Housing Trends

Housing Trends Over Time

How has the housing price index changed over the years?

This page focuses on the overall movement of housing price index values through time.

Annual Housing Price Index

The annual average provides a simplified view of the overall pattern in the dataset.

Average vs. Median

The mean and median provide two different summaries of the observations.

What Should We Notice?

Looking at the two summaries helps us examine whether the overall pattern is similar when using the mean and median.

The index is a relative measure, so the focus of this project is on changes and patterns over time, rather than interpreting the index as a dollar price.

Questions to Explore

How does the index change over time?
Are there periods with larger changes?
Do the mean and median show similar patterns?
How might the pattern differ between geographic regions?

Continue to Regional Comparisons to investigate geographic differences.

---
title: "Housing Trends"
---

# Housing Trends Over Time

How has the housing price index changed over the years?

This page focuses on the overall movement of housing price index values through time.

```{r}
#| echo: false
#| message: false
#| warning: false

library(tidyverse)

df <- read_csv("data/hpi_master.csv", show_col_types = FALSE)

annual <- df |>
  group_by(yr) |>
  summarize(
    average_index = mean(index_nsa, na.rm = TRUE),
    median_index = median(index_nsa, na.rm = TRUE),
    .groups = "drop"
  )
```

## Annual Housing Price Index

The annual average provides a simplified view of the overall pattern in the dataset.

```{r}
#| echo: false
#| message: false
#| warning: false

ggplot(annual, aes(x = yr, y = average_index)) +
  geom_line(linewidth = 1) +
  geom_point(size = 1.5) +
  theme_minimal() +
  labs(
    title = "Annual Average Housing Price Index",
    subtitle = "Average of non-seasonally adjusted observations",
    x = "Year",
    y = "Average Housing Price Index"
  )
```

## Average vs. Median

The mean and median provide two different summaries of the observations.

```{r}
#| echo: false
#| message: false
#| warning: false

annual_long <- annual |>
  pivot_longer(
    cols = c(average_index, median_index),
    names_to = "measure",
    values_to = "index"
  )

ggplot(annual_long, aes(x = yr, y = index, linetype = measure)) +
  geom_line(linewidth = 1) +
  theme_minimal() +
  labs(
    title = "Average and Median Housing Price Index",
    x = "Year",
    y = "Housing Price Index",
    linetype = "Measure"
  )
```

## What Should We Notice?

Looking at the two summaries helps us examine whether the overall pattern is similar when using the mean and median.

The index is a relative measure, so the focus of this project is on **changes and patterns over time**, rather than interpreting the index as a dollar price.

## Questions to Explore

- How does the index change over time?
- Are there periods with larger changes?
- Do the mean and median show similar patterns?
- How might the pattern differ between geographic regions?

Continue to **Regional Comparisons** to investigate geographic differences.