specific content when demo data is used in synthetic data

Author: devhelpr

src/assets/synthetic-data.tsx

@@ -129,12 +129,14 @@ def run():
             {'type': 'heading', 'data': sdgMethod}
     ))
     if isDemo:
-        setResult(json.dumps(
-            {'type': 'heading', 'data': '''Demo'''}
-        ))
-        setResult(json.dumps(
-            {'type': 'text', 'data': '''A demo dataset is loaded below. We will now generate synthetic data on the columns: 'sex', 'race1', 'ugpa', 'bar'. We will be using the Gaussian Copula method and evaluate the distribution and correlation differences between the real and synthetic data.'''}
-        ))
+        setResult(json.dumps({
+            'type': 'heading',
+            'headingKey': 'syntheticData.demo.heading'
+        }))
+        setResult(json.dumps({
+            'type': 'text',
+            'key': 'syntheticData.demo.description'
+        }))
 
     setResult(json.dumps(
         {'type': 'data-set-preview', 'data': ''}

src/index.css

@@ -6,4 +6,8 @@
     p a {
         @apply text-blue-500 underline;
     }
+
+    ul {
+        @apply list-disc list-inside;
+    }
 }

src/locales/en.json

@@ -57,6 +57,10 @@
         }
     },
     "syntheticData": {
+        "demo": {
+            "heading": "Information about demo dataset",
+            "description": "**UI text** A subset of the [Law School Admission Bar*](https://www.kaggle.com/datasets/danofer/law-school-admissions-bar-passage) dataset is used as a demo. Synthetic data will be generated for the following columns:\n  \n  \n- sex: student gender, i.e. 1 (male), 2 (female)\n- race1: race, i.e. asian, black, hispanic, white, other\n- ugpa: The student's undergraduate GPA, continous variable;\n- bar: Ground truth label indicating whether or not the student passed the bar, i.e. passed 1st time, passed 2nd time, failed, non-graduated\n  \n  \n\nThe CART method will be used  evaluate the distribution and correlation differences between the real and synthetic data.\n  \n  \n\n*The original paper can be found [here](https://files.eric.ed.gov/fulltext/ED469370.pdf)."
+        },
         "exportToPDF": "Download evaluation report as PDF",
         "exportToJSON": "Download synthetic data as JSON",
         "exportToCSV": "Download synthetic data as CSV",

src/locales/nl.json

@@ -57,6 +57,10 @@
         }
     },
     "syntheticData": {
+        "demo": {
+            "heading": "Informatie over demodataset",
+            "description": "**UI-tekst** Een subset van de [Law School Admission Bar*](https://www.kaggle.com/datasets/danofer/law-school-admissions-bar-passage) dataset wordt gebruikt als demo. Er zullen synthetische gegevens worden gegenereerd voor de volgende kolommen:\n  \n  \n\n- sex: geslacht van de student, d.w.z. 1 (man), 2 (vrouw)\n- race1: etniciteit, d.w.z. aziatisch, zwart, hispanic, wit, anders\n- ugpa: Het GPA van de student tijdens de undergraduate-opleiding, continue variabele;\n- bar: Waarheidslabel dat aangeeft of de student is geslaagd voor de bar, d.w.z. geslaagd 1e keer, geslaagd 2e keer, gezakt, niet-afgestudeerd\n  \n  \n\nDe CART-methode zal worden gebruikt om de verschillen in distributie en correlatie tussen de echte en synthetische gegevens te evalueren.\n  \n  \n\n*Het oorspronkelijke artikel is [hier](https://files.eric.ed.gov/fulltext/ED469370.pdf) te vinden."
+        },
         "exportToPDF": "Download evulatie rapport als PDF",
         "exportToJSON": "Download synthetische data als JSON",
         "exportToCSV": "Download synthetische data als CSV",