Data Explorer
Explore the Dataset
The visualizations throughout this project are based on the observations in hpi_master.csv.
This page provides a closer look at the structure of that dataset.
What Is in the Dataset?
Each row represents a housing price index observation for a particular geographic location and time period.
| Variable | Description |
|---|---|
hpi_type |
Type of housing price index |
hpi_flavor |
Index category |
frequency |
Frequency of the observation |
level |
Geographic level |
place_name |
Name of the geographic location |
place_id |
Geographic identifier |
yr |
Year |
period |
Month or quarter |
index_nsa |
Non-seasonally adjusted index |
index_sa |
Seasonally adjusted index |
rstderr |
Relative standard error when available |
note |
Additional information about an observation |
Observations by Year
The number of observations can vary across years.
Recent Observations
Here are 25 observations from the most recent years in the dataset.
# A tibble: 25 × 5
place_name yr period index_nsa index_sa
<chr> <dbl> <dbl> <dbl> <dbl>
1 East North Central Division 2026 6 393. 383.
2 East South Central Division 2026 6 430. 420.
3 Middle Atlantic Division 2026 6 424. 414.
4 Mountain Division 2026 6 620. 610.
5 New England Division 2026 6 464. 452.
6 Pacific Division 2026 6 475. 466.
7 South Atlantic Division 2026 6 476. 467.
8 West North Central Division 2026 6 435. 425.
9 West South Central Division 2026 6 434. 426.
10 United States 2026 6 452. 443.
# ℹ 15 more rowsWhy Explore the Raw Data?
Charts are summaries. Looking at the underlying observations helps us understand where those summaries come from.
For example, we can examine:
- Which locations are represented
- Which years contain observations
- How many observations are available
- How seasonally adjusted and non-seasonally adjusted values differ
This page connects the individual observations to the larger patterns shown throughout the project.