HW 5 DATA 110

library(readxl)

## Warning: package 'readxl' was built under R version 4.5.2

library(dplyr)

## Warning: package 'dplyr' was built under R version 4.5.2

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

library(ggplot2)

## Warning: package 'ggplot2' was built under R version 4.5.2

df <- read_excel("Airbnb_DC_25.csv")

room_prices <- df %>%
  group_by(room_type) %>%
  summarize(avg_price = mean(price, na.rm = TRUE))
room_prices

## # A tibble: 4 × 2
##   room_type       avg_price
##   <chr>               <dbl>
## 1 Entire home/apt      181.
## 2 Hotel room           346.
## 3 Private room         103.
## 4 Shared room         1455.

ggplot(room_prices, aes(x = room_type, y = avg_price, fill = room_type)) +
  geom_bar(stat = "identity") +
  labs(
    title = "Average Airbnb Price by Room Type in Washington DC",
    x = "Room Type",
    y = "Average Price per Night ($)",
    caption = "Data Source: Airbnb_DC_25 Dataset"
  ) +
  scale_fill_manual(values = c("blue", "orange", "green", "purple"))

Short Paragraph

• The visualization is a bar chart which shows the average nightly Airbnb by price by room type in Washington DC. Based on the chart, the shared rooms have a high mean price about $1455.47 per night, which is considered higher than the other categories. In comparison, hotel rooms average about $345.97, but normally entire homes or apartments have a mean price around about $181.11. Private rooms considerably have the lowest average price which is around $103.27 per night. There is a pattern which suggest a variation in prices which has a shared room category which is an outlier to the rest of the distribution.