Session Management

🏠 R Session Management: Your Digital Workspace

Imagine walking into your personal art studio every day. You have your brushes, your paints, your half-finished paintings, and notes about what you were working on. R’s session management is exactly like that—your personal workspace that remembers everything!

🎯 What You’ll Learn

Think of R as your personal assistant that keeps track of:

• Who you are (Session Information)
• What computer you’re using (System Information)
• Where your stuff is stored (Workspace Management)
• How to run your saved instructions (source Function)

📋 Session Information

What is Session Information?

Imagine you’re writing a diary entry. You’d write the date, maybe the weather, and what you did. R does the same thing—it keeps a “diary” about your current work session!

The Magic Command: sessionInfo()

sessionInfo()

This one command tells you EVERYTHING about your current R session:

# What you'll see:
# R version 4.3.2 (2023-10-31)
# Platform: x86_64-pc-linux-gnu
# Running under: Ubuntu 22.04.3 LTS
#
# Matrix products: default
# BLAS:   /usr/lib/...
#
# locale: en_US.UTF-8
#
# attached packages:
# [1] ggplot2_3.4.4

Why Does This Matter?

🎨 Story Time: Sarah wrote an amazing R script at work. She sent it to her friend Tom, but it didn’t work on his computer! Why? Because Tom had a different R version. If Sarah had shared her sessionInfo(), Tom would have known exactly what he needed!

Quick Session Checks

# What R version am I using?
R.version.string
# "R version 4.3.2 (2023-10-31)"

# What packages are loaded?
search()
# ".GlobalEnv" "package:stats" ...

# When did this session start?
Sys.time()

💻 System Information

Your Computer’s ID Card

Just like you have an ID card with your name and photo, your computer has one too! R can read it.

Key System Commands

# What's my computer's name?
Sys.info()["nodename"]

# What operating system?
Sys.info()["sysname"]  # "Linux", "Windows", "Darwin"

# Who's logged in?
Sys.info()["user"]

The Full Picture

# Get EVERYTHING about your system
Sys.info()

This returns:

• sysname → Operating System (Windows, Linux, Darwin)
• release → OS version
• nodename → Computer name
• machine → Processor type
• login → Your username
• user → Current user

🧭 Practical Example

# Make your code work on ANY computer!
if (Sys.info()["sysname"] == "Windows") {
  path <- "C:/Users/data/"
} else {
  path <- "/home/user/data/"
}

📁 Workspace Management

Your Digital Desk

Think of your workspace as your desk. On it, you have:

• Papers (data frames)
• Calculators (functions)
• Notes (variables)

R keeps all of this in its “Global Environment.”

Where Am I?

# What folder is R looking at right now?
getwd()
# "/home/student/my_project"

# Change to a different folder
setwd("/home/student/another_project")

What’s On My Desk?

# See everything in your workspace
ls()
# "my_data" "my_function" "result"

# See with more details
ls.str()

Cleaning Up

# Remove one thing
rm(old_variable)

# Remove multiple things
rm(var1, var2, var3)

# CLEAR EVERYTHING (be careful!)
rm(list = ls())

💾 Saving Your Work

# Save EVERYTHING to a file
save.image("my_work.RData")

# Save specific objects
save(my_data, my_model, file = "important.RData")

# Load it back later
load("my_work.RData")

Workspace Files Explained

graph TD
    A["Your R Session"] --> B[".RData File"]
    A --> C[".Rhistory File"]
    B --> D["All Variables"]
    B --> E["All Functions"]
    B --> F["All Data"]
    C --> G["Commands You Typed"]

📜 The source() Function

Running Saved Instructions

Imagine you write the same recipe every time you bake cookies. Wouldn’t it be easier to just say “follow the cookie recipe”? That’s what source() does!

How It Works

Step 1: Save your code in a file (like analysis.R)

# analysis.R
data <- read.csv("sales.csv")
summary(data)
plot(data$month, data$sales)

Step 2: Run it all with one command!

source("analysis.R")

✨ Magic! All the code runs automatically.

source() Options

# Basic usage
source("my_script.R")

# Show each line as it runs
source("my_script.R", echo = TRUE)

# Keep running even if there's an error
source("my_script.R", keep.source = TRUE)

# Run from the internet!
source("https://example.com/script.R")

🎭 Real-World Story

Monday Morning at DataCorp:

Alex arrives at work and opens R. Instead of typing 50 lines of code to load data and create reports, Alex just types:

source("monday_report.R")

☕ Coffee time while R does all the work!

Building Good Habits

graph TD
    A["Write Code in RStudio"] --> B["Save as .R File"]
    B --> C["Test It Works"]
    C --> D["Use source Next Time"]
    D --> E["Save Hours of Work!"]

🔧 Putting It All Together

A Day in the Life of an R User

# 1. Check your session
sessionInfo()

# 2. See where you are
getwd()

# 3. Load yesterday's work
load("project.RData")

# 4. See what you have
ls()

# 5. Run your analysis script
source("daily_analysis.R")

# 6. Save when done
save.image("project.RData")

🌟 Quick Reference

💡 Pro Tips

1. Always check sessionInfo() before sharing code — it helps others reproduce your work!

2. Use setwd() at the start of scripts — so R knows where to find your files.

3. Save your workspace regularly — computers crash, but .RData files don’t forget!

4. Put reusable code in .R files — then source() them whenever you need.

5. Name your objects clearly — when you run ls(), you’ll thank yourself!

🎉 You Did It!

Now you know how to:

• ✅ Check your session details
• ✅ Understand your system
• ✅ Manage your workspace like a pro
• ✅ Run saved scripts effortlessly

Your R workspace is now your organized, efficient, digital studio. Happy coding! 🚀