%matplotlib inline
We’ll revisit the Problem 3 of Assignment 2, where we had to manipulate some data from a fake library.
In this problem, we had the following format for the data:
[[123456,312314,531337],['John Doe',' Jane Miller','Ted Johnson'],[1.49,0.00,8.12]]
[[123456, 312314, 531337], ['John Doe', ' Jane Miller', 'Ted Johnson'], [1.49, 0.0, 8.12]]
(a) Construct a dictionary to store this data, using the student ID (the first big number) as key.
Use the same loop and logic than before.
data = []
with open("library_data.txt") as f:
for line in f:
data.append(line)
studentname_to_id = {}
library_data = {}
for item in data:
split = item.split(" ")
library_data[int(split[0])] = float(split[3]) # (a)
studentname_to_id[" ".join(split[1:3])] = int(split[0]) # (b)
print(library_data)
{123456: 1.49, 102931: 1.2, 391273: 10.39, 531337: 8.12, 312314: 0.0, 273263: 0.0}
(b) Create another dictionary which maps the name of the student to its student id:
print(studentname_to_id)
# desired output : {'Jane Miller': 312314, 'John Doe': 123456, 'Ted Johnson': 531337}
{'Fred Asteir': 102931, 'Ted Johnson': 531337, 'Johnny Depp': 273263, 'Jane Miller': 312314, 'John Doe': 123456, 'Sarah Connor': 391273}
(c) Print how much money 'John Doe' owes the library, using both of your dictionaries.
idnum = studentname_to_id['John Doe']
library_data[idnum]
1.49
(d) Create the list of the names of students owing more than £1.0 to the library.
for key in studentname_to_id: # (d)
idnum = studentname_to_id[key]
if library_data[idnum]>1.0:
print(key)
Fred Asteir Ted Johnson John Doe Sarah Connor
(a) In this problem we’ll use the text of Alice in Wonderland to construct dictionaries counting the
number of times particular words and pairs of words appear.
from urllib.request import urlopen
URL = "http://www.gutenberg.org/files/11/11.txt"
with urlopen(URL) as f:
with open("alice.txt","wb") as g:
g.write(f.read())
This will create a new file called "alice.txt"
(b) We'll process alice.txt in loops like this:
# load data
with open("alice.txt") as f:
lines=f.readlines()[40:]
# make single string (joining all lines with nothing ("") in between
lines="".join(lines)
print(lines[:1000])
CHAPTER I. Down the Rabbit-Hole Alice was beginning to get very tired of sitting by her sister on the bank, and of having nothing to do: once or twice she had peeped into the book her sister was reading, but it had no pictures or conversations in it, 'and what is the use of a book,' thought Alice 'without pictures or conversations?' So she was considering in her own mind (as well as she could, for the hot day made her feel very sleepy and stupid), whether the pleasure of making a daisy-chain would be worth the trouble of getting up and picking the daisies, when suddenly a White Rabbit with pink eyes ran close by her. There was nothing so VERY remarkable in that; nor did Alice think it so VERY much out of the way to hear the Rabbit say to itself, 'Oh dear! Oh dear! I shall be late!' (when she thought it over afterwards, it occurred to her that she ought to have wondered at this, but at the time it all seemed quite natural); but when the Rabbit actually TOOK A WATCH OUT OF ITS WAISTCO
# replace unwanted characters by whitespace
preprocessed=lines
to_delete=[":", "!", "?", ".", ",", ";", "\n", "\r", "\'", "\'s", "s\'", "\#", "*", "(", ")", "--"]
for item in to_delete:
preprocessed=preprocessed.replace(item, " ")
print(preprocessed[:1000])
CHAPTER I Down the Rabbit-Hole Alice was beginning to get very tired of sitting by her sister on the bank and of having nothing to do once or twice she had peeped into the book her sister was reading but it had no pictures or conversations in it and what is the use of a book thought Alice without pictures or conversations So she was considering in her own mind as well as she could for the hot day made her feel very sleepy and stupid whether the pleasure of making a daisy-chain would be worth the trouble of getting up and picking the daisies when suddenly a White Rabbit with pink eyes ran close by her There was nothing so VERY remarkable in that nor did Alice think it so VERY much out of the way to hear the Rabbit say to itself Oh dear Oh dear I shall be late when she thought it over afterwards it occurred to her that she ought to have wondered at this but at the time it all seemed quite natural but when the Rabbit actually TOOK A WATCH OUT OF ITS WAISTCO
# create word list
words=[word.lower() for word in preprocessed.split()]
print(words[:100])
['chapter', 'i', 'down', 'the', 'rabbit-hole', 'alice', 'was', 'beginning', 'to', 'get', 'very', 'tired', 'of', 'sitting', 'by', 'her', 'sister', 'on', 'the', 'bank', 'and', 'of', 'having', 'nothing', 'to', 'do', 'once', 'or', 'twice', 'she', 'had', 'peeped', 'into', 'the', 'book', 'her', 'sister', 'was', 'reading', 'but', 'it', 'had', 'no', 'pictures', 'or', 'conversations', 'in', 'it', 'and', 'what', 'is', 'the', 'use', 'of', 'a', 'book', 'thought', 'alice', 'without', 'pictures', 'or', 'conversations', 'so', 'she', 'was', 'considering', 'in', 'her', 'own', 'mind', 'as', 'well', 'as', 'she', 'could', 'for', 'the', 'hot', 'day', 'made', 'her', 'feel', 'very', 'sleepy', 'and', 'stupid', 'whether', 'the', 'pleasure', 'of', 'making', 'a', 'daisy-chain', 'would', 'be', 'worth', 'the', 'trouble', 'of', 'getting']
# compute histogram for single words
histogram_single={}
for word in words:
if word not in histogram_single:
histogram_single[word]=1
else:
histogram_single[word]+=1
# print sorted
for key,value in histogram_single.items():
print(key, value)
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notifies 1 cheered 3 pulling 1 tunnel 1 neat 1 occur 1 knave 9 write 6 rosetree 1 grunt 1 state 7 figures 1 got 45 fan 10 shrinking 4 louder 1 bill 17 met 4 disclaimer 3 shower 2 mile 2 any 76 boots 4 expression 1 concluded 2 nearer 5 displaying 4 pattern 1 agreed 1 writing 7 appealed 1 daresay 1 permanent 1 push 1 dears 3 whatsoever 1 chanced 1 interrupted 9 herald 1 lot 1 became 2 deductible 1 notion 3 chorus 6 breathe 2 speaker 1 by-the-bye 1 dates 1 darkness 1 wore 1 dinn 2 mustard 2 terror 1 801 1 11 2 mallets 1 paying 2 floor 3 knock 1 places 2 door 30 while 26 balanced 1 mistake 3 sea-shore 1 links 3 daisies 1 wish 22 undertone 2 thoroughly 2 juror 1 story 8 appeared 8 wooden 1 physical 2 incidental 1 wag 1 till 21 position 2 deepest 1 beautify 1 school 5 lit 1 nonproprietary 1 somersault 1 sobbed 1 ensuring 1 are 73 fairy-tales 1 indemnify 1 remember 14 muttered 2 pointing 4 bag 1 paragraphs 3 hungry 3 proofread 1 upsetting 1 ventured 4 compliance 5 soldiers 10 placed 1 fitness 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liked 6 meat 1 offend 1 twenty-four 2 angry 5 synonymous 1 statements 1 simple 5 ancient 1 all 200 rushed 1 end 20 years 2 wherever 2 royalty 3 cheeks 1 animal 2 fumbled 1 times 6 pace 1 stopped 3 ours 1 accusation 1 unlink 1 furrow 1 ask 11 states 14 cross 1 smiled 2 favourite 1 too 25 replace 1 cross-examine 2 guests 3 awfully 1 fishes 1 fifteenth 1 file 2 elsie 1 online 3 lamps 1 sense 3 fun 3 three 26 flower-beds 1 neighbouring 1 expense 1 safe 2 word 11 ve 44 diligently 1 lines 1 merchantibility 1 touch 1 rat-hole 1 curiouser 2 shape 1 watch 8 voices 3 remarking 3 come 45 truth 1 sits 1 removed 4 care 4 settled 3 "miss 1 make 30 pardon 6 reported 1 incomplete 1 footsteps 2 afford 1 leant 1 flurry 1 cried 20 run 4 arches 4 x 1 examining 1 exclusion 1 sharp 6 executive 1 atheling 1 whatever 3 forgotten 6 denial 1 downloading 1 candle 3 part 6 thimble 4 remarks 3 reply 5 precious 1 star-fish 1 caused 2 teacups 2 concert 2 dreadfully 6 would 83 596-1887 1 maximum 1 antipathies 1 sky 4 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treacle-well 2 modified 1 hush 3 because 16 real 3 plan 4 sighed 5 machines 1 circle 1 invented 1 ought 14 kings 1 same 25 hot-tempered 1 pepper 7 world 7 cunning 1 ugly 2 fright 2 nibbled 2 dripping 1 they 154 arithmetic 1 idea 15 conquest 1 cauldron 2 required 1 affair 1 broke 2 scale 1 helpless 1 meaning 8 cheerfully 1 either 11 treacle 5 catching 2 advise 1 reports 1 duck 4 supple 1 arrum 1 fire 3 interrupting 2 cakes 3 easily 4 venture 3 "turtle 1 boon 1 game 13 irs 1 were 85 swallowing 1 weeks 1 bother 1 cold 1 pig-baby 1 creature 4 f3 1 flock 1 burning 1 keeping 4 ut 1 bottom 4 page 2 "they 1 curtseying 1 principal 1 notice 8 northumbria 2 belong 1 quietly 5 music 3 snout 1 copyright 13 hot 5 sit 8 lie 2 squeezed 1 over 40 folded 3 esq 1 good-natured 1 survive 1 coming 8 modification 1 prove 1 educations 1 pigeon 12 have 85 worry 1 sitting 10 m 63 anywhere 2 tulip-roots 1 readable 2 present 3 taken 4 maps 1 pray 3 miserable 2 sneezes 2 right 34 meant 5 fountains 2 below 6 guilt 1 die 1 bowed 4 that 330 profits 1 "too 1 stick 4 ix 1 flung 1 donations 15 vinegar 1 special 1 called 15 more 50 seen 15 perfectly 4 pointed 1 facility 1 eat" 1 merrily 1 meet 3 turn-up 1 start 2 tones 2 edwin 1 data 1 so 152 redistribution 2 business@pglaf 1 stairs 3 hold 11 unless 6 gbnewby@pglaf 1 parts 1 quadrille 4 makes 12 sound 4 unfortunate 3 footmen 1 baby 13 lieu 2 contemptuously 2 contact 4 begin 13 haven 8 receiving 1 buttons 1 remaining 2 flower-pot 1 dance 13 cautiously 3 stand 6 fancy 7 "defects 1 scattered 1 linked 2 teapot 1 why 40 lastly 1 struck 2 ahem 1 wouldn 13 friends 2 received 6 foundation 24 open 7 unfolded 2 ma 3 officers 4 earth 4 screaming 1 uncommonly 1 bee 1 tells 2 knocked 1 already 3 opinion 1 burn 2 very 145 section 7 course 26 paid 6 frontispiece 1 suppressed 4 theirs 1 forepaws 1 one 106 org/fundraising 1 added 23 fight 2 pleased 7 general 6 us 15 flappers 1 capering 1 our 12 draw 7 obstacle 1 "i 10 camomile 1 inwards 1 sight 10 nonsense 7 beating 2 important 8 fell 6 boxed 1 clock 5 ebooks 7 lived 3 smallest 2 knelt 1 this 178 ful 1 suet 1 damaged 1 newspapers 1 farther 1 tiny 4 dark 3 address 1 "up 1 son 1 ill 2 holding 3 charitable 1 brave 1 read 14 beheading 1 setting 1 fourth 1 kitchen 4 throat 2 christmas 1 variations 1 croqueted 1 retire 1 city 1 stamping 2 passion 3 good 24 twelfth 1 fills 1 once 34 grumbled 1 however 21 confusing 3 drowned 1 glanced 1 talking 17 laughter 1 missed 2 atom 2 lazily 1 annoyed 1 hypertext 1 kiss 1 hour 2 moved 5 fidgeted 1 puss 1 maintaining 1 duchess 42 straight 2 production 1 4557 1 trotting 2 means 8 chrysalis 1 registered 2 happy 1 rubbed 1 hands 12 book-shelves 1 anxiously 14 order 3 fly 3 think 53 beheaded 3 splash 1 "never 1 ache 1 vote 1 alarmed 1 fur 3 adjourn 1 faces 5 sharing 2 funny 3 mercia 2 body 2 dozing 1 how 70 race-course 1 teaching 1 queen 75 medium 5 learnt 2 fee 8 alone 5 pour 1 snorting 1 elbow 3 until 5 saucepans 1 parchment 2 execution 3 entity 3 unusually 1 scolded 1 personal 2 drive 2 blasts 2 directed 2 staff 1 finish 5 planning 1 handwriting 1 expend 1 is 133 waters 1 rustled 1 ann 4 an 61 wriggling 1 several 5 brightened 2 instance 3 extras 1 included 2 carrying 2 something 18 table 18 mixed 2 owns 2 dropped 5 told 6 song 7 attends 1 railway 2 immediate 3 curving 1 puppy 7 succeeded 3 twinkle 7 snatch 2 paper 5 took 24 knew 15 never 46 question 17 provision 1 pennyworth 2 obtaining 2 moving 3 archbishop 2 bough 1 bristling 1 creep 1 hasn 2 taste 2 painting 2 graceful 1 comfortable 1 uncorked 1 distributor 1 queer-shaped 1 together 9 did 63 occasionally 1 heap 1 deletions 1 types 1 "coming 1 cleared 1 fighting 1 disk 1 chop 1 uncommon 1 act 1 acceptance 1 larger 7 hedge 2 wearily 1 journey 1 gazing 1 ridges 1 certainly 14 went 83 blown 1 nearly 13 and 933 toast 1 those 11 furious 1 beds 1 dry 8 sink 1 closed 2 actually 1 dismay 1 advance 3 cur 1 neck 7 shy 1 eager 3 ] 2 "take 1 raving 2 child-life 1 many 14 luckily 2 countries 1 haste 1 flamingo 5 arise 1 hat 1 oblong 1 new 8 hedgehog 7 hjckrrh 1 felt 23 spite 1 done 15 e-mail 1 sometimes 5 tougher 1 small 12 chose 2 salmon 1 call 9 side 17 pink 1 lady 3 guard 1 eyes 29 difficulties 1 puzzled 9 able 1 ears 5 gutenberg 26 somehow 1 honour 4 failure 1 asking 5 pence 1 when 80 could 78 lesson-book 1 payments 3 happen 8 trademark/copyright 1 considered 3 legal 2 muddle 1 jaws 2 keep 12 milk-jug 1 mournful 1 between 6 west 1 drawing 1 refund 9 engraved 1 free 8 heels 1 confusion 5 heads 10 paragraph 11 knocking 3 box 4 attending 3 trembling 6 whole 13 obliged 3 lowing 1 proceed 2 attempts 1 jar 2 receive 3 d 30 miss 3 above 3 beauti 1 expecting 3 sadly 5 complained 1 "keep 1 catch 4 wait 1 then 94 org/1/11/ 1 lacie 1 age 4 diamonds 1 arrived 1 earls 2 mayn 1 respect 1 specific 1 indemnity 1 living 2 forth 8 promise 1 wise 2 agent 1 edgar 1 visit 3 fashion 2 u 3 be 165 noticed 8 comply 6 finger 5 accidentally 1 eels 1 grin 6 of 625 recovered 2 often 6 copying 4 family 1 looking 30 encourage 1 yes 13 procession 5 laws 8 sulky 3 move 3 dive 1 silent 7 sticks 1 matters 2 shepherd 1 justice 1 puzzling 4 hunting 3 improve 1 piece 5 losing 1 powdered 1 filled 3 bursting 1 effort 2 england 1 sprawling 1 prepare 2 carroll 1 closer 1 see 69 line 2 watching 3 simpleton 1 chief 2 "come 2 series 1 remedies 2 paris 2 boldly 1 readily 1 "twinkle 1 much 51 finishing 1 eyelids 1 hurriedly 2 shyly 1 middle-aged 1 exempt 2 cheshire 7 inside 2 violence 1 conqueror 2 don 61 bowing 1 future 3 answers 1 secure 1 knuckles 1 shakespeare 1 alas 4 treat 1 dunce 1 pine-apple 1 quarrelling 2 proud 2 useful 2 shillings 1 rude 2 plate 3 containing 1 govern 1 sour 1 spoon 2 faint 1 elegant 1 widest 2 wags 1 rabbit 47 attempt 1 distance 8 likes 1 pepper-box 1 despair 1 tasted 3 rattle 1 locked 1 next 30 kind 8 splendidly 1 teases 1 clearer 1 strange 5 _i_ 2 turns 3 occasional 1 growls 1 politely 6 your 71 ii 1 roughly 1 whiskers 3 arm-chair 1 nowhere 2 credit 1 volunteer 1 circumstances 1 lock 1 toes 3
Modify this code so that it creates a new dictionary called words at (1).
For (2), if a word
is not already in the dictionary words, then add it to the dictionary with a value of 1.
If a
word is already in the dictionary words, then increment the value stored in the dictionary
by one.
At location (3), print out the dictionary words.
(b) How many times does the word “the” appear? What about the word “The”?
print(histogram_single["the"])
1807
(d) Modify the code so words are counted independent of whether they are made of upper or
lower case letters. i.e., “the”, “The” and “tHE” are all treated as the same word.
# See above
(e) Repeat the previous exercise, but instead of counting the number of times a word appears,
count the number of times pairs of words appear. You might find it useful to store the previous word in a variable.
def print_dict_sorted_by_value(d):
sorted_keys=sorted(d, key=d.get, reverse=True)
for k in sorted_keys:
print(k, d[k])
# compute histogram for single words
histogram_pairs={}
for i in range(len(words)-1):
pair=(words[i],words[i+1])
if pair not in histogram_pairs:
histogram_pairs[pair]=1
else:
histogram_pairs[pair]+=1
print_dict_sorted_by_value(histogram_pairs)
('said', 'the') 210 ('of', 'the') 155 ('said', 'alice') 116 ('in', 'a') 101 ('in', 'the') 93 ('to', 'the') 85 ('and', 'the') 85 ('it', 'was') 76 ('the', 'queen') 72 ('at', 'the') 63 ('the', 'king') 62 ('don', 't') 61 ('as', 'she') 61 ('she', 'had') 60 ('a', 'little') 59 ('i', 'm') 59 ('project', 'gutenberg-tm') 57 ('it', 's') 57 ('mock', 'turtle') 56 ('she', 'was') 55 ('and', 'she') 55 ('to', 'be') 53 ('the', 'mock') 53 ('the', 'gryphon') 53 ('the', 'hatter') 52 ('with', 'the') 51 ('went', 'on') 48 ('to', 'herself') 45 ('you', 'know') 45 ('the', 'duchess') 41 ('if', 'you') 39 ('said', 'to') 39 ('on', 'the') 37 ('out', 'of') 37 ('that', 'she') 35 ('she', 'said') 35 ('the', 'dormouse') 35 ('that', 's') 34 ('i', 've') 34 ('there', 'was') 34 ('and', 'then') 33 ('march', 'hare') 31 ('was', 'a') 31 ('she', 'could') 31 ('i', 'don') 30 ('the', 'other') 30 ('by', 'the') 30 ('all', 'the') 30 ('the', 'march') 30 ('so', 'she') 29 ('i', 'll') 29 ('of', 'this') 29 ('she', 'went') 29 ('the', 'mouse') 28 ('can', 't') 28 ('did', 'not') 28 ('i', 'can') 28 ('to', 'her') 28 ('with', 'a') 28 ('the', 'project') 28 ('that', 'it') 27 ('such', 'a') 27 ('the', 'caterpillar') 26 ('thought', 'alice') 26 ('it', 'and') 26 ('a', 'very') 25 ('to', 'alice') 25 ('of', 'a') 25 ('up', 'and') 25 ('at', 'all') 25 ('of', 'course') 24 ('into', 'the') 24 ('won', 't') 24 ('but', 'she') 23 ('the', 'cat') 23 ('there', 's') 23 ('to', 'see') 23 ('you', 're') 23 ('for', 'the') 23 ('the', 'same') 22 ('if', 'i') 22 ('white', 'rabbit') 22 ('it', 'said') 22 ('the', 'rabbit') 22 ('the', 'white') 22 ('one', 'of') 22 ('project', 'gutenberg') 22 ('1', 'e') 22 ('to', 'say') 21 ('the', 'door') 21 ('but', 'i') 21 ('as', 'it') 21 ('as', 'well') 21 ('could', 'not') 21 ('s', 'the') 20 ('her', 'head') 20 ('alice', 'and') 20 ('a', 'large') 20 ('was', 'the') 20 ('but', 'it') 20 ('to', 'do') 20 ('seemed', 'to') 20 ('must', 'be') 20 ('as', 'the') 19 ('and', 'was') 19 ('the', 'little') 19 ('they', 'were') 19 ('at', 'last') 19 ('when', 'she') 19 ('it', 'is') 19 ('about', 'it') 18 ('of', 'it') 18 ('you', 'are') 18 ('gutenberg-tm', 'electronic') 18 ('and', 'alice') 18 ('had', 'been') 18 ('she', 'thought') 18 ('i', 'think') 18 ('to', 'get') 18 ('at', 'once') 18 ('you', 'can') 18 ('this', 'time') 18 ('do', 'you') 17 ('for', 'a') 17 ('a', 'great') 17 ('of', 'her') 17 ('would', 'be') 17 ('it', 'had') 17 ('of', 'them') 17 ('looked', 'at') 17 ('i', 'should') 17 ('like', 'a') 17 ('alice', 'was') 17 ('and', 'i') 17 ('terms', 'of') 16 ('and', 'a') 16 ('electronic', 'works') 16 ('alice', 'i') 16 ('i', 'shall') 16 ('doesn', 't') 16 ('to', 'go') 16 ('this', 'agreement') 16 ('t', 'be') 16 ('the', 'first') 16 ('in', 'her') 15 ('the', 'jury') 15 ('a', 'minute') 15 ('sort', 'of') 15 ('again', 'and') 15 ('as', 'if') 15 ('into', 'a') 15 ('the', 'court') 15 ('that', 'the') 15 ('it', 'would') 15 ('but', 'the') 14 ('s', 'a') 14 ('when', 'i') 14 ('she', 'did') 14 ('are', 'you') 14 ('be', 'a') 14 ('and', 'as') 14 ('and', 'began') 14 ('s', 'no') 14 ('didn', 't') 14 ('t', 'know') 14 ('a', 'good') 14 ('just', 'as') 14 ('like', 'the') 14 ('i', 'wonder') 13 ('that', 'you') 13 ('end', 'of') 13 ('t', 'you') 13 ('a', 'long') 13 ('to', 'find') 13 ('you', 'may') 13 ('the', 'next') 13 ('or', 'two') 13 ('as', 'he') 13 ('i', 'must') 13 ('to', 'make') 13 ('they', 're') 13 ('back', 'to') 13 ('archive', 'foundation') 13 ('alice', 's') 13 ('and', 'said') 13 ('gutenberg', 'literary') 13 ('the', 'time') 13 ('she', 'felt') 13 ('wouldn', 't') 13 ('he', 'said') 13 ('literary', 'archive') 13 ('i', 'know') 13 ('the', 'whole') 13 ('she', 'began') 13 ('and', 'that') 13 ('know', 'what') 12 ('going', 'to') 12 ('would', 'not') 12 ('and', 'he') 12 ('i', 'wish') 12 ('your', 'majesty') 12 ('the', 'end') 12 ('the', 'way') 12 ('minute', 'or') 12 ('will', 'you') 12 ('what', 'i') 12 ('what', 'a') 12 ('is', 'the') 12 ('the', 'house') 12 ('alice', 'thought') 12 ('the', 'cook') 12 ('the', 'dodo') 12 ('i', 'never') 12 ('ought', 'to') 12 ('it', 'in') 12 ('from', 'the') 12 ('they', 'all') 12 ('and', 'they') 12 ('had', 'to') 12 ('was', 'not') 12 ('for', 'some') 12 ('the', 'words') 12 ('she', 'found') 12 ('for', 'it') 11 ('you', 'see') 11 ('when', 'the') 11 ('and', 'it') 11 ('with', 'one') 11 ('my', 'dear') 11 ('she', 'heard') 11 ('poor', 'alice') 11 ('you', 'must') 11 ('it', 'to') 11 ('the', 'work') 11 ('and', 'all') 11 ('do', 'not') 11 ('had', 'not') 11 ('alice', 'could') 11 ('wasn', 't') 11 ('and', 'went') 11 ('you', 'won') 11 ('alice', 'said') 11 ('tell', 'you') 11 ('was', 'going') 11 ('was', 'that') 11 ('the', 'baby') 11 ('the', 'right') 11 ('to', 'have') 11 ('and', 'looked') 11 ('them', 'and') 11 ('then', 'the') 11 ('the', 'terms') 11 ('down', 'the') 11 ('alice', 'as') 11 ('used', 'to') 11 ('i', 'd') 11 ('alice', 'had') 11 ('to', 'you') 11 ('about', 'the') 11 ('the', 'pigeon') 11 ('electronic', 'work') 11 ('go', 'on') 11 ('the', 'foundation') 11 ('if', 'it') 10 ('like', 'to') 10 ('well', 'as') 10 ('on', 'it') 10 ('time', 'she') 10 ('1', 'f') 10 ('near', 'the') 10 ('the', 'air') 10 ('very', 'much') 10 ('his', 'head') 10 ('for', 'she') 10 ('the', 'dance') 10 ('was', 'very') 10 ('you', 'd') 10 ('i', 'suppose') 10 ('took', 'the') 10 ('and', 'how') 10 ('to', 'a') 10 ('must', 'have') 10 ('at', 'this') 10 ('at', 'her') 10 ('king', 'and') 10 ('access', 'to') 10 ('got', 'to') 10 ('turning', 'to') 10 ('united', 'states') 10 ('till', 'she') 10 ('in', 'an') 10 ('did', 'you') 10 ('that', 'is') 10 ('this', 'work') 10 ('what', 'you') 10 ('had', 'a') 10 ('off', 'with') 10 ('a', 'low') 10 ('is', 'it') 10 ('alice', 'did') 10 ('ll', 'be') 9 ('no', 'use') 9 ('i', 'was') 9 ('the', 'sea') 9 ('then', 'she') 9 ('thought', 'it') 9 ('she', 'tried') 9 ('m', 'not') 9 ('they', 'had') 9 ('alice', 'in') 9 ('was', 'no') 9 ('she', 'looked') 9 ('sat', 'down') 9 ('if', 'she') 9 ('the', 'united') 9 ('had', 'never') 9 ('alice', 'replied') 9 ('that', 'they') 9 ('after', 'a') 9 ('paragraph', '1') 9 ('who', 'was') 9 ('join', 'the') 9 ('while', 'the') 9 ('s', 'all') 9 ('under', 'the') 9 ('the', 'knave') 9 ('with', 'his') 9 ('the', 'game') 9 ('m', 'a') 9 ('alice', 'to') 9 ('i', 'do') 9 ('before', 'she') 9 ('of', 'any') 9 ('it', 'as') 9 ('well', 'i') 9 ('there', 'were') 9 ('think', 'you') 9 ('in', 'my') 9 ('poor', 'little') 9 ('was', 'in') 9 ('you', 'like') 9 ('not', 'a') 9 ('when', 'they') 9 ('so', 'much') 9 ('you', 'said') 9 ('to', 'begin') 9 ('couldn', 't') 9 ('king', 'said') 9 ('the', 'poor') 9 ('and', 'when') 9 ('tried', 'to') 9 ('down', 'and') 9 ('the', 'garden') 9 ('of', 'project') 9 ('the', 'full') 9 ('the', 'table') 9 ('let', 'me') 8 ('the', 'best') 8 ('for', 'you') 8 ('haven', 't') 8 ('gutenberg-tm', 'license') 8 ('alice', 'it') 8 ('her', 'face') 8 ('it', 'she') 8 ('wish', 'i') 8 ('which', 'was') 8 ('oh', 'dear') 8 ('trying', 'to') 8 ('some', 'of') 8 ('cried', 'the') 8 ('in', 'that') 8 ('public', 'domain') 8 ('alice', 'looked') 8 ('now', 'and') 8 ('of', 'its') 8 ('she', 'came') 8 ('tell', 'me') 8 ('the', 'top') 8 ('at', 'any') 8 ('forth', 'in') 8 ('you', 'do') 8 ('have', 'been') 8 ('and', 'in') 8 ('it', 'll') 8 ('beautiful', 'soup') 8 ('she', 'ran') 8 ('the', 'footman') 8 ('with', 'her') 8 ('began', 'to') 8 ('up', 'to') 8 ('with', 'its') 8 ('round', 'the') 8 ('hadn', 't') 8 ('a', 'bit') 8 ('a', 'moment') 8 ('to', 'speak') 8 ('look', 'at') 8 ('set', 'forth') 8 ('a', 'mouse') 8 ('this', 'she') 8 ('on', 'a') 8 ('to', 'come') 8 ('to', 'ask') 8 ('think', 'i') 8 ('this', 'was') 8 ('were', 'all') 8 ('i', 'didn') 8 ('so', 'they') 8 ('of', 'that') 8 ('i', 'am') 8 ('in', 'it') 8 ('it', 'might') 8 ('through', 'the') 8 ('any', 'rate') 8 ('is', 'a') 8 ('the', 'rest') 8 ('use', 'of') 8 ('at', 'first') 8 ('was', 'quite') 8 ('little', 'thing') 8 ('on', 'their') 8 ('among', 'the') 8 ('gryphon', 'and') 8 ('like', 'that') 8 ('i', 'could') 8 ('oh', 'i') 8 ('she', 'got') 8 ('agree', 'to') 8 ('began', 'in') 8 ('the', 'moment') 8 ('how', 'to') 8 ('said', 'in') 8 ('he', 'was') 8 ('the', 'pool') 8 ('you', 'will') 8 ('that', 'i') 8 ('who', 'had') 8 ('and', 'there') 7 ('the', 'use') 7 ('"', 'said') 7 ('very', 'soon') 7 ('full', 'project') 7 ('at', 'it') 7 ('added', 'the') 7 ('so', 'that') 7 ('down', 'on') 7 ('the', 'reason') 7 ('and', 'this') 7 ('you', 'might') 7 ('of', 'hearts') 7 ('their', 'slates') 7 ('you', 'to') 7 ('herself', 'in') 7 ('beginning', 'to') 7 ('way', 'of') 7 ('and', 'yet') 7 ('m', 'afraid') 7 ('her', 'and') 7 ('fan', 'and') 7 ('to', 'think') 7 ('about', 'her') 7 ('she', 'would') 7 ('cried', 'alice') 7 ('as', 'i') 7 ('s', 'very') 7 ('about', 'in') 7 ('with', 'an') 7 ('their', 'heads') 7 ('tone', 'of') 7 ('and', 'had') 7 ('her', 'sister') 7 ('alice', 'who') 7 ('here', 'the') 7 ('looking', 'at') 7 ('queen', 's') 7 ('as', 'they') 7 ('to', 'them') 7 ('it', 'i') 7 ('queen', 'and') 7 ('got', 'up') 7 ('wonder', 'what') 7 ('the', 'trial') 7 ('indeed', 'said') 7 ('the', 'window') 7 ('the', 'distance') 7 ('by', 'this') 7 ('what', 'is') 7 ('off', 'the') 7 ('what', 'are') 7 ('now', 'i') 7 ('top', 'of') 7 ('up', 'into') 7 ('saying', 'to') 7 ('as', 'a') 7 ('alice', 'began') 7 ('isn', 't') 7 ('over', 'the') 7 ('at', 'least') 7 ('this', 'moment') 7 ('set', 'to') 7 ('work', 'or') 7 ('make', 'out') 7 ('for', 'her') 7 ('time', 'to') 7 ('t', 'think') 7 ('upon', 'a') 7 ('it', 'doesn') 7 ('some', 'time') 7 ('seem', 'to') 7 ('same', 'thing') 7 ('all', 'round') 7 ('as', 'you') 7 ('was', 'so') 7 ('went', 'to') 7 ('at', 'alice') 7 ('out', 'the') 7 ('the', 'wood') 7 ('quite', 'a') 7 ('that', 'said') 7 ('of', 'his') 7 ('the', 'three') 7 ('be', 'no') 7 ('of', 'sight') 7 ('not', 'like') 7 ('you', 'don') 7 ('in', 'all') 7 ('soo', 'oop') 7 ('i', 'hadn') 7 ('in', 'another') 7 ('am', 'i') 7 ('she', 's') 7 ('to', 'work') 7 ('it', 'must') 7 ('see', 'it') 7 ('will', 'be') 7 ('in', 'this') 7 ('you', 've') 7 ('called', 'out') 7 ('t', 'like') 7 ('that', 'he') 7 ('to', 'it') 7 ('or', 'any') 7 ('copies', 'of') 7 ('see', 'what') 7 ('good', 'deal') 7 ('i', 'have') 7 ('have', 'you') 7 ('and', 'what') 6 ('he', 'had') 6 ('on', 'which') 6 ('of', 'little') 6 ('the', 'middle') 6 ('alice', 'she') 6 ('t', 'have') 6 ('sitting', 'on') 6 ('hand', 'and') 6 ('said', 'this') 6 ('you', 'mean') 6 ('what', 'the') 6 ('the', 'lory') 6 ('try', 'the') 6 ('that', 'had') 6 ('t', 'said') 6 ('out', 'to') 6 ('but', 'they') 6 ('the', 'soldiers') 6 ('very', 'curious') 6 ('i', 'beg') 6 ('are', 'old') 6 ('it', 'so') 6 ('they', 'would') 6 ('the', 'fan') 6 ('then', 'it') 6 ('is', 'that') 6 ('her', 'hand') 6 ('number', 'of') 6 ('if', 'he') 6 ('was', 'now') 6 ('would', 'you') 6 ('the', 'world') 6 ('works', 'in') 6 ('dear', 'i') 6 ('you', 'll') 6 ('that', 'was') 6 ('a', 'few') 6 ('duchess', 'and') 6 ('she', 'might') 6 ('its', 'eyes') 6 ('m', 'sure') 6 ('tone', 'and') 6 ('so', 'very') 6 ('her', 'hands') 6 ('you', 'and') 6 ('ready', 'to') 6 ('it', 'but') 6 ('was', 'just') 6 ('know', 'the') 6 ('other', 'side') 6 ('have', 'to') 6 ('why', 'i') 6 ('all', 'her') 6 ('great', 'hurry') 6 ('alice', 'a') 6 ('she', 'spoke') 6 ('him', 'and') 6 ('i', 'haven') 6 ('the', 'chimney') 6 ('up', 'in') 6 ('the', 'copyright') 6 ('moral', 'of') 6 ('so', 'alice') 6 ('the', 'roof') 6 ('golden', 'key') 6 ('shan', 't') 6 ('her', 'eyes') 6 ('in', 'paragraph') 6 ('want', 'to') 6 ('and', 'very') 6 ('his', 'eyes') 6 ('felt', 'that') 6 ('found', 'it') 6 ('come', 'on') 6 ('the', 'great') 6 ('up', 'the') 6 ('said', 'nothing') 6 ('all', 'that') 6 ('the', 'moral') 6 ('or', 'other') 6 ('on', 'in') 6 ('was', 'sitting') 6 ('on', 'her') 6 ('oh', 'my') 6 ('it', 'a') 6 ('its', 'mouth') 6 ('not', 'the') 6 ('not', 'said') 6 ('was', 'looking') 6 ('please', 'your') 6 ('put', 'it') 6 ('could', 'see') 6 ('what', 'was') 6 ('you', 'were') 6 ('to', 'me') 6 ('the', 'last') 6 ('that', 'in') 6 ('he', 'spoke') 6 ('left', 'off') 6 ('close', 'to') 6 ('you', 'have') 6 ('which', 'the') 6 ('beg', 'your') 6 ('he', 'went') 6 ('on', 'and') 6 ('voice', 'and') 6 ('while', 'she') 6 ('as', 'soon') 6 ('a', 'curious') 6 ('three', 'gardeners') 6 ('more', 'than') 6 ('to', 'tell') 6 ('the', 'trees') 6 ('is', 'to') 6 ('which', 'way') 6 ('side', 'of') 6 ('herself', 'and') 6 ('the', 'executioner') 6 ('down', 'here') 6 ('alice', 'very') 6 ('she', 'knew') 6 ('a', 'thing') 6 ('its', 'head') 6 ('however', 'she') 6 ('to', 'look') 6 ('few', 'minutes') 6 ('a', 'tone') 6 ('the', 'name') 6 ('use', 'in') 6 ('soon', 'as') 6 ('little', 'door') 6 ('t', 'talk') 6 ('again', 'the') 6 ('after', 'all') 6 ('ve', 'got') 6 ('how', 'she') 6 ('d', 'better') 6 ('thought', 'and') 6 ('it', 'out') 6 ('no', 'one') 6 ('when', 'it') 6 ('found', 'herself') 6 ('you', 'a') 5 ('come', 'back') 5 ('is', 'i') 5 ('i', 'had') 5 ('last', 'the') 5 ('into', 'her') 5 ('about', 'and') 5 ('that', 'if') 5 ('said', 'and') 5 ('the', 'mushroom') 5 ('on', 'his') 5 ('looked', 'down') 5 ('offended', 'tone') 5 ('alice', 'that') 5 ('know', 'it') 5 ('in', 'at') 5 ('then', 'you') 5 ('was', 'too') 5 ('the', 'ground') 5 ('herself', 'i') 5 ('in', 'their') 5 ('of', 'tears') 5 ('what', 'would') 5 ('kid', 'gloves') 5 ('get', 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'this') 1 ('little', 'toss') 1 ('executioner', 'went') 1 ('rumbling', 'of') 1 ('serpent', 'screamed') 1 ('garden', 'how') 1 ('other', 'project') 1 ('tongue', 'said') 1 ('hatter', 'so') 1 ('everything', 'i') 1 ('dogs', 'it') 1 ('feeling', 'quite') 1 ('curiosity', 'and') 1 ('is', 'bill') 1 ('disappeared', 'so') 1 ('the', 'chief') 1 ('of', 'tiny') 1 ('a', 'couple') 1 ('somewhere', 'down') 1 ('s', 'plenty') 1 ('every', 'day') 1 ('receive', 'a') 1 ('queen', 'to-day') 1 ('the', 'archbishop') 1 ('half', 'afraid') 1 ('were', 'writing') 1 ('passage', 'not') 1 ('have', 'removed') 1 ('ugh', 'said') 1 ('a', 'pleasant') 1 ('one', 'would') 1 ('any', 'disclaimer') 1 ('with', 'these') 1 ('tea', 'i') 1 ('no', 'representations') 1 ('once', 'but') 1 ('charges', 'at') 1 ('all', 'use') 1 ('much', 'larger') 1 ('again', 'keep') 1 ('things', 'indeed') 1 ('in', 'most') 1 ('yourself', 'for') 1 ('much', 'evidence') 1 ('would', 'break') 1 ('riper', 'years') 1 ('alice', 'seriously') 1 ('thimble', 'said') 1 ('he', 'shall') 1 ('highest', 'tree') 1 ('be', 'some') 1 ('hear', 'about') 1 ('now', 'dinah') 1 ('very', 'rude') 1 ('means', 'that') 1 ('every', 'word') 1 ('can', 'receive') 1 ('head', 'contemptuously') 1 ('to', 'day') 1 ('make', 'any') 1 ('in', 'like') 1 ('will', 'prosecute') 1 ('by', 'u') 1 ('talk', 'in') 1 ('a', 'holiday') 1 ('carried', 'on') 1 ('upon', 'an') 1 ('goes', 'like') 1 ('difficulties', 'great') 1 ('d', 'get') 1 ('are', 'accepted') 1 ('the', 'games') 1 ('shared', 'with') 1 ('printed', 'editions') 1 ('new', 'computers') 1 ('would', 'always') 1 ('on', 'yawning') 1 ('kind', 'express') 1 ('plan', 'exclaimed') 1 ('how', 'fond') 1 ('pool', 'all') 1 ('it', 'never') 1 ('knot', 'said') 1 ('noticed', 'with') 1 ('ground', 'alice') 1 ('pig', 'alice') 1 ('was', 'full') 1 ('formats', 'will') 1 ('was', 'busily') 1 ('least', 'idea') 1 ('work', 'copyright') 1 ('queer', 'everything') 1 ('music', 'ah') 1 ('it', 'woke') 1 ('disclaimer', 'of') 1 ('brought', 'it') 1 ('coming', 'down') 1 ('christmas', 'and') 1 ('it', 'alice') 1 ('hedgehog', 'just') 1 ('with', 'us') 1 ('meeting', 'adjourn') 1 ('bottle', 'that') 1 ('here', 'why') 1 ('fig', 'said') 1 ('are', 'your') 1 ('branches', 'and') 1 ('tarts', 'made') 1 ('there', 'may') 1 ('very', 'true') 1 ('a', 'court') 1 ('she', 'left') 1 ('hastily', 'for') 1 ('set', 'out') 1 ('why', 'then') 1 ('stairs', 'how') 1 ('she', 'hurried') 1 ('plate', 'alice') 1 ('nevertheless', 'she') 1 ('executed', 'on') 1 ('sleep', 'when') 1 ('room', 'they') 1 ('on', 'tiptoe') 1 ('s', 'asleep') 1 ('panted', 'as') 1 ('lived', 'on') 1 ('contract', 'except') 1 ('production', 'promotion') 1 ('fall', 'a') 1 ('explanation', 'the') 1 ('left', 'alive') 1 ('you', 'forget') 1 ('e', '6') 1 ('plan', 'it') 1 ('in', 'to') 1 ('the', 'internal') 1 ('tail', 'as') 1 ('other', 'i') 1 ('sneezing', 'on') 1 ('advantage', 'said') 1 ('alice', 'loudly') 1 ('through', 'thought') 1 ('of', 'nearly') 1 ('kept', 'getting') 1 ('to', 'follow') 1 ('made', 'no') 1 ('took', 'me') 1 ('sink', 'into') 1 ('see', 'when') 1 ('denied', 'so') 1 ('nearer', 'alice') 1 ('had', 'meanwhile') 1 ('compliance', 'for') 1 ('that', 'ridiculous') 1 ('t', 'directed') 1 ('school', 'every') 1 ('i', 'daresay') 1 ('must', 'remember') 1 ('who', 'would') 1 ('had', 'caught') 1 ('the', 'pie') 1 ('eagerly', 'the') 1 ('cried', 'wake') 1 ('rabbit', 'hastily') 1 ('own', 'i') 1 ('slates', 'but') 1 ('the', 'directions') 1 ('they', 'wouldn') 1 ('thing', 'that') 1 ('he', 'hurried') 1 ('herself', 'lying') 1 ('good', 'advice') 1 ('of', 'finding') 1 ('treacle-well', 'eh') 1 ('with', 'only') 1 ('801', '596-1887') 1 ('m', 'why') 1 ('that', 'lay') 1 ('not', 'above') 1 ('seen', 'she') 1 ('4557', 'melan') 1 ('considered', 'him') 1 ('site', 'includes') 1 ('paw', 'round') 1 ('ground', 'so') 1 ('them', 'about') 1 ('dodo', 'then') 1 ('i', 'growl') 1 ('for', 'going') 1 ('happen', '"miss') 1 ('wine', 'she') 1 ('lory', 'with') 1 ('keeping', 'so') 1 ('court', 'all') 1 ('too', 'close') 1 ('your', 'opinion') 1 ('of', 'goldfish') 1 ('thrown', 'out') 1 ('them', 'but') 1 ('joined', 'wow') 1 ('had', 'somehow') 1 ('s', 'ears') 1 ('them', 'this') 1 ('that', 'again') 1 ('iv', 'the') 1 ('knocking', 'and') 1 ('came', 'flying') 1 ('such', 'dainties') 1 ('put', 'my') 1 ('soldiers', 'wandered') 1 ('like', 'keeping') 1 ('had', 'known') 1 ('further', 'opportunities') 1 ('gardeners', 'but') 1 ('but', 'was') 1 ('melancholy', 'air') 1 ('afraid', 'but') 1 ('that', 'curious') 1 ('called', 'the') 1 ('give', 'him') 1 ('the', 'status') 1 ('without', 'complying') 1 ('drew', 'her') 1 ('off', 'into') 1 ('gravy', 'and') 1 ('that', 'arise') 1 ('twelve', 'and') 1 ('fitness', 'for') 1 ('hands', 'at') 1 ('hatter', 'shook') 1 ('hear', 'some') 1 ('wore', 'his') 1 ('em', 'do') 1 ('garden', 'first') 1 ('the', 'tiny') 1 ('remaining', 'provisions') 1 ('hypertext', 'form') 1 ('how', 'surprised') 1 ('same', 'solemn') 1 ('anything', 'near') 1 ('writhing', 'of') 1 ('large', 'canvas') 1 ('table', 'nothing') 1 ('curious', 'croquet-ground') 1 ('off', 'quarrelling') 1 ('sugar', 'my') 1 ('life', 'just') 1 ('are', 'nobody') 1 ('of', 'mississippi') 1 ('org/fundraising', 'contributions') 1 ('and', 'opened') 1 ('fish', 'game') 1 ('broke', 'off') 1 ('noticing', 'her') 1 ('solemnly', 'presented') 1 ('on', 'till') 1 ('nicely', 'straightened') 1 ('lessen', 'from') 1 ('defective', 'or') 1 ('when', 'we') 1 ('"such', 'a') 1 ('poison', 'it') 1 ('idea', 'was') 1 ('struck', 'her') 1 ('to', 'settle') 1 ('were', 'nine') 1 ('m', 'said') 1 ('ran', 'as') 1 ('person', 'then') 1 ('whatever', 'happens') 1 ('angrily', 'at') 1 ('murdering', 'the') 1 ('one', 'time') 1 ('can', 'kick') 1 ('lesson-books', 'and') 1 ('old', 'thing') 1 ('real', 'turtle') 1 ('shore', 'and') 1 ('very', 'sulkily') 1 ('this', 'piece') 1 ('it', 'something') 1 ('constant', 'howling') 1 ('good', 'terms') 1 ('have', 'ordered') 1 ('been', 'found') 1 ('the', 'bread-knife') 1 ('i', 'cut') 1 ('queen', 'it') 1 ('last', 'they') 1 ('moment', 'they') 1 ('leaning', 'her') 1 ('very', 'grave') 1 ('that', 'your') 1 ('carrying', 'the') 1 ('usual', 'you') 1 ('bone', 'in') 1 ('sadly', 'down') 1 ('much', 'to-night') 1 ('nothing', 'when') 1 ('person', 'soon') 1 ('your', 'country') 1 ('to', 'run') 1 ('remembered', 'trying') 1 ('alice', 'besides') 1 ('to', 'wash') 1 ('by', 'talking') 1 ('nothing', 'nobody') 1 ('corner', 'but') 1 ('outdated', 'equipment') 1 ('take', 'no') 1 ('walked', 'a') 1 ('5', 'some') 1 ('provided', 'in') 1 ('hearth', 'and') 1 ('for', 'to') 1 ('with', 'pink') 1 ('go', 'no') 1 ('tears', 'which') 1 ('that', 'cheshire') 1 ('or', 'obtain') 1 ('this', 'of') 1 ('kept', 'fanning') 1 ('birds', 'why') 1 ('dance', '"') 1 ('three', 'were') 1 ('swallow', 'a') 1 ('name', 'alice') 1 ('"right', 'of') 1 ('usual', 'come') 1 ('this', 'fireplace') 1 ('things', 'don') 1 ('mouse', 'replied') 1 ('esq', 'hearthrug') 1 ('"with', 'what') 1 ('eats', 'cake') 1 ('screaming', 'with') 1 ('trial', 'stupid') 1 ('it', 'presently') 1 ('might', 'answer') 1 ('30', 'days') 1 ('get', 'us') 1 ('house', 'down') 1 ('wide', 'on') 1 ('favourite', 'word') 1 ('sounded', 'hoarse') 1 ('large', 'in') 1 ('alice', 'so') 1 ('serpent', 'it') 1 ('a', 'drawing') 1 ('she', 'sits') 1 ('very', 'sudden') 1 ('a', 'loose') 1 ('one', 'minute') 1 ('felt', 'dreadfully') 1 ('a', 'sleepy') 1 ('which', 'case') 1 ('sobs', 'choked') 1 ('2', 'if') 1 ('time', 'of') 1 ('displaying', 'the') 1 ('running', 'when') 1 ('and', 'yawned') 1 ('first', 'really') 1 ('license', 'and') 1 ('be', 'as') 1 ('finger', 'pressed') 1 ('she', 'wasn') 1 ('timidly', 'said') 1 ('fan', 'she') 1 ('knows', 'it') 1 ('gryphon', 'whispered') 1 ('away', 'some') 1 ('laws', 'and') 1 ('oh', 'as') 1 ('far', 'as') 1 ('perhaps', 'as') 1 ('yet', 'alice') 1 ('little', 'eyes') 1 ('people', 'that') 1 ('choked', 'and') 1 ('s', 'hand') 1 ('hurry', 'you') 1 ('head', 'would') 1 ('some', 'fun') 1 ('or', 'more') 1 ('passion', 'and') 1 ('tea', 'upon') 1 ('joined', 'the') 1 ('ever', 'thought') 1 ('no', 'you') 1 ('liability', 'to') 1 ('countries', 'are') 1 ('plainly', 'through') 1 ('and', 'giving') 1 ('busy', 'bee') 1 ('well', 'of') 1 ('it', 'mouse') 1 ('late', 'and') 1 ('alice', 'turned') 1 ('a', 'red') 1 ('next', 'peeped') 1 ('followed', 'by') 1 ('get', 'me') 1 ('thump', 'down') 1 ('the', 'roots') 1 ('indeed', 'and') 1 ('sending', 'me') 1 ('it', 'sounds') 1 ('he', 'doesn') 1 ('eyes', 'are') 1 ('he', 'knows') 1 ('remarkable', 'in') 1 ('for', 'yourself') 1 ('was', 'generally') 1 ('a', 'memorandum') 1 ('unimportant', 'of') 1 ('wonder', 'as') 1 ('so', 'out-of-the-way') 1 ('game', 's') 1 ('very', 'clear') 1 ('changed', 'several') 1 ('the', 'constant') 1 ('or', 'is') 1 ('your', 'cat') 1 ('cook', 'treacle') 1 ('a', 'consultation') 1 ('3', 'educational') 1 ('trying', 'which') 1 ('large', 'fan') 1 ('strange', 'tale') 1 ('found', 'to') 1 ('it', 'ran') 1 ('flung', 'down') 1 ('remark', 'with') 1 ('house', 'which') 1 ('moving', 'round') 1 ('afterwards', 'it') 1 ('mouse', 'getting') 1 ('look', 'so') 1 ('find', 'the') 1 ('nothing', 'written') 1 ('soldiers', 'had') 1 ('"they', 'all') 1 ('added', 'looking') 1 ('till', 'now') 1 ('straightening', 'itself') 1 ('treacle', 'out') 1 ('future', 'generations') 1 ('sigh', 'it') 1 ('begun', 'they') 1 ('out-of-the-way', 'down') 1 ('ve', 'fallen') 1 ('wags', 'its') 1 ('water', 'out') 1 ('not', 'contain') 1 ('for', 'shutting') 1 ('remember', 'about') 1 ('grumbled', 'you') 1 ('bottle', 'had') 1 ('school', 'said') 1 ('was', 'heard') 1 ('round', 'eager') 1 ('up', 'dormouse') 1 ('fix', 'the') 1 ('it', 'no') 1 ('and', 'granted') 1 ('soon', 'make') 1 ('queer', 'noises') 1 ('fancied', 'that') 1 ('three-legged', 'stool') 1 ('croqueting', 'one') 1 ('mouse', 'gave') 1 ('came', 'near') 1 ('soup', 'and') 1 ('up', 'now') 1 ('is', 'who') 1 ('so', 'desperate') 1 ('gryphon', 'she') 1 ('mouth', 'enough') 1 ('support', 'the') 1 ('there', 'she') 1 ('branches', 'of') 1 ('hers', 'would') 1 ('foundation', 'web') 1 ('other', 'form') 1 ('a', 'pleased') 1 ('quite', 'so') 1 ('getting', 'tired') 1 ('archbishop', 'of') 1 ('or', 'using') 1 ('hard', 'indeed') 1 ('sister', 'kissed') 1 ('and', 'c') 1 ('it', 'yet') 1 ('likely', 'true') 1 ('see', 'four') 1 ('hurry', 'an') 1 ('conger-eel', 'that') 1 ('to', 'execute') 1
(f) What are the most common words and pairs of words in Alice in Wonderland?
You might find the sorted function or the sort function for lists to be useful.
print_dict_sorted_by_value(histogram_single)
the 1807 and 933 to 805 a 689 of 625 it 605 she 553 i 533 you 477 said 462 in 425 alice 399 was 358 that 330 as 273 her 248 with 225 at 225 t 218 s 213 on 204 all 200 for 178 had 178 this 178 but 175 not 166 be 165 they 154 or 153 so 152 very 145 what 139 is 133 little 128 he 126 if 116 out 114 one 106 about 102 down 102 up 100 do 98 no 98 there 98 his 96 then 94 know 88 them 88 were 85 have 85 like 84 again 83 herself 83 would 83 went 83 when 80 project 79 could 78 any 76 by 76 queen 75 thought 74 can 73 are 73 off 73 your 71 how 70 see 69 me 68 time 68 into 67 who 65 its 63 king 63 m 63 did 63 an 61 don 61 well 60 now 60 my 58 began 58 turtle 58 gutenberg-tm 57 ll 57 which 56 mock 56 hatter 56 quite 55 gryphon 55 way 55 other 54 must 54 work 53 think 53 some 52 only 52 their 52 just 52 say 51 first 51 here 51 from 51 much 51 head 50 go 50 more 50 thing 49 " 48 voice 48 rabbit 47 such 46 never 46 looked 45 got 45 get 45 come 45 oh 44 ve 44 1 44 mouse 43 him 43 after 42 we 42 duchess 42 round 41 tone 40 dormouse 40 came 40 over 40 why 40 two 39 great 39 before 39 will 39 back 38 re 38 been 38 cat 37 found 35 nothing 34 march 34 without 34 right 34 once 34 works 33 last 33 long 33 large 33 tell 32 things 32 put 31 moment 31 hare 31 white 30 heard 30 door 30 make 30 made 30 d 30 looking 30 next 30 should 29 replied 29 dear 29 eyes 29 use 28 might 28 upon 28 e 28 look 28 caterpillar 28 going 27 away 27 may 27 poor 27 shall 27 seemed 27 electronic 27 while 26 three 26 won 26 than 26 course 26 gutenberg 26 day 25 rather 25 yet 25 too 25 soon 25 same 25 sure 24 foundation 24 good 24 took 24 added 23 felt 23 getting 22 set 22 wish 22 another 22 please 22 anything 22 ever 21 find 21 under 21 till 21 take 21 let 21 half 21 words 21 terms 21 old 21 minute 21 even 21 however 21 hand 20 end 20 cried 20 sort 20 curious 19 tried 19 feet 19 being 19 full 19 house 18 court 18 wonder 18 enough 18 agreement 18 soup 18 where 18 something 18 table 18 perhaps 17 jury 17 spoke 17 asked 17 bill 17 eat 17 sat 17 these 17 talking 17 question 17 side 17 garden 16 turned 16 am 16 through 16 doesn 16 hastily 16 used 16 bit 16 indeed 16 ran 16 both 16 people 16 high 16 because 16 give 15 face 15 saying 15 mad 15 hear 15 beginning 15 speak 15 near 15 change 15 gave 15 idea 15 donations 15 called 15 seen 15 us 15 knew 15 done 15 license 14 better 14 talk 14 dinah 14 suppose 14 trying 14 saw 14 air 14 silence 14 low 14 remember 14 everything 14 states 14 itself 14 didn 14 left 14 ought 14 read 14 anxiously 14 certainly 14 many 14 suddenly 13 room 13 dodo 13 sea 13 far 13 really 13 behind 13 gone 13 size 13 tea 13 grow 13 cook 13 literary 13 cats 13 beautiful 13 still 13 archive 13 always 13 close 13 kept 13 game 13 copyright 13 baby 13 begin 13 dance 13 wouldn 13 nearly 13 whole 13 yes 13 hardly 12 every 12 try 12 afraid 12 turning 12 deal 12 finished 12 help 12 life 12 arm 12 majesty 12 best 12 chapter 12 among 12 pigeon 12 makes 12 our 12 hands 12 small 12 keep 12 hurry 11 footman 11 tears 11 thinking 11 copy 11 minutes 11 mind 11 wasn 11 name 11 glad 11 hurried 11 growing 11 agree 11 whether 11 else 11 does 11 waited 11 pool 11 ask 11 word 11 most 11 though 11 gloves 11 either 11 hold 11 those 11 paragraph 11 f 10 own 10 turn 10 repeated 10 explain 10 yourself 10 mouth 10 remark 10 child 10 trademark 10 mean 10 children 10 having 10 trial 10 bottle 10 witness 10 lessons 10 opened 10 united 10 fan 10 soldiers 10 3 10 foot 10 offended 10 walked 10 few 10 different 10 against 10 rest 10 access 10 creatures 10 remarked 10 queer 10 sitting 10 "i 10 sight 10 heads 10 serpent 9 matter 9 has 9 party 9 hall 9 want 9 place 9 timidly 9 leave 9 mine 9 opportunity 9 sister 9 conversation 9 birds 9 waiting 9 answer 9 shook 9 join 9 angrily 9 tail 9 couldn 9 each 9 knave 9 interrupted 9 written 9 public 9 continued 9 believe 9 rate 9 key 9 glass 9 reason 9 least 9 shouted 9 together 9 call 9 puzzled 9 refund 9 window 8 running 8 hard 8 live 8 seem 8 whiting 8 hadn 8 associated 8 making 8 asleep 8 followed 8 sentence 8 days 8 five 8 nose 8 changed 8 slates 8 moral 8 play 8 learn 8 pig 8 gardeners 8 others 8 mushroom 8 beg 8 story 8 appeared 8 feel 8 adventures 8 number 8 marked 8 including 8 everybody 8 domain 8 lying 8 hearts 8 watch 8 wood 8 slowly 8 eagerly 8 exactly 8 top 8 http 8 ready 8 business 8 org 8 fact 8 person 8 nobody 8 meaning 8 notice 8 sit 8 coming 8 haven 8 important 8 means 8 fee 8 dry 8 new 8 happen 8 free 8 forth 8 noticed 8 laws 8 distance 8 kind 8 stood 7 drink 7 outside 7 feeling 7 bright 7 grown 7 sir 7 - 7 generally 7 wondering 7 fall 7 middle 7 lobsters 7 begun 7 manage 7 lory 7 tired 7 copies 7 isn 7 somebody 7 book 7 oop 7 soo 7 myself 7 distributing 7 goes 7 history 7 golden 7 deep 7 except 7 permission 7 dream 7 hair 7 shoes 7 repeat 7 state 7 writing 7 provide 7 eye 7 listen 7 lobster 7 understand 7 frightened 7 william 7 trees 7 evidence 7 almost 7 fetch 7 happened 7 subject 7 information 7 tarts 7 chin 7 surprised 7 pepper 7 world 7 fancy 7 open 7 section 7 pleased 7 draw 7 nonsense 7 ebooks 7 song 7 puppy 7 twinkle 7 larger 7 neck 7 hedgehog 7 silent 7 cheshire 7 shan 6 executed 6 ten 6 particular 6 distribute 6 himself 6 broken 6 along 6 arms 6 seven 6 sneezing 6 melancholy 6 c 6 trouble 6 within 6 youth 6 tax 6 father 6 ear 6 wow 6 exclaimed 6 english 6 roof 6 chimney 6 volunteers 6 bread-and-butter 6 lizard 6 sing 6 using 6 write 6 chorus 6 late 6 leaves 6 stupid 6 o 6 liked 6 times 6 pardon 6 sharp 6 forgotten 6 part 6 dreadfully 6 croquet 6 loud 6 nice 6 charge 6 distribution 6 web 6 inches 6 executioner 6 four 6 editions 6 jumped 6 stop 6 second 6 below 6 unless 6 stand 6 received 6 paid 6 general 6 fell 6 told 6 between 6 trembling 6 comply 6 grin 6 often 6 politely 6 tree 5 usual 5 likely 5 rule 5 swam 5 become 5 eggs 5 evening 5 4 5 prizes 5 stay 5 cause 5 crowded 5 curiosity 5 shriek 5 ground 5 direction 5 knee 5 home 5 tis 5 swim 5 gutenberg" 5 twice 5 aloud 5 rules 5 whispered 5 sounded 5 seems 5 altogether 5 interesting 5 certain 5 "project 5 doing 5 hookah 5 sleep 5 instantly 5 nearer 5 school 5 compliance 5 surprise 5 pack 5 posted 5 waving 5 sleepy 5 kid 5 wrong 5 pocket 5 drew 5 happens 5 sudden 5 limited 5 replacement 5 remembered 5 cut 5 speaking 5 nine 5 dare 5 form 5 across 5 impatiently 5 angry 5 simple 5 reply 5 owner 5 nervous 5 case 5 pair 5 ah 5 shrill 5 man 5 morning 5 shouldn 5 taking 5 shut 5 height 5 ebook 5 temper 5 passed 5 walk 5 young 5 unimportant 5 cannot 5 walking 5 sighed 5 treacle 5 quietly 5 hot 5 meant 5 clock 5 moved 5 faces 5 medium 5 alone 5 until 5 finish 5 several 5 dropped 5 paper 5 flamingo 5 sometimes 5 ears 5 asking 5 confusion 5 sadly 5 finger 5 procession 5 piece 5 strange 5 sides 4 freely 4 crumbs 4 grass 4 corner 4 argument 4 natural 4 rabbit-hole 4 animals 4 uncomfortable 4 frowning 4 fast 4 8 4 twinkling 4 paws 4 fallen 4 difficulty 4 shoulder 4 vanished 4 support 4 sounds 4 violently 4 hearing 4 girl 4 jurymen 4 dead 4 reach 4 pictures 4 capital 4 begins 4 provided 4 players 4 ordered 4 judge 4 allow 4 fish 4 spread 4 creating 4 crowd 4 busily 4 status 4 decidedly 4 savage 4 tale 4 fond 4 mary 4 ootiful 4 phrase 4 chance 4 since 4 yer 4 pale 4 collection 4 doubt 4 led 4 verses 4 taught 4 none 4 site 4 lay 4 answered 4 digging 4 providing 4 explanation 4 distributed 4 sharply 4 dish 4 mice 4 water 4 hers 4 beau 4 besides 4 beat 4 verse 4 short 4 damages 4 carried 4 shrinking 4 met 4 boots 4 displaying 4 pointing 4 ventured 4 law 4 reading 4 passage 4 sobs 4 mouths 4 stuff 4 bats 4 lives 4 format 4 screamed 4 worth 4 green 4 solemnly 4 fees 4 additional 4 confused 4 requirements 4 deeply 4 wanted 4 //pglaf 4 fellow 4 hours 4 thoughtfully 4 verdict 4 letter 4 mission 4 tongue 4 removed 4 care 4 run 4 arches 4 thimble 4 sky 4 severely 4 jury-box 4 less 4 holder 4 questions 4 fear 4 indignantly 4 consider 4 mabel 4 sigh 4 further 4 managed 4 located 4 guinea-pigs 4 held 4 says 4 jumping 4 grunted 4 otherwise 4 wonderland 4 jurors 4 porpoise 4 shoulders 4 also 4 hope 4 thank 4 individual 4 true 4 twelve 4 anyone 4 escape 4 breath 4 plan 4 duck 4 easily 4 creature 4 keeping 4 bottom 4 taken 4 bowed 4 stick 4 perfectly 4 quadrille 4 sound 4 contact 4 officers 4 earth 4 suppressed 4 tiny 4 kitchen 4 ann 4 honour 4 box 4 catch 4 age 4 copying 4 puzzling 4 alas 4 yesterday 3 hanging 3 sorts 3 9 3 limitation 3 user 3 butter 3 sent 3 obtain 3 appear 3 bat 3 em 3 faster 3 nor 3 fit 3 speech 3 croquet-ground 3 remained 3 eaglet 3 sobbing 3 applicable 3 tortoise 3 hoping 3 pattering 3 civil 3 brought 3 easy 3 equipment 3 alive 3 joined 3 smaller 3 suit 3 crash 3 "what 3 dull 3 pity 3 cake 3 bank 3 legs 3 owl 3 timid 3 paw 3 peeped 3 gravely 3 handed 3 guess 3 dogs 3 sad 3 somewhere 3 defective 3 nurse 3 takes 3 livery 3 staring 3 solemn 3 delight 3 complying 3 follow 3 panther 3 yours 3 defect 3 pieces 3 warranties 3 listening 3 wrote 3 choked 3 possibly 3 lost 3 out-of-the-way 3 pleaded 3 fury 3 throw 3 country 3 grave 3 girls 3 figure 3 shaking 3 5 3 return 3 hurt 3 friend 3 email 3 cost 3 finding 3 efforts 3 kick 3 considering 3 bringing 3 mentioned 3 to-day 3 pressed 3 official 3 nibbling 3 dog 3 performing 3 knowledge 3 rose-tree 3 proper 3 hoarse 3 week 3 printed 3 crossed 3 courage 3 trumpet 3 guessed 3 liability 3 sighing 3 salt 3 cards 3 cry 3 directly 3 immediately 3 repeating 3 growl 3 bring 3 longer 3 mark 3 7 3 roses 3 tossing 3 howling 3 bound 3 advantage 3 pat 3 upset 3 impossible 3 whisper 3 tails 3 instead 3 anxious 3 cheered 3 disclaimer 3 dears 3 notion 3 floor 3 mistake 3 links 3 paragraphs 3 hungry 3 hedgehogs 3 snail 3 caucus-race 3 sending 3 spectacles 3 opening 3 forgetting 3 slipped 3 crab 3 b 3 follows 3 telescope 3 master 3 edge 3 carefully 3 doth 3 wide 3 permitted 3 directions 3 love 3 themselves 3 show 3 shore 3 tucked 3 muttering 3 "there 3 teacup 3 2 3 putting 3 crown 3 royalty 3 stopped 3 guests 3 online 3 sense 3 fun 3 voices 3 remarking 3 settled 3 whatever 3 candle 3 remarks 3 gently 3 around 3 effect 3 "you 3 loudly 3 simply 3 miles 3 washing 3 needn 3 //www 3 money 3 worse 3 list 3 night 3 donate 3 serpents 3 picked 3 following 3 derivative 3 slate 3 caught 3 grand 3 constant 3 checked 3 nursing 3 boy 3 decided 3 french 3 noise 3 grinned 3 hush 3 real 3 fire 3 cakes 3 venture 3 music 3 folded 3 present 3 pray 3 meet 3 stairs 3 unfortunate 3 cautiously 3 ma 3 already 3 lived 3 dark 3 holding 3 passion 3 confusing 3 order 3 fly 3 beheaded 3 fur 3 funny 3 elbow 3 execution 3 entity 3 instance 3 immediate 3 succeeded 3 moving 3 advance 3 eager 3 lady 3 payments 3 considered 3 knocking 3 attending 3 obliged 3 receive 3 miss 3 above 3 expecting 3 visit 3 u 3 sulky 3 move 3 hunting 3 filled 3 watching 3 future 3 plate 3 tasted 3 turns 3 whiskers 3 toes 3 resting 2 morcar 2 laughed 2 wretched 2 difficult 2 playing 2 shorter 2 relief 2 brown 2 redistributing 2 pinch 2 pglaf 2 concept 2 usually 2 thoughts 2 changes 2 ashamed 2 destroy 2 accordance 2 changing 2 forehead 2 leaning 2 pause 2 conclusion 2 www 2 threw 2 mostly 2 regular 2 names 2 goose 2 barrowful 2 sneeze 2 remain 2 break 2 tea-party 2 custody 2 lefthand 2 busy 2 startled 2 bear 2 executions 2 based 2 crying 2 muchness 2 "plain 2 ring 2 alarm 2 denied 2 smiling 2 dishes 2 invited 2 specified 2 research 2 protect 2 produced 2 ordering 2 extremely 2 humbly 2 laid 2 collected 2 generations 2 wine 2 raised 2 federal 2 office 2 whom 2 mystery 2 claws 2 implied 2 shared 2 riddles 2 locks 2 trembled 2 comes 2 heart 2 six 2 presents 2 distant 2 sensation 2 active 2 fix 2 telling 2 copied 2 forgot 2 branches 2 hint 2 concerning 2 scream 2 90 2 three-legged 2 quickly 2 feelings 2 tea-time 2 fish-footman 2 weak 2 501 2 delighted 2 created 2 coaxing 2 dreadful 2 receipt 2 plenty 2 "how 2 flowers 2 clearly 2 year 2 assembled 2 abide 2 choice 2 offer 2 ornamented 2 yawned 2 contain 2 conversations 2 authority 2 ferrets 2 sh 2 plates 2 intellectual 2 wasting 2 poison 2 wild 2 cares 2 nicely 2 crimson 2 cup 2 wind 2 turtles 2 learning 2 comfits 2 purring 2 ringlets 2 sun 2 electronically 2 pinched 2 shutting 2 lap 2 imagine 2 cushion 2 showing 2 entirely 2 purpose 2 accident 2 rush 2 label 2 files 2 prisoner 2 frog 2 entangled 2 accepted 2 encouraging 2 splashing 2 ascii" 2 sang 2 triumphantly 2 occurred 2 given 2 thousand 2 picking 2 stole 2 deny 2 heavy 2 reaching 2 wink 2 smile 2 wash 2 sulkily 2 quick 2 disappeared 2 michael 2 giddy 2 kindly 2 whenever 2 locations 2 taller 2 share 2 pleasure 2 patiently 2 promoting 2 advisable 2 experiment 2 anger 2 search 2 uneasily 2 front 2 red 2 lovely 2 feeble 2 declare 2 considerable 2 row 2 "the 2 damage 2 knife 2 laughing 2 breach 2 bird 2 reasonable 2 shower 2 mile 2 concluded 2 became 2 breathe 2 dinn 2 mustard 2 11 2 paying 2 places 2 undertone 2 thoroughly 2 physical 2 position 2 muttered 2 rapidly 2 apples 2 ago 2 guinea-pig 2 employees 2 unrolled 2 wants 2 shouting 2 flat 2 half-past 2 pebbles 2 dinner 2 sisters 2 wonderful 2 dancing 2 pigs 2 started 2 remarkable 2 advice 2 twist 2 knot 2 neatly 2 manner 2 available 2 squeaking 2 swimming 2 giving 2 clear 2 doubtfully 2 doors 2 excellent 2 stretched 2 dipped 2 lonely 2 meekly 2 curled 2 forget 2 older 2 sorrowful 2 vanilla 2 secondly 2 depends 2 6 2 rome 2 charges 2 ugh 2 narrow 2 woman 2 computers 2 whose 2 goldfish 2 beasts 2 invitation 2 cupboards 2 unhappy 2 delightful 2 fancied 2 introduce 2 tumbling 2 hit 2 send 2 absurd 2 throwing 2 blew 2 drunk 2 proved 2 property 2 wildly 2 extraordinary 2 warranty 2 hate 2 twenty-four 2 years 2 wherever 2 animal 2 smiled 2 cross-examine 2 file 2 safe 2 curiouser 2 footsteps 2 caused 2 teacups 2 concert 2 thistle 2 persisted 2 computer 2 cool 2 merely 2 doubtful 2 bad 2 shaped 2 sooner 2 scroll 2 pie 2 tut 2 treading 2 month 2 bite 2 royalties 2 longed 2 contributions 2 flamingoes 2 royal 2 wandered 2 [later 2 ways 2 wandering 2 addressed 2 dispute 2 knows 2 blow 2 violent 2 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circumstances 1 lock 1
(a) Finding the index of the largest (or smallest) element in a list is a commonly needed operation, but Python does not provide this function in its standard library (numpy will provide those). Write two functions
def argmax(list_input):
idx = None
for i, item in enumerate(list_input):
if i == 0:
m = item
elif item > m:
idx = i
m = item
return idx
def argmin(list_input):
idx = None
for i, item in enumerate(list_input):
if i == 0:
m = item
elif item < m:
idx = i
m = item
return idx
that return the index of the largest and smallest element in the list list_input respectively. Example output:
>>> list1 = [1,3,2,6,0,2,3,4,5]
>>> argmax(list1)
3
>>> argmin(list1)
4
# try it here
list1 = [1,3,2,6,0,2,3,4,5]
print(argmin(list1))
4
(b) (extra) Instead of just finding the index of the largest or smallest element, one might be interested in the entire list of indices that would sort the list. In one of the previous exercises we presented you with this piece of code for finding the indices that sort a list.
l = [1,3,2,6,0,2,3,4,5]
list(zip(*sorted(zip(l, range(len(l))))))[1]
(4, 0, 2, 5, 1, 6, 7, 8, 3)
It works by combining the list with the list of indices, sorting the combined list, and then untangling the results. Have a look at the documentation of the zip function to understand how it works. Write a function:
def argsort(l):
sorted_index = []
index_and_item = []
for i, v in enumerate(l):
index_and_item.append((v, i))
for v, i in sorted(index_and_item):
sorted_index.append(i)
return sorted_index
def argsort_short(l):
return [i for (v, i) in sorted((v, i) for (i, v) in enumerate(l))]
print(argsort([1,3,2,6,0,2,3,4,5]))
print(argsort_short([1,3,2,6,0,2,3,4,5]))
[4, 0, 2, 5, 1, 6, 7, 8, 3] [4, 0, 2, 5, 1, 6, 7, 8, 3]
that returns the list of indices that would sort the list, but instead of using the hard to read
line above that uses zip, use list comprehensions. Example output:
>>> l = [1,3,2,6,0,2,3,4,5]
>>> argsort(l)
[4, 0, 2, 5, 1, 6, 7, 8, 3]
>>> [l[i] for i in argsort(l)]
[0, 1, 2, 2, 3, 3, 4, 5, 6]
# try it here
l = [1,3,2,6,0,2,3,4,5]
print(argsort(l))
print([l[i] for i in argsort(l)])
[4, 0, 2, 5, 1, 6, 7, 8, 3] [0, 1, 2, 2, 3, 3, 4, 5, 6]
Suppose you wish to send your friend a message, and if someone happens to look at it, you do not want them to know what it says.
A simple way of doing this is to replace each letter, with
a different one.
For example, suppose I wish to send the phrase “dancing is silent poetry”.
By exchanging each letter with another, we can encode this as: “robqwbu wg gwzsbh dcshfm”.
(a) Write a function that swaps the letter in a string according to a dictionary. For example:
def swapdict(string, dic):
swapped = ''
for c in string:
if c in dic:
swapped += dic[c]
else:
swapped += c
return swapped
>>> print swapdict('hello', {'e': 'i'})
hillo
>>> print swapdict('hello', {'l': 'w'})
hewwo
>>> print swapdict('hello', {'l': 'm', 'h': 'p', 'e': 'o', 'o': 'e'})
pomme
# your code here
print(swapdict('hello', {'e': 'i'}))
print(swapdict('hello', {'l': 'w'}))
print(swapdict('hello', {'l': 'm', 'h': 'p', 'e': 'o', 'o': 'e'}))
hillo hewwo pomme
(b) Write a function that generates a dictionary whose keys are letters of the alphabet, and whose values are those letters shifted along by a given number of letters.
def shiftdict(i):
import string
alphabet = string.ascii_lowercase
shiftdict = {}
for c in alphabet:
shifted = ord(c)+i
if shifted < ord('a'):
shifted = ord('z') - (ord('a') - shifted) + 1
elif shifted > ord('z'):
shifted = ord('a') + (shifted - ord('z')) - 1
shiftdict[c] = chr(shifted)
return shiftdict
shiftdict(13)
{'a': 'n', 'b': 'o', 'c': 'p', 'd': 'q', 'e': 'r', 'f': 's', 'g': 't', 'h': 'u', 'i': 'v', 'j': 'w', 'k': 'x', 'l': 'y', 'm': 'z', 'n': 'a', 'o': 'b', 'p': 'c', 'q': 'd', 'r': 'e', 's': 'f', 't': 'g', 'u': 'h', 'v': 'i', 'w': 'j', 'x': 'k', 'y': 'l', 'z': 'm'}
>>> print shiftdict(0)
{'a': 'a', 'b': 'b', ..., 'z': 'z'}
>>> print shiftdict(3)
{'a': 'd', 'b': 'e', ..., 'z': 'c'}
>>> print shiftdict(13)
{'a': 'n', 'b': 'o', ..., 'z': 'm'}
In the first case, the letters are not shifted, because the argument to shiftdict is zero. In the second case, letters are shifted along by three letters: “a” is the first letter, and “d” is the forth letter, and so key “a” points to letter “d”.
# try it here
print(shiftdict(3))
{'d': 'g', 'h': 'k', 'z': 'c', 'i': 'l', 'w': 'z', 'f': 'i', 'b': 'e', 'k': 'n', 'c': 'f', 'g': 'j', 'y': 'b', 't': 'w', 'j': 'm', 'o': 'r', 'u': 'x', 'l': 'o', 'r': 'u', 'e': 'h', 'a': 'd', 's': 'v', 'q': 't', 'x': 'a', 'n': 'q', 'p': 's', 'm': 'p', 'v': 'y'}
(c) Now we are ready to encode our message: “dancing is silent poetry”.
>>> print swapdict('dancing is silent poetry', shiftdict(14))
swapdict('dancing is silent poetry', shiftdict(14))
'robqwbu wg gwzsbh dcshfm'
(d) Write a function that takes a dictionary and swaps the roles of the keys and the values.
def invertdict(dictionary):
return dict((v, k) for k, v in dictionary.items())
Here are some examples to check it works:
>>> invertdict({'a':'b'})
{'b': 'a'}
>>> invertdict({'b':'a', 'a': 'b'})
{'a': 'b', 'b': 'a'}
>>> invertdict({'a':'b', 'b': 'c', 'c': 'a'})
{'a': 'c', 'b': 'a','c': 'b'}
print(invertdict({'a':'b'}))
print(invertdict({'b':'a', 'a': 'b'}))
print(invertdict({'a':'b', 'b': 'c', 'c': 'a'}))
{'b': 'a'} {'a': 'b', 'b': 'a'} {'a': 'c', 'b': 'a', 'c': 'b'}
(e) Can you decode this message, that was encoded using the same scheme? “qzuipo nblft ju tjnqmf ipqfgvmmz”. Use only invertdict, swapdict and shiftdict.
print(swapdict('dancing is silent poetry', shiftdict(14)))
print(swapdict('qzuipo nblft ju tjnqmf ipqfgvmmz', shiftdict(-1)))
robqwbu wg gwzsbh dcshfm python makes it simple hopefully
(f) You notice that your friend is sending encrypted messages to other people, but they appear to be encoded using a different argument to shiftdict.
Use a for-loop, swapdict and shiftdict to work out the encoding scheme, and what this message says: “nyhcpaf pz aol yvva vm spnoaulzz”.
for i in range(27):
print(swapdict('nyhcpaf pz aol yvva vm spnoaulzz', shiftdict(i)))
print("------")
print(swapdict('nyhcpaf pz aol yvva vm spnoaulzz', shiftdict(19)))
nyhcpaf pz aol yvva vm spnoaulzz ozidqbg qa bpm zwwb wn tqopbvmaa pajerch rb cqn axxc xo urpqcwnbb qbkfsdi sc dro byyd yp vsqrdxocc rclgtej td esp czze zq wtrseypdd sdmhufk ue ftq daaf ar xustfzqee tenivgl vf gur ebbg bs yvtugarff ufojwhm wg hvs fcch ct zwuvhbsgg vgpkxin xh iwt gddi du axvwicthh whqlyjo yi jxu heej ev bywxjduii xirmzkp zj kyv iffk fw czxykevjj yjsnalq ak lzw jggl gx dayzlfwkk zktobmr bl max khhm hy ebzamgxll alupcns cm nby liin iz fcabnhymm bmvqdot dn ocz mjjo ja gdbcoiznn cnwrepu eo pda nkkp kb hecdpjaoo doxsfqv fp qeb ollq lc ifdeqkbpp epytgrw gq rfc pmmr md jgefrlcqq fqzuhsx hr sgd qnns ne khfgsmdrr gravity is the root of lightness hsbwjuz jt uif sppu pg mjhiuoftt itcxkva ku vjg tqqv qh nkijvpguu judylwb lv wkh urrw ri oljkwqhvv kvezmxc mw xli vssx sj pmklxriww lwfanyd nx ymj wtty tk qnlmysjxx mxgboze oy znk xuuz ul romnztkyy nyhcpaf pz aol yvva vm spnoaulzz ------ gravity is the root of lightness