Analyze Financial Data with Python - Introduction to NumPy

                                

import numpy as np
numbers = np.array([-5, 4, 0, 2, 3])
positives = numbers[numbers > 0]
print(positives)
# Output: [4 2 3]


                              

                                

import numpy as np
numbers = np.array([-5, 4, 0, 2, 3])
is_positive = numbers > 0
print(is_positive)
# Output: [False  True False  True  True]


                              

                                

import numpy as np
imported_data = np.genfromtxt('filename.csv', delimiter=',')
print(imported_data)
# Output: Array created from the CSV data


                              

                                

import numpy as np
# Create a NumPy array from a list
my_array = np.array([1, 2, 3, 4])
print(my_array)
# Output: [1 2 3 4]


                              

                                

import numpy as np
matrix = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
print(matrix[0, 0])
# Output: 1
print(matrix[1, :])
# Output: [4 5 6]


                              

                                

import numpy as np
odds = np.array([1, 3, 5, 7, 9])
evens = odds + 1
print(evens)
# Output: [2 4 6 8 10]
array1 = np.array([1, 2, 3])
array2 = np.array([4, 3, 2])
new_array = array1 + array2
print(new_array)
# Output: [5 5 5]