{ "cells": [ { "cell_type": "markdown", "id": "33df9d15", "metadata": { "hideCode": false, "hidePrompt": false, "slideshow": { "slide_type": "slide" } }, "source": [ "# Data Structure Selection\n", "#### CS 65: Introduction to Computer Science I" ] }, { "cell_type": "markdown", "id": "1971c5c2", "metadata": { "hideCode": false, "hidePrompt": false, "slideshow": { "slide_type": "slide" } }, "source": [ "## What is a data structure?\n", "\n", "A __data structure__ is the _data types_, _collections_, and _relationships_ used for organizing data for a particular programming tasks along with the specific _operations_ that you utilize for that task" ] }, { "cell_type": "markdown", "id": "2aa0df43", "metadata": { "hideCode": false, "hidePrompt": false, "slideshow": { "slide_type": "fragment" } }, "source": [ "Core Python data structures\n", "* List\n", "* Tuple\n", "* Dictionary" ] }, { "cell_type": "markdown", "id": "77ea40da", "metadata": { "hideCode": false, "hideOutput": true, "hidePrompt": false, "slideshow": { "slide_type": "slide" } }, "source": [ "We've also see than you can combine these in many ways for more complex data\n", "\n", "* CSV files: 2D list of lists\n", "* images: 2D stucture of tuples\n", "* Zipcode dataset: dictionary of dictionaries (which had lists inside of them!)\n", "\n", "And you could think of more options like lists of dictionaries, 3D lists, etc.\n", "\n", "There are also many more canonical data structures (covered in Intro to CS II) like stacks, queues, heaps, trees, and graphs that can be built or imported from modules." ] }, { "cell_type": "markdown", "id": "5b17bc17", "metadata": { "hideCode": false, "hidePrompt": false, "slideshow": { "slide_type": "slide" } }, "source": [ "## How do you know which data structure to use for your problem?\n", "\n", "Consider:\n", "1. What are the characteristics of the data I need to organize?\n", "2. What relationships exist in the data?\n", " * Is it ordered?\n", " * Are the mappings like key-value pairs?\n", "3. What computational tasks do I need to be able to execute with this data?" ] }, { "cell_type": "markdown", "id": "1e54a48e", "metadata": { "hideCode": false, "hidePrompt": false, "slideshow": { "slide_type": "fragment" } }, "source": [ "Think about:\n", "1. One way you could do it\n", "2. Additional ways you could do it" ] }, { "cell_type": "markdown", "id": "8daaa920", "metadata": { "slideshow": { "slide_type": "fragment" } }, "source": [ "Decide which is best based on one or more of the following:\n", "* Which is easiest for you, the programmer, to implement\n", " - are there built-in types, modules, file formats available (e.g., csv and json)? \n", " - do you understand one way to do it more than the other?\n", " - will one of the ways take you longer to program?\n", "* Analyze how many operations will be needed for your task as the size of the data grows \n", " - Insert sort - nested loops, if you have $n$ elements, you hit each of them on the order of $n^2$ times\n", " - Find max - only visit each element once\n", " - Doing it formally: Intro to CS II and beyond\n", " - You can still think about it informally\n", "* __Benchmarking__ - implement both methods and test how long each takes for your tasks" ] }, { "cell_type": "markdown", "id": "ea397e90", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "## Example problem: word frequencies\n", "\n", "Take a large piece of text, and count how many times each word is used\n", "* Used in several kinds of text analysis problems like sentiment analysis and author detection\n", "\n", "\n", "Consider:\n", "* I need each word paired with its frequency (there is a mapping between the word and the frequency)\n", "* There is a potential order based alphabetically on the word or numerically on the frequency\n", "* I may want to display high-frequency words, look up the frequency of a specific word, compare word fequency between books\n", "\n", "Ways I can think of to do it:\n", "* A dictionary where the word is the key and the frequency is the value\n", "* A list of tuples where the second entry in the tuple is the word and the first is the frequency\n", "* A 2D list - same as above but inner list instead of tuple" ] }, { "cell_type": "code", "execution_count": 4, "id": "69ed74a5", 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7,\n", " 'hall,': 5,\n", " 'lit': 1,\n", " 'row': 2,\n", " 'lamps': 1,\n", " 'hanging': 3,\n", " 'roof.': 1,\n", " 'doors': 2,\n", " 'round': 30,\n", " 'locked;': 1,\n", " 'been': 36,\n", " 'side': 12,\n", " 'other,': 5,\n", " 'trying': 11,\n", " 'every': 12,\n", " 'door,': 9,\n", " 'walked': 10,\n", " 'sadly': 2,\n", " 'middle,': 3,\n", " 'wondering': 7,\n", " 'Suddenly': 1,\n", " 'three-legged': 2,\n", " 'table,': 5,\n", " 'solid': 1,\n", " 'glass;': 1,\n", " 'except': 4,\n", " 'tiny': 4,\n", " 'golden': 7,\n", " 'key,': 3,\n", " 'Alice’s': 9,\n", " 'first': 28,\n", " 'belong': 1,\n", " 'hall;': 1,\n", " 'but,': 6,\n", " 'alas!': 2,\n", " 'locks': 1,\n", " 'large,': 1,\n", " 'key': 5,\n", " 'small,': 1,\n", " 'any': 36,\n", " 'rate': 4,\n", " 'open': 6,\n", " 'them.': 2,\n", " 'However,': 13,\n", " 'second': 4,\n", " 'round,': 7,\n", " 'curtain': 1,\n", " 'before,': 11,\n", " 'door': 15,\n", " 'fifteen': 1,\n", " 'inches': 6,\n", " 'high:': 3,\n", " 'lock,': 1,\n", " 'delight': 1,\n", " 'fitted!': 1,\n", " 'opened': 9,\n", " 'led': 4,\n", " 'small': 8,\n", " 'larger': 3,\n", " 'than': 23,\n", " 'rat-hole:': 1,\n", " 'knelt': 1,\n", " 'along': 5,\n", " 'passage': 1,\n", " 'loveliest': 1,\n", " 'garden': 4,\n", " 'saw.': 1,\n", " 'longed': 2,\n", " 'wander': 1,\n", " 'those': 9,\n", " 'beds': 1,\n", " 'bright': 7,\n", " 'flowers': 2,\n", " 'cool': 2,\n", " 'fountains,': 1,\n", " 'head': 29,\n", " 'doorway;': 1,\n", " 'go': 38,\n", " 'through,”': 1,\n", " 'poor': 25,\n", " 'Alice,': 76,\n", " '“it': 5,\n", " 'without': 24,\n", " 'shoulders.': 1,\n", " 'Oh,': 3,\n", " 'shut': 4,\n", " 'telescope!': 1,\n", " 'only': 43,\n", " 'knew': 13,\n", " 'begin.”': 3,\n", " 'For,': 1,\n", " 'out-of-the-way': 3,\n", " 'happened': 3,\n", " 'lately,': 1,\n", " 'few': 9,\n", " 'indeed': 3,\n", " 'really': 9,\n", " 'impossible.': 1,\n", " 'waiting': 7,\n", " 'back': 29,\n", " 'half': 21,\n", " 'hoping': 3,\n", " 'find': 20,\n", " 'rules': 3,\n", " 'shutting': 2,\n", " 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53,\n", " 'finger': 3,\n", " 'deeply': 1,\n", " 'knife,': 1,\n", " 'usually': 2,\n", " 'bleeds;': 1,\n", " 'forgotten': 6,\n", " 'that,': 5,\n", " 'drink': 4,\n", " '“poison,”': 2,\n", " 'almost': 6,\n", " 'certain': 2,\n", " 'disagree': 1,\n", " 'you,': 25,\n", " 'sooner': 2,\n", " 'later.': 1,\n", " '_not_': 5,\n", " 'ventured': 4,\n", " 'taste': 2,\n", " 'finding': 3,\n", " 'nice,': 1,\n", " '(it': 4,\n", " 'had,': 1,\n", " 'fact,': 4,\n", " 'mixed': 2,\n", " 'flavour': 1,\n", " 'cherry-tart,': 1,\n", " 'custard,': 1,\n", " 'pine-apple,': 1,\n", " 'roast': 1,\n", " 'turkey,': 1,\n", " 'toffee,': 1,\n", " 'buttered': 1,\n", " 'toast,)': 1,\n", " 'finished': 7,\n", " 'off.': 5,\n", " '*': 60,\n", " '“What': 33,\n", " 'curious': 16,\n", " 'feeling!”': 1,\n", " 'Alice;': 16,\n", " 'telescope.”': 1,\n", " 'indeed:': 1,\n", " 'now': 23,\n", " 'ten': 5,\n", " 'high,': 3,\n", " 'face': 7,\n", " 'brightened': 2,\n", " 'size': 6,\n", " 'lovely': 2,\n", " 'garden.': 3,\n", " 'however,': 6,\n", " 'waited': 9,\n", " 'minutes': 7,\n", " 'shrink': 1,\n", " 'further:': 1,\n", " 'nervous': 4,\n", " 'this;': 2,\n", " '“for': 6,\n", " 'end,': 1,\n", " 'know,”': 8,\n", " '“in': 3,\n", " 'altogether,': 2,\n", " 'candle.': 1,\n", " 'then?”': 1,\n", " 'fancy': 3,\n", " 'flame': 1,\n", " 'candle': 2,\n", " 'blown': 1,\n", " 'out,': 13,\n", " 'thing.': 1,\n", " 'After': 5,\n", " 'while,': 4,\n", " 'more': 38,\n", " 'happened,': 2,\n", " 'decided': 3,\n", " 'once;': 1,\n", " 'alas': 1,\n", " 'Alice!': 3,\n", " 'table': 7,\n", " 'possibly': 3,\n", " 'reach': 4,\n", " 'it:': 9,\n", " 'plainly': 1,\n", " 'glass,': 2,\n", " 'best': 7,\n", " 'climb': 1,\n", " 'legs': 3,\n", " 'slippery;': 1,\n", " 'trying,': 1,\n", " 'thing': 35,\n", " 'sat': 17,\n", " 'cried.': 2,\n", " '“Come,': 9,\n", " 'there’s': 15,\n", " 'crying': 2,\n", " 'that!”': 7,\n", " 'sharply;': 1,\n", " 'advise': 1,\n", " 'leave': 7,\n", " 'minute!”': 1,\n", " 'generally': 5,\n", " 'gave': 15,\n", " 'advice,': 1,\n", " '(though': 1,\n", " 'seldom': 1,\n", " 'followed': 8,\n", " 'it),': 2,\n", " 'sometimes': 4,\n", " 'scolded': 1,\n", " 'severely': 3,\n", " 'bring': 2,\n", " 'tears': 4,\n", " 'eyes;': 1,\n", " 'remembered': 5,\n", " 'box': 3,\n", " 'cheated': 1,\n", " 'game': 6,\n", " 'croquet': 3,\n", " 'playing': 2,\n", " 'against': 9,\n", " 'child': 3,\n", " 'fond': 3,\n", " 'pretending': 1,\n", " 'two': 20,\n", " 'people.': 1,\n", " '“But': 19,\n", " 'now,”': 4,\n", " '“to': 4,\n", " 'pretend': 1,\n", " 'people!': 1,\n", " 'hardly': 11,\n", " 'enough': 10,\n", " 'left': 13,\n", " '_one_': 2,\n", " 'respectable': 1,\n", " 'person!”': 1,\n", " 'Soon': 1,\n", " 'eye': 4,\n", " 'glass': 4,\n", " 'lying': 8,\n", " 'table:': 1,\n", " 'cake,': 2,\n", " '“EAT': 1,\n", " 'ME”': 1,\n", " 'currants.': 1,\n", " '“Well,': 20,\n", " 'it,”': 18,\n", " 'makes': 11,\n", " 'grow': 13,\n", " 'larger,': 3,\n", " 'can': 27,\n", " 'key;': 1,\n", " 'smaller,': 3,\n", " 'creep': 1,\n", " 'door;': 1,\n", " 'garden,': 5,\n", " 'don’t': 48,\n", " 'care': 4,\n", " 'happens!”': 1,\n", " 'ate': 1,\n", " 'bit,': 2,\n", " 'anxiously': 13,\n", " '“Which': 3,\n", " 'way?': 1,\n", " 'Which': 3,\n", " 'way?”,': 1,\n", " 'holding': 2,\n", " 'growing,': 4,\n", " 'surprised': 6,\n", " 'remained': 3,\n", " 'same': 21,\n", " 'size:': 3,\n", " 'sure,': 2,\n", " 'happens': 2,\n", " 'eats': 1,\n", " 'expecting': 3,\n", " 'happen,': 1,\n", " 'dull': 2,\n", " 'stupid': 1,\n", " 'life': 2,\n", " 'common': 1,\n", " 'way.': 3,\n", " 'set': 14,\n", " 'work,': 1,\n", " 'cake.': 1,\n", " 'II.': 1,\n", " 'Pool': 1,\n", " 'Tears': 1,\n", " '“Curiouser': 1,\n", " 'curiouser!”': 1,\n", " 'cried': 18,\n", " 'surprised,': 1,\n", " 'forgot': 2,\n", " 'speak': 8,\n", " 'English);': 1,\n", " '“now': 1,\n", " 'opening': 3,\n", " 'largest': 1,\n", " 'telescope': 1,\n", " 'was!': 1,\n", " 'Good-bye,': 1,\n", " 'feet!”': 1,\n", " '(for': 1,\n", " 'far': 9,\n", " 'off).': 1,\n", " '“Oh,': 19,\n", " 'shoes': 5,\n", " 'stockings': 1,\n", " 'now,': 6,\n", " 'dears?': 1,\n", " 'sure': 16,\n", " '_I_': 13,\n", " 'shan’t': 4,\n", " 'able!': 1,\n", " 'deal': 11,\n", " 'myself': 2,\n", " 'you:': 1,\n", " 'can;—but': 1,\n", " 'kind': 6,\n", " 'them,”': 3,\n", " '“or': 5,\n", " 'won’t': 21,\n", " 'want': 9,\n", " 'go!': 1,\n", " 'give': 9,\n", " 'new': 4,\n", " 'pair': 5,\n", " 'boots': 3,\n", " 'Christmas.”': 1,\n", " 'planning': 1,\n", " '“They': 9,\n", " 'carrier,”': 1,\n", " 'thought;': 1,\n", " 'seem,': 1,\n", " 'sending': 2,\n", " 'presents': 2,\n", " 'one’s': 1,\n", " 'feet!': 1,\n", " 'odd': 1,\n", " 'directions': 1,\n", " 'look!': 1,\n", " '_Alice’s': 1,\n", " 'Right': 1,\n", " 'Foot,': 1,\n", " 'Esq.,': 1,\n", " 'Hearthrug,': 1,\n", " 'Fender,_': 1,\n", " '(_with': 1,\n", " 'love_).': 1,\n", " 'dear,': 6,\n", " 'nonsense': 1,\n", " 'talking!”': 1,\n", " 'Just': 5,\n", " 'struck': 2,\n", " 'roof': 5,\n", " 'hall:': 1,\n", " 'fact': 2,\n", " 'nine': 4,\n", " 'door.': 2,\n", " 'Poor': 1,\n", " 'side,': 3,\n", " 'eye;': 2,\n", " 'hopeless': 1,\n", " 'ever:': 1,\n", " 'cry': 3,\n", " '“You': 32,\n", " 'ashamed': 2,\n", " 'yourself,”': 1,\n", " '“a': 2,\n", " 'you,”': 6,\n", " 'this),': 1,\n", " 'way!': 1,\n", " 'Stop': 1,\n", " 'moment,': 5,\n", " 'you!”': 3,\n", " 'same,': 2,\n", " 'shedding': 1,\n", " 'gallons': 1,\n", " 'tears,': 3,\n", " 'until': 4,\n", " 'pool': 6,\n", " 'reaching': 1,\n", " 'hall.': 1,\n", " 'heard': 29,\n", " 'pattering': 3,\n", " 'distance,': 4,\n", " 'hastily': 7,\n", " 'dried': 1,\n", " 'coming.': 2,\n", " 'returning,': 1,\n", " 'splendidly': 1,\n", " 'dressed,': 1,\n", " 'white': 6,\n", " 'kid': 5,\n", " 'gloves': 5,\n", " 'fan': 8,\n", " 'other:': 3,\n", " 'he': 94,\n", " 'trotting': 2,\n", " 'hurry,': 1,\n", " 'muttering': 3,\n", " 'himself': 4,\n", " 'came,': 2,\n", " '“Oh!': 2,\n", " 'Duchess,': 8,\n", " 'Duchess!': 3,\n", " 'Oh!': 1,\n", " 'savage': 3,\n", " 'kept': 13,\n", " 'waiting!”': 1,\n", " 'desperate': 1,\n", " 'ready': 7,\n", " 'help': 9,\n", " 'one;': 2,\n", " 'so,': 7,\n", " 'began,': 6,\n", " 'low,': 6,\n", " 'timid': 3,\n", " 'voice,': 15,\n", " '“If': 14,\n", " 'please,': 3,\n", " 'sir—”': 1,\n", " 'violently,': 2,\n", " 'dropped': 4,\n", " 'fan,': 1,\n", " 'skurried': 1,\n", " 'darkness': 1,\n", " 'hard': 8,\n", " 'go.': 1,\n", " 'gloves,': 3,\n", " 'and,': 19,\n", " 'hall': 1,\n", " 'hot,': 1,\n", " 'fanning': 1,\n", " 'talking:': 1,\n", " '“Dear,': 1,\n", " 'queer': 9,\n", " 'everything': 9,\n", " 'to-day!': 1,\n", " 'yesterday': 2,\n", " 'usual.': 2,\n", " 'changed': 7,\n", " 'night?': 1,\n", " 'think:': 1,\n", " 'morning?': 1,\n", " 'feeling': 6,\n", " 'different.': 1,\n", " 'next': 20,\n", " 'question': 7,\n", " 'Who': 6,\n", " 'am': 13,\n", " 'I?': 1,\n", " 'Ah,': 1,\n", " '_that’s_': 3,\n", " 'puzzle!”': 1,\n", " 'thinking': 10,\n", " 'age': 2,\n", " '“I’m': 19,\n", " 'Ada,”': 1,\n", " 'hair': 5,\n", " 'goes': 7,\n", " 'ringlets,': 1,\n", " 'mine': 3,\n", " 'doesn’t': 16,\n", " 'ringlets': 1,\n", " 'all;': 2,\n", " 'can’t': 27,\n", " 'Mabel,': 2,\n", " 'know': 45,\n", " 'sorts': 3,\n", " 'she,': 4,\n", " ...}" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "with open(\"aliceinwonderland.txt\") as alicefile:\n", " alice_text = alicefile.read()\n", " \n", "#print(alice_text) \n", " \n", "alice_text = alice_text[1435:145451] #getting rid of the project Gutenberg stuff at the beginning and end\n", "alice_words = alice_text.split()\n", "\n", "#print(alice_words)\n", "\n", "word_frequencies_dict = {}\n", "\n", "for word in alice_words:\n", " if word in word_frequencies_dict:\n", " word_frequencies_dict[word] += 1\n", " else:\n", " word_frequencies_dict[word] = 1\n", "\n", "word_frequencies_dict" ] }, { "cell_type": "code", "execution_count": 5, "id": "d7210a26", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[[12, 'CHAPTER'],\n", " [1, 'I.'],\n", " [1, 'Down'],\n", " [1513, 'the'],\n", " [1, 'Rabbit-Hole'],\n", " [221, 'Alice'],\n", " [327, 'was'],\n", " [11, 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[2, 'sending'],\n", " [2, 'presents'],\n", " [1, 'one’s'],\n", " [1, 'feet!'],\n", " [1, 'odd'],\n", " [1, 'directions'],\n", " [1, 'look!'],\n", " [1, '_Alice’s'],\n", " [1, 'Right'],\n", " [1, 'Foot,'],\n", " [1, 'Esq.,'],\n", " [1, 'Hearthrug,'],\n", " [1, 'Fender,_'],\n", " [1, '(_with'],\n", " [1, 'love_).'],\n", " [6, 'dear,'],\n", " [1, 'nonsense'],\n", " [1, 'talking!”'],\n", " [5, 'Just'],\n", " [2, 'struck'],\n", " [5, 'roof'],\n", " [1, 'hall:'],\n", " [2, 'fact'],\n", " [4, 'nine'],\n", " [2, 'door.'],\n", " [1, 'Poor'],\n", " [3, 'side,'],\n", " [2, 'eye;'],\n", " [1, 'hopeless'],\n", " [1, 'ever:'],\n", " [3, 'cry'],\n", " [32, '“You'],\n", " [2, 'ashamed'],\n", " [1, 'yourself,”'],\n", " [2, '“a'],\n", " [6, 'you,”'],\n", " [1, 'this),'],\n", " [1, 'way!'],\n", " [1, 'Stop'],\n", " [5, 'moment,'],\n", " [3, 'you!”'],\n", " [2, 'same,'],\n", " [1, 'shedding'],\n", " [1, 'gallons'],\n", " [3, 'tears,'],\n", " [4, 'until'],\n", " [6, 'pool'],\n", " [1, 'reaching'],\n", " [1, 'hall.'],\n", " [29, 'heard'],\n", " [3, 'pattering'],\n", " [4, 'distance,'],\n", " [7, 'hastily'],\n", " [1, 'dried'],\n", " [2, 'coming.'],\n", " [1, 'returning,'],\n", " [1, 'splendidly'],\n", " [1, 'dressed,'],\n", " [6, 'white'],\n", " [5, 'kid'],\n", " [5, 'gloves'],\n", " [8, 'fan'],\n", " [3, 'other:'],\n", " [94, 'he'],\n", " [2, 'trotting'],\n", " [1, 'hurry,'],\n", " [3, 'muttering'],\n", " [4, 'himself'],\n", " [2, 'came,'],\n", " [2, '“Oh!'],\n", " [8, 'Duchess,'],\n", " [3, 'Duchess!'],\n", " [1, 'Oh!'],\n", " [3, 'savage'],\n", " [13, 'kept'],\n", " [1, 'waiting!”'],\n", " [1, 'desperate'],\n", " [7, 'ready'],\n", " [9, 'help'],\n", " [2, 'one;'],\n", " [7, 'so,'],\n", " [6, 'began,'],\n", " [6, 'low,'],\n", " [3, 'timid'],\n", " [15, 'voice,'],\n", " [14, '“If'],\n", " [3, 'please,'],\n", " [1, 'sir—”'],\n", " [2, 'violently,'],\n", " [4, 'dropped'],\n", " [1, 'fan,'],\n", " [1, 'skurried'],\n", " [1, 'darkness'],\n", " [8, 'hard'],\n", " [1, 'go.'],\n", " [3, 'gloves,'],\n", " [19, 'and,'],\n", " [1, 'hall'],\n", " [1, 'hot,'],\n", " [1, 'fanning'],\n", " [1, 'talking:'],\n", " [1, '“Dear,'],\n", " [9, 'queer'],\n", " [9, 'everything'],\n", " [1, 'to-day!'],\n", " [2, 'yesterday'],\n", " [2, 'usual.'],\n", " [7, 'changed'],\n", " [1, 'night?'],\n", " [1, 'think:'],\n", " [1, 'morning?'],\n", " [6, 'feeling'],\n", " [1, 'different.'],\n", " [20, 'next'],\n", " [7, 'question'],\n", " [6, 'Who'],\n", " [13, 'am'],\n", " [1, 'I?'],\n", " [1, 'Ah,'],\n", " [3, '_that’s_'],\n", " [1, 'puzzle!”'],\n", " [10, 'thinking'],\n", " [2, 'age'],\n", " [19, '“I’m'],\n", " [1, 'Ada,”'],\n", " [5, 'hair'],\n", " [7, 'goes'],\n", " [1, 'ringlets,'],\n", " [3, 'mine'],\n", " [16, 'doesn’t'],\n", " [1, 'ringlets'],\n", " [2, 'all;'],\n", " [27, 'can’t'],\n", " [2, 'Mabel,'],\n", " [45, 'know'],\n", " [3, 'sorts'],\n", " [4, 'she,'],\n", " ...]" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "with open(\"aliceinwonderland.txt\") as alicefile:\n", " alice_text = alicefile.read()\n", " \n", "alice_text = alice_text[1435:145451]\n", "alice_words = alice_text.split()\n", "\n", "word_frequencies_2dlist = []\n", "\n", "for word in alice_words:\n", " \n", " #search the list of tuples looking for this word\n", " found_word_in_list = False\n", " for freq in word_frequencies_2dlist:\n", " \n", " #if I find it, add one onto its counter and\n", " #flag that we found it\n", " if word == freq[1]:\n", " freq[0] += 1\n", " found_word_in_list = True\n", " \n", " #didn't find it in the loop above, so we add a new tuple\n", " #for the word with frequency 1\n", " if not found_word_in_list:\n", " word_frequencies_2dlist.append([1,word])\n", "\n", "word_frequencies_2dlist" ] }, { "cell_type": "markdown", "id": "3d46e7e4", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "## Analysis\n", "\n", "* It was easier for me to populate the dictionary than the 2D list\n", "* The dictionary build code ran faster than the 2D list\n", "* Dictionary - fast to look up a word, List - slow, requires loop" ] }, { "cell_type": "code", "execution_count": 6, "id": "133ae75a", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "221\n" ] } ], "source": [ "print( word_frequencies_dict[\"Alice\"] )" ] }, { "cell_type": "code", "execution_count": 7, "id": "4268c4c3", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "221\n" ] } ], "source": [ "for wordfreq in word_frequencies_2dlist:\n", " if \"Alice\" == wordfreq[1]:\n", " print(wordfreq[0])" ] }, { "cell_type": "markdown", "id": "f8a0e955", "metadata": {}, "source": [ "* Display sorted by frequency: dictonaries aren't ordered (would have to convert to a list), but I could sort the 2D list" ] }, { "cell_type": "code", "execution_count": 8, "id": "53a27e25", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[[1513, 'the'],\n", " [715, 'and'],\n", " [706, 'to'],\n", " [608, 'a'],\n", " [492, 'of'],\n", " [485, 'she'],\n", " [416, 'said'],\n", " [347, 'it'],\n", " [344, 'in'],\n", " [327, 'was'],\n", " [251, 'you'],\n", " [249, 'I'],\n", " [237, 'as'],\n", " [221, 'Alice'],\n", " [213, 'that'],\n", " [204, 'her'],\n", " [196, 'at'],\n", " [176, 'had'],\n", " [168, 'with'],\n", " [151, 'all'],\n", " [138, 'on'],\n", " [137, 'be'],\n", " [125, 'very'],\n", " [125, 'for'],\n", " [119, '“I'],\n", " [118, 'little'],\n", " [108, 'they'],\n", " [103, 'so'],\n", " [103, 'not'],\n", " [101, 'but'],\n", " [97, 'out'],\n", " [94, 'he'],\n", " [93, 'his'],\n", " [89, 'The'],\n", " [86, 'this'],\n", " [85, 'what'],\n", " [84, 'about'],\n", " [82, 'were'],\n", " [81, 'up'],\n", " [79, 'went'],\n", " [77, 'one'],\n", " [77, 'down'],\n", " [76, 'Alice,'],\n", " [74, 'like'],\n", " [73, 'have'],\n", " [69, 'if'],\n", " [68, 'would'],\n", " [68, 'or'],\n", " [67, 'into'],\n", " [66, 'when'],\n", " [64, 'no'],\n", " [63, 'thought'],\n", " [63, 'is'],\n", " [63, 'could'],\n", " [60, '*'],\n", " [57, 'its'],\n", " [56, 'Mock'],\n", " [55, 'my'],\n", " [54, 'Alice.'],\n", " [53, 'your'],\n", " [53, 'quite'],\n", " [53, 'by'],\n", " [52, 'an'],\n", " [50, 'then'],\n", " [50, 'their'],\n", " [50, 'did'],\n", " [49, 'them'],\n", " [49, 'And'],\n", " [48, 'who'],\n", " [48, 'don’t'],\n", " [47, 'some'],\n", " [47, 'see'],\n", " [46, 'time'],\n", " [46, 'me'],\n", " [46, 'do'],\n", " [46, 'began'],\n", " [45, 'looked'],\n", " [45, 'know'],\n", " [45, 'got'],\n", " [44, 'there'],\n", " [43, 'only'],\n", " [43, 'just'],\n", " [43, 'get'],\n", " [40, 'such'],\n", " [40, 'much'],\n", " [40, 'herself'],\n", " [39, 'must'],\n", " [39, 'great'],\n", " [38, '“and'],\n", " [38, 'off'],\n", " [38, 'more'],\n", " [38, 'it,'],\n", " [38, 'go'],\n", " [38, 'came'],\n", " [37, 'which'],\n", " [37, 'way'],\n", " [37, 'never'],\n", " [37, 'how'],\n", " [37, 'are'],\n", " [36, 'think'],\n", " [36, 'been'],\n", " [36, 'any'],\n", " [35, 'thing'],\n", 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'her,'],\n", " [18, 'eyes'],\n", " [18, 'cried'],\n", " [17, '“And'],\n", " [17, 'this,'],\n", " [17, 'sort'],\n", " [17, 'sat'],\n", " [17, 'even'],\n", " [17, 'Queen,'],\n", " [17, 'Mouse'],\n", " [16, '“How'],\n", " [16, 'use'],\n", " [16, 'under'],\n", " [16, 'turned'],\n", " [16, 'tone,'],\n", " [16, 'sure'],\n", " [16, 'is,'],\n", " [16, 'ever'],\n", " [16, 'eat'],\n", " [16, 'doesn’t'],\n", " [16, 'curious'],\n", " [16, 'again.'],\n", " [16, 'Hare'],\n", " [16, 'Alice;'],\n", " [15, '“The'],\n", " [15, '“It’s'],\n", " [15, 'you’re'],\n", " [15, 'wonder'],\n", " [15, 'while'],\n", " [15, 'we'],\n", " [15, 'voice,'],\n", " [15, 'there’s'],\n", " [15, 'minute'],\n", " [15, 'it.'],\n", " [15, 'gave'],\n", " [15, 'door'],\n", " [15, 'called'],\n", " [15, 'away'],\n", " [15, 'This'],\n", " [15, 'King,'],\n", " [15, 'It'],\n", " [15, 'Gryphon.'],\n", " [15, 'Duchess'],\n", " [15, 'But'],\n", " [14, '“That’s'],\n", " [14, '“If'],\n", " [14, 'words'],\n", " [14, 'was,'],\n", " [14, 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(convert to 2D list (or list of tuples) when necessary)\n", "\n", "If my application needs to display the words in order a frequency more often, and individual word lookup is leess common, then use 2D list." ] } ], "metadata": { "celltoolbar": "Slideshow", "hide_code_all_hidden": false, "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.8" } }, "nbformat": 4, "nbformat_minor": 5 }