Datajam-LIHTC.Rmd

---
title: "NC State Datajam"
author: "Walt DeGrange"
date: "March 3, 2018"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

## R Markdown

```{r Libraries}
library(magrittr)
library(ggplot2)
library(dplyr)
library(kableExtra)
library(knitr)
library(formattable)
```

```{r Data Import}
Demographic <- read.csv("LIHTC-Demographic.csv")
Demographic %<>% rename(Neighborhood = "ï..Neighborhood")
Value <- read.csv("LIHTC-Value.csv")
Value %<>% rename(Neighborhood = "ï..Neighborhood")
Numbers <- read.csv("LIHTC-Number.csv")
Numbers %<>% rename(Neighborhood = "ï..Neighborhood")
```

```{r Demo Analysis}

Change <- 0.5

Demographic$Median.Income..2000. <- currency(Demographic$Median.Income..2000.,digits = 0)

Demographic$Median.Income..2010. <- currency(Demographic$Median.Income..2010.,digits = 0)

Demographic$Median.Income..2015. <- currency(Demographic$Median.Income..2015.,digits = 0)

Demographic %>% filter((Median.Income..2000.*Change > Median.Income..2010. | Median.Income..2000.*Change > Median.Income..2015.) & City == "Charlotte") %>% select(Neighborhood,City,Median.Income..2000., Median.Income..2010., Median.Income..2015.) %>% kable("html") %>% kable_styling(bootstrap_options = "striped", full_width = F) 



```

```{r Analysis}

Value %<>% mutate(Difference = Dec.17-Jan.97, Grps = "A")

Value %<>% filter(!is.na(Difference))

Value$Grps[Value$Jan.97 > quantile(Value$Jan.97,0.50,na.rm = TRUE) & Value$Jan.97 <= quantile(Value$Jan.97,0.75,na.rm = TRUE)] <- "B"

Value$Grps[Value$Jan.97 > quantile(Value$Jan.97,0.25,na.rm = TRUE) & Value$Jan.97 <= quantile(Value$Jan.97,0.50,na.rm = TRUE)] <- "C"

Value$Grps[Value$Jan.97 <= quantile(Value$Jan.97,0.24,na.rm = TRUE)] <- "D"

Value$LIHTC.Present...0...No..1...Yes. <- as.character(Value$LIHTC.Present...0...No..1...Yes.)

Value %<>% rename("LIHTC" = "LIHTC.Present...0...No..1...Yes.")

Value %>% ggplot(aes(x=Grps,y=Difference))
+ geom_boxplot()
# + facet_grid(. ~ LIHTC)

Value %>% ggplot(aes(x=LIHTC,y=Difference))
+ geom_boxplot()
+ facet_grid(. ~ Grps)

Value %>% ggplot(aes(x=Grps,y=Difference))
+ geom_bar()
+ facet_grid(. ~ Grps)

Demographic %>% filter(Population..2000. > 9000) %>%    ggplot(aes(x=Neighborhood,y=Population..2000.))
+ geom_col()
```