This is my code for my charts.
FetchedData <- read.csv("https://raw.githubusercontent.com/drkblake/Data/main/DataWrangling.csv")
write.csv(FetchedData, "DataWrangling.csv", row.names = FALSE)
rm (FetchedData)
if (!require("tidyverse"))
install.packages("tidyverse")
## Loading required package: tidyverse
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.4 ✔ readr 2.1.5
## ✔ forcats 1.0.0 ✔ stringr 1.5.1
## ✔ ggplot2 3.4.4 ✔ tibble 3.2.1
## ✔ lubridate 1.9.3 ✔ tidyr 1.3.1
## ✔ purrr 1.0.2
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
library(tidyverse)
mydata <- read.csv("DataWrangling.csv")
mydata <- mydata %>%
mutate(Density = Households / Land_area) %>%
mutate(Density_2 = cut_number(Density, n = 2)) %>% mutate(Density_3 = cut_number(Density, n = 3))
mydata <- mydata %>%
mutate(
Density_2 = case_when(
Density_2 == "[7.35,28.6]" ~ "Low density",
Density_2 == "(28.6,583]" ~ "High density",
.default = "Error"
)
)
ggplot(mydata, aes(x=Pct_BB))+
geom_histogram(color = "gray",
fill = "darkblue")
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
ggplot(mydata, aes(x = Density,
y = Pct_College))+
geom_point(color = "red",
fill = "red")