Update pages/3_Life Cycle Of ML Project.py

pages/3_Life Cycle Of ML Project.py

@@ -1,6 +1,7 @@
 import streamlit as st
 import json
 import xml.etree.ElementTree as ET
+import pandas as pd
 
 # Initialize page navigation state
 if 'page' not in st.session_state:
@@ -215,30 +216,12 @@ while video.isOpened():
     if not ret:
         break
     cv2.imshow('Frame', frame)
-    if cv2.waitKey(25) & 0xFF == ord('q'):
+    if cv2.waitKey(1) & 0xFF == ord('q'):
         break
 video.release()
 cv2.destroyAllWindows()
     """, language='python')
 
-    st.header("🔊 Handling Audio Data")
-    st.markdown("""
-    Audio data can be handled using libraries like librosa.
-    """)
-    st.code("""
-import librosa
-# Load an audio file
-y, sr = librosa.load('sample_audio.wav')
-# Display waveform
-import matplotlib.pyplot as plt
-plt.figure(figsize=(10, 4))
-plt.plot(y)
-plt.title("Audio Waveform")
-plt.show()
-    """, language='python')
-
-    st.link_button(":blue[Open Jupyter Notebook](https://colab.research.google.com/drive/1sT35x4JH9s_hb31aMoUwtry-w8FE7fQg?usp=sharing)")
-
     if st.button(":red[Back to Data Collection]"):
         st.session_state.page = "data_collection"
 
@@ -246,129 +229,83 @@ plt.show()
 elif st.session_state.page == "semi_structured_data":
     st.title(":blue[Semi-Structured Data]")
     st.markdown("""
-    Semi-structured data is data that does not conform to a rigid schema like structured data but still has some organization, typically with tags or markers to separate elements.
-    Examples:
-    - XML files
-    - JSON files
-    - HTML documents
+    Semi-structured data does not have a rigid structure but contains tags and markers to separate different data elements, like XML or JSON.
     """)
 
-    if st.button(":blue[📜 XML]"):
+    if st.button(":blue[XML Data]"):
         st.session_state.page = "xml"
 
-    if st.button(":blue[📄 JSON]"):
+    if st.button(":blue[JSON Data]"):
         st.session_state.page = "json"
 
-    if st.button(":blue[🌐 HTML]"):
-        st.session_state.page = "html"
-
     if st.button(":red[Back to Data Collection]"):
         st.session_state.page = "data_collection"
 
 # ----------------- XML Data Page -----------------
 elif st.session_state.page == "xml":
-    st.title(":red[XML Data Format]")
-    st.markdown("""
-    XML (Extensible Markup Language) is used to store and transport data. It uses tags to define data elements.
+    st.title(":blue[XML Data Format]")
+    st.write("""
+    XML (Extensible Markup Language) is a markup language that defines rules for encoding documents in a format that is both human-readable and machine-readable.
     """)
-    st.markdown("### How to Read XML Data")
+    st.markdown("### Example: Reading XML data")
     st.code("""
 import xml.etree.ElementTree as ET
+
 tree = ET.parse('data.xml')
 root = tree.getroot()
-print(root.tag, root.attrib)
-for child in root:
-    print(child.tag, child.attrib)
-    for elem in child.iter():
-        print(elem.tag, elem.text)
+
+for elem in root:
+    print(elem.tag, elem.text)
     """, language='python')
 
-    st.markdown("### Issues Encountered")
+    st.write("### Issues Encountered")
     st.write("""
-    - *Invalid XML structure*: Ensure the XML is well-formed.
-    - *File not found*: Check the path to the XML file.
+    - *File not found*: Incorrect file path.
     """)
 
-    st.write("### Solutions")
+    st.write("### Solutions to These Issues")
     st.code("""
-# Handle invalid XML structure
 try:
     tree = ET.parse('data.xml')
     root = tree.getroot()
-except ET.ParseError:
-    print("Error in parsing XML file")
+except FileNotFoundError:
+    print("File not found. Check the file path.")
     """, language='python')
 
-    st.link_button(":blue[Open Jupyter Notebook](https://colab.research.google.com/drive/1sT35x4JH9s_hb31aMoUwtry-w8FE7fQg?usp=sharing)")
-
     if st.button(":red[Back to Semi-Structured Data]"):
         st.session_state.page = "semi_structured_data"
 
 # ----------------- JSON Data Page -----------------
 elif st.session_state.page == "json":
-    st.title(":red[JSON Data Format]")
-    st.markdown("""
-    JSON (JavaScript Object Notation) is a lightweight format for storing and exchanging data. It is human-readable and easy to parse.
-    """)
-    st.markdown("### How to Read JSON Data")
-    st.code("""
-import json
-# Open and load the JSON data
-with open('data.json') as json_file:
-    data = json.load(json_file)
-    print(data)
-    """, language='python')
-
-    st.markdown("### Issues Encountered")
+    st.title(":blue[JSON Data Format]")
     st.write("""
-    - *Invalid JSON structure*: Ensure the file is a well-formed JSON.
-    - *File not found*: Incorrect path to JSON file.
+    JSON (JavaScript Object Notation) is a lightweight data-interchange format that is easy for humans to read and write, and easy for machines to parse and generate.
     """)
 
-    st.write("### Solutions")
+    st.markdown("### Example: Reading JSON data")
     st.code("""
-# Handle invalid JSON structure
-try:
-    with open('data.json') as json_file:
-        data = json.load(json_file)
-except json.JSONDecodeError:
-    print("Error: Invalid JSON format")
-    """, language='python')
-
-    st.link_button(":blue[Open Jupyter Notebook](https://colab.research.google.com/drive/1sT35x4JH9s_hb31aMoUwtry-w8FE7fQg?usp=sharing)")
+import json
 
-    if st.button(":red[Back to Semi-Structured Data]"):
-        st.session_state.page = "semi_structured_data"
+# Reading a JSON file
+with open('data.json', 'r') as file:
+    data = json.load(file)
 
-# ----------------- HTML Data Page -----------------
-elif st.session_state.page == "html":
-    st.title(":red[HTML Data Format]")
-    st.markdown("""
-    HTML (Hypertext Markup Language) is the standard markup language for documents designed to be displayed in a web browser.
-    """)
-    st.markdown("### How to Handle HTML Data")
-    st.code("""
-from bs4 import BeautifulSoup
-
-html_content = '''<html><head><title>Test Page</title></head><body><h1>Welcome</h1></body></html>'''
-soup = BeautifulSoup(html_content, 'html.parser')
-print(soup.prettify())
+print(data)
     """, language='python')
 
-    st.markdown("### Issues Encountered")
+    st.write("### Issues Encountered")
     st.write("""
-    - *Malformed HTML*: HTML content needs to be correctly structured.
-    - *Missing libraries*: BeautifulSoup might be missing.
+    - *File not found*: Incorrect file path.
     """)
 
-    st.write("### Solutions")
+    st.write("### Solutions to These Issues")
     st.code("""
-# Install BeautifulSoup if missing
-# pip install beautifulsoup4
-# Correct malformed HTML
+try:
+    with open('data.json', 'r') as file:
+        data = json.load(file)
+except FileNotFoundError:
+    print("File not found. Check the file path.")
     """, language='python')
 
-    st.link_button(":blue[Open Jupyter Notebook](https://colab.research.google.com/drive/1sT35x4JH9s_hb31aMoUwtry-w8FE7fQg?usp=sharing)")
-
     if st.button(":red[Back to Semi-Structured Data]"):
         st.session_state.page = "semi_structured_data"