SESSION 11

Getting Started with R & Environment Setup 

R is a powerful statistical programming language widely used for data analysis, visualization, and social media analytics. Setting up your R environment is the first step toward leveraging its capabilities for your projects.

1. Installing R

Steps:

1. Download R:

   • Go to CRAN (Comprehensive R Archive Network).

   • Select your operating system (Windows, macOS, or Linux).

   • Follow the instructions to install R.

2. Verify Installation:

   • Open a terminal or command prompt.

Run the following command to check the version:
bash

R --version

2. • Alternatively, open the R console by typing R in your terminal or opening the R GUI.

2. Installing RStudio (Recommended IDE)

RStudio is an Integrated Development Environment (IDE) for R that simplifies coding, visualization, and project management.

Steps:

1. Download RStudio:

   • Go to the RStudio website.

   • Download the free desktop version compatible with your operating system.

2. Install RStudio:

   • Follow the installation steps for your OS.

   • Launch RStudio to start coding.

RStudio Features:

• Script Editor: Write and execute R scripts.

• Console: Interact with R directly.

• Environment Panel: Manage datasets and variables.

• Plots Panel: View and export visualizations.

3. Setting Up R Packages

R packages extend R's functionality for tasks like data manipulation, visualization, and social media analytics.

Key Packages:

• Data Manipulation: dplyr, tidyr

• Data Visualization: ggplot2, plotly

• Social Media Analytics: rtweet, tm, wordcloud

• APIs and Data Access: httr, jsonlite

• Text Analysis: tidytext, sentimentr

Installing Packages:

Install a package using the install.packages() function:
R

install.packages("ggplot2")

Load the package:
R

library(ggplot2)

4. Setting Up Your Working Directory

The working directory is the folder where R reads and writes files.

Steps:

Check your current working directory:
R

getwd()

Set a new working directory:
R

setwd("path/to/your/folder")

2. 
   

3. Alternatively, in RStudio:

   • Go to Session > Set Working Directory > Choose Directory.

5. Writing Your First R Script

1. Create a New Script:

   • Open RStudio, and go to File > New File > R Script.

Write Code:
R

# Basic arithmetic

result <- 5 + 3

print(result)

# Create a simple plot

x <- c(1, 2, 3, 4, 5)

y <- c(2, 4, 6, 8, 10)

plot(x, y, main = "Simple Plot", col = "blue")

2. 
   

3. Run the Code:

   • Highlight the code and press Ctrl + Enter (Windows) or Cmd + Enter (macOS).

6. Setting Up R for Social Media Analytics

To use R for social media analytics, you need specific libraries and API configurations.

Example: Setting Up rtweet for Twitter Analytics

Install and load the rtweet package:
R

install.packages("rtweet")

library(rtweet)

1. 
   

2. Authenticate with Twitter:

   • Create a Twitter Developer Account and get API keys.

Use rtweet for OAuth authentication:
R

token <- rtweet::create_token(

  app = "your_app_name",

  consumer_key = "your_consumer_key",

  consumer_secret = "your_consumer_secret",

  access_token = "your_access_token",

  access_secret = "your_access_secret"

)

Fetch data (e.g., tweets with a specific hashtag):
R

tweets <- search_tweets("#SocialMedia", n = 100, lang = "en")

head(tweets)

7. Configuring RMarkdown for Reports

RMarkdown allows you to create dynamic, reproducible reports with code, output, and text in a single document.

Steps:

Install rmarkdown:
R

install.packages("rmarkdown")

1. Create a new RMarkdown file:

   • In RStudio, go to File > New File > R Markdown.

2. Knit the file to HTML, PDF, or Word format.

8. Best Practices for R Environment Setup

1. Organize Projects:

   • Use RStudio projects to manage files and dependencies.

   • Go to File > New Project.

2. Use .Rprofile:

   • Add custom startup commands in the .Rprofile file.

   • Example: Automatically load packages or set working directories.

3. Version Control:

   • Integrate Git for version control using RStudio's Git tab.

4. Backup Your Work:

   • Regularly save your scripts and projects.