How to use the matplotlibs pyplot.scatter() function in Python
Overview
The pyplot.scatter() function in matplotlib is used to create a scatter plot. For further understanding, the pyplot module has a function called scatter(), among many other functions, which helps to create or draw a scatter plot.
A scatter plot is a type of plot that uses a dot to graphically represent two variables for a set of data. The scatter plot is used to show a relationship between two numeric variables. The dots in a scatter plot also represent a pattern from which certain data analysis conclusions can be made.
Creating a scatter plot
As mentioned earlier, we make use of the pyplot.scatter() function in matplotlib, which creates a scatter plot.
The pyplot.scatter() function must contain two (x and y-axis) arrays of the same length.
Code
import matplotlib.pyplot as pltimport numpy as npx = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])y = np.array([10, 50, 30, 40, 50, 25, 70, 15, 90, 65])plt.scatter(x, y)plt.show()
Output
Explanation
- Line 1: In the
matplotlibwe imported thepyplotmodule, which will help us to create plots. - Line 2: We imported the
numpymodule, which helps us create arrays. - Line 4 and 5: We created the arrays,
xandyfor both the x-axis and y-axis. They are both of equal length. - Line 7: Here, we used the
pyplot.scatter()method to create a scatter plot ofxandy. - Line 8: Using the
pyplot.show()function, we toldpyplotto show us the plot.
Multiple scatter plots
Interestingly, we can create multiple scatter plots on the same figure. This is usually done by data analysts to compare different data variables.
Code
import matplotlib.pyplot as pltimport numpy as np# the first scatter plotx = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])y = np.array([10, 50, 30, 40, 50, 25, 70, 15, 90, 65])plt.scatter(x, y)# the second scatter plotx = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])y1 = np.array([5, 35, 40, 45, 80, 20, 95, 55, 70, 10])plt.scatter(x,y1)plt.show()
Output
The two colors present in the plot are that of the first and second scatter plots. By default, pyplot returned blue and orange colors.
