Python - List and Dictionary Comprehension (Day 26)

This is a 100 Days challenge to learn a new language (Python). 100 Days of Code - The Complete Python Pro Bootcamp 

I will post some notes to motivate myself to finish this challenge.

The regular way to create a new list from an existing list

The example below is the regular way to create a new list calculated from an existing list.

Ex:

list = [1, 2, 3]

new_list = []

# Go through each item of the existing list

for num in list:

    # With some logic to get the new value

    new_value = num + 1

    # Append the new value to new_list

    new_list.append(new_value)

print(f"old list: {list}")

print(f"new list: {new_list}")

Result:

old list: [1, 2, 3]

new list: [2, 3, 4]

Using List Comprehension

List comprehensions provides a concise way to create lists.

* new_list = [new_item for item in list]

Ex:

list = [1, 2, 3]

new_list = [item + 1 for item in list]

print(f"old list: {list}")

print(f"new list: {new_list}")

Result:

old list: [1, 2, 3]

new list: [2, 3, 4]

List Comprehension is not only for List

It can be used with python sequence (an ordered set)

* list

* range

* string

* tuple

Ex: range

# get sequence 1, 2, 3, 4 from range(1, 5)

# and double the value

new_list = [number * 2 for number in range(1, 5)]

print(f"new_list: {new_list}")

Result:

new_list: [2, 4, 6, 8]

Ex: string

name = "Frank"

letter_list = [letter for letter in name]

print(f"letter_list: {letter_list}")

Result:

letter_list: ['F', 'r', 'a', 'n', 'k']

Conditional List Comprehension

We can even add some conditions in List Comprehension for filtering.

* new_list = [new_item for item in list if condition]

Ex:

number_list = [1, 2, 3, 4, 5, 6]

even_number_list = [num for num in number_list if num % 2 == 0]

print(f"even_number_list: {even_number_list}")

Result:

even_number_list: [2, 4, 6]

Exp - Get the common numbers from two files

Ex:

# file1.txt and file2.txt contain a bunch of numbers,

# each number on a new line.

# Create a list called result which contains the numbers

# that are common in both files.

with open("file1.txt", encoding="utf-8") as file:

    file_1 = file.readlines()

with open("file2.txt", encoding="utf-8") as file:

    file_2 = file.readlines()

result = [int(f1) for f1 in file_1 if f1 in file_2]

print(result)

Exp - Refactor the previous US State game

Ex: Previous version

# Define a dictionary

  output_disc = {"state": []}

  for state in states_list:

      if state not in correct_guess_states_list:

          output_disc["state"].append(state)

Ex: Using List Comprehension

  output_disc = {

  "state": [

        state for state in states_list if

state not in correct_guess_states_list

  ]

  }

Dictionary Comprehension

Reference

* new_dict = {new_key:new_value for item in list}

* new_dict = {new_key:new_value for (key, value) in dict.items()}

* new_dict = {new_key:new_value for (key, value) in dict.items() if condition}

Ex: Generate a dictionary based on a student list to generate student score randomly

import random

students = ["Andy", "Ben", "Calvin"]

# Generate a dictionary from a list

student_scores = {student: random.randint(50, 80) for student in students}

print(f"student_scores: {student_scores}")

Result:

student_scores: {'Andy': 79, 'Ben': 62, 'Calvin': 71}

Ex: Based on the previous example, generate a dictionary to filter out the students whose score is under 60

import random

students = ["Andy", "Ben", "Calvin"]

# Generate a dictionary from a list

student_scores = {student: random.randint(50, 80) for student in students}

# Generate a dictionary from an existing dict with condition

passed_students = {

    name: score for (name, score) in student_scores.items() if score >= 60

}

print(f"student_scores: {student_scores}")

print(f"passed_students: {passed_students}")

Result:

student_scores: {'Andy': 62, 'Ben': 52, 'Calvin': 62} passed_students: {'Andy': 62, 'Calvin': 62}

Project - NATO Alphabet

Reference

Ex: 

import pandas

# Using pandas to read csv file

nato_phonetic_alphabet_data_frame =

pandas.read_csv("nato_phonetic_alphabet.csv")

# Generate a dictionary to use alphabet as a key and

# relating word as a value

# {"A": "Alfa", "B": "Bravo"}

nato_phonetic_alphabet_dict = {

    row["letter"]: row["code"]

    for (index, row) in nato_phonetic_alphabet_data_frame.iterrows()

}

# Ask Users to enter a word

user_input = input("Enter a word? ")

# Use List Comprehension to create a result list

# Loop through all letters of user input and

# get the mapping word by dictionary

result = [nato_phonetic_alphabet_dict[letter] for letter in

user_input.upper()]

print(result)

Result:

Enter a word? Frank ['Foxtrot', 'Romeo', 'Alfa', 'November', 'Kilo']