Loading and Exploring a Dataset Using R Functions

In this section, we'll load and explore a dataset using R functions. Before starting with the implementation, check the version by typing version in the console and checking the details, as follows:

Let's begin by following these steps:

1. Install the following packages and libraries:
   

install.packages("ggplot2")
install.packages("tibble")
install.packages("dplyr")
install.packages("Lock5Data")

2. Get the current working directory by using the getwd(".") command:

[1] "C:/Users/admin/Documents/GitHub/Applied-DataVisualization-with-ggplot2-and-R"

3. Set the current working directory to Chapter 1 by using the following command:

setwd("C:/Users/admin/Documents/GitHub/Applied-DataVisualization-with-ggplot2-and-R/Lesson1")

4. Use the require command to open the template_Lesson1.R file, which has the necessary libraries.
   
5. Read the following data file, provided in the data directory:

df_hum <- read.csv("data/historical-hourly-weather-data/humidity.csv")

The following libraries have now been loaded:

• Graphical visualization package:

require("ggplot2") 

• Build a data frame or list and some other useful commands:

require("tibble") 

• A built-in dataset package in R:

require("Lock5Data") 

Use the following commands to determine the data frame details, as follows:

#Display the column names
colnames(df_hum)

Take a look at the output screenshot, as shown here:

Use the following command:

#Number of columns and rows
ndim(df_hum) 

A summary of the data frame can be seen with the following code:

str(df_hum)

Take a look at the output screenshot, as shown here: