Load Data#1

MedSale<-read.csv("MeDian_Sale_Prices_2012-2024.csv")

Load Data 2

MedSale2224<-read.csv("Median_Sales_Prices2022-AUG2024.csv")

##Packages

library(dplyr)
## 
## 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(tidyverse)
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ forcats   1.0.0     ✔ readr     2.1.5
## ✔ ggplot2   3.5.1     ✔ stringr   1.5.1
## ✔ lubridate 1.9.3     ✔ tibble    3.2.1
## ✔ purrr     1.0.2     ✔ tidyr     1.3.1
## ── 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(reshape2)
## 
## Attaching package: 'reshape2'
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## The following object is masked from 'package:tidyr':
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##     smiths

Wide to Long

Long<-
  MedSale %>%
  pivot_longer(
    cols=!Region,
    names_to = "Date",
    values_to = "Median_Prices") %>%
  print()
## # A tibble: 1,064 × 3
##    Region      Date   Median_Prices
##    <chr>       <chr>  <chr>        
##  1 " National" Jan.12 "$159,000 "  
##  2 " National" Feb.12 "$160,000 "  
##  3 " National" Mar.12 "$171,000 "  
##  4 " National" Apr.12 "$178,000 "  
##  5 " National" May.12 "$186,000 "  
##  6 " National" Jun.12 "$194,000 "  
##  7 " National" Jul.12 "$192,000 "  
##  8 " National" Aug.12 "$191,000 "  
##  9 " National" Sep.12 "$187,000 "  
## 10 " National" Oct.12 "$185,000 "  
## # ℹ 1,054 more rows

Long to Wide

Wide<-
  MedSale2224 %>%
  pivot_wider(
    names_from = "PeriodEnd",
    values_from = "MedianSale") %>%
  print()
## # A tibble: 7 × 33
##   Region `22-Jan` `22-Feb` `22-Mar` `22-Apr` `22-May` `22-Jun` `22-Jul` `22-Aug`
##   <chr>  <chr>    <chr>    <chr>    <chr>    <chr>    <chr>    <chr>    <chr>   
## 1 " Nat… "$378 "  "$392 "  "$415 "  "$426 "  "$433 "  "$429 "  "$415 "  "$409 " 
## 2 "Bost… "$596 "  "$595 "  "$637 "  "$675 "  "$690 "  "$705 "  "$687 "  "$675 " 
## 3 "Chic… "$290 "  "$292 "  "$310 "  "$328 "  "$329 "  "$340 "  "$325 "  "$310 " 
## 4 "Los … "$825 "  "$840 "  "$875 "  "$900 "  "$900 "  "$890 "  "$862 "  "$845 " 
## 5 "Phil… "$250 "  "$250 "  "$265 "  "$275 "  "$287 "  "$297 "  "$280 "  "$275 " 
## 6 "Seat… "$720 "  "$751 "  "$825 "  "$851 "  "$853 "  "$825 "  "$798 "  "$780 " 
## 7 "Wash… "$475 "  "$496 "  "$525 "  "$550 "  "$555 "  "$550 "  "$530 "  "$520 " 
## # ℹ 24 more variables: `22-Sep` <chr>, `22-Oct` <chr>, `22-Nov` <chr>,
## #   `22-Dec` <chr>, `23-Jan` <chr>, `23-Feb` <chr>, `23-Mar` <chr>,
## #   `23-Apr` <chr>, `23-May` <chr>, `23-Jun` <chr>, `23-Jul` <chr>,
## #   `23-Aug` <chr>, `23-Sep` <chr>, `23-Oct` <chr>, `23-Nov` <chr>,
## #   `23-Dec` <chr>, `24-Jan` <chr>, `24-Feb` <chr>, `24-Mar` <chr>,
## #   `24-Apr` <chr>, `24-May` <chr>, `24-Jun` <chr>, `24-Jul` <chr>,
## #   `24-Aug` <chr>

##Describe a row

Wide Format: Each row represents a region, with separate columns for median home sale prices on for each month from 2012 to August 2024.

Long format: Each row represents the median home sale price for a region in a specific month.

THE END