wip: puma map new york cbsa

Author: jaanli

docs/new-york-area.md

@@ -10,27 +10,60 @@ const db = DuckDBClient.of({data: FileAttachment("data/income-histogram-historic
 ```js
 const uniqueYears = await db.query("SELECT DISTINCT year FROM data WHERE year BETWEEN 2010 AND 2022 ORDER BY year").then(data => data.map(d => d.year));
 const yearRange = [uniqueYears[0], uniqueYears[uniqueYears.length - 1]];
-const yearInput = Inputs.range(yearRange, {step: 1, value: uniqueYears[0], width: 150});
+const yearInput = Inputs.range(yearRange, {
+  step: 1,
+  value: uniqueYears[0],
+  width: 150,
+  validate: (input) => input.value !== "2020"
+});
 const selectedYear = Generators.input(yearInput);
 yearInput.querySelector("input[type=number]").remove();
 ```
 
 
 ```js
-// Fetch the mapping of PUMA codes to their names
-const pumaNameMapping = await db.query(`
-  SELECT DISTINCT puma, puma_name, state_code FROM data
-`).then(data => new Map(data.map(d => [d.puma, d.puma_name, d.state_code])));
+// Hardcoded state code to state name mapping
+const stateCodeToName = {
+  '09': 'Connecticut',
+  '34': 'New Jersey',
+  '36': 'New York',
+  '42': 'Pennsylvania',
+  '44': 'Rhode Island'
+};
+
+// Fetch PUMA details, including state names based on the hardcoded map
+const pumaDetails = await db.query(`
+  SELECT DISTINCT puma, puma_name, state_code FROM data WHERE year = ${selectedYear}
+`).then(data => data.map(d => ({
+  puma: d.puma,
+  stateCode: d.state_code,
+  label: `${stateCodeToName[d.state_code]} - ${d.puma_name.replace("PUMA", "").trim()}`
+})));
+
+console.log("PUMA Details:", pumaDetails);
+
+// Sort pumaDetails alphabetically by state name and then by PUMA code
+pumaDetails.sort((a, b) => {
+  const stateCompare = stateCodeToName[a.stateCode].localeCompare(stateCodeToName[b.stateCode]);
+  if (stateCompare !== 0) return stateCompare;
+  return a.puma.localeCompare(b.puma);
+});
+
+console.log("Sorted PUMA Details:", pumaDetails);
 ```
 
 ```js
-const selectedPUMAName = pumaNameMapping.get(selectedPUMA);
+const PUMAInput = Inputs.select(pumaDetails, {
+  label: "Select PUMA",
+  value: d => d.puma,
+  format: d => d.label
+});
+const selectedPUMADetails = Generators.input(PUMAInput);
 ```
 
 ```js
-const uniquePUMAs = await db.query(`SELECT DISTINCT puma FROM data WHERE year = ${selectedYear}`).then(data => data.map(d => d.puma));
-const PUMAInput = Inputs.select(uniquePUMAs, {label: "Select PUMA", value: uniquePUMAs[0]});
-const selectedPUMA = Generators.input(PUMAInput);
+const selectedPUMA = selectedPUMADetails.puma;
+const selectedStateCode = selectedPUMADetails.stateCode;
 ```
 
 ```js
@@ -45,9 +78,9 @@ const orderSectors = await db.query(`
 ```
 
 ```js
-const income = db.query(`
+const income = await db.query(`
   SELECT income, count, sector FROM data
-  WHERE year = ${selectedYear} AND puma = ${selectedPUMA}
+  WHERE year = ${selectedYear} AND puma = '${selectedPUMA}' AND state_code = '${selectedStateCode}'
 `);
 ```
 
@@ -83,14 +116,16 @@ function incomeChart(income, width) {
 ```
 
 <div class="card">
-  <h2>The sectors in which people earn the most money shift across time and space</h2>
-  <h3>How much income per year x million people reported earning in the 2010–2022 American Community Surveys run by the United States' Census Bureau, categorized by their sector of employment, specifically for areas overlapping with the New York-Newark-Jersey City core-based statistical area in 2020.</h3>
-  <h3><code style="font-size: 90%;"><a href="https://github.com/jaanli/exploring_american_community_survey_data/blob/main/american_community_survey/models/public_use_microdata_sample/figures/income-histogram-with-sector-historical-inflation-adjusted-industry-mapped.sql">Code for data transform</a></code></h3>
-  <div style="display: flex; align-items: center;">
-    <h1 style="margin-top: 0.5rem;">${selectedYear}</h1>
-    ${yearInput}
-    <h1 style="margin-top: 0.5rem;">${pumaNameMapping.get(selectedPUMA)}</h1>
-    ${PUMAInput}
-  </div>
-  ${resize((width) => incomeChart(income, width))}
-</div>
+ <h2>The sectors in which people earn the most money shift across time and space</h2>
+ <h3>How much income per year x million people reported earning in the 2010–2022 American Community Surveys run by the United States' Census Bureau, categorized by their sector of employment, specifically for areas overlapping with the New York-Newark-Jersey City core-based statistical area in 2020.</h3>
+ <h3><code style="font-size: 90%;"><a href="https://github.com/jaanli/exploring_american_community_survey_data/blob/main/american_community_survey/models/public_use_microdata_sample/figures/income-histogram-with-sector-historical-inflation-adjusted-industry-mapped.sql">Code for data transform</a></code></h3>
+ <div style="display: flex; align-items: center;">
+   <h1 style="margin-top: 0.5rem;">${selectedPUMADetails.label}</h1>
+   ${PUMAInput}
+ </div>
+ <div style="display: flex; align-items: center;">
+   <h1 style="margin-top: 0.5rem;">${selectedYear}</h1>
+   ${yearInput}
+ </div>
+ ${resize((width) => incomeChart(income, width))}
+</div>