updating homework

app/pages/week_2.py

@@ -52,16 +52,17 @@ def show():
     
     # Using a function from the library
     print(math.sqrt(16))  # This will print 4.0
-        """, line_numbers=True)
+        """, language="python", line_numbers=True)
     
     # Interactive Import Exercise
     st.subheader("Try it yourself!")
     import_code = st.text_area("Try importing and using the math library:", 
                              "import math\nprint(math.sqrt(25))", 
                              height=100)
+    st.code(import_code, language="python", line_numbers=True)
     if st.button("Run Import Code"):
         output = capture_output(import_code)
-        st.code(output, line_numbers=True)
+        st.code(output, language="python", line_numbers=True)
     
     # Print Statements Section
     st.header("2. Print Statements")
@@ -80,16 +81,17 @@ def show():
     
     # Print multiple items
     print("The answer is:", 42)
-        """, line_numbers=True)
+        """, language="python", line_numbers=True)
     
     # Interactive Print Exercise
     st.subheader("Try it yourself!")
     print_code = st.text_area("Try some print statements:", 
                             'print("Hello, World!")\nname = "Python"\nprint(f"Hello, {name}!")', 
                             height=100)
+    st.code(print_code, language="python", line_numbers=True)
     if st.button("Run Print Code"):
         output = capture_output(print_code)
-        st.code(output, line_numbers=True)
+        st.code(output, language="python", line_numbers=True)
     
     # Basic Arithmetic Section
     st.header("3. Basic Arithmetic")
@@ -114,16 +116,17 @@ def show():
     # Division
     result = 15 / 3
     print(result)  # Prints 5.0
-        """, line_numbers=True)
+        """, language="python", line_numbers=True)
     
     # Interactive Arithmetic Exercise
     st.subheader("Try it yourself!")
     arithmetic_code = st.text_area("Try some arithmetic operations:", 
                                  'print(5 + 3)\nprint(10 - 4)\nprint(6 * 7)\nprint(15 / 3)', 
                                  height=100)
+    st.code(arithmetic_code, language="python", line_numbers=True)
     if st.button("Run Arithmetic Code"):
         output = capture_output(arithmetic_code)
-        st.code(output, line_numbers=True)
+        st.code(output, language="python", line_numbers=True)
     
     # Lists Section
     st.header("4. Lists")
@@ -145,16 +148,74 @@ def show():
     
     # List length
     print(len(fruits))  # Prints 4
-        """, line_numbers=True)
+        """, language="python", line_numbers=True)
     
     # Interactive List Exercise
     st.subheader("Try it yourself!")
     list_code = st.text_area("Try working with lists:", 
                            'fruits = ["apple", "banana", "cherry"]\nprint(fruits[0])\nfruits.append("orange")\nprint(fruits)\nprint(len(fruits))', 
                            height=100)
+    st.code(list_code, language="python", line_numbers=True)
     if st.button("Run List Code"):
         output = capture_output(list_code)
-        st.code(output, line_numbers=True)
+        st.code(output, language="python", line_numbers=True)
+    
+    # Loops Section
+    st.header("5. Loops")
+    st.markdown("""
+    Loops are used to repeat a block of code multiple times. Python has two main types of loops:
+    - `for` loops: Used to iterate over a sequence (like a list, string, or range)
+    - `while` loops: Used to repeat code while a condition is true
+    """)
+    
+    with st.expander("For Loop Examples"):
+        st.code("""
+    # Basic for loop
+    fruits = ["apple", "banana", "cherry"]
+    for fruit in fruits:
+        print(fruit)
+    
+    # For loop with range
+    for i in range(5):  # Prints numbers 0 to 4
+        print(i)
+    
+    # For loop with index
+    for i, fruit in enumerate(fruits):
+        print(f"Index {i}: {fruit}")
+        """, language="python", line_numbers=True)
+    
+    with st.expander("While Loop Examples"):
+        st.code("""
+    # Basic while loop
+    count = 0
+    while count < 5:
+        print(count)
+        count += 1
+    
+    # While loop with break
+    while True:
+        user_input = input("Enter 'quit' to exit: ")
+        if user_input == 'quit':
+            break
+        print(f"You entered: {user_input}")
+        """, language="python", line_numbers=True)
+    
+    # Interactive Loop Exercise
+    st.subheader("Try it yourself!")
+    st.markdown("""
+    Try these exercises:
+    1. Create a for loop that prints numbers from 1 to 10
+    2. Create a while loop that counts down from 5 to 1
+    3. Use a for loop to print each letter in your name
+    """)
+    
+    loop_code = st.text_area("Write your loop code here:", 
+                           '# Exercise 1\nfor i in range(1, 11):\n    print(i)\n\n# Exercise 2\ncount = 5\nwhile count > 0:\n    print(count)\n    count -= 1\n\n# Exercise 3\nname = "Python"\nfor letter in name:\n    print(letter)', 
+                           height=150)
+    st.code(loop_code, language="python", line_numbers=True)
+    if st.button("Run Loop Code"):
+        output = capture_output(loop_code)
+        st.code(output, language="python", line_numbers=True)
     
     # Practice Exercise
     st.header("Practice Exercise")
@@ -171,32 +232,125 @@ def show():
     practice_code = st.text_area("Write your solution here:", 
                                'import math\n\nnumbers = [4, 9, 16, 25]\n\nfor num in numbers:\n    print(f"Number: {num}, Square root: {math.sqrt(num)}")', 
                                height=150)
+    st.code(practice_code, language="python", line_numbers=True)
     if st.button("Run Practice Code"):
         output = capture_output(practice_code)
-        st.code(output, line_numbers=True)
+        st.code(output, language="python", line_numbers=True)
     
     st.markdown("""
     ## Part 2: Data Cleaning Lab
     
     In this lab, we'll learn how to clean and prepare data using pandas. We'll work with the Advertising dataset and practice common data cleaning techniques.
     
-    This lab is hosted in a Jupyter notebook environment. We will create a new notebook for this lab.
+    Let's start with some basic examples of working with data in pandas:
     """)
 
+    # Example 1: Reading CSV from URL
+    st.header("Example 1: Reading CSV from URL")
+    st.markdown("""
+    There are several ways to read a CSV file from a URL using pandas. Here are some examples:
+    """)
+    
+    with st.expander("Method 1: Using pandas.read_csv()"):
+        st.code("""
+    import pandas as pd
+    
+    # Method 1: Direct URL
+    url = "https://www.statlearning.com/s/Advertising.csv"
+    df = pd.read_csv(url)
+    print(df.head())
+        """, line_numbers=True)
+    
+    with st.expander("Method 2: Using requests and StringIO"):
+        st.code("""
+    import pandas as pd
+    import requests
+    from io import StringIO
+    
+    # Method 2: Using requests
+    url = "https://www.statlearning.com/s/Advertising.csv"
+    response = requests.get(url)
+    data = StringIO(response.text)
+    df = pd.read_csv(data)
+    print(df.head())
+        """, line_numbers=True)
+    
+    # Example 2: Answering Questions about the Dataset
+    st.header("Example 2: Answering Questions about the Dataset")
+    st.markdown("""
+    Once we have loaded our data, we can answer various questions about it. Here are some common questions and how to answer them:
+    """)
+    
+    with st.expander("Question 1: How many rows and columns are in the dataset?"):
+        st.code("""
+    # Get the shape of the dataframe
+    print(f"Number of rows: {df.shape[0]}")
+    print(f"Number of columns: {df.shape[1]}")
+        """, line_numbers=True)
+    
+    with st.expander("Question 2: What are the column names and data types?"):
+        st.code("""
+    # Get column names
+    print("Column names:")
+    print(df.columns.tolist())
+    
+    # Get data types
+    print("\nData types:")
+    print(df.dtypes)
+        """, line_numbers=True)
+    
+    with st.expander("Question 3: What are the basic statistics of numerical columns?"):
+        st.code("""
+    # Get descriptive statistics
+    print(df.describe())
+        """, line_numbers=True)
+    
+    with st.expander("Question 4: Are there any missing values?"):
+        st.code("""
+    # Check for missing values
+    print("Missing values per column:")
+    print(df.isnull().sum())
+        """, line_numbers=True)
+    
+    with st.expander("Question 5: What are the unique values in categorical columns?"):
+        st.code("""
+    # For each column, print unique values
+    for column in df.select_dtypes(include=['object']).columns:
+        print(f"\nUnique values in {column}:")
+        print(df[column].unique())
+        """, line_numbers=True)
+    
+    # Interactive Exercise
+    st.header("Try it yourself!")
+    st.markdown("""
+    Now it's your turn to try these examples. Use the code editor below to:
+    1. Load the Advertising dataset from the URL
+    2. Answer the questions above about the dataset
+    """)
+    
+    # Code editor for interactive exercise
+    exercise_code = st.text_area("Write your code here:", 
+                               'import pandas as pd\n\n# Your code here', 
+                               height=200)
+    
+    if st.button("Run Code"):
+        output = capture_output(exercise_code)
+        st.code(output, line_numbers=True)
     
     st.markdown("""
     ## Week 2: Reference Material
     
     Please refer to the following links:
-    - [Pandas Documentation](https://pandas.pydata.org/docs/)
-    - [Numpy Documentation](https://numpy.org/doc/)
-    - [Matplotlib Documentation](https://matplotlib.org/stable/users/index.html)
-    - [Seaborn Documentation](https://seaborn.pydata.org/index.html)
-    For learning more about python use the following link:
-    - [Introduction to Statistical Learning](https://www.statlearning.com/resources-python)
-    - [Learning Python notebook](https://github.com/intro-stat-learning/ISLP_labs/blob/stable/Ch02-statlearn-lab.ipynb)
-    For our dataset used today for class:
-    - [Advertising Dataset](https://www.statlearning.com/s/Advertising.csv)
+    - Library Documentation
+        - [Pandas Documentation](https://pandas.pydata.org/docs/)
+        - [Numpy Documentation](https://numpy.org/doc/)
+        - [Matplotlib Documentation](https://matplotlib.org/stable/users/index.html)
+        - [Seaborn Documentation](https://seaborn.pydata.org/index.html)
+    - Learning Python
+        - [Introduction to Statistical Learning](https://www.statlearning.com/resources-python)
+        - [Learning Python notebook](https://github.com/intro-stat-learning/ISLP_labs/blob/stable/Ch02-statlearn-lab.ipynb)
+        For our dataset used today for class:
+        - [Advertising Dataset](https://www.statlearning.com/s/Advertising.csv)
     """)
     
     # Weekly Assignment
@@ -211,17 +365,7 @@ def show():
         - What is the data type of each variable?
         - What is the range of each variable?
         - What is the mean of each variable?
-    
+    4. Think about what research question you want to answer with this dataset.
     **Due Date:** End of Week 2
     """)
-    
-    # Assignment Submission
-    #st.subheader("Submit Your Assignment")
-    #with st.form("assignment_form"):
-    #    script_file = st.file_uploader("Upload your Python script (.py)")
-    #    comments = st.text_area("Additional comments or questions")
-    #    if st.form_submit_button("Submit Assignment"):
-    #        if script_file is not None:
-    #            st.success("Assignment submitted successfully!")
-    #        else:
-    #            st.error("Please upload your Python script.")
+