Question

Question 2. Numpy and line plot Run the following code in the template file to load data into a Numpy array. flights = load_dataset('flights') data = np.array(flights['passengers']) data [15 marks] (a) [8 marks] Make a line plot to show the data in the array and draw a horizontal line to show the average of the values. Your figure should look like this: (b) [7 marks] Find all the elements that are larger than the average, and count them. Print these elements, their indexes and the number (count) of these elements.

          Question 2. Numpy and line plot
Run the following code in the template file to load data into a Numpy array.
flights = load_dataset('flights')
data = np.array(flights['passengers'])
data
[15 marks]
(a) [8 marks] Make a line plot to show the data in the array and draw a horizontal line to show the
average of the values. Your figure should look like this:
(b) [7 marks] Find all the elements that are larger than the average, and count them. Print these
elements, their indexes and the number (count) of these elements.

Question 2. Numpy and line plot
Run the following code in the template file to load data into a Numpy array.
flights = loaddataset('flights')
data = np.array(flights['passengers'])
data
[15 marks]
(a) [8 marks] Make a line plot to show the data in the array and draw a horizontal line to show the
average of the values. Your figure should look like this:
(b) [7 marks] Find all the elements that are larger than the average, and count them. Print these
elements, their indexes and the number (count) of these elements.

Added by Kenneth P.

Question

Please give Ace some feedback