Census Data

library(tidyverse)
library(tidycensus)
census_api_key("b5e3d2da685c019db5e7c341c3949706ef5df120",install = TRUE, overwrite = TRUE)

Your original .Renviron will be backed up and stored in your R HOME directory if needed.
Your API key has been stored in your .Renviron and can be accessed by Sys.getenv("CENSUS_API_KEY"). 
To use now, restart R or run `readRenviron("~/.Renviron")`

[1] "b5e3d2da685c019db5e7c341c3949706ef5df120"

readRenviron("~/.Renviron")

Introduction

For our project, we initially began by looking at the English proficiency of foreign born Spanish speakers in NJ. To do this, we combined two datasets, one which included the number of foreign born Spanish-speakers who reported speaking English “very well”, and another for those who reported speaking English “not very well”. By combining these datasets, we were able to compare these numbers in one graph, which made visualizing the statistics much more efficient.

We later decided to add another layer to our project by looking at the English proficiency of foreign born “Other-Language” speakers in NJ. We wanted to see which of our two groups reported a higher English proficiency. As you can see below, the differences are quite drastic. Foreign born speakers of “other languages” report higher English proficiencies than those who speak Spanish. These results will be discussed in further detail below.

Our final graph is very similar to a facet-wrap of all our graphs. We used the census codes for all four datasets to combine them into one graph and compare the results more efficently. This allowed us to see the differences and similarities between these groups without having to scroll between two graphs. We also kept the colors uniform throughout our project since we believe this enhances its readability.

nj <- get_acs(geography = "state", 
      variables = c(Very_Well = "B06007_036", Not_Very_Well = "B06007_037"), 
      state = "34",
      year = 2015)

Getting data from the 2011-2015 5-year ACS

ggplot(nj, aes(x = variable, y =estimate / 1000, color = variable, fill = variable))+
  geom_col(width = 0.5)+
  ggtitle("English Proficiency of Foreign Born Spanish Speakers in NJ")+
  xlab("English Proficiency")+
  ylab("Number of Speakers (In Thousands)")

Spanish in NJ

This graph looks at the English proficiency of NJ residents who were not born in the US and who also speak Spanish. This graph does not make any distinctions based on age of the speaker nor country of origin. The variables listed in the x-axis represent the binary options that speakers had to choose from when assessing their English proficiency, “very well” and “not very well”. The y-axis represent the number of speakers that selected each option in thousands.

As demonstrated above, the amount of Spanish speakers who report not speakng English very well is much higher than those who report speaking English very well, the numbers are around 475,000 and 225,000 respectively. In other words, approximately 1/3 of the foreign-born Spanish-speaking population reports speaking English very well.

nj <- get_acs(geography = "state", 
      variables = c(VeryWell = "B06007_039", NotVeryWell = "B06007_040"), 
      state = "34",
      year = 2015)

Getting data from the 2011-2015 5-year ACS

ggplot(nj, aes(x = variable, y =estimate / 1000, color = variable, fill = variable))+
  geom_col(width = 0.5)+
  ggtitle("English Proficiency of Foreign Born 'Other Language' \n Speakers in NJ")+
  xlab("English Proficiency")+
  ylab("Number of Speakers (In Thousands)")

Other Languages in NJ

This graph shows the English proficiency of foregin born non-Spanish speakers in New Jersey. The x axis shows the level of proficiency, and the y axis measures the number of speakers in 1000s. The data did not specify the age, sex, or the education level of these speakers.Color was used to emphasize proficiency levels. In this group, more people believe that they speak English “very well” than “not very well”however,the number of speakers isn’t significantly different between these groups. There are about 5000 people who believe that they speak English very well and there are about 4000 people who believe that they don’t speak English well. The difference between the two groups is only 1000 people. The difference in this demographic is significantly smaller than the difference in the group of foregin born Spanish speakers.

nj <- get_acs(geography = "state", 
      variables = c(SpanVeryWell = "B06007_036", SpanNotVeryWell = "B06007_037",OLVeryWell = "B06007_039", OLNotVeryWell = "B06007_040"), 
      state = "34",
      year = 2015)

Getting data from the 2011-2015 5-year ACS

ggplot(nj, aes(x = variable, y =estimate / 1000, fill = variable))+
  geom_col(width = 0.5)+
  scale_fill_manual(values = c("#F8766D","#00BFC4","#F8766D","#00BFC4"))+
  ggtitle("English Proficiency of Foreign Born Speakers in NJ")+
  xlab("English Proficiency")+
  ylab("Number of Speakers (In Thousands)")

A Linguistically Diverse New Jersey

The graph above explores the English proficiency of foreign born residents of New Jersey whose native language is other than English. These speakers are categorized between native speakers of Spanish and native speakers of other languages. As seen in the data, the number of native Spanish speakers and native speakers of other languages who do not speak English well are relatively high, with approximately 400,000 and 475,000 people in each category, respectively. These numbers are only eclipsed by the number of native speakers of other languages who do speak English well, which totals to nearly 525,000 residents. The smallest population is the number of native Spanish speakers who do speak English well, which numbers approximately 215,000 speakers.

Ultimately, what can be determined from this graph is that the number of native Spanish speakers living in New Jersey who cannot speak English well is higher than that of the number of native speakers of other languages who do not speak English well. Additionally, the number of native Spanish speakers who cannot speak English well is also higher than the number of native Spanish speakers who do speak English well. Contrarily, the number of native speakers of other languages who speak English well is higher than the total amount of native speakers of other languages who speak do not speak English well.