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#install.packages("openintro")
library(tidyverse)
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.2.0     ✔ readr     2.1.6
## ✔ forcats   1.0.1     ✔ stringr   1.6.0
## ✔ ggplot2   4.0.2     ✔ tibble    3.3.1
## ✔ lubridate 1.9.5     ✔ tidyr     1.3.2
## ✔ purrr     1.2.1     
## ── 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(openintro)
## Loading required package: airports
## Loading required package: cherryblossom
## Loading required package: usdata
data(cchousing)

str(cchousing)
## tibble [75 × 1] (S3: tbl_df/tbl/data.frame)
##  $ price: num [1:75] 506 614 755 483 588 ...
summary(cchousing)
##      price       
##  Min.   : 400.1  
##  1st Qu.: 522.0  
##  Median : 582.1  
##  Mean   : 611.6  
##  3rd Qu.: 686.7  
##  Max.   :1093.7

Average monthly, the median, the max & minnimum cost for housing to show the range of housing.

cchousing%>%
  summarize(
    average_price = mean(price),
    median_price = median(price),
    max_price = max(price),
    min_price = min(price))
## # A tibble: 1 × 4
##   average_price median_price max_price min_price
##           <dbl>        <dbl>     <dbl>     <dbl>
## 1          612.         582.     1094.      400.

##Cleaning

housing_clean <-cchousing %>%
  filter(!is.na(price))%>%
  select(price)
head(housing_clean)
## # A tibble: 6 × 1
##   price
##   <dbl>
## 1  506.
## 2  614.
## 3  755.
## 4  483.
## 5  588.
## 6  609.

##Scatterplot of Cost for every student

ggplot(housing_clean, aes(x = 1:75, y = price))+
  geom_point(color = "black")+
  labs(
    title = "Community College Housing Cost",
    x = "Student Number",
    y = "Monthly Cost"
  )