Lecture 5 - Plotting in R
# Topics for Today! 1. Topic: Loading in data 2. Topic: Managing data in dataframes 3. Topic: Basic plotting in R - hist() and boxplot() 4. Topic: Basic plotting in R- A first look at plot() ## Recommended further reading 1. Reading and writing data in R (Ch. 3.1 in Book 1, Ch. 2.6 in Book 2) 2. Managing data from dataframes (Ch. 3.2.4.5+3.2.4.6 in Book 1) 3. Plotting catagorical data with hist(), boxplot() (4.4.2-4 in Book 1, 3.4.1-2 in Book 2) 4. Plotting continuous data with plot() (4.4.1 in Book 1, 4.2.1 in Book 2) # 1. Topic: Loading Data ```{r} getwd() # this is the directory in which you can access files setwd("/Users/mike/Desktop/R Materials/mih140/Lecture 5 - Introduction to Plotting in R/") # this is my directory where I save things. # Set your directory to whereever you downloaded the RegionEx_Data.txt # To load the data use the read.table() command ?read.table() flight_data = read.table("RegionEx_Data.txt", sep = "\t") flight_data = read.table("RegionEx_Data.txt", header = T, sep = "\t") # Notice we used the sep = "\t" since the file is a tab separated # If the file is a .csv, use sep = "," or read.csv(filename) # To view the table try the View(df) command View(flight_data) # Note there are two airlines in the dataset unique(flight_data$Airline) # this is the unique() function, it returns the unique elements in a vector ``` # 2. Topic: Managing data from dataframes. ```{r} # Using names() we can get all column names of the flightdata dataset names(flight_data) # Using class() we can get the type of the data class(flight_data$Arrival.delay.in.minutes) #integer class(flight_data$Airline) #factor # Note the last catagory is a "factor". Factors a special data types for catagorical variables. We can convert other character vectors to factors using the as.factor() method. flight_data$Delay.indicator = as.factor(flight_data$Delay.indicator) flight_data$Day.of.Week = as.factor(flight_data$Day.of.Week) # Lets isolate all flight data for the two airlines flight_data_MDA = flight_data[flight_data$Airline == "MDA",] flight_data_RegionEx = flight_data[flight_data$Airline == "RegionEx",] # We can use the table() function to examine 1 dimension data. table(flight_data_RegionEx$Delay.indicator) table(flight_data_RegionEx$Delay.indicator)/nrow(flight_data_RegionEx) ``` # 3. Topic: Basic plotting in R - hist() and boxplot() ```{r} # Lets reload our data file from before, and isolate the regionEx data. flight_data = read.table("RegionEx_Data.txt", header = T, sep = "\t", stringsAsFactors = F) flight_data_RegionEx = flight_data[flight_data$Airline == "RegionEx",] # To explore the data lets try making a histogram of the delays delays= flight_data_RegionEx$Arrival.delay.in.minutes # To make a histogram in R we use the hist() function # Example. hist(delays) # This makes a very basic histogram. We customize using many of R features. # We can change the title using the main = "" parameter # Ex. hist(delays, main = "Delays in Minutes") # Similarly we can change the x and y labels using parameters xlab = "" and ylab = "" # Ex. hist(delays, main = "Delays in Minutes", xlab = "Arrival Delay (min)", ylab = "# of delays") # Further we can manually set the bins using the parameter breaks = c(b1, b2, .., bk) # Ex. hist(delays, main = "Delays in Minutes", xlab = "Arrival Delay (min)", ylab = "# of delays", breaks = seq(min(delays)-10,max(delays)+10,10)) # Notice I create bins using seq(min(delays)-10,max(delays)+10,10), run this code to see what it does. Why do I have the -10, +10 in the code? # Similar to a histogram we can make a box plot using the command boxplot() # Ex. boxplot(delays) # boxplot can be customized just like hist() # Ex. boxplot(delays, main = "Delays in Minutes", xlab = "Arrival Delay (min)", ylab = "# of delays") ``` # 4. Topic: Basic plotting in R - plot() ```{r} # Plotting continous varibles using plot() delays= flight_data_RegionEx$Arrival.delay.in.minutes num_of_passengers = flight_data_RegionEx$Number.of.passengers plot(delays ~ num_of_passengers) # this plots number of pass on the x vs delays on the y # We can title it similar to before plot(delays ~ num_of_passengers, main = "Delay vs. Passenger Load", xlab = "Number of Passengers", ylab = "Delay (min)") # More on this next time! ```
