Update pages/3_NumpyBasics.py

pages/3_NumpyBasics.py

@@ -1,123 +1,143 @@
 import streamlit as st
 import numpy as np
 
-# Example functions
+# Example functions with explanations
 def example1():
+    explanation = "Importing the NumPy library."
     code = "import numpy as np"
     exec(code)
-    return code
+    return explanation, code
 
 def example2():
+    explanation = "Creating a simple NumPy array."
     code = "array = np.array([1, 2, 3, 4, 5])\narray"
     array = np.array([1, 2, 3, 4, 5])
-    return code, array
+    return explanation, code, array
 
 def example3():
+    explanation = "Creating an array with a range of values from 0 to 9."
     code = "array = np.arange(10)\narray"
     array = np.arange(10)
-    return code, array
+    return explanation, code, array
 
 def example4():
+    explanation = "Creating an array with 5 evenly spaced values between 0 and 1."
     code = "array = np.linspace(0, 1, 5)\narray"
     array = np.linspace(0, 1, 5)
-    return code, array
+    return explanation, code, array
 
 def example5():
+    explanation = "Reshaping a 2D array from shape (2, 3) to (3, 2)."
     code = "array = np.array([[1, 2, 3], [4, 5, 6]])\nreshaped_array = array.reshape((3, 2))\nreshaped_array"
     array = np.array([[1, 2, 3], [4, 5, 6]])
     reshaped_array = array.reshape((3, 2))
-    return code, reshaped_array
+    return explanation, code, reshaped_array
 
 def example6():
+    explanation = "Slicing a 1D array to get elements from index 1 to 3."
     code = "array = np.array([1, 2, 3, 4, 5])\narray[1:4]"
     array = np.array([1, 2, 3, 4, 5])
     sliced_array = array[1:4]
-    return code, sliced_array
+    return explanation, code, sliced_array
 
 def example7():
+    explanation = "Using fancy indexing to select specific elements from a 2D array."
     code = "array = np.array([[1, 2], [3, 4], [5, 6]])\nfancy_indexed_array = array[[0, 1], [1, 0]]\nfancy_indexed_array"
     array = np.array([[1, 2], [3, 4], [5, 6]])
     fancy_indexed_array = array[[0, 1], [1, 0]]
-    return code, fancy_indexed_array
+    return explanation, code, fancy_indexed_array
 
 def example8():
+    explanation = "Using boolean indexing to select elements greater than 3."
     code = "array = np.array([1, 2, 3, 4, 5])\nboolean_indexed_array = array[array > 3]\nboolean_indexed_array"
     array = np.array([1, 2, 3, 4, 5])
     boolean_indexed_array = array[array > 3]
-    return code, boolean_indexed_array
+    return explanation, code, boolean_indexed_array
 
 def example9():
+    explanation = "Performing element-wise multiplication of a 1D array by 2."
     code = "array = np.array([1, 2, 3, 4, 5])\narray * 2"
     array = np.array([1, 2, 3, 4, 5])
     result = array * 2
-    return code, result
+    return explanation, code, result
 
 def example10():
+    explanation = "Calculating the sum of all elements in a 2D array."
     code = "array = np.array([[1, 2, 3], [4, 5, 6]])\nnp.sum(array)"
     array = np.array([[1, 2, 3], [4, 5, 6]])
     result = np.sum(array)
-    return code, result
+    return explanation, code, result
 
 def example11():
+    explanation = "Calculating the dot product of two matrices."
     code = "matrix = np.array([[1, 2], [3, 4]])\nnp.dot(matrix, matrix)"
     matrix = np.array([[1, 2], [3, 4]])
     result = np.dot(matrix, matrix)
-    return code, result
+    return explanation, code, result
 
 def example12():
+    explanation = "Performing broadcasting by adding two 1D arrays element-wise."
     code = "array = np.array([1, 2, 3])\narray + np.array([4, 5, 6])"
     array = np.array([1, 2, 3])
     result = array + np.array([4, 5, 6])
-    return code, result
+    return explanation, code, result
 
 def example13():
+    explanation = "Generating a 2x2 array with random values between 0 and 1."
     code = "random_array = np.random.random((2, 2))\nrandom_array"
     random_array = np.random.random((2, 2))
-    return code, random_array
+    return explanation, code, random_array
 
 def example14():
+    explanation = "Sorting a 1D array in ascending order."
     code = "array = np.array([3, 1, 2])\nnp.sort(array)"
     array = np.array([3, 1, 2])
     sorted_array = np.sort(array)
-    return code, sorted_array
+    return explanation, code, sorted_array
 
 def example15():
+    explanation = "Finding the index of a value in a sorted array."
     code = "array = np.array([1, 2, 3, 4, 5])\nnp.searchsorted(array, 3)"
     array = np.array([1, 2, 3, 4, 5])
     index = np.searchsorted(array, 3)
-    return code, index
+    return explanation, code, index
 
 def example16():
     from skimage import data
+    explanation = "Calculating the mean value of an image."
     code = "from skimage import data\nimage = data.camera()\nnp.mean(image)"
     image = data.camera()
     mean_value = np.mean(image)
-    return code, mean_value
+    return explanation, code, mean_value
 
 def example17():
+    explanation = "Simulating random positions and velocities in a 2D space."
     code = "positions = np.random.random((10, 2))\nvelocities = np.random.random((10, 2))\npositions + velocities"
     positions = np.random.random((10, 2))
     velocities = np.random.random((10, 2))
     result = positions + velocities
-    return code, result
+    return explanation, code, result
 
 def example18():
+    explanation = "Calculating the mean of each column in a 2D array."
     code = "data = np.random.random((100, 4))\nnp.mean(data, axis=0)"
     data = np.random.random((100, 4))
     mean_values = np.mean(data, axis=0)
-    return code, mean_values
+    return explanation, code, mean_values
 
 def example19():
+    explanation = "Calculating the element-wise power of a 1D array."
     code = "array = np.array([1, 2, 3])\nnp.power(array, 3)"
     array = np.array([1, 2, 3])
     result = np.power(array, 3)
-    return code, result
+    return explanation, code, result
 
 def example20():
+    explanation = "Calculating the cumulative sum of a 1D array."
     code = "array = np.array([1, 2, 3, 4, 5])\nnp.cumsum(array)"
     array = np.array([1, 2, 3, 4, 5])
     result = np.cumsum(array)
-    return code, result
+    return explanation, code, result
 
 examples = [
     ("Example 1: Import NumPy", example1),
@@ -146,7 +166,8 @@ st.title("NumPy Course with Streamlit")
 
 for title, func in examples:
     st.header(title)
+    explanation, code, result = func()
+    st.write(explanation)
+    st.code(code)
     if st.button(f"Run {title.split(':')[0]}"):
-        code, result = func()
-        st.code(code)
         st.write("Output:", result)