updating datasets for balacing

api/home/admin.py

@@ -2,6 +2,8 @@
 
 # Register your models here.
 
-from .models import DarkPatternReport
+from .models import DarkPatternReport, FAQData
+
+admin.site.register(DarkPatternReport)
+admin.site.register(FAQData)
 
-admin.site.register(DarkPatternReport)

api/home/faqs_save.py

@@ -0,0 +1,16 @@
+# Saving the data to models.py from csv file as input
+
+import pandas as pd
+from home.models import FAQData
+
+def save_from_csv(file_path):
+    # Read the CSV file into a DataFrame
+    faq_df = pd.read_csv(file_path)
+
+    # Iterate over each row and save to FAQData model
+    for index, row in faq_df.iterrows():
+        FAQData.objects.create(question=row['question'], answer=row['answer'])
+
+if __name__ == "__main__":
+    file_path = "faqs.csv"
+    save_from_csv(file_path)

api/home/migrations/0002_faqdata.py

@@ -0,0 +1,21 @@
+# Generated by Django 5.0.1 on 2024-02-13 06:21
+
+from django.db import migrations, models
+
+
+class Migration(migrations.Migration):
+
+    dependencies = [
+        ('home', '0001_initial'),
+    ]
+
+    operations = [
+        migrations.CreateModel(
+            name='FAQData',
+            fields=[
+                ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
+                ('question', models.CharField(max_length=200)),
+                ('answer', models.TextField()),
+            ],
+        ),
+    ]

api/home/models.py

@@ -12,3 +12,9 @@ class DarkPatternReport(models.Model):
     def __str__(self):
         return f"{self.name} - {self.website_name} "
 
+class FAQData(models.Model):
+    question = models.CharField(max_length=200)
+    answer = models.TextField()
+
+    def __str__(self):
+        return self.question

api/home/views.py

@@ -6,18 +6,21 @@
 import base64
 from PIL import Image
 
-from .models import DarkPatternReport
+from .models import DarkPatternReport,FAQData
 from django.contrib import messages
 
 # Create your views here.
 
+import pandas as pd
 
 def index(request):
     return render(request, "index.html")
 
 
 def faqs(request):
-    return render(request, "faqs.html")
+    faqs = FAQData.objects.all()
+    return render(request, "faqs.html", {"faqs": faqs})
+
 
 def termsConditions(request):
     return render(request, "termsConditions.html")
@@ -97,3 +100,6 @@ def reportDp(request):
 
     return render(request, "report.html")
 
+
+
+

api/mlApi/download.py

@@ -4,23 +4,35 @@
 import pandas as pd
 file_path = "F:/backup-kali/codeFiles/projects/cognigaurd/api/datasets/dp_dataset.tsv"
 
+file_path2 = "F:/backup-kali/codeFiles/projects/cognigaurd/api/datasets/new_dp_dataset_final.tsv"
+
 df = pd.read_csv(file_path, sep='\t')
 
-uniqueVal1 = df['Pattern Category'].unique()
-uniqueVal2 = df['text'].unique()
-uniqueVal3 = df['label'].unique()
+df2  = pd.read_csv(file_path2, sep='\t')
+
+# uniqueVal2 = df['Pattern Category'].nunique()
+# print(uniqueVal2)
+
+# # Check for NaN values in the entire DataFrame
+# nan_values = df.isna().sum()
+
+dark_pattern_counts = df['Pattern Category'].value_counts()
+
+dark_pattern_counts2 = df2['Pattern Category'].value_counts()   
+
+
 
+print(dark_pattern_counts)
 
-# Check for NaN values in the entire DataFrame
-nan_values = df.isna().sum()
+print(dark_pattern_counts2)
 
 # Alternatively, you can use df.isnull().sum()
 
 # Print or use the information about NaN values
-print(nan_values)
+# print(nan_values)
 
-print(uniqueVal1)
-print(uniqueVal3)
+# print(uniqueVal1)
+# print(uniqueVal3)
 
-new_df = df[['text', 'Pattern Category']]
-new_df.to_csv('F:/backup-kali/codeFiles/projects/cognigaurd/api/datasets/new_dp_dataset.csv',sep="\t", index=False)
+# new_df = df[['text', 'Pattern Category']]
+# new_df.to_csv('F:/backup-kali/codeFiles/projects/cognigaurd/api/datasets/new_dp_dataset.csv',sep="\t", index=False)

api/templates/faqs.html

@@ -17,21 +17,22 @@ <h2 class="font-medium">Clarity beyond Words</h2>
         <h1 class="font-medium font-secondary">FAQs</h1>
         <div class="faqs">
             <div class="faqs-div">
+                {% if faqs %}
+
                 <div class="faq">
                     <div class="faq-question">
                         <span class="material-symbols-outlined">adjust</span>
-                        <span class="faq-ques-text">What is Cogniguard?</span>
+                        <span class="faq-ques-text">{{ faqs.question }}</span>
                         <i class="material-symbols-outlined faq-button">expand_more</i>
                     </div>
                     <div class="faq-answer hide" id="faq1-content">
-                        <p>Cogniguard is a sophisticated web extension designed to amplify online transparency. It
-                            provides users with a transparency score for visited websites, detecting and alerting users
-                            about the presence of dark patterns. This empowers users to make informed decisions and
-                            protect their privacy.</p>
+                        <p> {{ faqs.answer}} </p>
                     </div>
                 </div>
 
-                <div class="faq">
+                {% endif %}
+
+                {% comment %} <div class="faq">
                     <div class="faq-question">
                         <span class="material-symbols-outlined">adjust</span>
                         <span class="faq-ques-text"> How does Cogniguard work?</span>
@@ -143,7 +144,7 @@ <h1 class="font-medium font-secondary">FAQs</h1>
                             "Cogniguard," and follow the installation instructions. Once installed, the extension will
                             work seamlessly in the background to enhance your browsing experience.</p>
                     </div>
-                </div>
+                </div> {% endcomment %}
             </div>
         </div>
     </section>