Add numpy-pandas practice problems (L1 basics)

Author: Brian Elinsky

7-numpy-pandas/L1_basics/array_creation.py

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+"""
+Array Creation Exercises
+
+Problem N1.01 - N1.03
+"""
+import numpy as np
+
+
+def identity_matrix_3x3() -> np.ndarray:
+    """
+    N1.01: Create a 3x3 identity matrix.
+
+    Returns:
+        np.ndarray: 3x3 identity matrix
+    """
+    # TODO - you fill in here
+    pass
+
+
+def zeros_with_fifth_one() -> np.ndarray:
+    """
+    N1.02: Create an array of 10 zeros, then set the 5th value (index 4) to 1.
+
+    Returns:
+        np.ndarray: Array of shape (10,) with zeros except index 4 is 1
+    """
+    # TODO - you fill in here
+    pass
+
+
+def random_array_0_to_1() -> np.ndarray:
+    """
+    N1.03: Create an array of 10 random numbers between 0 and 1.
+
+    Returns:
+        np.ndarray: Array of shape (10,) with random values in [0, 1)
+    """
+    # TODO - you fill in here
+    pass
+
+
+# ============ Tests ============
+if __name__ == '__main__':
+    # Test N1.01
+    result = identity_matrix_3x3()
+    expected = np.eye(3)
+    assert result is not None, "N1.01: Function returned None"
+    assert result.shape == (3, 3), f"N1.01: Expected shape (3,3), got {result.shape}"
+    assert np.array_equal(result, expected), "N1.01: Not an identity matrix"
+    print("N1.01 identity_matrix_3x3: PASSED")
+
+    # Test N1.02
+    result = zeros_with_fifth_one()
+    expected = np.zeros(10)
+    expected[4] = 1
+    assert result is not None, "N1.02: Function returned None"
+    assert result.shape == (10,), f"N1.02: Expected shape (10,), got {result.shape}"
+    assert np.array_equal(result, expected), f"N1.02: Expected {expected}, got {result}"
+    print("N1.02 zeros_with_fifth_one: PASSED")
+
+    # Test N1.03
+    result = random_array_0_to_1()
+    assert result is not None, "N1.03: Function returned None"
+    assert result.shape == (10,), f"N1.03: Expected shape (10,), got {result.shape}"
+    assert np.all((result >= 0) & (result < 1)), "N1.03: Values should be in [0, 1)"
+    print("N1.03 random_array_0_to_1: PASSED")
+
+    print("\nAll array creation tests passed!")

7-numpy-pandas/L1_basics/broadcasting.py

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+"""
+Broadcasting Exercises
+
+Problem N1.06
+"""
+import numpy as np
+
+
+def add_1d_to_each_row(arr_2d: np.ndarray, arr_1d: np.ndarray) -> np.ndarray:
+    """
+    N1.06: Add a 1D array to each row of a 2D array.
+
+    Example:
+        arr_2d = [[1, 1, 1],
+                  [2, 2, 2],
+                  [3, 3, 3]]
+        arr_1d = [1, 2, 3]
+
+        Output = [[2, 3, 4],
+                  [3, 4, 5],
+                  [4, 5, 6]]
+
+    Args:
+        arr_2d: 2D array of shape (n, m)
+        arr_1d: 1D array of shape (m,)
+
+    Returns:
+        np.ndarray: Result of adding arr_1d to each row of arr_2d
+    """
+    # TODO - you fill in here
+    pass
+
+
+# ============ Tests ============
+if __name__ == '__main__':
+    # Test N1.06
+    arr_2d = np.array([[1, 1, 1],
+                       [2, 2, 2],
+                       [3, 3, 3]])
+    arr_1d = np.array([1, 2, 3])
+    result = add_1d_to_each_row(arr_2d, arr_1d)
+    expected = np.array([[2, 3, 4],
+                         [3, 4, 5],
+                         [4, 5, 6]])
+    assert result is not None, "N1.06: Function returned None"
+    assert np.array_equal(result, expected), f"N1.06: Expected\n{expected}\ngot\n{result}"
+    print("N1.06 add_1d_to_each_row: PASSED")
+
+    # Test with different values
+    arr_2d = np.ones((3, 3))
+    arr_1d = np.array([10, 20, 30])
+    result = add_1d_to_each_row(arr_2d, arr_1d)
+    expected = np.array([[11, 21, 31],
+                         [11, 21, 31],
+                         [11, 21, 31]])
+    assert np.array_equal(result, expected), f"N1.06 (test 2): Expected\n{expected}\ngot\n{result}"
+    print("N1.06 add_1d_to_each_row (test 2): PASSED")
+
+    print("\nAll broadcasting tests passed!")

7-numpy-pandas/L1_basics/indexing_slicing.py

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+"""
+Indexing and Slicing Exercises
+
+Problem N1.04 - N1.05
+"""
+import numpy as np
+
+
+def last_three_reversed(a: np.ndarray) -> np.ndarray:
+    """
+    N1.04: Given an array, extract the last 3 elements and reverse them.
+
+    Example:
+        Input:  np.arange(10, 100, 10)  # [10, 20, 30, 40, 50, 60, 70, 80, 90]
+        Output: [90, 80, 70]
+
+    Args:
+        a: Input array
+
+    Returns:
+        np.ndarray: Last 3 elements in reverse order
+    """
+    # TODO - you fill in here
+    pass
+
+
+def replace_even_with_negative_one(a: np.ndarray) -> np.ndarray:
+    """
+    N1.05: Replace all even numbers with -1 in an array.
+
+    Note: Modify and return a copy, don't modify the original.
+
+    Example:
+        Input:  [1, 2, 3, 4, 5, 6]
+        Output: [1, -1, 3, -1, 5, -1]
+
+    Args:
+        a: Input array of integers
+
+    Returns:
+        np.ndarray: Array with even numbers replaced by -1
+    """
+    # TODO - you fill in here
+    pass
+
+
+# ============ Tests ============
+if __name__ == '__main__':
+    # Test N1.04
+    a = np.arange(10, 100, 10)
+    result = last_three_reversed(a)
+    expected = np.array([90, 80, 70])
+    assert result is not None, "N1.04: Function returned None"
+    assert np.array_equal(result, expected), f"N1.04: Expected {expected}, got {result}"
+    print("N1.04 last_three_reversed: PASSED")
+
+    # Test N1.05
+    a = np.array([1, 2, 3, 4, 5, 6])
+    result = replace_even_with_negative_one(a)
+    expected = np.array([1, -1, 3, -1, 5, -1])
+    assert result is not None, "N1.05: Function returned None"
+    assert np.array_equal(result, expected), f"N1.05: Expected {expected}, got {result}"
+    # Make sure original wasn't modified
+    assert np.array_equal(a, np.array([1, 2, 3, 4, 5, 6])), "N1.05: Original array was modified"
+    print("N1.05 replace_even_with_negative_one: PASSED")
+
+    print("\nAll indexing/slicing tests passed!")

7-numpy-pandas/solutions/array_creation.py

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+"""Solutions for Array Creation Exercises"""
+import numpy as np
+
+
+def identity_matrix_3x3() -> np.ndarray:
+    return np.eye(3)
+
+
+def zeros_with_fifth_one() -> np.ndarray:
+    arr = np.zeros(10)
+    arr[4] = 1
+    return arr
+
+
+def random_array_0_to_1() -> np.ndarray:
+    return np.random.random(10)

7-numpy-pandas/solutions/broadcasting.py

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+"""Solutions for Broadcasting Exercises"""
+import numpy as np
+
+
+def add_1d_to_each_row(arr_2d: np.ndarray, arr_1d: np.ndarray) -> np.ndarray:
+    return arr_2d + arr_1d

7-numpy-pandas/solutions/indexing_slicing.py

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+"""Solutions for Indexing and Slicing Exercises"""
+import numpy as np
+
+
+def last_three_reversed(a: np.ndarray) -> np.ndarray:
+    return a[-3:][::-1]
+
+
+def replace_even_with_negative_one(a: np.ndarray) -> np.ndarray:
+    result = a.copy()
+    result[result % 2 == 0] = -1
+    return result