# Data Visualization — Line Plot

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Learn the basics of data visualization using line plots

# About the Author

**Benjamin O. Tayo** is a data science educator, tutor, coach, mentor, and consultant. Contact me for more information about our services and pricing: benjaminobi@gmail.com

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# INTRODUCTION

After reading this article, the reader will learn the following:

- Define a line plot
- Generate a line plot using python
- Fit a simple linear regression model and visualize the result using a line plot

Learn about data visualization using **scatter plots** by clicking on the link below:

A line plot is used in data science to quantify the functional relationship between the independent variable x and the dependent variable y. Using simple linear regression, the relation between x and y can be expressed as *y = a + b x*, where *a* and *b *are the regression coefficients to be determined.

# Python Implementation of a Line Plot

As an illustration, we will fit a simple linear regression model and then visualize the result using a line graph.

## Example 1: Tesla stock price vs. Apple stock price

`# import necessary libraries`

import numpy as np

import pandas as pd

import matplotlib.pyplot as plt

import seaborn as sns

# obtain dataset

data = pd.read_csv('https://raw.githubusercontent.com/bot13956/datasets/master/tech-stocks-04-2021.csv')

# Example 1: Tesla stock price vs Apply stock price

# define x and y

x = data.AAPL.values[0:11]

y = data.TSLA.values[0:11]

# fit simple linear…