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()

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 ...')

how to plot in python

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)