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()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()python plot
import matplotlib.pyplot as plt
plt.plot([1, 2, 3, 4], [1, 4, 9, 16])
plt.show()plot using matplotlib
import matplotlib.pyplot as plt
plt.plot([1, 2, 3, 4])
plt.ylabel('some numbers')
plt.show()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()pyplot.plot
plot([x], y, [fmt], *, data=None, **kwargs)
plot([x], y, [fmt], [x2], y2, [fmt2], ..., **kwargs)Copyright © 2021 Codeinu
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