A short explanation of python collections and numpy arrays

python_collections.py

import numpy as np

# A List is a collection which is ordered and changeable.
# In Python lists are written with square brackets: [1,2,3,4,5]
numbers_as_list = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]

# A NumPy array is a collection which is ordered and changeable.
# Numpy arrays must contain elements of the same type.
numbers_as_numpy_array = np.array(numbers_as_list)

# Different behaviour of lists and numpy arrays when multiplying by a scalar
print(numbers_as_list * 2)  # Duplicate the list
print(numbers_as_numpy_array * 2)   # Multiply each element by 2

numbers_as_list[5] = "5" # This is allowed
numbers_as_numpy_array = np.array(numbers_as_list)  # This will fail on the first operation

print(numbers_as_list * 2)  # Will work

try:
    print(numbers_as_numpy_array * 2)   # Will throw an error because of the string
except Exception as e:
    print(e)

# Other collections types:
# A tuple is a collection which is ordered and unchangeable.
# In Python tuples are written with round brackets: (1,2,3,4,5)
# A set is a collection which is unordered and unindexed.
# In Python sets are written with curly brackets: {1,2,3,4,5}
# A dictionary is a collection which is unordered, changeable and indexed.
# In Python dictionaries are written with curly brackets, and they have keys and values:
# {"name":"John", "age":36}