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All Languages >> Python >> plot using matplotlib

“plot using matplotlib” Code Answer’s

how to plot a graph using matplotlib

python by . on Feb 10 2020 Comment

from matplotlib import pyplot as plt
plt.plot([0, 1, 2, 3, 4, 5], [0, 1, 4, 9, 16, 25])
plt.show()

matplotlib plot

python by Uptight Unicorn on Jan 05 2021 Comment

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()

Source: matplotlib.org

python plot

python by mrjakobdk on Dec 09 2020 Donate Comment

import matplotlib.pyplot as plt
plt.plot([1, 2, 3, 4], [1, 4, 9, 16])
plt.show()

Source: matplotlib.org

plot using matplotlib

python by Plain Platypus on Feb 21 2020 Comment

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

Source: matplotlib.org

how do a plot on matplotlib python

python by SimTheGreat

on Jun 29 2020 Comment

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 ...')

python plot

python by Mckynde

on Jun 05 2020 Donate Comment

import matplotlib.pyplot as plt
import numpy as np

# Simple data to display in various forms
x = np.linspace(0, 2 * np.pi, 400)
y = np.sin(x ** 2)

fig, axarr = plt.subplots(2, 2)
fig.suptitle("This Main Title is Nicely Formatted", fontsize=16)

axarr[0, 0].plot(x, y)
axarr[0, 0].set_title('Axis [0,0] Subtitle')
axarr[0, 1].scatter(x, y)
axarr[0, 1].set_title('Axis [0,1] Subtitle')
axarr[1, 0].plot(x, y ** 2)
axarr[1, 0].set_title('Axis [1,0] Subtitle')
axarr[1, 1].scatter(x, y ** 2)
axarr[1, 1].set_title('Axis [1,1] Subtitle')

# Fine-tune figure;
# hide x ticks for top plots and y ticks for right plots

plt.setp([a.get_xticklabels() for a in axarr[0, :]], visible=False)
plt.setp([a.get_yticklabels() for a in axarr[:, 1]], visible=False)


# Tight layout often produces nice results
# but requires the title to be spaced accordingly

fig.tight_layout()
fig.subplots_adjust(top=0.88)

plt.show()

Source: stackoverflow.com

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