In [1]:

%matplotlib inline

Scientific Programming in Python - Dictionaries and Functions¶

Problem 1. Library, with dictionaries¶

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:

In [2]:

[[123456,312314,531337],['John Doe',' Jane Miller','Ted Johnson'],[1.49,0.00,8.12]]

Out[2]:

[[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.

In [3]:

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:

In [4]:

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.

In [5]:

idnum = studentname_to_id['John Doe']
library_data[idnum]

Out[5]:

1.49

(d) Create the list of the names of students owing more than £1.0 to the library.

In [6]:

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

Problem 2. Counting words¶

(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.

In [7]:

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:

In [8]:

# 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

In [9]:

# 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

In [10]:

# 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']

In [11]:

# 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)

resting 2
processing 1
stood 7
carrier 1
yesterday 3
f 10
believed 1
judging 1
sides 4
purple 1
morcar 2
some 52
seaside 1
suddenly 13
hanging 3
sorts 3
freely 4
disclaim 1
north 1
whistle 1
tree 5
9 3
problem 1
pitied 1
shan 6
up 100
saves 1
usual 5
use 28
tone 40
laughed 2
window 8
behead 1
wretched 2
own 10
running 8
difficult 2
likely 5
executed 6
breeze 1
ten 6
hard 8
limitation 3
crumbs 4
shedding 1
playing 2
turn 10
refund" 1
shorter 2
grass 4
give 15
rose 1
adding 1
said 462
relief 2
live 8
empty 1
speed 1
corner 4
should 29
drink 7
rich 1
brown 2
like 84
redistributing 2
eh 1
house 18
particular 6
argument 4
mustard-mine 1
burnt 1
denies 1
presented 1
canterbury 1
banks 1
hatching 1
stool 1
increasing 1
nothing 34
user 3
bitter 1
producing 1
addressing 1
night-air 1
natural 4
need 1
pinch 2
pglaf 2
concept 2
butter 3
rabbit-hole 4
feebly 1
outside 7
license 14
comfort 1
animals 4
serpent 9
distribute 6
non 1
contradicted 1
cart-horse 1
evidently 1
usually 2
uncomfortable 4
to-night 1
thoughts 2
going 27
sent 3
better 14
accept 1
changes 2
hurry 11
ashamed 2
feeling 7
licking 1
obtain 3
passing 1
bright 7
sixpence 1
footman 11
passionate 1
again 83
might 28
recognised 1
crouched 1
white 30
protection 1
destroy 2
"french 1
talk 14
frowning 4
accordance 2
preserve 1
changing 2
appear 3
letters 1
forehead 2
wider 1
straightening 1
face 15
fast 4
leaning 2
inkstand 1
bat 3
toffee 1
creation 1
pause 2
fading 1
steam-engine 1
"with 1
clamour 1
meal 1
conclusion 2
www 2
grown 7
executes 1
or 153
8 4
elect 1
daughter 1
twinkling 4
additions 1
sign 1
untwist 1
em 3
away 27
uglification 1
repeated 10
faster 3
nor 3
who 65
quite 55
chatte 1
threw 2
mostly 2
tears 11
scaly 1
matter 9
errors 1
piteous 1
fit 3
rule 5
bleeds 1
himself 6
ye 1
oyster 1
two 39
paws 4
swam 5
wings 1
necessarily 1
regular 2
curious 19
seem 8
names 2
fallen 4
unsolicited 1
hardly 12
speech 3
goose 2
fifth 1
difficulty 4
whiting 8
barrowful 2
become 5
hadn 8
strength 1
every 12
croquet-ground 3
explain 10
remained 3
sneeze 2
internal 1
eggs 5
tidy 1
remain 2
shoulder 4
eaglet 3
sir 7
cheap 1
engaged 1
absence 1
break 2
housemaid 1
goals 1
tea-party 2
evening 5
vanished 4
unwillingly 1
works 33
perhaps 17
appears 1
listened 1
she 553
eaten 1
custody 2
despite 1
hung 1
hurrying 1
broken 6
support 4
owed 1
lefthand 2
familiarly 1
- 7
"who 1
sorry 1
direct 1
try 12
pg 1
generally 7
sobbing 3
can 73
brass 1
idiotic 1
hopeless 1
indirectly 1
busy 2
injure 1
along 6
helped 1
tumbled 1
wondering 7
shrieked 1
may 27
stupidest 1
crept 1
startled 2
garden 16
room 13
my 58
applicable 3
fall 7
account 1
sounds 4
hundred 1
tortoise 3
bear 2
frying-pan 1
executions 2
middle 7
paused 1
based 2
hoping 3
proposal 1
crying 2
wrapping 1
low-spirited 1
xi 1
whoever 1
violently 4
woke 1
punished 1
grazed 1
hearing 4
thinking 11
codes 1
muchness 2
scratching 1
backs 1
dodo 13
pattering 3
1500 1
has 9
muchness" 1
produce 1
beast 1
enormous 1
memorandum 1
"plain 2
turned 16
seldom 1
water-well 1
arms 6
ring 2
shade 1
alarm 2
denied 2
possession 1
gregory 1
morsel 1
smiling 2
girl 4
dishes 2
variety 1
invited 2
globe 1
terribly 1
party 9
civil 3
approach 1
jurymen 4
specified 2
derision 1
research 2
irritated 1
noticing 1
condemn 1
brought 3
slippery 1
jogged 1
tell 32
easy 3
know 88
roared 1
whereupon 1
equipment 3
donors 1
protect 2
alive 3
4 5
dead 4
produced 2
ordering 2
joined 3
welcome 1
round 41
hall 9
edition 1
shingle 1
be" 1
saying 15
smaller 3
prizes 5
fixed 1
stay 5
reach 4
hoped 1
yourself 10
afraid 12
associated 8
rabbits 1
faintly 1
suit 3
blame 1
extremely 2
normans 1
am 16
centre 1
method 1
humbly 2
paperwork 1
laid 2
lake 1
tinkling 1
cause 5
seven 6
lobsters 7
crash 3
hated 1
curls 1
"what 3
favoured 1
breathe" 1
crowded 5
dull 3
pity 3
meanwhile 1
lad 1
dinah 14
immense 1
pictures 4
finds 1
put 31
save 1
capital 4
begun 7
collected 2
submitted 1
not 166
suppose 14
driest 1
commotion 1
ever 21
cake 3
sneezing 6
he 126
sends 1
returning 1
bank 3
ak 1
legs 3
sixteenth 1
hand 20
generations 2
proprietary 1
tipped 1
head 50
trusts 1
oneself 1
begins 4
owl 3
provided 4
lately 1
express 1
periodic 1
timid 3
shiny 1
distraction 1
prohibition 1
committed 1
truthful 1
languid 1
wine 2
wander 1
making 8
raised 2
copy 11
federal 2
measure 1
began 58
pulled 1
office 2
peering 1
curiosity 5
whom 2
skurried 1
last 33
players 4
court 18
mystery 2
ordered 4
claws 2
paw 3
zip 1
financial 1
alice 399
judge 4
peeped 3
rapped 1
spot 1
implied 2
clean 1
stigand 1
nasty 1
ceiling 1
rightly 1
onions 1
shriek 5
thin 1
honest 1
want 9
gravely 3
furrows 1
gryphon 55
manage 7
shilling 1
shared 2
indignant 1
place 9
herself 83
remembering 1
practice 1
ground 5
asleep 8
annoy 1
crawled 1
officer 1
mouth 10
frighten 1
2001 1
809 1
back 38
inclined 1
toss 1
panted 1
riddles 2
allow 4
jelly-fish 1
skirt 1
fish 4
moderate 1
unlocking 1
handed 3
locks 2
pencil 1
accustomed 1
red-hot 1
custard 1
fourteenth 1
spread 4
trembled 2
conger-eel 1
comes 2
flying 1
assistance 1
guess 3
dogs 3
creating 4
heart 2
sad 3
turning 12
character 1
pretty 1
doubled-up 1
company 1
somewhere 3
histories 1
six 2
processions 1
presents 2
distant 2
station 1
sensation 2
txt 1
laugh 1
pretexts 1
looked 45
defective 3
melancholy 6
timidly 9
lory 7
content 1
active 2
discovered 1
c 6
death 1
sea 13
nurse 3
takes 3
fix 2
remark 10
crowd 4
thick 1
"birds 1
busily 4
leave 9
telling 2
livery 3
status 4
thrown 1
seals 1
imitated 1
direction 5
land 1
staring 3
coils 1
mine 9
tomorrow 1
disagree 1
possibility 1
adoption 1
strings 1
wits 1
grey 1
minutes 11
solemn 3
trying 14
far 13
returns 1
outdated 1
accessible 1
pounds 1
copied 2
pencils 1
mind 11
delight 3
forgot 2
complying 3
vanishing 1
really 13
branches 2
day-school 1
follow 3
stiff 1
chimneys 1
trouble 6
require 1
flinging 1
trials 1
ein 1
v 1
fair 1
hint 2
uncomfortably 1
especially 1
within 6
panther 3
hedges 1
concerning 2
swallowed 1
getting 22
leaders 1
kissed 1
scream 2
audibly 1
decidedly 4
pleasing 1
soothing 1
arch 1
90 2
three-legged 2
yours 3
found 35
explanations 1
fits 1
savage 4
opportunity 9
indicating 1
neighbour 1
quickly 2
knee 5
toys 1
defect 3
wonder 18
tale 4
dreamy 1
fond 4
followed 8
tired 7
wife 1
mary 4
through 16
me 68
writhing 1
youth 6
tea-things 1
leaving 1
copies 7
behind 13
consultation 1
feelings 2
tea-time 2
fish-footman 2
doesn 16
trickling 1
ootiful 4
canvas 1
holiday 1
which 56
queer-looking 1
poky 1
reduced 1
grinning 1
phrase 4
weak 2
riper 1
turkey 1
way 55
begged 1
501 2
chance 4
"much 1
find 21
cattle 1
snappishly 1
corrupt 1
tax 6
sister 9
pieces 3
conversation 9
warning 1
child 10
warranties 3
delighted 2
created 2
lewis 1
inquisitively 1
listening 3
perform 1
patriotic 1
choke 1
coaxing 2
liable 1
dreadful 2
father 6
butterfly 1
soft 1
eats 1
since 4
suppress 1
wrote 3
sleep" 1
choked 3
receipt 2
plenty 2
"how 2
jury-men 1
gained 1
flowers 2
fat 1
ear 6
clearly 2
possibly 3
tried 19
worried 1
originator 1
positively 1
look-out 1
lost 3
you 477
terrier 1
year 2
yer 4
whispers 1
out-of-the-way 3
home 5
dropping 1
gone 13
existence 1
chains 1
educational 1
assembled 2
nile 1
pale 4
expressing 1
tis 5
long 33
pleaded 3
peeping 1
wondered 1
nay 1
abide 2
overhead 1
collection 4
choice 2
doubt 4
say 51
offer 2
interest 1
day 25
shelves 1
birds 9
ornamented 2
enjoy 1
hid 1
trademark 10
after-time 1
baked 1
incessantly 1
dreaming 1
oh 44
as 273
yawned 2
international 1
fury 3
isn 7
respectful 1
swim 5
led 4
sentence 8
forty-two 1
belt 1
rippling 1
contain 2
days 8
five 8
them 88
raising 1
first 51
frog-footman 1
saucer 1
queens 1
throw 3
yelp 1
conversations 2
limbs 1
accounting 1
jack-in-the-box 1
dodged 1
enough 18
hollow 1
howled 1
time 68
promised 1
t 218
settling 1
fanning 1
verses 4
pay 1
ink 1
taught 4
country 3
bed 1
authority 2
ferrets 2
needs 1
overcome 1
shrimp 1
wow 6
gutenberg" 5
sh 2
plates 2
draggled 1
determine 1
after 42
ridge 1
double 1
sternly 1
brushing 1
like" 1
growled 1
$1 1
mad 15
fortunately 1
somebody 7
sentenced 1
calmly 1
grave 3
intellectual 2
fluttered 1
corporation 1
wasting 2
book 7
delay 1
moment 31
twice 5
attempted 1
replied 29
mouse 43
banquet 1
poison 2
becoming 1
wild 2
saw 14
choosing 1
raw 1
performed 1
melan 1
bathing 1
calculate 1
tea-tray 1
reasons 1
wasn 11
marmalade 1
lesson 1
girls 3
cares 2
nicely 2
hoarsely 1
consequential 1
figure 3
none 4
downward 1
site 4
size 13
lay 4
vii 1
crimson 2
air 14
profit 1
bore 1
nose 8
array 1
brother 1
addresses 1
agreement 18
heard 30
shaking 3
displayed 1
vulgar 1
mean 10
5 3
doze 1
cup 2
but 175
answered 4
return 3
interpreted 1
hurt 3
closely 1
into 67
waiting 9
"will 1
dormouse 40
exclaimed 6
persons 1
appearance 1
affectionately 1
digging 4
providing 4
waste 1
oop 7
arm-in-arm 1
set 22
children 10
aloud 5
wind 2
tremulous 1
branch 1
turtles 2
rules 5
stingy 1
answer 9
classics 1
learning 2
birthday 1
comfits 2
name 11
askance 1
mouse-traps 1
we 42
friend 3
well 60
hearth 1
slate-pencil 1
purring 2
ringlets 2
email 3
soo 7
highest 1
deal 12
sun 2
"let 1
sizes 1
project 79
stockings 1
imposed 1
version 1
eating 1
explanation 4
electronically 2
cost 3
coward 1
beak 1
exists 1
minding 1
arranged 1
finding 3
charities 1
efforts 3
murdering 1
hastily 16
finished 12
english 6
dig 1
distributed 4
org/license 1
having 10
myself 7
shark 1
contempt 1
houses 1
roof 6
trial 10
unenforceability 1
sharply 4
kick 3
tea 13
distributing 7
bent 1
rope 1
revenue 1
dreamed 1
bottle 10
shook 9
poor 27
softly 1
glad 11
hurried 11
considering 3
tillie 1
whispered 5
silence 14
bringing 3
currants 1
mentioned 3
such 46
puffed 1
stalk 1
clinging 1
pinched 2
shutting 2
tremble 1
sounded 5
chimney 6
lap 2
hear 15
seems 5
to-day 3
imagine 2
pressed 3
binary 1
official 3
altogether 5
nibbling 3
righthand 1
changed 8
dog 3
murder 1
slates 8
farm-yard 1
hopeful 1
poured 1
skimming 1
cushion 2
performing 3
join 9
great 39
tureen 1
sharks 1
ledge 1
gay 1
showing 2
growing 11
entirely 2
library 1
jury 17
rise 1
milk 1
fellows 1
undo 1
altered 1
elbows 1
purpose 2
knowledge 3
dish 4
grow 13
with 225
mice 4
feared 1
accident 2
volunteers 6
water 4
angrily 9
rose-tree 3
derived 1
introduced 1
energetic 1
stopping 1
tail 9
was 358
rush 2
proper 3
feet 19
thatched 1
kneel 1
label 2
files 2
orange 1
hoarse 3
hers 4
cook 13
underneath 1
bread-and-butter 6
interesting 5
flown 1
moral 8
do 98
prisoner 2
lizard 6
lower 1
w 1
play 8
doorway 1
certain 5
director 1
frog 2
agree 11
stays 1
learn 8
comfortably 1
axes 1
prettier 1
literary 13
shrieks 1
chuckled 1
morals 1
died 1
therefore 1
odd 1
witness 10
curtsey 1
beau 4
low 14
lessons 10
loving 1
calling 1
humble 1
entangled 2
happening 1
stolen 1
help 12
vegetable 1
accepted 2
besides 4
encouraging 2
whether 11
splashing 2
"uglification 1
original 1
transcribe 1
ascii" 2
crawling 1
sang 2
brush 1
triumphantly 2
whiles 1
week 3
choose 1
quicker 1
corners 1
obsolete 1
cats 13
renamed 1
beat 4
accessed 1
prize 1
indirect 1
sand 1
glaring 1
verse 4
printed 3
magpie 1
short 4
mock 56
crossed 3
occurred 2
request 1
argued 1
balls 1
goes 7
twinkled 1
courage 3
trumpet 3
history 7
shall 27
guessed 3
fanned 1
liability 3
couldn 9
tie 1
given 2
thousand 2
picking 2
stole 2
deny 2
golden 7
"purpose" 1
pig 8
heavy 2
solid 1
sighing 3
salt 3
cards 3
cry 3
directly 3
pleasant 1
immediately 3
execute 1
deep 7
reaching 2
repeating 3
ridiculous 1
actual 1
void 1
damages 4
reminding 1
work 53
desperately 1
cucumber-frames 1
uniform 1
wink 2
org/donate 1
its 63
squeaked 1
spoke 17
smile 2
representations 1
gardeners 8
growl 3
bring 3
wash 2
longer 3
others 8
good-bye 1
sulkily 2
sing 6
mark 3
thanked 1
$5 1
except 7
roast 1
opened 10
under 21
7 3
about 102
quick 2
no 98
ending 1
life 12
carried 4
disappeared 2
each 9
subscribe 1
michael 2
giddy 2
roses 3
remove 1
"project 5
smoke 1
provisions 1
mournfully 1
books 1
united 10
gross 1
common 1
kindly 2
explained 1
sweet-tempered 1
tossing 3
howling 3
whenever 2
clapping 1
locations 2
completely 1
thunder 1
taller 2
shock 1
asked 17
doing 5
share 2
opposite 1
throne 1
bound 3
pleasure 2
"such 1
patiently 2
advantage 3
includes 1
lessen 1
promoting 2
leap 1
invent 1
tight 1
as-is 1
pat 3
idiot 1
pegs 1
spreading 1
upset 3
before 39
else 11
impossible 3
saucepan 1
service 1
whisper 3
right-hand 1
permission 7
brandy 1
dream 7
"before 1
hair 7
using 6
advisable 2
whistling 1
mushroom 8
for 178
experiment 2
standing 1
played 1
seated 1
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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”?

In [12]:

print(histogram_single["the"])

(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.

In [13]:

# 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.

In [14]:

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', 'to') 5
('one', 'side') 5
('to', 'put') 5
('to', 'leave') 5
('to', 'eat') 5
('which', 'she') 5
('said', 'i') 5
('that', 'makes') 5
('on', 'one') 5
('in', 'fact') 5
('gloves', 'and') 5
('put', 'on') 5
('as', 'much') 5
('only', 'a') 5
('down', 'at') 5
('as', 'to') 5
('work', 'is') 5
('to', 'hear') 5
('first', 'she') 5
('thought', 'to') 5
('i', 'only') 5
('information', 'about') 5
('me', 'said') 5
('too', 'much') 5
('trembling', 'voice') 5
('made', 'out') 5
('herself', 'as') 5
('should', 'think') 5
('heard', 'a') 5
('such', 'as') 5
('or', 'a') 5
('t', 'believe') 5
('she', 'remembered') 5
('to', 'listen') 5
('go', 'and') 5
('be', 'said') 5
('that', 'alice') 5
('thought', 'she') 5
('of', 'things') 5
('made', 'her') 5
('then', 'i') 5
('all', 'i') 5
('know', 'i') 5
('and', 'you') 5
('donations', 'to') 5
('can', 'be') 5
('down', 'to') 5
('distribution', 'of') 5
('rest', 'of') 5
('"project', 'gutenberg"') 5
('would', 'have') 5
('was', 'an') 5
('sure', 'i') 5
('i', 'to') 5
('not', 'at') 5
('another', 'moment') 5
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('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.

In [15]:

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
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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
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exclamation 1
oldest 1
geography 1
fairly 1
fireplace 1
pressing 1
named 1
gravy 1
opportunities 1
hm 1
dainties 1
squeeze 1
steady 1
fork 1
manners 1
understood 1
sheep-bells 1
lark 1
blades 1
possessed 1
thirty 1
signify 1
performances 1
ravens 1
display 1
viii 1
good-naturedly 1
feather 1
unable 1
conduct 1
iv 1
arguments 1
20% 1
licensed 1
organized 1
blows 1
dressed 1
punitive 1
rats 1
farmer 1
swallow 1
viewed 1
collar 1
rustling 1
noises 1
beloved 1
refreshments 1
rises 1
"edwin 1
eleventh 1
deserved 1
plainly 1
sage 1
quiver 1
lullaby 1
offers 1
teeth 1
flew 1
arrow 1
magic 1
encouraged 1
fifteen 1
punching 1
nest 1
curtain 1
couple 1
grief 1
flame 1
win 1
include 1
someone 1
lest 1
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modified 1
machines 1
circle 1
invented 1
kings 1
hot-tempered 1
cunning 1
dripping 1
arithmetic 1
conquest 1
required 1
affair 1
scale 1
helpless 1
cheerfully 1
advise 1
reports 1
supple 1
arrum 1
"turtle 1
boon 1
irs 1
swallowing 1
weeks 1
bother 1
cold 1
pig-baby 1
f3 1
flock 1
burning 1
ut 1
"they 1
curtseying 1
principal 1
belong 1
snout 1
squeezed 1
esq 1
good-natured 1
survive 1
modification 1
prove 1
educations 1
worry 1
tulip-roots 1
maps 1
guilt 1
die 1
profits 1
"too 1
ix 1
flung 1
vinegar 1
special 1
pointed 1
facility 1
eat" 1
merrily 1
turn-up 1
edwin 1
data 1
business@pglaf 1
gbnewby@pglaf 1
parts 1
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buttons 1
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scattered 1
teapot 1
lastly 1
ahem 1
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uncommonly 1
bee 1
knocked 1
opinion 1
frontispiece 1
theirs 1
forepaws 1
org/fundraising 1
flappers 1
capering 1
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camomile 1
inwards 1
boxed 1
knelt 1
ful 1
suet 1
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newspapers 1
farther 1
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son 1
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setting 1
fourth 1
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variations 1
croqueted 1
retire 1
city 1
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fills 1
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laughter 1
lazily 1
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hypertext 1
kiss 1
fidgeted 1
puss 1
maintaining 1
production 1
4557 1
chrysalis 1
happy 1
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book-shelves 1
splash 1
"never 1
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vote 1
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adjourn 1
dozing 1
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pour 1
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expend 1
waters 1
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extras 1
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provision 1
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creep 1
graceful 1
comfortable 1
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occasionally 1
heap 1
deletions 1
types 1
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fighting 1
disk 1
chop 1
uncommon 1
act 1
acceptance 1
wearily 1
journey 1
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ridges 1
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toast 1
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beds 1
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actually 1
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cur 1
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"take 1
child-life 1
countries 1
haste 1
arise 1
hat 1
oblong 1
hjckrrh 1
spite 1
e-mail 1
tougher 1
salmon 1
pink 1
guard 1
difficulties 1
able 1
somehow 1
failure 1
pence 1
lesson-book 1
trademark/copyright 1
muddle 1
milk-jug 1
mournful 1
west 1
drawing 1
engraved 1
heels 1
lowing 1
attempts 1
beauti 1
complained 1
"keep 1
wait 1
org/1/11/ 1
lacie 1
diamonds 1
arrived 1
mayn 1
respect 1
specific 1
indemnity 1
promise 1
agent 1
edgar 1
accidentally 1
eels 1
family 1
encourage 1
dive 1
sticks 1
shepherd 1
justice 1
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sprawling 1
carroll 1
closer 1
simpleton 1
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"twinkle 1
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eyelids 1
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violence 1
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answers 1
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shakespeare 1
treat 1
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pine-apple 1
shillings 1
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wags 1
attempt 1
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pepper-box 1
despair 1
rattle 1
locked 1
splendidly 1
teases 1
clearer 1
occasional 1
growls 1
ii 1
roughly 1
arm-chair 1
credit 1
volunteer 1
circumstances 1
lock 1

Problem 4. ArgMax and ArgSort¶

(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

In [16]:

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

In [17]:

# try it here
list1 = [1,3,2,6,0,2,3,4,5]
print(argmin(list1))

(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.

In [18]:

l = [1,3,2,6,0,2,3,4,5]
list(zip(*sorted(zip(l, range(len(l))))))[1]

Out[18]:

(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:

In [19]:

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]

In [20]:

# 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]

Problem 5. Simple ciphers¶

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:

In [21]:

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

In [22]:

# 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.

In [23]:

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)

Out[23]:

{'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”.

In [24]:

# 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))

In [25]:

swapdict('dancing is silent poetry', shiftdict(14))

Out[25]:

'robqwbu wg gwzsbh dcshfm'

(d) Write a function that takes a dictionary and swaps the roles of the keys and the values.

In [26]:

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'}

In [27]:

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.

In [28]:

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”.

In [29]:

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

In [ ]: