Make a map of where people in the UK vote

CenterUKVoting.r

Now start with maps and locations

See if i can get the center of constituencies
data from https://geoportal.statistics.gov.uk/datasets/westminster-parliamentary-constituencies-december-2017-super-generalised-clipped-boundaries-in-the-uk/data

```{r}

locat<-read_csv("Westminster_Parliamentary_Constituencies_December_2017_Super_Generalised_Clipped_Boundaries_in_the_UK.csv")#, sheet = 2, skip=6 , header=TRUE
head(locat)

```



```{r}
# xls files
election<-read_excel("Current-Parliament-Election-Results.xlsx", sheet = 3)
head(election)
```

```{r}
unique(election$CandidateParty)
```

Plaid Cymru
UK Independence Party
Sinn Fein
Democratic Unionist Party
Scottish National Party

Ok this works lets try it with just Conservative candidates
1 Load everyone in the first node into election

Conservative
Liberal Democrat
Labour

```{r}
library(tidyverse)
election <-
  election %>%
  filter(CandidateParty=="UK Independence Party")
head(election)
```

Now combine this with the consituency location data above

```{r}
where<-merge(locat, election, by.x="pcon17nm", by.y="ConstituencyName")
head(where)
```

I did this before at https://gist.github.com/cavedave/ed66f1961e144adb14c9898e58b42ff7

Get total number of Conservative votes
Votes 13147245
https://en.wikipedia.org/wiki/2017_United_Kingdom_general_election
says 13,636,684

Labour votes 11042160
Liberal Democrat 2264797
Scottish National Party 971555
DUP 292316
SF 238915
Plaid Cymru 160620
UK Independence Party 575660


```{r}
sum(where$Votes)
```

Now order by longitude

long
<dbl>
lat
<dbl>



```{r}


where<-where[order(where$long),]
head(where)
```

```{r}
tail(where)
```


```{r}
thresholdValue <- (575660/2)



#head east until you have counted half the people
where<-where[order(where$long),]

ix <- length(which(cumsum(where$Votes) <= thresholdValue))
first<-where[ix,]$long

#head east until you have counted half the people
where<-where[order(where$lat),]

iy <- length(which(cumsum(where$Votes) <= thresholdValue))
second<-where[iy,]$lat




```



```{r}
first
```

```{r}
second
```
Conservative -1.3548  52.114
Labour -1.4682 52.4867
Liberal Democrat -1.3942 51.6339
Population in total -1.317, y =52.442
SNP -3.9501 55.9377
Liberal Democrats -1.3942 51.6339
DUP -6.2016 54.595
SF -6.7131 54.5684 Sinn Féin
PC -3.9222 51.7883 	#008142
Ukip   -1.2537 52.3466 70147A

```{r}
library("ggplot2")
theme_set(theme_bw())
library("sf")
library(maps)


```



```{r}
library(sf)
library(raster)
library(dplyr)
library(spData)
#library(spDataLarge)
```



```{r}
library(tmap)    # for static and interactive maps
library(leaflet) # for interactive maps
library(mapview) # for interactive maps
library(ggplot2) # tidyverse data visualization package
library(shiny)   # for web applications
```

```{r}
library(ggplot2)
library(ggmap)
library(maps)
library(mapdata)
```




```{r}


usa <- map_data(map = "world", region = "UK")

p<-ggplot() + 
  geom_polygon(data = usa, aes(x=long, y = lat, group = group), fill = NA, color = "black") + 
  coord_fixed(1.3)+

 
  #  Conservative -1.3548  52.114
    annotate("point", x = -1.3548, y =52.114, colour = "#0087DC", size = 4)+
            annotate(geom="text", x = -1.3548, y =52.014, label="Conservative",color="#0087DC",size = 5)+

#Labour -1.4682 52.4867
      annotate("point", x = -1.4682, y =52.4867, colour = "#DC241f", size = 4)+
          annotate(geom="text", x=-1.6582, y=52.682, label="Labour",
              color="#DC241f",size = 5)+
#Liberal Democrat -1.3942 51.6339
        annotate("point", x = -1.3942, y =51.6339, colour = "#FAA61A", size = 4)+
          annotate(geom="text", x=-.88042, y =51.6339, label="Lib Dem",
              color="#FAA61A",size = 5)+
#Population in total -1.317, y =52.442
        annotate("point", x = -1.317, y =52.442, colour = "black", size = 4)+
        annotate(geom="text", x=-1.317, y=52.302, label="Population",
              color="black",size = 5)+
#snp -3.9501 55.9377
        annotate("point", x = -3.9501, y =55.9377, colour = "navy", size = 4)+##FDF38E
      annotate(geom="text", x=-3.950, y=55.7377, label="SNP",
              color="navy",size = 5)+
#DUP -6.2016 54.595
        annotate("point", x = -6.2016, y =54.595, colour = "#D46A4C", size = 4)+ 
    annotate(geom="text", x=-6.0016, y=54.395, label="DUP",
              color="#D46A4C",size = 5)+
#SF -6.7131 54.5684 Sinn Féin
        annotate("point", x = -6.7131, y =54.5684, colour = "#326760", size = 4)+
  annotate(geom="text", x=-6.7131, y=54.7684, label="Sinn Féin",
              color="#326760",size = 5)+
#PC -3.9222 51.7883 	#008142
        annotate("point", x = -3.9222, y =51.7883, colour = "#008142", size = 4)+ 
    annotate(geom="text", x = -3.2022, y =51.7883, label="Plaid Cymru",
              color="#008142",size = 5)+
#Ukip   -1.2537 52.3466 70147A
        annotate("point", x = -1.2537, y =52.5466, colour = "#70147A", size = 4) +
annotate(geom="text", x=-0.9037, y=52.5466, label="UKIP",
              color="#70147A",size = 5)+
  #theme(plot.title = element_text(size=22),plot.title = element_text(hjust = 0.5))
theme_classic()+
  
theme(line = element_blank(),
        #text = element_blank(),
  axis.text.x=element_blank(),
        axis.ticks.x=element_blank(),
      axis.text.y =element_blank(),
        axis.ticks.y=element_blank(),
        plot.title = element_text(size = 17, face = "bold",hjust = 0.5))+
   ggtitle("Center of Voting of UK parties",
              subtitle = "Half voters are North and half East of thier parties point")+

ggsave("VotingCentre.png",height=15, width=10)
p
```