Intro to Maps, Filters and List Comprehension in Python

• How to use Maps, Filters and List Comprehension in Python.
  • Maps
    • Let's Solve some Problems!
  • Filters
    • Let's Solve some Problems
  • List Comprehensions

How to use Maps, Filters and List Comprehension in Python.

This notebook will covers the tutorial of map,filter and list comprehension. It's me learning these python goodies and documenting aside, so someday I could look up and revise stuffs.

I am going through the course on Coursera called Python-3 Programming from University of Michigan. Gotta admit I learnt alot of Python from there and still doing. Earlier I used to take notes on Notion, but now I thought of getting my hands dirty by coding along and take notes in Colab.

Also anyone interested or wanna refresh their Python skills could even make use of it.

Maps

Python provides built-in functions map and filter, even a new syntax called list comprehension that lets you express a mapping/filtering operation. Most documentations and programmers use list comprehension and it seem's more like a pythonic way of writing code.

Map, and filter are commands that you would use in high-performance computing on big datasets. http://en.wikipedia.org/wiki/MapReduce

def doubleStuff(a_list):
  '''
  Returns a new list in which contains doubles of the elements in a list
  '''
  # Accum list 
  new_list = []

  # Looping through values and making the calculation
  for value in a_list:
    double_elem = 2 * value 
    new_list.append(double_elem)
  return new_list

# Using the above function 
a_list = [1 , 2, 3 , 4, 5 , 6]
print(f'List before the values were got double: {a_list}')
double_list = doubleStuff(a_list)
print(f'\nThe list after the values they got double the number: {double_list}')

List before the values were got double: [1, 2, 3, 4, 5, 6]

The list after the values they got double the number: [2, 4, 6, 8, 10, 12]

We can write the above function with less than one line of code using the map function.

Map is a function which takes functions as the first input and sequence as an second input. map(function , sequence). Map just says apply the transforms (function) to every element in this sequence.

Map always expects a transformer function.

def double(value):
  return 2*value

map_double_list = list(map(double , a_list))
print(f'Using map function: {map_double_list}')

Using map function: [2, 4, 6, 8, 10, 12]

I earlier tried just map(double , a_list) which gave me just the map object. It turns out to be enclosing the map object by a list will gives us the list object.

But why this happens? Map function returns an iterator, it doesn't want to store the list in it's memory. It's still an iterator and we can grab the list we needed by enclosing the map object by a list which prevents pain to memory .

# Multiply 5 to every value

map_lambda_list = list(map(lambda value: 5*value , a_list))
print(f'Multiplying 5 to every element: {map_lambda_list}')

Multiplying 5 to every element: [5, 10, 15, 20, 25, 30]

Let's Solve some Problems!

Gotta go through more: https://www.w3resource.com/python-exercises/map/index.php

1. Below we have provided a list of strings called abbrevs. Use map to produce a new list called abbrevs_upper that contains all the same strings in upper case.

abbrevs = ['usa' , 'esp' , 'chn' , 'jpn' , 'mex' , 'can' , 'rus' ,  'rsa' , 'jam']

upperAbbrev_list = []
for abbrev in abbrevs:
  upperAbbrev_list.append(abbrev.upper())
print(upperAbbrev_list)

['USA', 'ESP', 'CHN', 'JPN', 'MEX', 'CAN', 'RUS', 'RSA', 'JAM']

upperCase_abbrevs = list(map(lambda abbrev: abbrev.upper() , abbrevs))
print(upperCase_abbrevs)

['USA', 'ESP', 'CHN', 'JPN', 'MEX', 'CAN', 'RUS', 'RSA', 'JAM']

1. Using map, create a list assigned to the variable greeting_doubled that doubles each element in the list.

lst = [["hi", "bye"], "hello", "goodbye", [9, 2], 4]

lst = [["hi", "bye"], "hello", "goodbye", [9, 2], 4]

greeting_doubled = list(map(lambda element: 2 * element , lst))
print(greeting_doubled)

[['hi', 'bye', 'hi', 'bye'], 'hellohello', 'goodbyegoodbye', [9, 2, 9, 2], 8]

1. Write a Python program to add three given lists using Python map and lambda

list(map(lambda a,b,c: a + b + c , [1 , 2 ,3] , [4 ,5 , 6] , [7 ,8 , 9]))

[12, 15, 18]

Filters

Filter function filter takes two arguments same like our map which has both function and a sequence parameters. Instead mapping them or making calculation with eachother, filter filters out the numbers either True or False.

The function takes one item and return True if the item should. It is automatically called for each item in the sequence

filter returns an iterator object like map, so we gotta wrap them by list.

def keep_evens(a_list):
  new_list = []
  for elem in a_list:
    if elem % 2 == 0:
      new_list.append(elem)
  return new_list

# Using the above function 
mixList = [2 , 88 , 33 , 22 , 14 , 0 , 8 , 10 , 20 , 4]
evenList = keep_evens(mixList)
print(evenList)

[2, 88, 22, 14, 0, 8, 10, 20, 4]

filterEvenList = list(filter(lambda elem: elem % 2 == 0 , mixList))
print(filterEvenList)

[2, 88, 22, 14, 0, 8, 10, 20, 4]

Let's Solve some Problems

1. Using filter, filter lst so that it only contains words containing the letter 'o'. Assign to variable lst2.

lst = ['witch' , 'halloween' , 'pumpkin' , 'cat' , 'candy' , 'wagon' ,'moon']

lst = ['witch' , 'halloween' , 'pumpkin' , 'cat' , 'candy' , 'wagon' , 'moon']

lst2 = list(filter(lambda elem: 'o' in elem , lst))
print(lst2)

['halloween', 'wagon', 'moon']

1. Write code to assign to the variable filter_testing all the elements in lst_check that have a 'w' in them using filter.

lst_check = ['plums', 'watermelon', 'kiwi', 'strawberries', 'blueberries', 'peaches', 'apples', 'mangos', 'papaya']

lst_check = ['plums', 'watermelon', 'kiwi', 'strawberries', 'blueberries', 'peaches', 'apples', 'mangos', 'papaya']

filter_testing = list(filter(lambda word: 'w' in word , lst_check))
print(filter_testing)

['watermelon', 'kiwi', 'strawberries']

List Comprehensions

Before we saw those two functions namely map and filter turns out to be we don't want to use them much (or) in other words we can use list comprehensions inplace of using map and filter. Better we can pull off more flexibility by using list comprehensions.

In simple words list comprehensions is a convinient syntax to do map and filter operations.

Basic Syntax of list comprehension:

[ <transformer_expression> for <iterator_variable> in <sequence> if <filteration_expression>]

def double(value):
  return 2*value

map_double_list = list(map(double , a_list))
print(f'Using map function: {map_double_list}')

Using map function: [2, 4, 6, 8, 10, 12]

a_list

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

compre_double_list = [value * 2 for value in a_list]
compre_double_list

[2, 4, 6, 8, 10, 12]

Breaking down by the syntax:

• transformer_expression : value * 2
• iterator_varaible : value
• sequence : a_list

filterEvenList = list(filter(lambda elem: elem % 2 == 0 , mixList))
print(filterEvenList)

[2, 88, 22, 14, 0, 8, 10, 20, 4]

mixList

[2, 88, 33, 22, 14, 0, 8, 10, 20, 4]

filterListComprehension = [element for element in mixList if element % 2 == 0]
filterListComprehension

[2, 88, 22, 14, 0, 8, 10, 20, 4]

filterListComprehension == filterEvenList

True

Write code to assign to the variable compri all the values of the key name in any of the sub-dictionaries in the dictionary tester. Do this using a list comprehension.

tester = {'info': [{"name": "Lauren", 'class standing': 'Junior', 'major': "Information Science"},{'name': 'Ayo', 'class standing': "Bachelor's", 'major': 'Information Science'}, {'name': 'Kathryn', 'class standing': 'Senior', 'major': 'Sociology'}, {'name': 'Nick', 'class standing': 'Junior', 'major': 'Computer Science'}, {'name': 'Gladys', 'class standing': 'Sophomore', 'major': 'History'}, {'name': 'Adam', 'major': 'Violin Performance', 'class standing': 'Senior'}]}

inner_list = tester['info']
#print(inner_list)

# For Readability
import json 
print(json.dumps(inner_list , indent = 2))

[
  {
    "name": "Lauren",
    "class standing": "Junior",
    "major": "Information Science"
  },
  {
    "name": "Ayo",
    "class standing": "Bachelor's",
    "major": "Information Science"
  },
  {
    "name": "Kathryn",
    "class standing": "Senior",
    "major": "Sociology"
  },
  {
    "name": "Nick",
    "class standing": "Junior",
    "major": "Computer Science"
  },
  {
    "name": "Gladys",
    "class standing": "Sophomore",
    "major": "History"
  },
  {
    "name": "Adam",
    "major": "Violin Performance",
    "class standing": "Senior"
  }
]

nameList = []
if True: 
  for dict_name in inner_list:
    name = dict_name['name']
    nameList.append(name)
  print(nameList)

['Lauren', 'Ayo', 'Kathryn', 'Nick', 'Gladys', 'Adam']

compri = [dict_value['name'] for dict_value in inner_list if True]
compri

['Lauren', 'Ayo', 'Kathryn', 'Nick', 'Gladys', 'Adam']