Update pages/Data Collection.py

pages/Data Collection.py

@@ -6,39 +6,26 @@ st.set_page_config(
     page_icon="🚀",
     layout="wide"
 )
-# Global CSS for consistent styling across all pages
+
+# Global CSS for consistent styling
 st.markdown("""
     <style>
     body, .stApp {
-        color: #4F4F4F; /* Replace with your desired font color */
-        background-color: #FFFFFF; /* Optional: Set a fixed background color */
+        color: #4F4F4F;
+        background-color: #FFFFFF;
     }
     h1, h2, h3, h4, h5, h6 {
-        color: #BB3385; /* Replace with your heading color */
+        color: #BB3385;
     }
     p {
-        color: #4F4F4F; /* Replace with your paragraph text color */
+        color: #4F4F4F;
     }
     ul li {
-        color: #4F4F4F; /* List item color */
+        color: #4F4F4F;
     }
     </style>
 """, unsafe_allow_html=True)
 
-st.markdown(
-    """
-    <style>
-    .stApp {
-        background-image: url("https://huggingface.co/spaces/LakshmiHarika/MachineLearning/resolve/main/DALL%C2%B7E%202024-12-03%2023.34.47%20-%20A%20simple%20and%20elegant%20background%20image%20for%20an%20AI-themed%20web%20application.%20The%20background%20should%20feature%20a%20soft%20gradient%20transitioning%20from%20white%20to%20ligh.webp");
-        background-size: cover;
-        background-repeat: no-repeat;
-        background-attachment: fixed;
-    }
-    </style>
-    """,
-    unsafe_allow_html=True
-)
-
 # Page Title
 st.markdown("""
     <div style="text-align: left; margin-top: 20px;">
@@ -48,8 +35,7 @@ st.markdown("""
 
 # Introduction Text
 st.write("""
-**Data** is the measurements that are collected as a source of Information.
-It refers to raw facts, figures, and observations that can be collected, stored, and processed.
+**Data** refers to raw facts, figures, and observations that can be collected, stored, and processed.
 It has no meaning on its own until it is organized or analyzed to derive useful information.
 """)
 
@@ -74,39 +60,26 @@ if data_type == "Structured Data":
         </div>
     """, unsafe_allow_html=True)
 
-    st.markdown("""
-        <div style="text-align: left; margin-top: 20px;">
-            <h4 style="color: #5b2c6f;">Definition:</h4>
-        </div>
-    """, unsafe_allow_html=True)
     st.write("""
-    Structured data refers to information that is organized and formatted in a predefined manner, making it easy to store, retrieve, and analyze.
+    **Structured data** refers to information that is organized and formatted in a predefined manner, making it easy to store, retrieve, and analyze.
     It is typically stored in tabular formats like rows and columns, where each field contains a specific type of information.
     
     This type of data is often used in relational databases and spreadsheets, where relationships between data points are explicitly defined.
     """)
 
-    st.markdown("""
-        <div style="text-align: left; margin-top: 20px;">
-            <h4 style="color: #5b2c6f;">Characteristics:</h4>
-        </div>
-    """, unsafe_allow_html=True)
     st.write("""
+    **Characteristics:**
     - Follows a fixed schema.
     - Can be easily searched using query languages like SQL.
     - Suitable for quantitative analysis.
     """)
 
-    st.markdown("""
-        <div style="text-align: left; margin-top: 20px;">
-            <h4 style="color: #5b2c6f;">Example:</h4>
-        </div>
-    """, unsafe_allow_html=True)
     st.write("""
+    **Example:**
     A database of students with fields like ID, name, age, and gender:
     """)
 
-    # Corrected table for the Student database example
+    # Display Structured Data Table
     student_data = {
         "Id": [100, 101, 102, 103],
         "Name": ["Lakshmi Harika", "Varshitha", "Hari Chandan", "Shamitha"],
@@ -114,107 +87,76 @@ if data_type == "Structured Data":
         "Gender": ["Female", "Female", "Male", "Female"]
     }
     df = pd.DataFrame(student_data)
-    st.markdown(df.style.set_table_styles(
-        [{
-            'selector': 'thead th',
-            'props': 'font-weight: bold;'
-        }]
-    ).hide(axis="index").to_html(), unsafe_allow_html=True)
-
-    # Transition to Data Formats in Structured Data
+    st.dataframe(df)
+
+    # Data Formats in Structured Data
+    st.write("""
+    **Data Formats in Structured Data:**
+    - **Excel**: Widely used for tabular data, calculations, and data visualization.
+    """)
+
+    # Button to Explore Excel
+    if st.button("Explore Excel"):
+        st.write("Redirecting to Excel page...")
+        # Add functionality to redirect or display additional details here
+
+# Unstructured Data Section
+elif data_type == "Unstructured Data":
     st.markdown("""
         <div style="text-align: left; margin-top: 20px;">
-            <h4 style="color: #5b2c6f;">Data Formats in Structured Data:</h4>
+            <h3 style="color: #e25822;">What is Unstructured Data?</h3>
         </div>
     """, unsafe_allow_html=True)
-    
+
     st.write("""
-    Structured data can be stored and managed in various formats, each designed for specific use cases.
-    Some common data formats include:
+    **Unstructured data** refers to information that does not follow a predefined format or structure.
+    It is typically raw data that lacks a clear, organized schema, making it harder to store and analyze using traditional tools.
     
-    - **Excel**: Widely used for tabular data, calculations, and data visualization.
-        """)
-    
-    # Add a button to navigate to the Excel page
-    if st.button("Explore Excel"):
-        st.query_params["page"] = "Excel"
-        st.rerun()
-
-    # Unstructured Data Section
-    elif data_type == "Unstructured Data":
-        st.markdown("""
-            <div style="text-align: left; margin-top: 20px;">
-                <h3 style="color: #e25822;">What is Unstructured Data?</h3>
-            </div>
-        """, unsafe_allow_html=True)
-    
-        st.markdown("""
-            <div style="text-align: left; margin-top: 20px;">
-                <h4 style="color: #5b2c6f;">Definition:</h4>
-            </div>
-        """, unsafe_allow_html=True)
-        st.write("""
-        Unstructured data refers to information that does not follow a predefined format or structure.
-        It is typically raw data that lacks a clear, organized schema, making it harder to store and analyze using traditional tools.
-        
-        Examples include multimedia files (images, videos, audio), emails, and social media posts.
-        """)
-    
-        st.markdown("""
-            <div style="text-align: left; margin-top: 20px;">
-                <h4 style="color: #5b2c6f;">Characteristics:</h4>
-            </div>
-        """, unsafe_allow_html=True)
-        st.write("""
-        - Does not follow a specific schema or structure.
-        - Cannot be stored in traditional tabular formats like rows and columns.
-        - Requires advanced tools like machine learning or natural language processing (NLP) for analysis.
-        """)
-    
-        st.markdown("""
-            <div style="text-align: left; margin-top: 20px;">
-                <h4 style="color: #5b2c6f;">Example:</h4>
-            </div>
-        """, unsafe_allow_html=True)
-        st.write("""
-        Examples of unstructured data include:
-        - **Images**: Photos, screenshots, or scanned documents.
-        - **Audio**: Podcasts, voice recordings, or music files.
-        - **Videos**: Recorded lectures, surveillance footage, or YouTube videos.
-        - **Text**: Emails, social media posts, and blog articles.
-        """)
-    
-        # Transition to Formats in Unstructured Data
-        st.markdown("""
-            <div style="text-align: left; margin-top: 20px;">
-                <h4 style="color: #5b2c6f;">Data Formats in Unstructured Data:</h4>
-            </div>
-        """, unsafe_allow_html=True)
-    
-        st.write("""
-        Unstructured data can exist in various formats, often requiring specialized tools for processing. Common formats include:
-        
-        - **Images**: Formats like JPEG, PNG, BMP, and TIFF.
-        - **Audio**: Formats like MP3, WAV, and FLAC.
-        - **Videos**: Formats like MP4, AVI, and MKV.
-        - **Text**: Formats like TXT, LOG, and DOCX.
-        """)
-    
-        # Add a button to navigate to specific formats
-        if st.button("Explore Unstructured Data"):
-            # Display buttons for each format
-            st.write("Select a format to explore:")
-            
+    Examples include multimedia files (images, videos, audio), emails, and social media posts.
+    """)
+
+    st.write("""
+    **Characteristics:**
+    - Does not follow a specific schema or structure.
+    - Cannot be stored in traditional tabular formats like rows and columns.
+    - Requires advanced tools like machine learning or natural language processing (NLP) for analysis.
+    """)
+
+    st.write("""
+    **Example:**
+    Examples of unstructured data include:
+    - **Images**: Photos, screenshots, or scanned documents.
+    - **Audio**: Podcasts, voice recordings, or music files.
+    - **Videos**: Recorded lectures, surveillance footage, or YouTube videos.
+    - **Text**: Emails, social media posts, and blog articles.
+    """)
+
+    # Data Formats in Unstructured Data
+    st.write("""
+    **Data Formats in Unstructured Data:**
+    - **Images**: Formats like JPEG, PNG, BMP, and TIFF.
+    - **Audio**: Formats like MP3, WAV, and FLAC.
+    - **Videos**: Formats like MP4, AVI, and MKV.
+    - **Text**: Formats like TXT, LOG, and DOCX.
+    """)
+
+    # Explore Formats
+    if st.button("Explore Unstructured Data"):
+        st.write("Select a format to explore:")
+        col1, col2, col3, col4 = st.columns(4)
+
+        with col1:
             if st.button("Images"):
-                st.write("Images are a type of unstructured data often used in computer vision. Common formats: JPEG, PNG.")
-            
+                st.write("Images are often used in computer vision tasks. Common formats: JPEG, PNG.")
+
+        with col2:
             if st.button("Audio"):
                 st.write("Audio files represent sound data. Common formats: MP3, WAV.")
-            
+
+        with col3:
             if st.button("Video"):
                 st.write("Video files combine visual and audio data. Common formats: MP4, AVI.")
-            
+
+        with col4:
             if st.button("Text"):
                 st.write("Text data includes raw documents like emails or logs. Common formats: TXT, DOCX.")
-    
-