keithgalli / numpy

Jupyter Notebook & Data Associated with my Tutorial video on the Python NumPy Library

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numpy's Issues

a few issues with the code

It seems like there are a few issues in the provided code. I will point them out and provide corrected code where needed.

1. In the "Accessing/Changing specific elements, rows, columns, etc" section, there's an attempt to change elements of the array b using a list of lists. This will result in a ValueError. To update elements of a NumPy array, you should use the correct syntax.

2. In the "Random Integer values" section, the function np.random.randint should be used with the low and high parameters to specify the range of random integers. The code provided is not syntactically correct.

Here's the corrected code with explanations:

import numpy as np

# The Basics
a = np.array([1, 2, 3], dtype='int32')
print(a)

b = np.array([[9.0, 8.0, 7.0], [6.0, 5.0, 4.0]])
print(b)

# Get Dimension
a.ndim

# Get Shape
b.shape

# Get Type
a.dtype

# Get Size
a.itemsize

# Get total size
a.nbytes

# Get number of elements
a.size

# Accessing/Changing specific elements, rows, columns, etc
a = np.array([[1, 2, 3, 4, 5, 6, 7], [8, 9, 10, 11, 12, 13, 14]])
print(a)

# Get a specific element [r, c]
a[1, 5]

# Get a specific row
a[0, :]

# Get a specific column
a[:, 2]

# Getting a little more fancy [startindex:endindex:stepsize]
a[0, 1:-1:2]

a[1, 5] = 20

# Corrected way to change elements of a NumPy array
a[:, 2] = 1  # Change the entire column to 1
print(a)

# Initializing Different Types of Arrays
np.zeros((2, 3))

np.ones((4, 2, 2), dtype='int32')

np.full((2, 2), 99)

np.random.rand(4, 2)

np.random.randint(-4, 8, size=(3, 3))

np.identity(5)

# Repeat an array
arr = np.array([[1, 2, 3]])
r1 = np.repeat(arr, 3, axis=0)
print(r1)

output = np.ones((5, 5))
print(output)

z = np.zeros((3, 3))
z[1, 1] = 9
output[1:-1, 1:-1] = z
print(output)

# Be careful when copying arrays!!!
a = np.array([1, 2, 3])
b = a.copy()
b[0] = 100
print(a)

# Mathematics
a = np.array([1, 2, 3, 4])
print(a)

a + 2

a - 2

a * 2

a / 2

b = np.array([1, 0, 1, 0])
a + b

a ** 2

np.cos(a)

# Linear Algebra
a = np.ones((2, 3))
print(a)

b = np.full((3, 2), 2)
print(b)

np.matmul(a, b)

# Statistics
stats = np.array([[1, 2, 3], [4, 5, 6]])
print(stats)

np.min(stats)

np.max(stats, axis=1)

np.sum(stats, axis=0)

I've corrected the issues in the code related to updating elements in the array and the usage of np.random.randint. The corrected code should work as expected.

Error handling

In [34]

Instead of :

replace

b[:,1,:] = [[9,9,9],[8,8]]

We use :
b[:,1,:] = [[9,9],[8,8]]