matlibplot plot code example

Example 1: 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 2: plot using matplotlib

import matplotlib.pyplot as plt
plt.plot([1, 2, 3, 4])
plt.ylabel('some numbers')
plt.show()

Example 3: matplotlib.pyplot

import numpy as np
import matplotlib.pyplot as plt

x = np.arange(0, 5, 0.1);
y = np.sin(x)
plt.plot(x, y)

Example 4: how do a plot on matplotlib python

import matplotlib.pyplot as plt
%matplotlib inline
plt.plot(data)
#this is not nessisary but makes your plot more readable
plt.ylabel('y axis means ...')
plt.xlabel('x axis means ...')

Example 5: matplotlib plot

>>> rng = np.arange(50)
>>> rnd = np.random.randint(0, 10, size=(3, rng.size))
>>> yrs = 1950 + rng

>>> fig, ax = plt.subplots(figsize=(5, 3))
>>> ax.stackplot(yrs, rng + rnd, labels=['Eastasia', 'Eurasia', 'Oceania'])
>>> ax.set_title('Combined debt growth over time')
>>> ax.legend(loc='upper left')
>>> ax.set_ylabel('Total debt')
>>> ax.set_xlim(xmin=yrs[0], xmax=yrs[-1])
>>> fig.tight_layout()