# Problem 1¶

Import the NumPy library under the alias np.

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# Problem 2¶

Given the following NumPy array, return the first element and the last element.

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arr = np.array([8,2,4,9,7,3,8,1])

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#Return the first element here

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#Returns the last element here


# Problem 3¶

Given the following NumPy array, return the entire array except for the last element.

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new_arr = np.array([1,6,4,8,7,5,2,1,4,5,6,1,4,5,6,2,1])

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#Place your solution here


# Problem 4¶

Change the second element of this_arr to 4.

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this_arr = np.array([2,4,89,7,5,4,2,6,4,5,78,1,6,9,7,456,12,45])

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#Place your solution here
this_arr[1] = 4


# Problem 5¶

Given the array original_array, create a reference to that array called reference_array. Change the second element of reference_array to 16 and then print original_array to verify that it modified the original data structure.

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original_array = np.array([12,45,86,79,45,26,13,46,28])

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#Solution goes here


# Problem 6¶

Given the array first_array, create a copy of the array called copy_array. Change the third element of copy_array to 42 and then print first_array to verify that its elements remain unchanged.

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first_array = np.array([16,45,75,16,43,45,78,19,23,46,79,58])

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#Solution goes here


# Problem 7¶

Given the two-dimensional array matrix, print the value 35.

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matrix = np.array([[15, 120, 115],[230, 35, 130],[335, 420, 425]])

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#Solution goes here


# Problem 8¶

Given the array integer_array, print a NumPy array of Boolean values that indicate whether the corresponding values in integer_array are greater than 4.

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integer_array = np.array([2,6,4,9,8,5,3,1,2,5,4,8,7,5,6])

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#Solution goes here


# Problem¶

Given the same array integer_array, print a new NumPy array that only includes the values from integer_array that are less then 6.

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