Pyplot is a sub-module of the matplotlib library for Python.
It is a library consisting of a collection of functions/methods used for plotting simple 2D graphs using Python.
Pyplot can be imported using import matplotlib.pyplot.
To clarify, matplotlib is a pre-existing library, while pyplot is a part/module of the matplotlib library installed alongside matplotlib.
For simplicity, from here onwards, pyplot in the code will be referred to as plt. This can be done in the code using import matplotlib.pyplot as plt.
pyplotBefore we start making graphs, we have the ability to add/change different characteristics of the graphs we want to create. For example:
Changing the name of the axis using plt.xlabel('X-Axis name') or plt.ylabel('Y-Axis name')
Changing the title of the graph with plt.title('new title')
Creating a legend with the syntax plt.legend([""])
Changing the color scheme
The data for scatter graphs, bar graphs, etc., can be created with the help of lists or even dictionaries. For example:
# X-axis and Y-axis valuesx = [10,20,30,40,50]y = [23,34,45,56,67]
A line graph is a graph that shows change over time or the relation between two or more categories of data.
These can be created using plt.plot(x value set , y value set) .
Note: The process of making a scatter chart is mostly the same as that of making a line graph, with the main difference being that the graph syntax used is
plt.scatter(X-Axis values, Y-axis values).
# Example of a Line graphimport matplotlib.pyplot as pltx = [10,20,30,40,50]y = [63,36,92,36,46]plt.plot(x,y)plt.show()
Bar graphs are used to compare things between different groups or to track changes over time.
These can be created using plt.bar(X-Axis values, Y-axis values).
Note: The process of making a histogram is mostly the same as that of making a bar graph, with the main difference being the graph syntax used is
plt.hist(X-Axis values, Y-axis values).
# Example of a Bar Graphfrom matplotlib import pyplot as pltbrand ='Brand A','Brand B','Brand C','Brand D'sales = [30,60,29,50]plt.bar(brand,sales)plt.legend(["Sales"])plt.show()
A pie chart is a type of graph that represents data in a circular graph. Each division shows the relative size of the data. Pie charts can be used to show the percentages of a whole.
These can be made by inserting plt.pie(data values). The pie chart slices will be divided based on the ratio of the data values.
# Example of a Pie Chartimport matplotlib.pyplot as pltx = [10,20,30,40]plt.pie(x)plt.show()
Note: The distance of each slice can be specified while creating the pie chart by adding the
explode = (Distance of each slice from center)after the data set with a comma.
For example:
import matplotlib.pyplot as pltx = [10,20,30,40]e =(1,0,2,4)plt.pie(x,explode = e)plt.show()