DCFS_Maps_8_27 for DV.Rmd

---
title: "DCFS Maps 8 - 27 Data"
author: 
- "Daniel Abrams Law Clinic"
- "Jason Winik"
output: pdf_document
---
```{r, echo=FALSE, include= FALSE}
library(devtools)
library(choroplethrZip)
library(choroplethr)
library(choroplethrMaps)
library(tidyverse)
library(usmap)
library(cowplot)
library(ggmap)
library(ggplot2)
library(kableExtra)
library(showtext)
library(extrafont)
library(waffle)
#font_import("C:/Windows/Fonts")

df <- read.csv('C:/Users/jwini/OneDrive/Documents/Python Scripts/DCFS-Lead-Testing/DCFS_clean_8_27.csv')
#filter NA's in df addresses

#filter non-IL addresses

df_zip <- read.csv('C:/Users/jwini/OneDrive/Documents/Python Scripts/DCFS-Lead-Testing/DCFS_zip_8_27.csv')
df_county <- read.csv('C:/Users/jwini/OneDrive/Documents/Python Scripts/DCFS-Lead-Testing/DCFS_county_8_27.csv')
  

#add fips
df_county$fips <- fips("IL", county = df_county$county)


```

# DCFS Lead Analysis

# Latest Test Positive (Required Facilities)
\begin{itemize}
  \item Facilities required to test for lead that most recently tested positive for lead. A facility that is required to test meets the following criteria:
    \subitem Building date prior to January 1, 2000
    \subitem Provides childcare services for children ages 0 to 6.
  \item The \textbf{Latest Test Positive Percent} maps show what percentage of required facilities most recently tested positive for lead, $$\frac{Number\ of\ Positive}{Number\ of\ Positive + Number\ of\ Negative}$$ The \textbf{Latest Test Positive Count} maps show how many facilities tested positive for lead, of those required to test.
\end{itemize}

# First Test Positive (All Facilities)
\begin{itemize}
  \item The \textbf{Positive First Test (Percent)} maps show what percentage of facilities tested positive for lead on their first test, regardless of whether they were required to test based on the building age and age range of services offered $$\frac{Number\ of\ Positive}{Number\ of\ Positive\ +\ Number\ of\ Negative}$$
  \item The \textbf{Positive First Test (Count)} maps show how many facilities tested positive for lead.
\end{itemize}

# Should have Tested but Did Not (Required Facilities)
\begin{itemize}
  \item Facilities that are required to test for lead, but have yet to do so. A facility that is required to test meets the following criteria:
    \subitem Building date prior to January 1, 2000
    \subitem Provides childcare services for children ages 0 to 6.
    \subitem Note: This does NOT include facilities without a building date or no information about the age of the children services are provided for. This figures only include facilities we know for a fact needed to test, but did not. 
\end{itemize}


```{r, include=FALSE}
# FIPS Code Groups for Choropleth Maps
state = 'illinois'
cook_fips <- 17031
rockford_fips <- 17201
peoria_fips <- 17143
quincy_fips <- 17001
champaign_fips <- 17019
metro_fips <- c(17013, 17027, 17083, 17117, 17119, 17133, 17163) #bond, calhoun, clinton, jersey, macoupin, madison, monroe, st.clair
metro_msa <- 'St. Louis, MO-IL'
cook_will_dupage_fips <- c(17031,17197,17043, 17097)

```

## Latest Test Positive Count
```{r, echo=FALSE, warning=FALSE, message=FALSE, fig.width=11, height = 12}
#setup county
 
ltp_count_county <- df_county
names(ltp_count_county)[names(ltp_count_county)== 'fips'] <- "region"
names(ltp_count_county)[names(ltp_count_county)== 'ltp_count_bucket'] <- "value"

#ltp_count_county$value <- as.numeric(ltp_count_county$value)
ltp_count_county$region <- as.numeric(ltp_count_county$region)  

#Setup Zip
ltp_count_zip <- df_zip %>%
  mutate(region = as.character(zip))
#(ltp_count_zip)[names(ltp_count_zip)== 'zip'] <- "region"
names(ltp_count_zip)[names(ltp_count_zip)== 'ltp_count_bucket'] <- "value"

#ltp_count_zip$value <- as.numeric(ltp_count_zip$value)
#ltp_count_zip$region <- as.numeric(as.character(ltp_count_zip$region))
#ltp_count_zip[,"region"] <- as.numeric(factor(ltp_count_zip[,"region"]))

#Illinois
IL_latest_count <- county_choropleth(ltp_count_county,
               state_zoom = state,
               legend = "Count",
               num_colors = 7) +
  scale_fill_brewer(name = "Count of Facilities", palette='YlOrRd')+    ggtitle("Latest Test Exceeding Limit: Illinois (County)")+      theme(text = element_text(family = "Gotham Medium", color = "#7E0000"))
IL_latest_count


#Chicago
chi_latest_count <- zip_choropleth(ltp_count_zip,
               county_zoom = cook_fips,
               title = "Latest Test Positive: Cook County",
               legend = "Count",
               num_colors = 8) +
  scale_fill_brewer(name = "Count of Facilities", palette='YlOrRd')+    ggtitle("Latest Test Exceeding Limit: Cook County (Zip)")+      theme(text = element_text(family = "Gotham Medium", color = "#7E0000"))
chi_latest_count


```

```{r pdf, message=FALSE, warning=FALSE, include=FALSE, Lower Resolution, eval=FALSE}
#Illinois
pdf("C:/Users/jwini/OneDrive/Documents/Python Scripts/DCFS-Lead-Testing/LTP_count_Illinois.pdf")
IL_latest_count
dev.off()

#Cook
pdf("C:/Users/jwini/OneDrive/Documents/Python Scripts/DCFS-Lead-Testing/LTP_count_cook.pdf")
chi_latest_count
dev.off()



```


\newpage

# Should Have Tested But Didn't


```{r echo=FALSE, fig.width=10, message=FALSE, warning=FALSE}
 

# county
not_tested_county <- df_county
names(not_tested_county)[names(not_tested_county)== 'fips'] <- "region"
names(not_tested_county)[names(not_tested_county)== 'should_bucket'] <- "value"


not_tested_county$region <- as.numeric(not_tested_county$region)

#zip 

not_tested_zip <- df_zip
names(not_tested_zip)[names(not_tested_zip)== 'zip'] <- "region"
names(not_tested_zip)[names(not_tested_zip)== 'should_bucket'] <- "value"


#not_tested_zip$value <- as.numeric(not_tested_zip$value) 
not_tested_zip$region <- as.character(not_tested_zip$region) 

#Illinois

IL_should <- county_choropleth(not_tested_county,
                               state_zoom = state,
                               title = "Should Have Been Tested (County): Illinois",
                               num_colors = 8) +
  scale_fill_brewer(name = "Count of Facilities", palette='BuPu')+    ggtitle("Should Have Been Tested: Illinois (County)")+      theme(text = element_text(family = "Gotham Medium", color = "#7E0000"))
IL_should


#Chicago
chi_should <- zip_choropleth(not_tested_zip,
               county_zoom = cook_fips,
               title = "Should Have Been Tested (Zip): Cook County",
               legend = "Count",
               num_colors = 8) +
  scale_fill_brewer(name = "Count of Facilities", palette='BuPu')+    ggtitle("Should Have Been Tested: Cook County (Zip)")+      theme(text = element_text(family = "Gotham Medium", color = "#7E0000"))
chi_should




```

```{r pdf, message=FALSE, warning=FALSE, include=FALSE, Lower Resolution, eval=FALSE}
#Illinois
pdf("C:/Users/jwini/OneDrive/Documents/Python Scripts/DCFS-Lead-Testing/should_Illinois.pdf")
IL_should
dev.off()

#Cook
pdf("C:/Users/jwini/OneDrive/Documents/Python Scripts/DCFS-Lead-Testing/should_cook.pdf")
chi_should
dev.off()



```

# Any Test Positive (Count) 
```{r, echo=FALSE, warning=FALSE, message = FALSE, fig.width=10, height = 12}
#county setup
atp_count_county <- df_county

names(atp_count_county)[names(atp_count_county)== 'fips'] <- "region"
names(atp_count_county)[names(atp_count_county)== 'atp_count_bucket'] <- "value"
atp_count_county <- atp_count_county[c("region", "value")]

atp_count_county$region <- as.numeric(atp_count_county$region)


#setup map - zip

atp_count_zip <- df_zip
names(atp_count_zip)[names(atp_count_zip)== 'zip'] <- "region"
names(atp_count_zip)[names(atp_count_zip)== 'atp_count_bucket'] <- "value"


#atp_count_zip$value <- as.numeric(atp_count_zip$value)
atp_count_zip$region <- as.character(atp_count_zip$region)

#Illinois
IL_ATP_count <- county_choropleth(atp_count_county,
               state_zoom = state,
               title = "Any Test Exceeding Limit Count by County: Illinois",
               legend = "Count",
               num_colors = 8) +
  scale_fill_brewer(name = "Count of Facilities", palette='YlOrRd')+    ggtitle("Any Test Exceeding Limit Count: Illinois (County)")+ theme(text = element_text(family = "Gotham Medium", color = "#7E0000"))


#Chicago
chi_ATP_count <- zip_choropleth(atp_count_zip,
               county_zoom = cook_fips,
               title = "Any Test Exceeding Limit Count by Zip: Cook County",
               legend = "Count",
               num_colors = ) +
  scale_fill_brewer(name = "Count of Facilities", palette='YlOrRd')+    ggtitle("Any Test Exceeding Limit Count: Cook County (Zip)")+      theme(text = element_text(family = "Gotham Medium", color = "#7E0000"))




IL_ATP_count
chi_ATP_count

# 17015, 17013, 17027, 17083, 170117, 170119, 170133, 170163
```

```{r pdf, echo=FALSE, message=FALSE, warning=FALSE, Lower Resolution, eval=FALSE}
#Illinois
pdf("C:/Users/jwini/OneDrive/Documents/Python Scripts/DCFS-Lead-Testing/ATP_count_Illinois.pdf")
IL_ATP_count
dev.off()

#Cook
pdf("C:/Users/jwini/OneDrive/Documents/Python Scripts/DCFS-Lead-Testing/ATP_count_cook.pdf")
chi_ATP_count
dev.off()


```





# ATP Children Maps

```{r, echo=FALSE, warning=FALSE, message = FALSE, fig.width=11, height = 12}
#county setup
atp_max_county <- df_county

names(atp_max_county)[names(atp_max_county)== 'fips'] <- "region"
names(atp_max_county)[names(atp_max_county)== 'atp_mc_bucket'] <- "value"
atp_max_county <- atp_max_county[c("region", "value")]

atp_max_county$region <- as.numeric(atp_max_county$region)


#setup map - zip

atp_max_zip <- df_zip
names(atp_max_zip)[names(atp_max_zip)== 'zip'] <- "region"
names(atp_max_zip)[names(atp_max_zip)== 'atp_mc_bucket'] <- "value"

atp_max_zip$region <- as.character(atp_max_zip$region)
#atp_max_county$value <- as.numeric(atp_max_county$value)


#Illinois
IL_ATP_child_count <- county_choropleth(atp_max_county,
               state_zoom = state,
               title = "Max Capacity at Facilities Exceeding Limit: Illinois (County)",
               legend = "Number of Children",
               num_colors = 8) +
  scale_fill_brewer(name = "Number of Children", palette='YlOrRd')+    ggtitle("Max Capacity at Facilities Exceeding Limit: Illinois (County)")+ theme(text = element_text(family = "Gotham Medium", color = "#7E0000"))
IL_ATP_child_count

#Chicago
chi_ATP_child_count <- zip_choropleth(atp_max_zip,
               county_zoom = cook_fips,
               title = "Max Capacity of Children at Facilities that Tested Exceeding Limit by Zip: Cook County",
               legend = "Number of Children",
               num_colors = 8) +
  scale_fill_brewer(name = "Number of Children", palette='YlOrRd')+    ggtitle("Max Capacity at Facilities Exceeding Limit: Cook County (Zip)")+      theme(text = element_text(family = "Gotham Medium", color = "#7E0000"))
chi_ATP_child_count

```

```{r pdf, message=FALSE, warning=FALSE, include=FALSE, Lower Resolution, eval=FALSE}
#Illinois
pdf("C:/Users/jwini/OneDrive/Documents/Python Scripts/DCFS-Lead-Testing/ATP_child_count_Illinois.pdf")
IL_ATP_child_count
dev.off()

#Cook
pdf("C:/Users/jwini/OneDrive/Documents/Python Scripts/DCFS-Lead-Testing/ATP_child_count_cook.pdf")
chi_ATP_child_count
dev.off()


```

# LTP Children Maps

```{r, echo=FALSE, warning=FALSE, message = FALSE, fig.width=11, height = 12}
#county setup
ltp_max_county <- df_county

names(ltp_max_county)[names(ltp_max_county)== 'fips'] <- "region"
names(ltp_max_county)[names(ltp_max_county)== 'ltp_mc_bucket'] <- "value"
ltp_max_county <- ltp_max_county[c("region", "value")]

ltp_max_county$region <- as.numeric(ltp_max_county$region)


#setup map - zip

ltp_max_zip <- df_zip
names(ltp_max_zip)[names(ltp_max_zip)== 'zip'] <- "region"
names(ltp_max_zip)[names(ltp_max_zip)== 'ltp_mc_bucket'] <- "value"

ltp_max_zip$region <- as.character(ltp_max_zip$region)
#ltp_max_county$value <- as.numeric(ltp_max_county$value)


#Illinois
IL_LTP_child_count <- county_choropleth(ltp_max_county,
               state_zoom = state,
               title = "Max Capacity of Children at Facilities Exceeding Limit: Illinois (County)",
               legend = "Number of Children",
               num_colors = 8) +
  scale_fill_brewer(name = "Number of Children", palette='YlOrRd')+    ggtitle("Max Capacity of Children, Latest Test Exceeding Limit: Illinois (County)")+ theme(text = element_text(family = "Gotham Medium", color = "#7E0000"))
IL_LTP_child_count

#Chicago
chi_LTP_child_count <- zip_choropleth(ltp_max_zip,
               county_zoom = cook_fips,
               title = "Max Capacity, Latest Test Positive Facilities by Zip: Cook County",
               legend = "Number of Children",
               num_colors = 9) +
  scale_fill_brewer(name = "Number of Children", palette='YlOrRd')+    ggtitle("Max Capacity of Children, Latest Test Exceeding Limit: Cook County (Zip)")+      theme(text = element_text(family = "Gotham Medium", color = "#7E0000"))
chi_LTP_child_count

```


```{r pdf, message=FALSE, warning=FALSE, include=FALSE, Lower Resolution, eval=FALSE}
#Illinois
pdf("C:/Users/jwini/OneDrive/Documents/Python Scripts/DCFS-Lead-Testing/LTP_child_count_Illinois.pdf")
IL_LTP_child_count
dev.off()

#Cook
pdf("C:/Users/jwini/OneDrive/Documents/Python Scripts/DCFS-Lead-Testing/LTP_child_count_cook.pdf")
chi_LTP_child_count
dev.off()


```



\newpage


\newpage

# Should Have Tested But Didn't


```{r echo=FALSE, fig.width=10, message=FALSE, warning=FALSE}
 

# county
not_tested_county <- df_county
names(not_tested_county)[names(not_tested_county)== 'fips'] <- "region"
names(not_tested_county)[names(not_tested_county)== 'should_bucket'] <- "value"


not_tested_county$region <- as.numeric(not_tested_county$region)

#zip 

not_tested_zip <- df_zip
names(not_tested_zip)[names(not_tested_zip)== 'zip'] <- "region"
names(not_tested_zip)[names(not_tested_zip)== 'should_bucket'] <- "value"


#not_tested_zip$value <- as.numeric(not_tested_zip$value) 
not_tested_zip$region <- as.character(not_tested_zip$region) 

#Illinois

IL_should <- county_choropleth(not_tested_county,
                               state_zoom = state,
                               title = "Should Have Been Tested (County): Illinois",
                               num_colors = 8) +
  scale_fill_brewer(name = "Count of Facilities", palette='YlOrRd')+    ggtitle("Should Have Been Tested: Illinois (County)")+      theme(text = element_text(family = "Gotham Medium", color = "#7E0000"))
IL_should


#Chicago
chi_should <- zip_choropleth(not_tested_zip,
               county_zoom = cook_fips,
               title = "Should Have Been Tested (Zip): Cook County",
               legend = "Count",
               num_colors = 8) +
  scale_fill_brewer(name = "Count of Facilities", palette='YlOrRd')+    ggtitle("Should Have Been Tested: Cook County (Zip)")+      theme(text = element_text(family = "Gotham Medium", color = "#7E0000"))
chi_should




```

```{r pdf, message=FALSE, warning=FALSE, include=FALSE, Lower Resolution, eval=FALSE}
#Illinois
pdf("C:/Users/jwini/OneDrive/Documents/Python Scripts/DCFS-Lead-Testing/should_Illinois.pdf")
IL_should
dev.off()

#Cook
pdf("C:/Users/jwini/OneDrive/Documents/Python Scripts/DCFS-Lead-Testing/shouldt_cook.pdf")
chi_should
dev.off()


```

# Any Test Positive (Count) 
```{r, echo=FALSE, warning=FALSE, message = FALSE, fig.width=10, height = 12}
#county setup
atp_count_county <- df_county

names(atp_count_county)[names(atp_count_county)== 'fips'] <- "region"
names(atp_count_county)[names(atp_count_county)== 'atp_count_bucket'] <- "value"
atp_count_county <- atp_count_county[c("region", "value")]

atp_count_county$region <- as.numeric(atp_count_county$region)


#setup map - zip

atp_count_zip <- df_zip
names(atp_count_zip)[names(atp_count_zip)== 'zip'] <- "region"
names(atp_count_zip)[names(atp_count_zip)== 'atp_count_bucket'] <- "value"


#atp_count_zip$value <- as.numeric(atp_count_zip$value)
atp_count_zip$region <- as.character(atp_count_zip$region)

#Illinois
IL_ATP_count <- county_choropleth(atp_count_county,
               state_zoom = state,
               title = "Any Test Exceeding Limit Count by County: Illinois",
               legend = "Count",
               num_colors = 8) +
  scale_fill_brewer(name = "Count of Facilities", palette='YlOrRd')+    ggtitle("Any Test Exceeding Limit Count: Illinois (County)")+ theme(text = element_text(family = "Gotham Medium", color = "#7E0000"))


#Chicago
chi_ATP_count <- zip_choropleth(atp_count_zip,
               county_zoom = cook_fips,
               title = "Any Test Exceeding Limit Count by Zip: Cook County",
               legend = "Count",
               num_colors = ) +
  scale_fill_brewer(name = "Count of Facilities", palette='YlOrRd')+    ggtitle("Any Test Exceeding Limit Count: Cook County (Zip)")+      theme(text = element_text(family = "Gotham Medium", color = "#7E0000"))


IL_ATP_count
chi_ATP_count

# 17015, 17013, 17027, 17083, 170117, 170119, 170133, 170163
```

```{r pdf, message=FALSE, warning=FALSE, include=FALSE, Lower Resolution, eval=FALSE}
#Illinois
pdf("C:/Users/jwini/OneDrive/Documents/Python Scripts/DCFS-Lead-Testing/ATP_count_Illinois.pdf")
IL_ATP_count
dev.off()

#Cook
pdf("C:/Users/jwini/OneDrive/Documents/Python Scripts/DCFS-Lead-Testing/ATP_count_cook.pdf")
chi_ATP_count
dev.off()

```


# ATP Children Maps

```{r, echo=FALSE, warning=FALSE, message = FALSE, fig.width=11, height = 12}
#county setup
atp_max_county <- df_county

names(atp_max_county)[names(atp_max_county)== 'fips'] <- "region"
names(atp_max_county)[names(atp_max_county)== 'atp_mc_bucket'] <- "value"
atp_max_county <- atp_max_county[c("region", "value")]

atp_max_county$region <- as.numeric(atp_max_county$region)


#setup map - zip

atp_max_zip <- df_zip
names(atp_max_zip)[names(atp_max_zip)== 'zip'] <- "region"
names(atp_max_zip)[names(atp_max_zip)== 'atp_mc_bucket'] <- "value"

atp_max_zip$region <- as.character(atp_max_zip$region)
#atp_max_county$value <- as.numeric(atp_max_county$value)


#Illinois
IL_ATP_child_count <- county_choropleth(atp_max_county,
               state_zoom = state,
               title = "Max Capacity at Facilities Exceeding Limit: Illinois (County)",
               legend = "Number of Children",
               num_colors = 8) +
  scale_fill_brewer(name = "Number of Children", palette='YlOrRd')+    ggtitle("Max Capacity at Facilities Exceeding Limit: Illinois (County)")+ theme(text = element_text(family = "Gotham Medium", color = "#7E0000"))
IL_ATP_child_count

#Chicago
chi_ATP_child_count <- zip_choropleth(atp_max_zip,
               county_zoom = cook_fips,
               title = "Max Capacity of Children at Facilities that Tested Exceeding Limit by Zip: Cook County",
               legend = "Number of Children",
               num_colors = 8) +
  scale_fill_brewer(name = "Number of Children", palette='YlOrRd')+    ggtitle("Max Capacity at Facilities Exceeding Limit: Cook County (Zip)")+      theme(text = element_text(family = "Gotham Medium", color = "#7E0000"))
chi_ATP_child_count

```

```{r pdf, message=FALSE, warning=FALSE, include=FALSE, Lower Resolution, eval=FALSE}
#Illinois
pdf("C:/Users/jwini/OneDrive/Documents/Python Scripts/DCFS-Lead-Testing/ATP_child_count_Illinois.pdf")
IL_ATP_child_count
dev.off()

#Cook
pdf("C:/Users/jwini/OneDrive/Documents/Python Scripts/DCFS-Lead-Testing/ATP_child_count_cook.pdf")
chi_ATP_child_count
dev.off()

```

# LTP Children Maps

```{r, echo=FALSE, warning=FALSE, message = FALSE, fig.width=12, height = 12}
#county setup
ltp_max_county <- df_county

names(ltp_max_county)[names(ltp_max_county)== 'fips'] <- "region"
names(ltp_max_county)[names(ltp_max_county)== 'ltp_mc_bucket'] <- "value"
ltp_max_county <- ltp_max_county[c("region", "value")]

ltp_max_county$region <- as.numeric(ltp_max_county$region)


#setup map - zip

ltp_max_zip <- df_zip
names(ltp_max_zip)[names(ltp_max_zip)== 'zip'] <- "region"
names(ltp_max_zip)[names(ltp_max_zip)== 'ltp_mc_bucket'] <- "value"

ltp_max_zip$region <- as.character(ltp_max_zip$region)
#ltp_max_county$value <- as.numeric(ltp_max_county$value)


#Illinois
IL_LTP_child_count <- county_choropleth(ltp_max_county,
               state_zoom = state,
               title = "Max Capacity of Children at Facilities Exceeding Limit: Illinois (County)",
               legend = "Number of Children",
               num_colors = 8) +
  scale_fill_brewer(name = "Number of Children", palette='YlOrRd')+    ggtitle("Max Capacity of Children, Latest Test Exceeding Limit: Illinois (County)")+ theme(text = element_text(family = "Gotham Medium", color = "#7E0000"))
IL_LTP_child_count

#Chicago
chi_LTP_child_count <- zip_choropleth(ltp_max_zip,
               county_zoom = cook_fips,
               title = "Max Capacity, Latest Test Positive Facilities by Zip: Cook County",
               legend = "Number of Children",
               num_colors = ) +
  scale_fill_brewer(name = "Number of Children", palette='YlOrRd')+    ggtitle("Max Capacity of Children, Latest Test Exceeding Limit: Cook County (Zip)")+      theme(text = element_text(family = "Gotham Medium", color = "#7E0000"))
chi_LTP_child_count

```


```{r pdf, message=FALSE, warning=FALSE, include=FALSE, Lower Resolution, eval=FALSE}
#Illinois
pdf("C:/Users/jwini/OneDrive/Documents/Python Scripts/DCFS-Lead-Testing/LTP_child_count_Illinois.pdf")
IL_LTP_child_count
dev.off()

#Cook
pdf("C:/Users/jwini/OneDrive/Documents/Python Scripts/DCFS-Lead-Testing/LTP_child_count_cook.pdf")
chi_LTP_child_count
dev.off()


```




# Latest Test Positive Choropleth, LTP Children Bubble

```{r, echo=FALSE, warning=FALSE, message = FALSE, fig.width=10, height = 12}
#county setup
atp_count_county <- df_county

names(atp_count_county)[names(atp_count_county)== 'fips'] <- "region"
names(atp_count_county)[names(atp_count_county)== 'atp_count_bucket'] <- "value"
atp_count_county <- atp_count_county[c("region", "value", "atp_max_capacity_req")]

atp_count_county$region <- as.numeric(atp_count_county$region)


bubble <- atp_count_county 
names(bubble)[names(bubble)== "value"] <- "atp_count_bucket"
names(bubble)[names(bubble)== "atp_max_capacity_req"] <- "value"

#setup map - zip

atp_count_zip <- df_zip
names(atp_count_zip)[names(atp_count_zip)== 'zip'] <- "region"
names(atp_count_zip)[names(atp_count_zip)== 'atp_count_bucket'] <- "value"
atp_count_zip <- atp_count_zip[c("region", "value", "atp_max_capacity_req")]

#atp_count_zip$value <- as.numeric(atp_count_zip$value)
atp_count_zip$region <- as.character(atp_count_zip$region)


#Illinois
IL_ATP_count <- county_choropleth(atp_count_county,
               state_zoom = state,
               title = "Any Test Exceeding Limit Count by County: Illinois",
               legend = "Count",
               num_colors = 8) +
geom_sf(pch = 21,
          aes(size = 'atp_max_capacity_req'),
          fill = alpha("red", 0.7),
          col = "grey20") +
  scale_fill_brewer(name = "Count of Facilities", palette='YlOrRd')+    ggtitle("Any Test Exceeding Limit Count: Illinois (County)")+ theme(text = element_text(family = "Gotham Medium", color = "#7E0000"))


#Chicago
chi_ATP_count <- zip_choropleth(atp_count_zip,
               county_zoom = cook_fips,
               title = "Any Test Exceeding Limit Count by Zip: Cook County",
               legend = "Count",
               num_colors = ) +
  scale_fill_brewer(name = "Count of Facilities", palette='YlOrRd')+    ggtitle("Any Test Exceeding Limit Count: Cook County (Zip)")+      theme(text = element_text(family = "Gotham Medium", color = "#7E0000"))


IL_ATP_count
chi_ATP_count

# 17015, 17013, 17027, 17083, 170117, 170119, 170133, 170163
```






## Waffle Chart

```{r}
cook_df <- df_county %>%
  filter(county == "Cook County") %>%
  summarise(not_positive = sum(required_testing_tested - any_test_positive_req),
            any_test_positive_req = sum(any_test_positive_req),
            latest_test_positive_req = sum(latest_test_positive_required))

cook_df <- gather(cook_df, testing_type, count_facilities, not_positive:latest_test_positive_req)

cook_df$count_facilities <- cook_df$count_facilities / 20

waffle(cook_df, rows = 5, size = .5, legend_pos = "bottom",
  colors = c("#c7d4b6", "#a3aabd", "#a0d0de"))





```

# Required to Test

```{r}
cook_df_req <- df_county %>%
  filter(county == "Cook County") %>%
  summarise(any_test_neg_req = sum(required_testing_tested-any_test_positive_req),
            no_test = sum(required_testing_not_tested),
            any_test_positive_req = sum(any_test_positive_req))

cook_df <- gather(cook_df_req, testing_type, count_facilities, 1:3)

cook_df$count_facilities <- cook_df$count_facilities / 20

required_waffle <- waffle(cook_df, rows = 5, size = .5, legend_pos = "bottom",
  colors = c("#c7d4b6", "gold1", "orangered4"))




pdf("C:/Users/jwini/OneDrive/Documents/Python Scripts/DCFS-Lead-Testing/required_waffles.pdf")
required_waffle
dev.off()

```