Update pages/Data Collection.py

pages/Data Collection.py

@@ -66,76 +66,77 @@ data_type = st.radio(
     ("Structured Data", "Unstructured Data", "Semi-Structured Data")
 )
 
-# Structured Data Section
-# Ensure session state is initialized
+# Ensure session state for Explore Excel is initialized
 if "explore_excel" not in st.session_state:
     st.session_state.explore_excel = False
 
-if data_type == "Structured Data" and not st.session_state.explore_excel:
-    st.markdown("""
-        <div style="text-align: left; margin-top: 20px;">
-            <h3 style="color: #e25822;">What is Structured 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("""
-    **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.
-    """)
-
-    st.markdown("""
-        <div style="text-align: left; margin-top: 20px;">
-            <h4 style="color: #5b2c6f;">Characteristics:</h4>
-        </div>
-    """, unsafe_allow_html=True)
-    st.write("""
-    - 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;">Examples:</h4>
-        </div>
-    """, unsafe_allow_html=True)
-    st.write("""
-    A database of students with fields like ID, name, age, and gender:
-    """)
-
-    student_data = {
-        "Id": [100, 101, 102, 103],
-        "Name": ["Lakshmi Harika", "Varshitha", "Hari Chandan", "Shamitha"],
-        "Age": [22, 23, 22, 23],
-        "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)
-
-    st.markdown("""
-        <div style="text-align: left; margin-top: 20px;">
-            <h4 style="color: #5b2c6f;">Data Formats in Structured Data:</h4>
-        </div>
-    """, unsafe_allow_html=True)
-
-    st.write("Click to explore Structured Data Formats:")
-    if st.button("Structured Data Formats"):
-        st.write("Select a format to explore:")
-
-        # Sub-buttons for specific formats
-        col1, = st.columns(1)
-
-        with col1:
-            if st.button("Explore Excel"):
-                st.session_state.explore_excel = True
-
+if not st.session_state.explore_excel:
+    if data_type == "Structured Data":
+        st.markdown("""
+            <div style="text-align: left; margin-top: 20px;">
+                <h3 style="color: #e25822;">What is Structured 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("""
+        **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.
+        """)
+
+        st.markdown("""
+            <div style="text-align: left; margin-top: 20px;">
+                <h4 style="color: #5b2c6f;">Characteristics:</h4>
+            </div>
+        """, unsafe_allow_html=True)
+        st.write("""
+        - 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;">Examples:</h4>
+            </div>
+        """, unsafe_allow_html=True)
+        st.write("""
+        A database of students with fields like ID, name, age, and gender:
+        """)
+
+        student_data = {
+            "Id": [100, 101, 102, 103],
+            "Name": ["Lakshmi Harika", "Varshitha", "Hari Chandan", "Shamitha"],
+            "Age": [22, 23, 22, 23],
+            "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)
+
+        st.markdown("""
+            <div style="text-align: left; margin-top: 20px;">
+                <h4 style="color: #5b2c6f;">Data Formats in Structured Data:</h4>
+            </div>
+        """, unsafe_allow_html=True)
+
+        st.write("Click to explore Structured Data Formats:")
+        if st.button("Structured Data Formats"):
+            st.write("Select a format to explore:")
+
+            # Sub-buttons for specific formats
+            col1, = st.columns(1)
+
+            with col1:
+                if st.button("Explore Excel"):
+                    st.session_state.explore_excel = True
+
+# Excel Content
 if st.session_state.explore_excel:
     st.markdown("""
         <div style="text-align: left; margin-top: 20px;">