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()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()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()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 ...')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()Copyright © 2021 Codeinu
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