Flu and Pneumonia Deaths NYC 2014

library(tidyverse)
library(ggplot2)
library(readr)
library(knitr)
library(kableExtra)

raw_NYC_death <- read_csv("Desktop/Stuff & Things/School/Grad School/DUE Methods 1/part2/data/raw/New_York_City_Leading_Causes_of_Death_20241214.csv")

NYC_death <- raw_NYC_death|>
  filter(Year >= 2014,
         `Leading Cause`== "Influenza (Flu) and Pneumonia (J09-J18)",
         `Race Ethnicity` != "Not Stated/Unknown",
         `Race Ethnicity` != "Other Race/ Ethnicity")|>
  group_by(`Race Ethnicity`, Sex)|> 
  summarise(`Death Rate`)|>
  ungroup()

ggplot(data = NYC_death, aes(x=`Race Ethnicity`, y=`Death Rate`,fill = Sex))+
  theme(axis.text.x=element_text(angle=90,hjust=1,vjust=0.5))+
  geom_bar(position='dodge', stat='identity')+
  labs(title = "Death Rate from Flu and Pneumonia in 2014",
    caption = "Source: NYC OpenData")

This graph shows that the highest rate of deaths from the flu and pneumonia happen in the White and Black communities. Something I found interesting was the wide disparity in deaths between AAPI men and women, with men dying more much more frequently than the women.

kable(NYC_death, format = "html")|>
  kable_styling(bootstrap_options = c("striped", "hover"), full_width = F)

Race Ethnicity	Sex	Death Rate
Asian and Pacific Islander	F	12.8
Asian and Pacific Islander	M	18.3
Black Non-Hispanic	F	25.3
Black Non-Hispanic	M	28
Hispanic	F	17.2
Hispanic	M	16.7
White Non-Hispanic	F	39.7
White Non-Hispanic	M	37.4