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DATA VISUALISATION IN PYTHON

The Matplotlib package in Python is used to visualise data using a variety of charts or graphs, also called plots.
The pyplot, a sub-library of Matplotlib, is a collection of functions that helps in creating different types of charts.
The different kinds of plotting the data using this package are as follows:
u Line Plot: A Line plot or a line chart is used to visualise the relationship between two variables by connecting
data points with straight lines. The data points are represented by two variables, X and Y, each on a different
axis. It's particularly useful for displaying trends over time, making it a common tool for time series data.
u Scatter Plot: A Scatter plot is also known as a Scatter graph. It uses multiple pairs of two variables – X and Y,
represented by dots represent the relation between the two variables. Scatter plots are used to represent
discontinuous data.
Some common elements of Matplotlib plots are:
u Axis Titles or Labels: Axis titles or Labels help in describing the values plotted on the individual axis.

u Chart Title: This is a descriptive name given for the content of the plot.
Let us learn to create a line plot and a scatter plot with the help of examples.
Example 1: Line Plot

Program to create a line plot from a (2, 4) to another point (8, 9).
Code:
import matplotlib.pyplot as plt

import numpy as np
xaxis = np.array([2, 5])
yaxis = np.array([9, 10])
plt.plot(xaxis, yaxis)
plt.show()
The output of the above code is as shown in the figure.
Example 2: Scatter Plot
Program to create a scatter plot using the set of points (2, 3), (5, 5), (6, 7), (8, 10), and (9, 18).

Code:
import matplotlib.pyplot as plt
x = [2, 5, 6, 8, 9]
y = [3,5,7,10,18]
plt.scatter(x, y)
plt.title("Scatter Chart")

plt.xlabel('x-axis')
plt.ylabel('y-axis')
plt.show()
LOW/NO-CODE AI FOR STATISTICAL DATA

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