Python is the most used language for Matplotlib is a plotting library for creating static, animated, and interactive visualizations in Python. Matplotlib can be used in Python scripts, the Python and IPython shell, web application servers, and various graphical user interface toolkits like Tkinter, awxPython, etc.
Note: For more information, refer to Python Matplotlib – An Overview
Installing Matplotlib
To use Pyplot we must first download the Matplotlib module. For this write the following command:
pip install matplotlib
What is Pyplot in Matplotlib?
Pyplot is a Matplotlib module that provides a MATLAB-like interface. Matplotlib is designed to be as usable as MATLAB, with the ability to use Python and the advantage of being free and open-source. Each pyplot function makes some changes to a figure: e.g., creates a figure, creates a plotting area in a figure, plots some lines in a plotting area, decorates the plot with labels, etc. The various plots we can utilize using Pyplot are Line Plot, Histogram, Scatter, 3D Plot, Image, Contour, and Polar.
Syntax :
matplotlib.pyplot.plot(*args, scalex=True, scaley=True, data=None, **kwargs)
Parameters:
This function accepts parameters that enable us to set axes scales and format the graphs. These parameters are mentioned below :-
- plot(x, y): plot x and y using default line style and color.
- plot.axis([xmin, xmax, ymin, ymax]): scales the x-axis and y-axis from minimum to maximum values
- plot.(x, y, color=’green’, marker=’o’, linestyle=’dashed’, linewidth=2, markersize=12):
x and y co-ordinates are marked using circular markers of size 12 and green color line with — style of width 2- plot.xlabel(‘X-axis’): names x-axis
- plot.ylabel(‘Y-axis’): names y-axis
- plot(x, y, label = ‘Sample line ‘): plotted Sample Line will be displayed as a legend
Plotting in Matplotlib
We will import the matplotlib library and then plot some example data points.
Python3
# Python program to show plot functionimport matplotlib.pyplot as pltplt.plot([1, 2, 3, 4], [1, 4, 9, 16])plt.axis([0, 6, 0, 20])plt.show() |
OUTPUT :
The plot function marks the x-coordinates(1, 2, 3, 4) and y-coordinates(1, 4, 9, 16) in a linear graph with specified scales.
Pyplot Examples
For the sake of example, we will use Electricity Power Consumption datasets of India and Bangladesh. Here, we are using Google Public Data as a data source.
We will plot power consumption in kWh by India and Bangladesh with years as X-axis.
Example 1: Linear Plot using matplotlib.pyplot
Python3
# Python Program to illustrate Linear Plottingimport matplotlib.pyplot as plt# year contains the x-axis values# and e-india & e-bangladesh# are the y-axis values for plotting year = [1972, 1982, 1992, 2002, 2012]e_india = [100.6, 158.61, 305.54, 394.96, 724.79]e_bangladesh = [10.5, 25.21, 58.65, 119.27, 274.87]# plotting of x-axis(year) and# y-axis(power consumption)with different colored labels of two countriesplt.plot(year, e_india, color ='orange', label ='India')plt.plot(year, e_bangladesh, color ='g', label ='Bangladesh')# naming of x-axis and y-axisplt.xlabel('Years')plt.ylabel('Power consumption in kWh')# naming the title of the plotplt.title('Electricity consumption per capita\ of India and Bangladesh')plt.legend()plt.show() |
Output :
Line Plot
Example 2: Linear Plot with line formatting
In this example we will plot the same plot but with a variation in the lines plotted. We can use dashed line or a line with markers.
Python3
# Python Program to illustrate Linear Plottingimport matplotlib.pyplot as pltyear = [1972, 1982, 1992, 2002, 2012]e_india = [100.6, 158.61, 305.54, 394.96, 724.79]e_bangladesh = [10.5, 25.21, 58.65, 119.27, 274.87]# formatting of line style and# plotting of co-ordinatesplt.plot(year, e_india, color ='orange', marker ='o', markersize = 12, label ='India')plt.plot(year, e_bangladesh, color ='g', linestyle ='dashed', linewidth = 2, label ='Bangladesh')plt.xlabel('Years')plt.ylabel('Power consumption in kWh')plt.title('Electricity consumption per \capita of India and Bangladesh')plt.legend()plt.show() |
Output:
Line Plot with Line Formatting
