** is a correct syntax to create a NumPy array?**
(A) np.createArray([1, 2, 3, 4, 5])
(B) np.array([1, 2, 3, 4, 5])
(C) np.object([1, 2, 3, 4, 5])

**Which of the following arrays is a two dimensional (2-D) array?**
(A) 42
(B) [1, 2, 3, 4, 5]
(C) [[1, 2, 3], [4, 5, 6]]

** is a correct syntax to check the number of dimensions in an array?**
(A) np.ndim
(B) np.ndim()
(C) np.dim()
(D) np.dim

** is a correct syntax to print the first item of an array?**
(A) print(myArr,1)
(B) print(myArr[1])
(C) print(myArr[0])

** is a correct syntax to print the number 8 from the array below:**
arr = np.array([[1,2,3,4,5], [6,7,8,9,10]])
(A) print(arr[7, 2])
(B) print(arr[3, 0])
(C) print(arr[1, 2])

** is a correct syntax to print the numbers [3, 4, 5] from the array below:**
arr = np.array([1,2,3,4,5,6,7])
(A) print(arr[2:4])
(B) print(arr[3:6])
(C) print(arr[2:5])
(D) print(arr[2:6])

**Which syntax would print the last 4 numbers from the array below:**
arr = np.array([1,2,3,4,5,6,7])
(A) print(arr[3:])
(B) print(arr[:4])
(C) print(arr[4])
(D) print(arr[4:])

**Which syntax would print every other item from the array below:**
arr = np.array([1,2,3,4,5,6,7])
(A) print(arr(0: step = 2))
(B) print(arr[::2])
(C) print(arr[1:3:5:7])

** is a correct syntax to check the data type of an array?**
(A) arr.dtype
(B) arr.datatype
(C) arr.ntype
(D) arr.type

**When using the NumPy random module, how can you return a random number from 0 to 100?**
(A) random.randint(100)
(B) random.rand(100)
(C) random.rand()

** is a correct syntax to create an array of type float?**
(A) arr = np.float([1, 2, 3, 4])
(B) arr = np.array([1, 2, 3, 4]).toFloat()
(C) arr = np.array([1, 2, 3, 4], dtype='f')

**Only one of the following statements is true when it comes to Views in NumPy, which one?**
(A) The view SHOULD NOT be affected by the changes made to the original array.
(B) The view SHOULD be affected by the changes made to the original array.

**Only one of the following statements is true when it comes to Copies in NumPy, which one?**
(A) The copy SHOULD be affected by the changes made to the original array.
(B) The copy SHOULD NOT be affected by the changes made to the original array.

**In NumPy, what does the SHAPE of an array mean?**
(A) The shape is the number of rows.
(B) The shape is the number of elements in each dimension.
(C) The shape is the number of columns.

** is a correct syntax to return the shape of an array?**
(A) shape(arr)
(B) arr.shape()
(C) arr.shape

** is a correct method to join two or more arrays?**
(A) array_join()
(B) join()
(C) concatenate()

** is a correct method to split arrays?**
(A) All the other 3 answers are correct
(B) hstack()
(C) vstack()
(D) array_split()

** is a correct method to search for a certain value in an array?**
(A) search()
(B) where()
(C) find()

** is a correct syntax to return the index of all items that has the value 4 from the array below:**
arr = np.array([1,4,3,4,5,4,4])?
(A) np.where(arr == 4)
(B) arr.search(4)
(C) arr.where()

** is a correct method to sort the elements of an array?**
(A) sort()
(B) order()
(C) orderby()

**When using the NumPy random module, how can you return a Normal Data Distrbution with 1000 numbers, concentrated around the number 50, with a standard deviation of 0.2?**
(A) random.normal(size=1000, loc=50, scale=0.2)
(B) random.normal(size=1000, normal=50, s=0.1)
(C) random.normal(size=1000, mean=50, deviation=0.2)

** is a correct syntax to mathematically add the numbers of arr1 to the numbers of arr2?**
(A) sum(arr1, arr2)
(B) np.add(arr1, arr2)
(C) np.append(arr1, arr2)

** is a correct syntax to subtract the numbers from arr1 with the numbers from arr2?**
(A) np.substract(arr1, arr2)
(B) np.min(arr1, arr2)
(C) np.sub(arr1, arr2)
(D) np.minus(arr1, arr2)

** is a correct method to round decimals in NumPy?**
(A) All the other 3 are rounding methods in NumPy
(B) np.trunc()
(C) np.fix()
(D) np.around()

** would be the answer of this cummulative summation in NumPy?**
arr = np.array([1,2,3])
print(np.cumsum(arr))
(A) [3 6 9]
(B) [9]
(C) [1 3 6]
(D) [6]