This repository has some code I'm using to work with DC's Open Data portal. Currently, this includes:

1. R scripts used to pull data from the API, clean up some column names, and then push this data to a local postgres database
2. a dbt project to clean up data in the database
3. any SQL used to generate schemas, queries, etc. from the local postgres database

Working with data from the API can be a bit annoying/time-consuming. Many of the datasets available have hundreds of thousands of records, and the API has a rate limit of 1000 records per request. My solution to this was to spin up a local postgres server, collect the data + do a bit of name cleanup in R, populate the postgres database, then use dbt to run some tests against the raw data + clean it up for analysis.

With this data now being available to me via SQL, it makes doing analysis quite a bit easier than having to tap the API every time I want a data source. In addition, using the offset in the API functions I wrote, I can append new data to the tables easily.

In the terminal, I can spin up my postgres dataset using brew:

brew services start postgresql@14

Now, instead of using the API directly, I can access information via SQL. This is quite powerful combined with R, since I can query the dataset directly and do things like plotting:

library(ggplot2)

source("utils.R")

## connect to the local postgresDB
conn <- connect_to_db()

## query the DB
conn |> 
  query_db(
    "
    SELECT 
      EXTRACT(YEAR FROM report_date)::Int AS report_year,
      COUNT(*)::INT AS n_crashes
    FROM dc_open_data_dev.raw__crashes
    WHERE report_date IS NOT NULL
      AND EXTRACT(YEAR FROM report_date) < 2023
        AND EXTRACT(YEAR FROM report_date) >= 2010
    GROUP BY EXTRACT(YEAR FROM report_date)
    ORDER BY report_year
    "
  ) |> 
## create a plot from the queried data
  ggplot() +
  aes(x = report_year, y = n_crashes) +
  geom_line(size = 1.5, color = "deepskyblue4") +
  labs(
    x = "\nYear Reported", 
    y = "Num. Reported Crashes", 
    title = "Crashes in Washington, D.C.", 
    subtitle = "sourced from DC's Open Data Portal"
  ) +
  scale_x_continuous(labels = round) +
  theme_minimal() +
  theme(
    panel.grid.major = element_blank(), 
    panel.grid.minor = element_blank(),
    panel.grid.major.y = element_line(color = "grey95", linetype = "dashed"),
    plot.title = element_text(size = 24, face = "bold"), 
    plot.subtitle = element_text(face = "italic")
  )