Intro to R

# Packages ####
# once you install packages to your computer, you can "check them out" of your packages library each time you need them

library(tidyverse)# really neat collection of packages! https://www.tidyverse.org/ 
library(lubridate)
library(plotly)
library(ggmap)


# Working Directory ####

setwd('C:/Users/ct991305/Documents/Workshop Material/2020-12-17-telemetry-packages-FACT/') #set folder you're going to work in
getwd() #check working directory

#you can also change it in the RStudio interface by navigating in the file browser where your working directory should be, 
#and clicking on the blue gear icon "More", and select "Set As Working Directory".

3 + 5 #maths! including - , *, /

weight_kg <- 55 #assignment operator! for objects/variables. shortcut: alt + - 
weight_kg

weight_lb <- 2.2 * weight_kg #can assign output to an object. can use objects to do calculations

# Challenge 1:
# if we change the value of weight_kg to be 100, does the value of weight_lb also change automatically?
# remember: you can check the contents of an object by simply typing out its name

#functions take "arguments": you have to tell them what to run their script against

ten <- sqrt(weight_kg) #contain calculations wrapped into one command to type. 

round(3.14159) #don't have to assign

args(round) #the args() function will show you the required arguments of another function

?round #will show you the full help page for a function, so you can see what it does, 


#Challenge 2: can you round the value 3.14159 to two decimal places?
# using args() should give a clue!

weight_g <- c(21, 34, 39, 54, 55) #use the combine function to join values into a vector object

length(weight_g) #explore vector
class(weight_g) #a vector can only contain one data type
str(weight_g) #find the structure of your object.

#our vector is numeric. 
#other options include: character (words), logical (TRUE or FALSE), integer etc.

animals <- c("mouse", "rat", "dog") #to create a character vector, use quotes


#Challenge 3: what data type will this vector become? You can check using class()
#challenge3 <- c(1, 2, 3, "4")

animals #calling your object will print it out
animals[2] #square brackets = indexing. selects the 2nd value in your vector

weight_g > 50 #conditional indexing: selects based on criteria
weight_g[weight_g <=30 | weight_g == 55] #many new operators here!  
                                         #<= less than or equal to, | "or", == equal to
weight_g[weight_g >= 30 & weight_g == 21] #  >=  greater than or equal to, & "and" 
                                          # this particular example give 0 results - why?

heights <- c(2, 4, 4, NA, 6)
mean(heights) #some functions cant handle NAs
mean(heights, na.rm = TRUE) #remove the NAs before calculating

#other ways to get a dataset without NAs:

heights[!is.na(heights)] #select for values where its NOT NA 
#[] square brackets are the base R way to select a subset of data --> called indexing
#! is an operator that reverses the function

na.omit(heights) #omit the NAs

heights[complete.cases(heights)] #select only complete cases

#Challenge 4: 
#1. Using this vector of heights in inches, create a new vector, heights_no_na, with the NAs removed.
  #heights <- c(63, 69, 60, 65, NA, 68, 61, 70, 61, 59, 64, 69, 63, 63, NA, 72, 65, 64, 70, 63, 65)
#2. Use the function median() to calculate the median of the heights vector.
#BONUS: Use R to figure out how many people in the set are taller than 67 inches.