code: # NUMPY MANIPULATIONS OF ARRAYS
  # Santiago Garcia Arango
  # -------------------------------------------------------------------------
  import numpy as np
  
  my_array = np.arange(1, 11)  # [1,2,..,8,9,10]
  print("my_array=\n", my_array, "\n")
  
  
  # -----------------CHECKING CONDITIONS IN ARRAY ITEMS----------------------
  # FIRST WAY...
  # This is how we show boolean result of a desired condition of an array
  boolean_array = my_array > 5
  print("my_array > 5 --> ", boolean_array, "\n")
  # We can take advantage of the boolean_array, by calling the main array...
  # ..."evaluated" in the True statements of the boolean_array.
  # This will give us only the original array where the conditions are True
  print("my_array[boolean_array] = ", my_array[boolean_array], "\n")
  
  # SECOND WAY...
  # This previous two step process is usually done in one step!!!
  # Remark: This is the most common way to to this!!!
  print("my_array[my_array>5] = ", my_array[my_array > 5], "\n")
  
  
  # -----------------------CREATE MATRICES EASIER----------------------------
  # Example: create this matrix:
  # 1 1 1 1 1
  # 1 0 0 0 1
  # 1 0 9 0 1
  # 1 0 0 0 1
  # 1 1 1 1 1
  
  cool_matrix = np.ones((5, 5))
  cool_matrix[1:4, 1:4] = 0
  cool_matrix[2, 2] = 9
  print("cool_matrix:\n", cool_matrix, "\n")
  
apis: numpy.arange numpy.ones