplotlib import pyplot as plt
# Median Developer Salaries by Age
dev_x = [25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35]
dev_y = [38496, 42000, 46752, 49320, 53200,
56000, 62316, 64928, 67317, 68748, 73752]
plt.plot(dev_x, dev_y)
plt.xlabel('Ages')
plt.ylabel('Median Salary (USD)')
plt.title('Median Salary (USD) by Age')
plt.show()
#Basic line graph using python module matplotlib
Example 6: python plot
import matplotlib.pyplot as plt
plt.plot([1, 2, 3, 4], [1, 4, 9, 16])
plt.show()