Plotting using ggplot2
First, we need to install the library using following command
install.packages("ggplot2")
- ggplot is a popular data visualization package in R programming.
Then we can use it as usual by importing the library into script.
R
# Importing librarylibrary(ggplot2)# Reading DatasetSalaryData <- read.csv("placement.csv")# Preparing modelmodel <- lm(package ~ cgpa, data = SalaryData)png(file = "placement_stats.png")ggplot(SalaryData, aes(x = cgpa, y = package)) + geom_point() + # For displaying points geom_smooth(method = "lm", se = FALSE) + # for displaying line labs(title = "CGPA and Package regression", x = "CGPA", y = "Y") |
Output:
It works in similar manner as previous one, both line of best fit and points are plotted on the graph
Without geom_point (plotting points absent)
R
# Importing librarylibrary(ggplot2)# Reading DatasetSalaryData <- read.csv("placement.csv")# Preparing modelmodel <- lm(package ~ cgpa, data = SalaryData)png(file = "placement_stats.png")ggplot(SalaryData, aes(x = cgpa, y = package)) + geom_smooth(method = "lm", se = FALSE) + # geom_points removed labs(title = "CGPA and Package regression", x = "CGPA", y = "Y") |
Output:
plotting points absent
When removing geom_point parameter the plotting points are not displayed on the graph while keeping everything same.
Without geom_smooth (line absent)
R
# Importing librarylibrary(ggplot2)# Reading DatasetSalaryData <- read.csv("placement.csv")# Preparing modelmodel <- lm(package ~ cgpa, data = SalaryData)png(file = "placement_stats.png")ggplot(SalaryData, aes(x = cgpa, y = package)) + geom_point()+ labs(title = "CGPA and Package regression", x = "CGPA", y = "Y") |
Output:
line absent
When removing geom_smooth parameter the line of best fit is not displayed on the graph while keeping everything same.
How to Plot the Linear Regression in R
In this article, we are going to learn to plot linear regression in R. But, to plot Linear regression, we first need to understand what exactly is linear regression.
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