Update pages/3_Life Cycle Of ML Project.py
Browse files
pages/3_Life Cycle Of ML Project.py
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@@ -262,3 +262,54 @@ data = '''
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"age": 25,
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"skills": ["Python", "Machine Learning"]
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}
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"age": 25,
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"skills": ["Python", "Machine Learning"]
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}
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'''
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# Parse JSON
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parsed_data = json.loads(data)
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print(parsed_data['name']) # Output: Alice
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""", language='python')
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st.header("🔹 Reading JSON Files")
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st.code("""
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# Reading a JSON file
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with open('data.json', 'r') as file:
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data = json.load(file)
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print(data)
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""", language='python')
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st.header("🔹 XML Data")
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st.markdown("""
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XML is a markup language that defines a set of rules for encoding documents.
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""")
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st.code("""
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import xml.etree.ElementTree as ET
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# Sample XML data
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xml_data = '''
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<person>
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<name>Bob</name>
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<age>30</age>
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<city>New York</city>
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</person>
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'''
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# Parse XML
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root = ET.fromstring(xml_data)
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print(root.find('name').text) # Output: Bob
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""", language='python')
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st.markdown("### Challenges with Semi-Structured Data")
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st.write("""
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- **Complex Parsing**: Requires specialized parsers.
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- **Nested Data**: Can be deeply nested, making it harder to process.
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""")
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st.markdown("### Solutions")
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st.write("""
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- **Libraries**: Use libraries like json, xml.etree.ElementTree, and yaml for parsing.
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- **Validation**: Validate data formats to avoid parsing errors.
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""")
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# Back to Data Collection
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if st.button("Back to Data Collection"):
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st.session_state.page = "data_collection"
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