PYTHON

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()

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 ...')

python plot

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()

matplotlib.plot python

x = [1, 2, 3]
>>> y = np.array([[1, 2], [3, 4], [5, 6]])
>>> plot(x, y)

matplotlib.plot python

x = [1, 2, 3]
>>> y = np.array([[1, 2], [3, 4], [5, 6]])
>>> plot(x, y)

how to plot using matplotlib

import matplotlib
matplotlib.rc('text',usetex=True)
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
import numpy as np

text = 'egin{tabular}{|c|c|}hline1&2\hline3&4\hlineend{tabular}'

fig, ax = plt.subplots(1)

img = ax.imshow(np.zeros((10,10)), cmap=plt.cm.gray)
txt = ax.text( 4.5,
          4.5,
          text,
          fontsize=24,
          ha='center',
          va='center',
          bbox=dict(alpha=0))

fig.canvas.draw()
bbox = txt.get_bbox_patch()
xmin = bbox.get_window_extent().xmin
xmax = bbox.get_window_extent().xmax
ymin = bbox.get_window_extent().ymin
ymax = bbox.get_window_extent().ymax

xmin, ymin = fig.transFigure.inverted().transform((xmin, ymin))
xmax, ymax = fig.transFigure.inverted().transform((xmax, ymax))

dx = xmax-xmin
dy = ymax-ymin

# The bounding box vals can be tweaked manually here.
rect = Rectangle((xmin-0.02,ymin-0.01), dx+0.04, dy+0.05, fc='w', transform=fig.transFigure)

ax.add_patch(rect)
fig.canvas.draw()
ax.axis('off')
plt.savefig('ok.png',bbox_inches='tight')

pyplot.plot

plot([x], y, [fmt], *, data=None, **kwargs)
plot([x], y, [fmt], [x2], y2, [fmt2], ..., **kwargs)