Our group aims to examine religious adherence in multiple ways throughout the United States. The first portion of this project, which focused on reproducing the data of the original author can be found here: http://rpubs.com/aray/religious_adherence

Jason’s Analysis

While comparing the 6 states that are scattered across the US, some similarities and differences are observed. These states, with the exception of Texas, seem to have only a few regions where the religious adherence rate is high. Texas, on the other hand, has many more high adherence regions to portray their strong religious beliefs. Religious adherence rate appears to increase in the central part of the US. Observing from the US country religious adherence data, other states such as North and South Dakota, which are located in the central part of the US, also seem to have high religious adherence rate like Texas.

library(foreign) 
counties <- read.spss("U.S. Religion Census Religious Congregations and Membership Study, 2010 (County File).SAV", to.data.frame = TRUE)
library(choroplethr)
library(ggplot2)
library(viridis)
counties <- counties[!is.na(counties$TOTRATE),]
counties$region <- counties$FIPS
counties$value <- counties$TOTRATE
counties[(counties$value > 1000),'value'] <- 1000.
choro = CountyChoropleth$new(counties)
choro$title = "Total Religious Adherents by County"
choro$set_num_colors(1)
choro$ggplot_polygon = geom_polygon(aes(fill = value), color = NA)
choro$ggplot_scale = scale_fill_gradientn(name = "Adherence raten(per 1000 population)", colours = viridis(32), limits = c(0, 1000))
choro$render()

choro = CountyChoropleth$new(counties)
choro$title = "Total Religious Adherents in California"
choro$set_num_colors(1)
choro$set_zoom("california")
choro$ggplot_polygon = geom_polygon(aes(fill = value), color = NA)
choro$ggplot_scale = scale_fill_gradientn(name = "Adherence raten(per 1000 population)", colours = viridis(32))
choro$render()

choro = CountyChoropleth$new(counties)
choro$title = "Total Religious Adherents in Washington"
choro$set_num_colors(1)
choro$set_zoom("washington")
choro$ggplot_polygon = geom_polygon(aes(fill = value), color = NA)
choro$ggplot_scale = scale_fill_gradientn(name = "Adherence raten(per 1000 population)", colours = viridis(32))
choro$render()

choro = CountyChoropleth$new(counties)
choro$title = "Total Religious Adherents in Colorado"
choro$set_num_colors(1)
choro$set_zoom("colorado")
choro$ggplot_polygon = geom_polygon(aes(fill = value), color = NA)
choro$ggplot_scale = scale_fill_gradientn(name = "Adherence raten(per 1000 population)", colours = viridis(32))
choro$render()

choro = CountyChoropleth$new(counties)
choro$title = "Total Religious Adherents in Texas"
choro$set_num_colors(1)
choro$set_zoom("texas")
choro$ggplot_polygon = geom_polygon(aes(fill = value), color = NA)
choro$ggplot_scale = scale_fill_gradientn(name = "Adherence raten(per 1000 population)", colours = viridis(32))
choro$render()

choro = CountyChoropleth$new(counties)
choro$title = "Total Religious Adherents in Florida"
choro$set_num_colors(1)
choro$set_zoom("florida")
choro$ggplot_polygon = geom_polygon(aes(fill = value), color = NA)
choro$ggplot_scale = scale_fill_gradientn(name = "Adherence raten(per 1000 population)", colours = viridis(32))
choro$render()

choro = CountyChoropleth$new(counties)
choro$title = "Total Religious Adherents in Maine"
choro$set_num_colors(1)
choro$set_zoom("maine")
choro$ggplot_polygon = geom_polygon(aes(fill = value), color = NA)
choro$ggplot_scale = scale_fill_gradientn(name = "Adherence raten(per 1000 population)", colours = viridis(32))
choro$render()

Nate’s Analysis

Overall, adherence rates for all religions in Massachusetts is relatively low, except for rates near the Boston area. It appears as though that religions other than Black Protestant, Catholic, and Muslim are very popular in Martha’s Vineyard, off of the south-western coast of Cape Cod. This seems to be an interesting finding, because the reason for this extremely high “Other” religious adherence rates doesn’t seem to be very obvious. Black Protestant adherence rates are very low throughout the state, but have two hot-spots: In the Boston area, and in the south-central region of Massachusetts. Catholic adherence rates are pretty high overall throughout the state, except for Martha’s Vineyard. Lastly, Muslim adherence rates are extremely low throughout the state, except in the Boston area.

#Total Religious Adherents in Mass:
 choro = CountyChoropleth$new(counties)
 choro$title = "Total Religious Adherents in Massachusetts"
 choro$set_num_colors(1)
 choro$set_zoom("massachusetts")
 choro$ggplot_polygon = geom_polygon(aes(fill = value), color = NA)
 choro$ggplot_scale = scale_fill_gradientn(name = "Adherence raten(per 1000 population)", colours = viridis(32))
 choro$render()

#Muslims in Massachusetts:
counties$value <- counties$MSLMRATE
choro = CountyChoropleth$new(counties)
choro$title = "Muslims in Massachusetts"
choro$set_num_colors(1)
choro$set_zoom("massachusetts")
choro$ggplot_polygon = geom_polygon(aes(fill = value), color = NA)
choro$ggplot_scale = scale_fill_gradientn(name = "Adherence raten(per 1000 population)", colours = viridis(32))
choro$render()
## Warning in self$bind(): The following regions were missing and are being
## set to NA: 25007, 25023, 25003, 25011, 25019

#Catholics in Massachusetts:
counties$value <- counties$CATHRATE
choro = CountyChoropleth$new(counties)
choro$title = "Catholics in Massachusetts"
choro$set_num_colors(1)
choro$set_zoom("massachusetts")
choro$ggplot_polygon = geom_polygon(aes(fill = value), color = NA)
choro$ggplot_scale = scale_fill_gradientn(name = "Adherence raten(per 1000 population)", colours = viridis(32))
choro$render()

#Black Protestants in Massachusetts:
counties$value <- counties$BPRTRATE
choro = CountyChoropleth$new(counties)
choro$title = "Black Protestants in Massachusetts"
choro$set_num_colors(1)
choro$set_zoom("massachusetts")
choro$ggplot_polygon = geom_polygon(aes(fill = value), color = NA)
choro$ggplot_scale = scale_fill_gradientn(name = "Adherence raten(per 1000 population)", colours = viridis(32))
choro$render()
## Warning in self$bind(): The following regions were missing and are being
## set to NA: 25007, 25021, 25001, 25011, 25019

#Other Religious Adherents in Massachusetts:
counties$value <- counties$OTHRATE
choro = CountyChoropleth$new(counties)
choro$title = "Other Religious Adherents in Massachusetts"
choro$set_num_colors(1)
choro$set_zoom("massachusetts")
choro$ggplot_polygon = geom_polygon(aes(fill = value), color = NA)
choro$ggplot_scale = scale_fill_gradientn(name = "Adherence raten(per 1000 population)", colours = viridis(32))
choro$render()

Abby’s Analysis

The aim of my analysis was to analyze the total religious adherence of Massachusetts and its neighbors to see if Massachusetts is unique in some way. The results of this analysis were that Massachusetts does seem to have a different level of religious adherence than its neighbors. Though Connecticut and Massachusetts do seem similar, there is a sharp difference between northern Massachusetts and southern Vermont and New Hampshire. It is interesting to observe how there is a distinct difference across state boundaries. In other states, like Michigan, even where the state of interest is not surrounded on all sides, there seem to be more gradual transitions across borders.

counties$value <- counties$TOTRATE
choro = CountyChoropleth$new(counties)
choro$title = "Religious Adherence 
in Massachusetts and Neighbors"
choro$set_num_colors(1)
choro$set_zoom(c("massachusetts", "new hampshire", "vermont", "maine", "connecticut", "rhode island"))
choro$ggplot_polygon = geom_polygon(aes(fill = value), color = NA)
choro$ggplot_scale = scale_fill_gradientn(name = "Adherence raten(per 1000 population)", colours = viridis(32))
choro$render()

counties$value <- counties$TOTRATE
choro = CountyChoropleth$new(counties)
choro$title = "Religious Adherence 
in Michigan and Neighbors"
choro$set_num_colors(1)
choro$set_zoom(c("michigan", "minnesota", "wisconsin", "ohio", "indiana", "illinois"))
choro$ggplot_polygon = geom_polygon(aes(fill = value), color = NA)
choro$ggplot_scale = scale_fill_gradientn(name = "Adherence raten(per 1000 population)", colours = viridis(32))
choro$render()