From 4faa902ee7f56c4fd6fc549f98877180b80a7ca2 Mon Sep 17 00:00:00 2001
From: Megan Le <meganlecs@gmail.com>
Date: Sat, 11 May 2024 16:34:55 -0400
Subject: [PATCH] landing page salary/rent regression

---
 src/routes/+page.svelte | 71 +++++++++++++++++++++++++++++++++++++----
 1 file changed, 65 insertions(+), 6 deletions(-)

diff --git a/src/routes/+page.svelte b/src/routes/+page.svelte
index 2dbf038..00d6da5 100644
--- a/src/routes/+page.svelte
+++ b/src/routes/+page.svelte
@@ -1,24 +1,83 @@
 <svelte:head>
 	<title>Commute Time Dashboard</title>
     <link href="https://fonts.googleapis.com/css2?family=Assistant:wght@400;500;700&display=swap" rel="stylesheet">
+    <script src="https://cdn.plot.ly/plotly-latest.min.js" type="text/javascript"></script>
 </svelte:head>
 
 
+
 <script>
-function goToDashboard(){
-    window.location.href = './dashboard';
-    return false;
-}
+    function goToDashboard(){
+        window.location.href = './dashboard';
+        return false;
+    }
+     // Calculate regression line
+ const regressionLine = (xArr, yArr) => {
+        const xMean = xArr.reduce((acc, val) => acc + val, 0) / xArr.length;
+        const yMean = yArr.reduce((acc, val) => acc + val, 0) / yArr.length;
+
+        const numerator = xArr.reduce((acc, x, i) => acc + (x - xMean) * (yArr[i] - yMean), 0);
+        const denominator = xArr.reduce((acc, x) => acc + (x - xMean) ** 2, 0);
+
+        const slope = numerator / denominator;
+        const intercept = yMean - slope * xMean;
+
+        return xArr.map(x => slope * x + intercept);
+    };
+
+    const rentData = [2607.0, 3539.0, 3718.0, 3633.0, 3518.0, 2750.0, 3633.0, 3539.0, 3140.0, 3250.0, 2377.0, 3749.0, 2377.0, 3151.0, 2607.0, 2497.0, 2680.0, 2607.0, 2377.0, 3539.0, 2397.0, 3213.0, 3213.0, 3046.0, 3539.0, 2497.0, 2481.0, 2730.0, 3570.0, 2481.0, 3633.0, 3539.0, 3151.0, 3633.0, 3046.0, 2499.0]
+
+    const rentNeighborhoodNames = ["Allston", "Area 2/MIT", "Back Bay", "Baldwin", "Beacon Hill", "Brighton", "Cambridge Highlands","Cambridgeport", "Charlestown", "Chinatown", "Dorchester", "Downtown", "East Boston","East Cambridge","Fenway", "Hyde Park","Jamaica Plain","Longwood", "Mattapan", "Mid-Cambridge","Mission Hill","Neighborhood Nine","North Cambridge","North End","Riverside", "Roslindale", "Roxbury", "South Boston","South Boston Waterfront","South End","Strawberry Hill","The Port","Wellington-Harrington","West Cambridge","West End","West Roxbury"]
+
+    const salaryData = [71.83164739884393, 175.4480640393143, 147.05532554953237, 77.08398116226142, 112.21782230147907, 71.33450183064579, 77.08398116226142, 175.4480640393143, 78.91006001263423, 128.85338481959695, 59.683840847913864, 188.8833296001792, 59.68693009118541, 129.98903006318127, 81.23144565599719, 55.42134944612286, 69.7178024833959, 78.51204242827254, 43.01632438125329, 175.4480640393143, 57.423773287850956, 119.74381474710542, 119.74381474710542, 50.297506925207756, 175.4480640393143, 46.62062546537602, 72.66275149537792, 81.42493396724775, 165.73921750105174, 68.2045719844358, 77.08398116226142, 175.4480640393143, 129.98903006318127, 77.08398116226142, 109.57901280044203, 46.774375352244974]
+
+    const data = [{
+        x: rentData,
+        y: salaryData,
+        mode: "markers",
+        type: "scatter",
+        text: rentNeighborhoodNames,
+        showlegend: false,
+        name: "",
+        hoverinfo: "text"
+    }];
+
+    const regressionY = regressionLine(rentData, salaryData);
+
+    let regressionTrace = {
+        x: rentData,
+        y: regressionY,
+        mode: "lines",
+        type: "scatter",
+        name: "",
+        showlegend: false,
+        hoverinfo: "none"
+    };
+
+    let layout = {
+        xaxis: { range: [2300, 3800], title: "Average 1 Bedroom Apartment Rent" },
+        yaxis: { range: [0, 200], title: "Average Salary (in thousands of dollars per year)" },
+        title: "Average Salary vs. Average Rent by Neighborhood"
+    };
+
+     // Create the Plotly plot once the component is mounted
+    import { onMount } from 'svelte';
+
+    onMount(() => {
+        Plotly.newPlot("salaryPlot", [...data, regressionTrace], layout);
+    });
 </script>
 
 <div class="intro-container">
     <h2>How are transportation options and rent prices limiting your access to high-paying jobs?</h2>
     <p>As rent prices climb in the Boston area, many tenants are being driven farther away from the center of the city<sup><a href="https://www.cbsnews.com/boston/news/boston-high-rent-city-workers-city-council-residence-requirement/">1</a>, <a href="https://www.forbes.com/sites/andrewdepietro/2023/01/24/the-average-rent-in-boston-now-rivals-bay-area-cities/?sh=7e5080d9434b">2</a></sup>. Unfortunately, this displacement often means living farther away from areas that are dense with high-paying job opportunities. Though many workers resort to long daily commutes, studies have also found that increased commute times are associated with reduced work and life satisfaction and decreased physical health<sup><a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9819363/">3</a></sup>.</p>
 
-    <p>But just how large is the trade-off between rent and commute time? Our analyses find that in the Boston area, a <b>$100 increase in rent</b> per bedroom is about equivalent to a <b>1 minute and 45 second decrease in commute</b> time. We also find complementary evidence that neighborhoods with high rent prices tend to have more businesses and job opportunities (normalized by population) and offer higher salaries.
+    <p>But just how large is the trade-off between rent and commute time? Our analyses find that in the Boston area, a <b>$100 increase in rent</b> per bedroom is about equivalent to a <b>1 minute and 45 second decrease in commute</b> time. We also find complementary evidence that neighborhoods with high rent prices tend to have more businesses and job opportunities (normalized by population) and offer higher salaries. The following plot shows the average salary for workers in a given neighborhood regressed against the average 1 bedroom apartment rent (with data for both Boston and Cambridge area neighborhoods).
     </p>
 
-    <p>In this visualization, you’ll explore how high rent prices reduce your housing options, then see how existing transportation options can limit the areas you’re able to work in (depending on how long you would be willing to commute).</p>
+    <div id="salaryPlot"></div>
+
+    <p>In the following dashboard, you’ll get to explore how the variables of rent, commute time, and salary interact with each other by seeing how high rent prices can reduce your housing options, then visualizing how existing transportation options can limit the areas you’re able to work in (depending on how long you would be willing to commute).</p>
     <button on:click={goToDashboard}>Enter</button>
 </div>