The Python library Matplotlib contains the pyplot module, which provides users with an interface for graphing data. Pyplot contains over 100 functions, from acorr to yticks. You must import the module, and plt is the standard variable name used.
from matplotlib import pyplot as plt
Here are some of the most common pyplot functions:
| Function | Description |
|---|---|
| Plot | plots y versus x as lines and/or markers |
| Show | displays a figure |
| Axis | sets some axis properties |
| Xlabel | sets the label for the x-axis |
| Ylabel | sets the label for the y-axis |
| Title | sets a title for the axes |
| Subplot | adds a subplot to the current figure |
| Subplots_adjust | tunes the subplot layout |
| Legend | places a legend on the axes |
| Figure | creates a new figure |
| Savefig | saves the current figure |
Matplotlib’s pyplot.axis function takes one parameter, which must be a four-item array, and returns the current axes’ limits. The four items should contain enough info to define an x axis and a y axis by minimum and maximum values. The array must order these values as follows: x-axis minimum, x-axis maximum, y-axis minimum, y-axis maximum.
x = range(12)y = [2,8,20,40,70,300,930,7000,68000,500000,4000000, 2000000]plt.plot(x, y)#x-axis minimum is 0, x-axis maximum is 11; y-axis minimum is 300, y-axis maximum is 500000plt.axis([0,11,300,500000])plt.show()
In Python’s Matplotlib, the pyplot.plot() function can accept parameters to set the color(color), linestyle(linestyle) and marker(marker) for line graph. Color values can be HTML color names or HEX codes. Line styles can be dashed('--') or dotted('..'). Markers can be circles('o'), squares('s'), stars('*'), or other shapes.
pyplot.plot(days, money_spent, color='green', linestyle='--')pyplot.plot(days, money_spent_2, color='#AAAAAA', marker='o')
In Python’s Matplotlib, subplots can overlap, either horizontally or vertically. The function pyplot.subplots_adjust() can set better spacing around each subplot in a figure. It can set values for left, right, bottom and top margins, plus the horizontal(wspace) and vertical(hspace) spaces between adjacent subplots.
import matplotlib.pyplot as plt# Left Plotplt.subplot(1, 2, 1)plt.plot([-2, -1, 0, 1, 2], [4, 1, 0, 1, 4])# Right Plotplt.subplot(1, 2, 2)plt.plot([-2, -1, 0, 1, 2], [4, 1, 0, 1, 4])# Subplot Adjustplt.subplots_adjust(wspace=1.3)plt.show()
In Python’s Matplotlib, the x-tick and y-tick marks of the plot can be changed using functions ax.set_xticks() and ax.set_yticks(). These functions accepts an array of values representing tick mark positions.
import matplotlib.pyplot as pltax = plt.subplot()plt.plot([0, 1, 2, 3, 4], [0, 1, 4, 9, 16])plt.plot([0, 1, 2, 3, 4], [0, 1, 8, 27, 64])ax.set_xticks([1, 2, 4])
In Python, the Matplotlib’s pyplot.subplot() function can be used to create a figure with a grid of subplots. The function accepts number of rows, number of columns, and the current index as arguments.
import matplotlib.pyplot as plt# Datasetsx = [1, 2, 3, 4]y = [1, 2, 3, 4]# First Subplotplt.subplot(1, 2, 1)plt.plot(x,y, color='green')plt.title('First Subplot')# Second Subplotplt.subplot(1, 2, 2)plt.plot(x,y, color='blue')plt.title('Second Subplot')# Display both subplotsplt.show()
In Python’s Matplotlib, a figure is a container that holds plots. It can hold a single plot or multiple plots. When a figure holds multiple separate plots, those are called subplots.