Project 1
Mario Vallejo
2023-10-30
#1
library(tidycensus)
census_api_key("844a362e7335694a2b5aef39ff772e6544fb127b", overwrite = TRUE, install= 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] "844a362e7335694a2b5aef39ff772e6544fb127b"readRenviron("~/.Renviron")
Sys.getenv("CENSUS_API_KEY")## [1] "844a362e7335694a2b5aef39ff772e6544fb127b"var <- c('B19013_001E','B03002_012E','B03002_004E','B01001_002E',
'B01001_026E', 'B01001_001E', 'B01002_001E')
Victoria_segregation <- get_acs(geography = "tract", variables = var, county = "Victoria",
state = "TX",output="wide", geometry = TRUE)## Getting data from the 2017-2021 5-year ACS## Downloading feature geometry from the Census website. To cache shapefiles for use in future sessions, set `options(tigris_use_cache = TRUE)`.##
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names(Victoria_segregation)[3] <- 'MedianHouseholdIncome'
names(Victoria_segregation)[5] <- 'Hispanic Population'
names(Victoria_segregation)[7] <- 'NonHispanicAfricanAmericanPopulation'
names(Victoria_segregation)[9] <- 'Male'
names(Victoria_segregation)[11] <- 'Female'
names(Victoria_segregation)[13] <- 'Total Population'
names(Victoria_segregation)[15] <- 'Median Age of County'
Victoria_segregation$B19013_001M<-NULL
Victoria_segregation$B03002_012M<-NULL
Victoria_segregation$B03002_004M<-NULL
Victoria_segregation$B01001_002M<-NULL
Victoria_segregation$B01001_026M<-NULL
Victoria_segregation$B01001_001M<-NULL
Victoria_segregation$B01002_001M<-NULL
#3
write.csv(Victoria_segregation, "C:/Users/Mario/Documents/Wei CLASS Folder/Victoria_seg3.csv")
#4 Scatter Plot
library(ggplot2)
ggplot(data = Victoria_segregation, aes(x = NonHispanicAfricanAmericanPopulation,
y = MedianHouseholdIncome)) +
geom_point()## Warning: Removed 1 rows containing missing values (`geom_point()`).
#5 Histogram
ggplot(data.frame(x =Victoria_segregation$`Median Age of County`), aes(x)) +
geom_histogram(binwidth = 5, fill = "lightblue", color = "black") +
labs(
title = "Histogram",
x = "Age",
y = "Tract"
)## Warning: Removed 1 rows containing non-finite values (`stat_bin()`).
#6
library(ggplot2)
#I know you asked for Total Population but my county has "NA" which for a row, that causes an error
# Therefore, I use Hispanic Population to show you I know how to use funcation
df <- density(Victoria_segregation$`Hispanic Population`,)
plot(df, main="Probability Density Function", xlab="X Values", ylab="Density")
#7
cdf <- ecdf(Victoria_segregation$MedianHouseholdIncome)
plot(cdf, main = "Cumulative Density Function", xlab = "X Values", ylab = "CDF")
#8
boxplot(Victoria_segregation$MedianHouseholdIncome, main="Box Plot Example", ylab="Data Values") 
#9
library(sf)## Linking to GEOS 3.11.2, GDAL 3.6.2, PROJ 9.2.0; sf_use_s2() is TRUElibrary(tmap)## The legacy packages maptools, rgdal, and rgeos, underpinning the sp package,
## which was just loaded, will retire in October 2023.
## Please refer to R-spatial evolution reports for details, especially
## https://r-spatial.org/r/2023/05/15/evolution4.html.
## It may be desirable to make the sf package available;
## package maintainers should consider adding sf to Suggests:.
## The sp package is now running under evolution status 2
## (status 2 uses the sf package in place of rgdal)## Breaking News: tmap 3.x is retiring. Please test v4, e.g. with
## remotes::install_github('r-tmap/tmap')Victoria_segregation$percentage_Hisp <- 100*Victoria_segregation$`Hispanic Population`/Victoria_segregation$`Total Population`
tm_shape(Victoria_segregation) +tm_fill(col = "percentage_Hisp")+ tm_layout(title = "Hispanic Percent")
#10
Victoria_segregation$moreFemale <- Victoria_segregation$Female > Victoria_segregation$Male
tm_shape(Victoria_segregation) +tm_fill(col = "moreFemale")+ tm_layout(title = "More Female Population")
#11 Do not know how to do