################# 
### Objective ###
#################

## Define the following terms as they relate to R: object, assign, call, function, arguments, options.
## Create objects and assign values to them in R.
## Learn how to name objects.
## Save a script file for later use.
## Use comments to inform script.
## Solve simple arithmetic operations in R.
## Call functions and use arguments to change their default options.
## Inspect the content of vectors and manipulate their content.
## Subset and extract values from vectors.
## Analyze vectors with missing data.


##########
# Objects
#########

3 + 5
12 / 7

area_hectares <- 1.0
area_hectares

2.47 * area_hectares

area_hectares <- 2.5

2.47 * area_hectares

area_acres <- 2.47 * area_hectares

area_hectares <- 50

area_acres


###################
### Challenge 1 ###
###################

## What are the values after each statement in the following?

length <- 2.5
width <- 3.2
area <- length * width
area

# change the values of length and width
length <- 7.0
width <- 6.5

# does the value of area change?
area

# how about now? 
area <- length * width
area


###############################
# Functions and their arguments
###############################

# 1.1 Round pi (3.14159) using the round function



# 1.2 Get information about the round function and it's arguments



# 1.3  Round pi to 2 digits using the digits argument



########################
# Vectors and data types
########################

# 2.1 Create a numeric vector with the c() function



# 2.2 Create a character vector with the c() function



# 2.3 Inspect the contents of your vectors using the length(), class(), and str() functions



# 2.4 Add more elements to your vector using the c() function



# 2.5 Create an integer vector with the colon



###################
### Challenge 2 ###
###################

## Atomic vectors can be of type character, numeric (or double), integer, and logical.

## 1. What happens if we try to mix these types in a single vector? 
##    HINT: Use class() to check the data type of your objects.
##    Why do you think this happens?

vec_num_char <- c(1, 2, 3, "a")
vec_num_logical <- c(1, 2, 3, TRUE)
vec_char_logical <- c("a", "b", "c", TRUE)
vec_tricky <- c(1, 2, 3, "4")

## 2. How many values in vec_combined_logical are "TRUE" (as a character) in the following example:

vec_num_logical <- c(1, 2, 3, TRUE)
vec_char_logical <- c("a", "b", "c", TRUE)
vec_combined_logical <- c(vec_num_logical, vec_char_logical)


####################
# Subsetting vectors
####################

# 3.1 Copy the character vector from 2.2 above or create one



# 3.2 Extract/Display a single value from the vector 



# 3.3 Extract/Display multiple values from the vector



# 3.4 Create a logical vector using a logical test on a vector



# 3.5 Use the logical test to select values from the vector



# 3.6 Use the %in% operator to check each element of a vector against another

possessions <- c("car", "bicycle", "radio", "television", "mobile_phone")
possessions %in% c("car", "boat")


####################
# Missing data
####################

# 4.1 Create a vector that includes the NA value



# 4.2 Find the mean and max values of the vector



# 4.3 Use is.na() to extract elements that are NOT missing values 



# 4.4 Use na.omit() to return the object with incomplete cases removed



# 4.5 Use complete.cases() to extract those elements which are complete cases 



###################
### Challenge 4 ###
###################

rooms <- c(1, 2, 1, 1, NA, 3, 1, 3, 2, 1, 1, 8, 3, 1, NA, 1)

## 1. Using this vector of rooms, create a new vector with the NAs removed.



## 2. Use the function median() to calculate the median of the vector.



## 3. Use R to figure out how many households in the set use more than 2 rooms for sleeping.



####################
# Prepare for Data
####################

## 5.1 Create a subdirectory for the raw data

dir.create("data")

## 5.2 Put the data file in the directory
## The data is at https://ndownloader.figshare.com/files/11492171

download.file("https://ndownloader.figshare.com/files/11492171",
              "data/SAFI_clean.csv", mode = "wb")
			  
## 5.3 Install the Tidyverse Package
##     This only needs to be done once on a computer. 

install.packages("tidyverse")

## 5.4 Test that the tidyverse package loads properly 
##     This needs to be doen every time R is started

library(tidyverse)