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added new tennis dataset
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elizaan committed Jul 12, 2024
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Binary file modified public/Upset-Alttext-User-Survey/assets/VO1.png
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2 changes: 1 addition & 1 deletion public/Upset-Alttext-User-Survey/assets/covidVis.md
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<h1 style="text-align: center;">Dataset: Covid Symptoms</h1>

<div class="image-container">
<img src="./assets/VO1.png" alt="Covid Symptoms" width="492" height="1200"/>
<img src="./assets/VO1.png" alt="Covid Symptoms" width="610" height="1180"/>
</div>

</body>
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19 changes: 19 additions & 0 deletions public/Upset-Alttext-User-Survey/assets/tennisText.md
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<h1 style="text-align: center;">Dataset: Tennis Grand Slam Winners</h1>

## UpSet Introduction
This is an UpSet plot that visualizes set intersection. To learn about UpSet plots, visit https://upset.app.

## Dataset Properties
The dataset contains 4 sets and 208 elements, of which 4 sets are shown in the plot.

## Set Properties
The set sizes are roughly equal, ranging from 42 to 58. The largest set is Australian Open with 58 elements, followed by French Open with 56, US Open with 52, and Wimbledon with 42.

## Intersection Properties
The plot is sorted by size in descending order. There are 15 non-empty intersections, all of which are shown in the plot. The largest 5 intersections are Just French Open (23), Just Australian Open (22), Just US Open (11), Australian Open, US Open, and Wimbledon (10), and French Open, Australian Open, US Open, and Wimbledon (9).

## Statistical Information
The average intersection size is 7, and the median is 5. The 90th percentile is 22, and the 10th percentile is 1. The largest set, Australian Open, is present in 53.3% of all non-empty intersections. The smallest set, Wimbledon, is present in 53.3% of all non-empty intersections.

## Trend Analysis
The intersection sizes peak at a value of 23 and then drastically flatten down to 1. An all set intersection is present with a size of 9. The individual set intersections are in large and largest intersections. The low degree set intersections lie in small and medium sized intersections. The medium degree set intersections can be seen among small sized intersections. Among the large sized intersections, the high order set intersections are significantly present.
37 changes: 37 additions & 0 deletions public/Upset-Alttext-User-Survey/assets/tennisTextandVis.md
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<h1 style="text-align: center;">Dataset: Tennis Grand Slam Winners</h1>

<!DOCTYPE html>
<html>
<head>
<style>
.container {
display: flex;
gap: 20px;
}
.column {
padding: 10px;
}
</style>
</head>
<body>

<div class="container">
<div class="column">
<img style="width: 500px;" src="./assets/VO3.png" alt="Tennis Grand Slam Winners">
</div>
<div class="column">
<h2>Dataset Properties</h2>
<p>The dataset contains 4 sets and 208 elements, of which 4 sets are shown in the plot.</p>
<h2>Set Properties</h2>
<p>The set sizes are roughly equal, ranging from 42 to 58. The largest set is Australian Open with 58 elements, followed by French Open with 56, US Open with 52, and Wimbledon with 42.</p>
<h2>Intersection Properties</h2>
<p>The plot is sorted by size in descending order. There are 15 non-empty intersections, all of which are shown in the plot. The largest 5 intersections are Just French Open (23), Just Australian Open (22), Just US Open (11), Australian Open, US Open, and Wimbledon (10), and French Open, Australian Open, US Open, and Wimbledon (9).</p>
<h2>Statistical Information</h2>
<p>The average intersection size is 7, and the median is 5. The 90th percentile is 22, and the 10th percentile is 1. The largest set, Australian Open, is present in 53.3% of all non-empty intersections. The smallest set, Wimbledon, is present in 53.3% of all non-empty intersections.</p>
<h2>Trend Analysis</h2>
<p>The intersection sizes peak at a value of 23 and then drastically flatten down to 1. An all set intersection is present with a size of 9. The individual set intersections are in large and largest intersections. The low degree set intersections lie in small and medium sized intersections. The medium degree set intersections can be seen among small sized intersections. Among the large sized intersections, the high order set intersections are significantly present.</p>
</div>
</div>

</body>
</html>
20 changes: 20 additions & 0 deletions public/Upset-Alttext-User-Survey/assets/tennisVis.md
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<!DOCTYPE html>
<html>
<head>
<style>
.image-container {
display: flex;
justify-content: center;
}
</style>
</head>
<body>

<h1 style="text-align: center;">Dataset: Tennis Grand Slam Winners</h1>

<div class="image-container">
<img src="./assets/VO3.png" alt="Covid Symptoms" width="610" height="700"/>
</div>

</body>
</html>
144 changes: 135 additions & 9 deletions public/Upset-Alttext-User-Survey/config.json
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"path": "Upset-Alttext-User-Survey/assets/covidTextandVis.md"

},
"Tennis-Vis-Q1": {
"baseComponent": "VO-image1",
"path": "Upset-Alttext-User-Survey/assets/tennisVis.md"
},
"Tennis-Vis-Q2": {
"baseComponent": "VO-image2",
"path": "Upset-Alttext-User-Survey/assets/tennisVis.md"
},
"Tennis-Vis-Q3": {
"baseComponent": "VO-image3",
"path": "Upset-Alttext-User-Survey/assets/tennisVis.md"
},
"Tennis-Text-Q1": {
"baseComponent": "TO-text1",
"path": "Upset-Alttext-User-Survey/assets/tennisText.md"
},
"Tennis-Text-Q2": {
"baseComponent": "TO-text2",
"path": "Upset-Alttext-User-Survey/assets/tennisText.md"
},
"Tennis-Text-Q3": {
"baseComponent": "TO-text3",
"path": "Upset-Alttext-User-Survey/assets/tennisText.md"
},
"Tennis-Both-Q1": {
"baseComponent": "TandV1",
"path": "Upset-Alttext-User-Survey/assets/tennisTextandVis.md"
},
"Tennis-Both-Q2": {
"baseComponent": "TandV2",
"path": "Upset-Alttext-User-Survey/assets/tennisTextandVis.md"
},
"Tennis-Both-Q3": {
"baseComponent": "TandV3",
"path": "Upset-Alttext-User-Survey/assets/tennisTextandVis.md"
},
"GoT-Vis-Q1": {
"baseComponent": "VO-image1",
"path": "Upset-Alttext-User-Survey/assets/GoTVis.md"
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{
"order": "fixed",
"components": [
"Covid-Both-Q1",
"Covid-Both-Q2",
"Covid-Both-Q3"
"Tennis-Both-Q1",
"Tennis-Both-Q2",
"Tennis-Both-Q3"
]
}
]
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{
"order": "fixed",
"components": [
"Covid-Both-Q1",
"Covid-Both-Q2",
"Covid-Both-Q3"
"Tennis-Both-Q1",
"Tennis-Both-Q2",
"Tennis-Both-Q3"
]
}
]
Expand All @@ -990,9 +1026,9 @@
{
"order": "fixed",
"components": [
"GoT-Vis-Q1",
"GoT-Vis-Q2",
"GoT-Vis-Q3"
"Tennis-Vis-Q1",
"Tennis-Vis-Q2",
"Tennis-Vis-Q3"
]

},
Expand All @@ -1013,6 +1049,96 @@
]
}
]
},
{
"order":"latinSquare",
"components": [
{
"order": "fixed",
"components": [
"Covid-Vis-Q1",
"Covid-Vis-Q2",
"Covid-Vis-Q3"
]

},
{
"order": "fixed",
"components": [
"Tennis-Text-Q1",
"Tennis-Text-Q2",
"Tennis-Text-Q3"
]
},
{
"order": "fixed",
"components": [
"GoT-Both-Q1",
"GoT-Both-Q2",
"GoT-Both-Q3"
]
}
]
},
{
"order":"latinSquare",
"components": [
{
"order": "fixed",
"components": [
"Tennis-Vis-Q1",
"Tennis-Vis-Q2",
"Tennis-Vis-Q3"
]

},
{
"order": "fixed",
"components": [
"GoT-Text-Q1",
"GoT-Text-Q2",
"GoT-Text-Q3"
]
},
{
"order": "fixed",
"components": [
"Covid-Both-Q1",
"Covid-Both-Q2",
"Covid-Both-Q3"
]
}
]
},
{
"order":"latinSquare",
"components": [
{
"order": "fixed",
"components": [
"GoT-Vis-Q1",
"GoT-Vis-Q2",
"GoT-Vis-Q3"
]

},
{
"order": "fixed",
"components": [
"Tennis-Text-Q1",
"Tennis-Text-Q2",
"Tennis-Text-Q3"
]
},
{
"order": "fixed",
"components": [
"Covid-Both-Q1",
"Covid-Both-Q2",
"Covid-Both-Q3"
]
}
]
}

]
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