---
title: "Reproducing Maps"
author: ""
date: "`r Sys.Date()`"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Reproducing Maps}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r setup, include = FALSE}

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  message = FALSE, warning = FALSE
)
knitr::opts_chunk$set(error = TRUE)
```
```{r libraries}
library(dplyr)
library(ggplot2)
library(knitr)
library(tidyr)
library(salem)
```
### Maps

We can use maps to represent the geographic distribution over time 
spatially.  The salem_region data set is an sf (simple features) data 
set that provides geographic data for the towns in the three Massachuessets 
counties represented in our data: Essex, Middlesex and Sussex. 

To use this data you will need to install the sf package. The code at the
start of the second code chunk tests for whether you have done this.

Not all of the towns in these three counties
had accusations: the majority did not. The data also include the total
accused for each town and the monthly accused for the towns that ever had an 
accusation. However, these variables should _never_ be used outside of maps
because the results will be incorrect. 
This is because many towns have multiple records. This is especially true if 
they include islands, which is common in this region of the state. 
These are based on modern municipal boundaries which are close to
but not the same as the historical ones. There are many geographic analyses
that can be done. Below a comparison of the distribution of whether towns
had at least on accusation in each of four months
is given.

First, create variables indicating whether towns did or did not have 
an accusation in a month and remove the TOWN_LABELs for all the towns that never
had an accusation.

Here `requireNamespace` is used to check whether the `sf` package is installed.
That is because `sf` is only suggested and not required. It can be complex to
install on some computers.

```{r}
if (!requireNamespace("sf", quietly = TRUE)) {
      knitr::knit_exit()
}
```


```{r eval=TRUE,fig.width=8, fig.height=8}
# Set up some common elements.



      p1 <- ggplot(salem_region)  +
             geom_sf_text(aes(label = TOWN_LABEL), color = "blue", size = 2, 
                              nudge_x = 5,
                               nudge_y = 5, na.rm = TRUE) 
        p2 <- scale_fill_manual(values = c( "grey", "red"), na.value = "white") 


```

```{r eval=TRUE}


newdata <- salem_region |> mutate(February.Any = February > 0, 
                                       March.Any = March > 0,
                                   April.Any = April > 0, May.Any = May > 0,
                                   June.Any = June > 0, July.Any = July > 0,
                                   August.Any = August > 0,
                                   September.Any = September >0,
                                   October.Any = October > 0,
                                   November.Any = November > 0,
                                   TOWN_LABEL = ifelse(n_accused == 0, 
                                                       NA,  TOWN_LABEL)
                                   )

```



```{r eval=TRUE,fig.width=6, fig.height=6}

      p1  + geom_sf(data = newdata,  
                    aes(geometry = geometry,  fill = February.Any
                        ), color = "black", 
                    size = .1)+
                   labs(title = "Location of Accusations in February") +
                   scale_fill_manual(values = c( "grey", "red"), na.value = "white",
                                     labels = c("None", "At least 1", "Never"))  +
                  theme(legend.title = element_blank(), legend.position = "bottom")

      p1  + geom_sf(data = newdata,  
                    aes(geometry = geometry,  fill = March.Any
                        ), color = "black", 
                    size = .1)+
                   labs(title = "Location of Accusations in March") +
                   scale_fill_manual(values = c( "grey", "red"), na.value = "white",
                                     labels = c("None", "At least 1", "Never"))  +
                  theme(legend.title = element_blank(), legend.position = "bottom")
      
      p1  + geom_sf(data = newdata,  
                    aes(geometry = geometry,  fill = April.Any
                        ), color = "black", 
                    size = .1)+
                   labs(title = "Location of Accusations in April") +
                  scale_fill_manual(values = c( "grey", "red"), na.value = "white",
                                    labels = c("None", "At least 1", "Never")) +
                  theme(legend.title = element_blank(), legend.position = "bottom")
      
      p1 +  geom_sf(data = newdata, 
                    aes(geometry = geometry, fill = July.Any), 
                    color = "black", size = .1) +
                    labs(title = "Location of Accusations in July") +
                    scale_fill_manual(values = c( "grey", "red"), na.value = "white",
                                      labels = c("None", "At least 1", "Never")) +
                  theme(legend.title = element_blank(), legend.position = "bottom")
  
      p1 + geom_sf(data = newdata,  
                   aes(fill = August.Any, geometry = geometry), 
                   color = "black", 
                   size = .1) +
                  labs(title = "Location of Accusations in August",
                       labels = c("None", "At least 1", "Never")) +
                  scale_fill_manual(values = c( "grey", "red"), na.value = "white",
                                    labels = c("None", "At least 1", "Never")) +
                  theme(legend.title = element_blank(), legend.position = "bottom")
      
       p1 + geom_sf(data = newdata,  
                   aes(fill = October.Any, geometry = geometry), 
                   color = "black",
                   size = .1) +
                   labs(title = "Location of Accusations in October",
                        ) +
                  scale_fill_manual(values = c( "grey", "red"), na.value = "white",
                                    labels = c("None", "At least 1", "Never"))  +
                  theme(legend.title = element_blank(), legend.position = "bottom") 
      p1 + geom_sf(data = newdata,  
                   aes(fill = November.Any, geometry = geometry), 
                   color = "black",
                   size = .1) +
                   labs(title = "Location of Accusations in November") +
                   scale_fill_manual(values = c( "grey", "red"), na.value = "white",
                                    labels = c("None", "At least 1", "Never"))  +
                   theme(legend.title = element_blank(), legend.position = "bottom")

```