---
title: "Data Challenge #3"
author: "Rodrigo Zamith"
output:
  html_document:
    df_print: paged
    theme: spacelab
---

```{r global_options, include=FALSE}
knitr::opts_chunk$set(fig.width=12, fig.height=8, warning=FALSE)
```

Complete instructions for this Challenge may be [found here](challenge_3.html).

### Part 1

I'll begin by loading the datasets that have been provided for the analysis:

```{r message=FALSE, warning=FALSE}
# Load data
library(tidyverse)
shef_appropriations <- read_csv("http://projects.rodrigozamith.com/datastorytelling/data/Public_FTE_Enrollment_and_Educational_Appropriations_per_FTE_FY_1992_to_2017.csv")
nyfed_student_debt_balance <- read_csv("http://projects.rodrigozamith.com/datastorytelling/data/Student_Loan_Debt_Balance_per_Capita_by_State.csv")
nyfed_student_debt_balance_delinquent <- read_csv("http://projects.rodrigozamith.com/datastorytelling/data/Percent_of_Student_Loan_Debt_Balance_90plus_Days_Delinquent_by_State.csv")
nyfed_total_debt <- read_csv("http://projects.rodrigozamith.com/datastorytelling/data/Total_Debt_Balance_and_Its_Composition.csv")
nyfed_delinquent_debt_type <- read_csv("http://projects.rodrigozamith.com/datastorytelling/data/Percent_of_Balance_90plus_Days_Delinquent_by_Loan_Type.csv")
nyfed_total_debt_by_age <- read_csv("http://projects.rodrigozamith.com/datastorytelling/data/Total_Debt_by_Product_Type_and_Age.csv")
doe_collection_agencies <- read_csv("http://projects.rodrigozamith.com/datastorytelling/data/Default_Recoveries_by_Private_Collection_Agency_FY18Q4.csv")
college_scorecard_subset <- read_csv("http://projects.rodrigozamith.com/datastorytelling/data/College_Scorecard_Most_Recent_Cohorts_Scorecard_Elements.csv", na="NULL")
```

Then, I wanted to do ... so I .... This helped me find out that .... Here's the code for doing all this:

```{r}
# Your code here
```

I also noticed that ..., so I dug deeper into that by .... That's why I said in the story that .... Here's the code for that:

```{r}
# Your code here
```

### Part 2

Story here.
