In [1]:

    

import graphlab


    

In [2]:

    

people = graphlab.SFrame('people_wiki.gl/')


    

    




[INFO] This non-commercial license of GraphLab Create is assigned to satishkt@gmail.comand will expire on September 24, 2016. For commercial licensing options, visit https://dato.com/buy/.

[INFO] Start server at: ipc:///tmp/graphlab_server-22356 - Server binary: /Users/Satish/.graphlab/anaconda/lib/python2.7/site-packages/graphlab/unity_server - Server log: /tmp/graphlab_server_1444964071.log
[INFO] GraphLab Server Version: 1.6.1

In [3]:

    

people.head()


    

    
Out[3]:





    

        
URI
        
name
        
text
    
    

        
<http://dbpedia.org/resou
rce/Digby_Morrell> ...
        
Digby Morrell
        
digby morrell born 10
october 1979 is a former ...
    
    

        
<http://dbpedia.org/resou
rce/Alfred_J._Lewy> ...
        
Alfred J. Lewy
        
alfred j lewy aka sandy
lewy graduated from ...
    
    

        
<http://dbpedia.org/resou
rce/Harpdog_Brown> ...
        
Harpdog Brown
        
harpdog brown is a singer
and harmonica player who ...
    
    

        
<http://dbpedia.org/resou
rce/Franz_Rottensteiner> ...
        
Franz Rottensteiner
        
franz rottensteiner born
in waidmannsfeld lower ...
    
    

        
<http://dbpedia.org/resou
rce/G-Enka> ...
        
G-Enka
        
henry krvits born 30
december 1974 in tallinn ...
    
    

        
<http://dbpedia.org/resou
rce/Sam_Henderson> ...
        
Sam Henderson
        
sam henderson born
october 18 1969 is an ...
    
    

        
<http://dbpedia.org/resou
rce/Aaron_LaCrate> ...
        
Aaron LaCrate
        
aaron lacrate is an
american music producer ...
    
    

        
<http://dbpedia.org/resou
rce/Trevor_Ferguson> ...
        
Trevor Ferguson
        
trevor ferguson aka john
farrow born 11 november ...
    
    

        
<http://dbpedia.org/resou
rce/Grant_Nelson> ...
        
Grant Nelson
        
grant nelson born 27
april 1971 in london  ...
    
    

        
<http://dbpedia.org/resou
rce/Cathy_Caruth> ...
        
Cathy Caruth
        
cathy caruth born 1955 is
frank h t rhodes ...
    

[10 rows x 3 columns]

In [4]:

    

len(people)


    

    
Out[4]:





59071

In [5]:

    

obama = people[people['name'] == 'Barack Obama']


    

In [6]:

    

obama


    

    
Out[6]:





    

        
URI
        
name
        
text
    
    

        
<http://dbpedia.org/resou
rce/Barack_Obama> ...
        
Barack Obama
        
barack hussein obama ii
brk husen bm born august ...
    

[? rows x 3 columns]
Note: Only the head of the SFrame is printed. This SFrame is lazily evaluated.
You can use len(sf) to force materialization.

In [7]:

    

obama['text']


    

    
Out[7]:





dtype: str
Rows: ?
['barack hussein obama ii brk husen bm born august 4 1961 is the 44th and current president of the united states and the first african american to hold the office born in honolulu hawaii obama is a graduate of columbia university and harvard law school where he served as president of the harvard law review he was a community organizer in chicago before earning his law degree he worked as a civil rights attorney and taught constitutional law at the university of chicago law school from 1992 to 2004 he served three terms representing the 13th district in the illinois senate from 1997 to 2004 running unsuccessfully for the united states house of representatives in 2000in 2004 obama received national attention during his campaign to represent illinois in the united states senate with his victory in the march democratic party primary his keynote address at the democratic national convention in july and his election to the senate in november he began his presidential campaign in 2007 and after a close primary campaign against hillary rodham clinton in 2008 he won sufficient delegates in the democratic party primaries to receive the presidential nomination he then defeated republican nominee john mccain in the general election and was inaugurated as president on january 20 2009 nine months after his election obama was named the 2009 nobel peace prize laureateduring his first two years in office obama signed into law economic stimulus legislation in response to the great recession in the form of the american recovery and reinvestment act of 2009 and the tax relief unemployment insurance reauthorization and job creation act of 2010 other major domestic initiatives in his first term included the patient protection and affordable care act often referred to as obamacare the doddfrank wall street reform and consumer protection act and the dont ask dont tell repeal act of 2010 in foreign policy obama ended us military involvement in the iraq war increased us troop levels in afghanistan signed the new start arms control treaty with russia ordered us military involvement in libya and ordered the military operation that resulted in the death of osama bin laden in january 2011 the republicans regained control of the house of representatives as the democratic party lost a total of 63 seats and after a lengthy debate over federal spending and whether or not to raise the nations debt limit obama signed the budget control act of 2011 and the american taxpayer relief act of 2012obama was reelected president in november 2012 defeating republican nominee mitt romney and was sworn in for a second term on january 20 2013 during his second term obama has promoted domestic policies related to gun control in response to the sandy hook elementary school shooting and has called for full equality for lgbt americans while his administration has filed briefs which urged the supreme court to strike down the defense of marriage act of 1996 and californias proposition 8 as unconstitutional in foreign policy obama ordered us military involvement in iraq in response to gains made by the islamic state in iraq after the 2011 withdrawal from iraq continued the process of ending us combat operations in afghanistan and has sought to normalize us relations with cuba', ... ]

In [8]:

    

clooney = people[people['name'] == 'George Clooney']
clooney['text']


    

    
Out[8]:





dtype: str
Rows: ?
['george timothy clooney born may 6 1961 is an american actor writer producer director and activist he has received three golden globe awards for his work as an actor and two academy awards one for acting and the other for producingclooney made his acting debut on television in 1978 and later gained wide recognition in his role as dr doug ross on the longrunning medical drama er from 1994 to 1999 for which he received two emmy award nominations while working on er he began attracting a variety of leading roles in films including the superhero film batman robin 1997 and the crime comedy out of sight 1998 in which he first worked with a director who would become a longtime collaborator steven soderbergh in 1999 clooney took the lead role in three kings a wellreceived war satire set during the gulf warin 2001 clooneys fame widened with the release of his biggest commercial success the heist comedy oceans eleven the first of the film trilogy a remake of the 1960 film with frank sinatra as danny ocean he made his directorial debut a year later with the biographical thriller confessions of a dangerous mind and has since directed the drama good night and good luck 2005 the sports comedy leatherheads 2008 the political drama the ides of march 2011 and the comedydrama war film the monuments men 2014he won an academy award for best supporting actor for the middle east thriller syriana 2005 and subsequently earned best actor nominations for the legal thriller michael clayton 2007 the comedydrama up in the air 2009 and the drama the descendants 2011 in 2013 he received the academy award for best picture for producing the political thriller argo alongside ben affleck and grant heslov he is the only person ever to be nominated for academy awards in six categoriesclooney is sometimes described as one of the most handsome men in the world in 2005 tv guide ranked clooney no 1 on its 50 sexiest stars of all time list in 2009 he was included in times annual time 100 as one of the most influential people in the world clooney is also noted for his political activism and has served as one of the united nations messengers of peace since january 31 2008 his humanitarian work includes his advocacy of finding a resolution for the darfur conflict raising funds for the 2010 haiti earthquake 2004 tsunami and 911 victims and creating documentaries such as sand and sorrow to raise awareness about international crises he is also a member of the council on foreign relations', ... ]

In [9]:

    

obama['word_count'] = graphlab.text_analytics.count_words(obama['text'])


    

In [10]:

    

print obama['word_count']


    

    




[{'operations': 1, 'represent': 1, 'office': 2, 'unemployment': 1, 'is': 2, 'doddfrank': 1, 'over': 1, 'unconstitutional': 1, 'domestic': 2, 'named': 1, 'ending': 1, 'ended': 1, 'proposition': 1, 'seats': 1, 'graduate': 1, 'worked': 1, 'before': 1, 'death': 1, '20': 2, 'taxpayer': 1, 'inaugurated': 1, 'obamacare': 1, 'civil': 1, 'mccain': 1, 'to': 14, '4': 1, 'policy': 2, '8': 1, 'has': 4, '2011': 3, '2010': 2, '2013': 1, '2012': 1, 'bin': 1, 'then': 1, 'his': 11, 'march': 1, 'gains': 1, 'cuba': 1, 'californias': 1, '1992': 1, 'new': 1, 'not': 1, 'during': 2, 'years': 1, 'continued': 1, 'presidential': 2, 'husen': 1, 'osama': 1, 'term': 3, 'equality': 1, 'prize': 1, 'lost': 1, 'stimulus': 1, 'january': 3, 'university': 2, 'rights': 1, 'gun': 1, 'republican': 2, 'rodham': 1, 'troop': 1, 'withdrawal': 1, 'involvement': 3, 'response': 3, 'where': 1, 'referred': 1, 'affordable': 1, 'attorney': 1, 'school': 3, 'senate': 3, 'house': 2, 'national': 2, 'creation': 1, 'related': 1, 'hawaii': 1, 'born': 2, 'second': 2, 'street': 1, 'election': 3, 'close': 1, 'operation': 1, 'insurance': 1, 'sandy': 1, 'afghanistan': 2, 'initiatives': 1, 'for': 4, 'reform': 1, 'federal': 1, 'review': 1, 'representatives': 2, 'debate': 1, 'current': 1, 'state': 1, 'won': 1, 'marriage': 1, 'victory': 1, 'unsuccessfully': 1, 'reauthorization': 1, 'keynote': 1, 'full': 1, 'patient': 1, 'august': 1, 'degree': 1, '44th': 1, 'bm': 1, 'mitt': 1, 'attention': 1, 'delegates': 1, 'lgbt': 1, 'job': 1, 'protection': 2, 'address': 1, 'ask': 1, 'november': 2, 'debt': 1, 'by': 1, 'care': 1, 'on': 2, 'great': 1, 'defense': 1, 'signed': 3, 'libya': 1, 'receive': 1, 'of': 18, 'months': 1, 'against': 1, 'foreign': 2, 'spending': 1, 'american': 3, 'harvard': 2, 'act': 8, 'military': 4, 'hussein': 1, 'or': 1, 'first': 3, 'and': 21, 'major': 1, 'clinton': 1, '1997': 1, 'campaign': 3, 'russia': 1, 'wall': 1, 'legislation': 1, 'into': 1, 'primary': 2, 'community': 1, 'three': 1, 'down': 1, 'hook': 1, 'ii': 1, '63': 1, 'americans': 1, 'elementary': 1, 'total': 1, 'earning': 1, 'often': 1, 'barack': 1, 'law': 6, 'from': 3, 'raise': 1, 'district': 1, 'representing': 1, 'nine': 1, 'reinvestment': 1, 'arms': 1, 'relations': 1, 'nobel': 1, 'start': 1, 'dont': 2, 'tell': 1, 'iraq': 4, 'convention': 1, 'strike': 1, 'served': 2, 'john': 1, 'was': 5, 'war': 1, 'form': 1, 'that': 1, 'tax': 1, 'sufficient': 1, 'republicans': 1, 'resulted': 1, 'hillary': 1, 'taught': 1, 'honolulu': 1, 'filed': 1, 'regained': 1, 'july': 1, 'hold': 1, 'with': 3, 'he': 7, '13th': 1, 'made': 1, 'brk': 1, '1996': 1, 'whether': 1, 'reelected': 1, 'budget': 1, 'us': 6, 'nations': 1, 'recession': 1, 'while': 1, 'economic': 1, 'limit': 1, 'policies': 1, 'promoted': 1, 'called': 1, 'at': 2, 'control': 4, 'supreme': 1, 'ordered': 3, 'nominee': 2, 'process': 1, '2000in': 1, '2012obama': 1, 'received': 1, 'romney': 1, 'briefs': 1, 'defeated': 1, 'general': 1, 'states': 3, 'as': 6, 'urged': 1, 'in': 30, 'sought': 1, 'organizer': 1, 'shooting': 1, 'increased': 1, 'normalize': 1, 'lengthy': 1, 'united': 3, 'court': 1, 'recovery': 1, 'laden': 1, 'laureateduring': 1, 'peace': 1, 'administration': 1, '1961': 1, 'illinois': 2, 'other': 1, 'which': 1, 'party': 3, 'primaries': 1, 'sworn': 1, '2007': 1, 'obama': 9, 'columbia': 1, 'combat': 1, 'after': 4, 'islamic': 1, 'running': 1, 'levels': 1, 'two': 1, 'included': 1, 'president': 4, 'repeal': 1, 'nomination': 1, 'the': 40, 'a': 7, '2009': 3, 'chicago': 2, 'constitutional': 1, 'defeating': 1, 'treaty': 1, 'relief': 2, '2004': 3, 'african': 1, '2008': 1, 'democratic': 4, 'consumer': 1, 'began': 1, 'terms': 1}]

In [11]:

    

obama_word_count_table = obama[['word_count']].stack('word_count', new_column_name = ['word','count'])


    

In [12]:

    

obama_word_count_table.head()


    

    
Out[12]:





    

        
word
        
count
    
    

        
cuba
        
1
    
    

        
relations
        
1
    
    

        
sought
        
1
    
    

        
combat
        
1
    
    

        
ending
        
1
    
    

        
withdrawal
        
1
    
    

        
state
        
1
    
    

        
islamic
        
1
    
    

        
by
        
1
    
    

        
gains
        
1
    

[10 rows x 2 columns]

In [13]:

    

obama_word_count_table.sort('count',ascending=False)


    

    
Out[13]:





    

        
word
        
count
    
    

        
the
        
40
    
    

        
in
        
30
    
    

        
and
        
21
    
    

        
of
        
18
    
    

        
to
        
14
    
    

        
his
        
11
    
    

        
obama
        
9
    
    

        
act
        
8
    
    

        
he
        
7
    
    

        
a
        
7
    

[273 rows x 2 columns]
Note: Only the head of the SFrame is printed.
You can use print_rows(num_rows=m, num_columns=n) to print more rows and columns.

In [17]:

    

people['word_count'] = graphlab.text_analytics.count_words(people['text'])
people.head()


    

    
Out[17]:





    

        
URI
        
name
        
text
        
word_count
    
    

        
<http://dbpedia.org/resou
rce/Digby_Morrell> ...
        
Digby Morrell
        
digby morrell born 10
october 1979 is a former ...
        
{'selection': 1,
'carltons': 1, 'being': ...
    
    

        
<http://dbpedia.org/resou
rce/Alfred_J._Lewy> ...
        
Alfred J. Lewy
        
alfred j lewy aka sandy
lewy graduated from ...
        
{'precise': 1, 'thomas':
1, 'closely': 1, ...
    
    

        
<http://dbpedia.org/resou
rce/Harpdog_Brown> ...
        
Harpdog Brown
        
harpdog brown is a singer
and harmonica player who ...
        
{'just': 1, 'issued': 1,
'mainly': 1, 'nominat ...
    
    

        
<http://dbpedia.org/resou
rce/Franz_Rottensteiner> ...
        
Franz Rottensteiner
        
franz rottensteiner born
in waidmannsfeld lower ...
        
{'all': 1,
'bauforschung': 1, ...
    
    

        
<http://dbpedia.org/resou
rce/G-Enka> ...
        
G-Enka
        
henry krvits born 30
december 1974 in tallinn ...
        
{'they': 1,
'gangstergenka': 1, ...
    
    

        
<http://dbpedia.org/resou
rce/Sam_Henderson> ...
        
Sam Henderson
        
sam henderson born
october 18 1969 is an ...
        
{'currently': 1, 'less':
1, 'being': 1, ...
    
    

        
<http://dbpedia.org/resou
rce/Aaron_LaCrate> ...
        
Aaron LaCrate
        
aaron lacrate is an
american music producer ...
        
{'exclusive': 2,
'producer': 1, 'show' ...
    
    

        
<http://dbpedia.org/resou
rce/Trevor_Ferguson> ...
        
Trevor Ferguson
        
trevor ferguson aka john
farrow born 11 november ...
        
{'taxi': 1, 'salon': 1,
'gangs': 1, 'being': 1, ...
    
    

        
<http://dbpedia.org/resou
rce/Grant_Nelson> ...
        
Grant Nelson
        
grant nelson born 27
april 1971 in london  ...
        
{'houston': 1, 'frankie':
1, 'labels': 1, ...
    
    

        
<http://dbpedia.org/resou
rce/Cathy_Caruth> ...
        
Cathy Caruth
        
cathy caruth born 1955 is
frank h t rhodes ...
        
{'phenomenon': 1,
'deborash': 1, 'both' ...
    


    

        
tfidf
    
    

        
{'selection':
3.836578553093086, ...
    
    

        
{'precise':
6.44320060695519, ...
    
    

        
{'just':
2.7007299687108643, ...
    
    

        
{'all':
1.6431112434912472, ...
    
    

        
{'they':
1.8993401178193898, ...
    
    

        
{'currently':
1.637088969126014, ...
    
    

        
{'exclusive':
10.455187230695827, ...
    
    

        
{'taxi':
6.0520214560945025, ...
    
    

        
{'houston':
3.935505942157149, ...
    
    

        
{'phenomenon':
5.750053426395245, ...
    

[10 rows x 5 columns]

In [20]:

    

tfidf = graphlab.text_analytics.tf_idf(people['word_count'])
tfidf[0]


    

    
Out[20]:





{'docs': {'10': 2.3157231098806563,
  '1979': 2.6032908378122737,
  '19982000': 6.509158574746988,
  '2000': 1.8763068991994527,
  '2001': 1.9280249665871378,
  '2002': 1.8753125887822302,
  '2003': 1.8013702663900752,
  '2005': 1.6425861253275964,
  '2006': 1.520737905384506,
  '2007': 1.4879730697555795,
  '2008': 1.5093391374786154,
  '2009': 1.5644364836042695,
  '2011': 1.7023470901042916,
  '2013': 1.9545642372230505,
  '2014': 2.2073995783446634,
  '21': 2.797250863489293,
  '32': 4.3717697890214335,
  '44game': 9.887883100557085,
  'a': 0.022476737890332586,
  'acted': 4.137429106591736,
  'afl': 4.70049729471633,
  'aflfrom': 10.986495389225194,
  'against': 4.015921958283749,
  'age': 2.138848033513307,
  'along': 2.5088749729287803,
  'also': 0.4627270916162349,
  'and': 0.002980575592194913,
  'as': 0.2543390440248236,
  'assistant': 2.5220702633476124,
  'at': 0.8612771466165147,
  'australia': 2.86858644684204,
  'australian': 8.630007339620153,
  'before': 2.9935647453367427,
  'being': 1.7938099524877322,
  'blues': 4.064837205074066,
  'born': 0.268196273764765,
  'box': 4.576320507259028,
  'brisbaneafter': 10.986495389225194,
  'bullants': 7.489987827758714,
  'by': 0.37455341206197373,
  'career': 1.3050270203415668,
  'carlton': 10.682096983163913,
  'carltons': 7.0744723837970485,
  'cause': 4.8023464982877115,
  'club': 11.043158373020127,
  'clubs': 3.4464050690798693,
  'coach': 5.444264118987054,
  'coached': 3.9925624140020046,
  'coburg': 7.851001173296044,
  'college': 1.5613662703175555,
  'continued': 2.720588055069447,
  'corey': 6.486685718894929,
  'currently': 1.637088969126014,
  'david': 2.4512658353228582,
  'delisted': 5.816011394187043,
  'digby': 8.347438059609935,
  'district': 2.774469584601757,
  'division': 2.7906099979103978,
  'draft': 3.240194726993755,
  'drawn': 4.96062941539988,
  'during': 1.3174651479035495,
  'early': 1.929422753652229,
  'edflhe': 10.986495389225194,
  'education': 2.4487155642005685,
  'end': 4.839120211828286,
  'essendon': 6.016682089649193,
  'exchange': 4.113331555012676,
  'falcons': 5.868501576808439,
  'first': 0.6956048713993103,
  'five': 2.2137301792754096,
  'following': 1.9609195556941061,
  'football': 25.58570665567139,
  'footballer': 3.2388985505323085,
  'for': 0.29145011737314763,
  'former': 1.3573131120992086,
  'forward': 3.8848194176057507,
  'from': 0.5875106759712689,
  'game': 2.4168995190159084,
  'games': 2.2331239682242914,
  'goalkicker': 6.859361004180102,
  'goals': 3.4581636225179473,
  'has': 0.428497539744039,
  'hawks': 5.531174273867493,
  'he': 1.280211345952344,
  'hill': 3.794313330511949,
  'his': 0.7878343656409719,
  'in': 0.01255028255157884,
  'is': 0.02761625047551999,
  'its': 1.6875948402695313,
  'kangaroos': 20.726873835958425,
  'kicked': 5.142950972193835,
  'leading': 5.061504320250359,
  'league': 8.342695137239867,
  'losing': 3.773463729390325,
  'mckernan': 9.600201028105303,
  'melbourne': 3.8914310119380633,
  'morrell': 46.88528738395547,
  'northern': 3.310021742836038,
  'october': 1.9182947844101343,
  'of': 0.016624704796446097,
  'other': 1.4424007566948476,
  'parade': 5.510031837293684,
  'perth': 5.051601193605607,
  'physical': 4.001779069106929,
  'play': 2.270287418073342,
  'played': 4.636320601315451,
  'playing': 4.182005515547123,
  'premier': 3.6766139034004075,
  'premiership': 4.5439552227569955,
  'recruited': 4.4897203990393315,
  'retiring': 3.8140708121003493,
  'rookie': 4.104057918227347,
  'round': 2.897933583948961,
  'rules': 3.8272034844276295,
  'season': 5.6626008156972025,
  'selection': 3.836578553093086,
  'senior': 6.897159666747814,
  'shifted': 5.634637255749128,
  'since': 1.455376717308041,
  'spanned': 5.531174273867493,
  'strathmore': 8.588600116426823,
  'sydney': 3.5981675296480873,
  'teaches': 3.7712554104950966,
  'teague': 9.04058524016988,
  'the': 0.0027426017494956603,
  'third': 2.3506306680914584,
  'time': 1.3253342074200498,
  'to': 0.23472468840899613,
  'traded': 3.952107459309691,
  'twice': 3.3301582227950113,
  'until': 1.7591012626831841,
  'vfl': 5.253154112327449,
  'vflaffiliate': 7.431147327735781,
  'victorian': 4.564873121418676,
  'was': 0.3968289280609173,
  'west': 5.205210090246754,
  'western': 3.0880842964135953,
  'who': 0.9098952189804214,
  'with': 1.0123432126103034}}

In [21]:

    

people['tfidf'] = tfidf['docs']


    

In [22]:

    

obama = people[people['name'] == 'Barack Obama']


    

In [23]:

    

obama[['tfidf']].stack('tfidf',new_column_name=['word','tfidf']).sort('tfidf',ascending=False)


    

    
Out[23]:





    

        
word
        
tfidf
    
    

        
obama
        
43.2956530721
    
    

        
act
        
27.678222623
    
    

        
iraq
        
17.747378588
    
    

        
control
        
14.8870608452
    
    

        
law
        
14.7229357618
    
    

        
ordered
        
14.5333739509
    
    

        
military
        
13.1159327785
    
    

        
involvement
        
12.7843852412
    
    

        
response
        
12.7843852412
    
    

        
democratic
        
12.4106886973
    

[273 rows x 2 columns]
Note: Only the head of the SFrame is printed.
You can use print_rows(num_rows=m, num_columns=n) to print more rows and columns.

In [24]:

    

clinton = people[people['name'] == 'Bill Clinton']


    

In [25]:

    

beckham = people[people['name'] == 'David Beckham']


    

In [26]:

    

graphlab.distances.cosine(obama['tfidf'][0],clinton['tfidf'][0])


    

    
Out[26]:





0.8339854936884277

In [27]:

    

graphlab.distances.cosine(obama['tfidf'][0],beckham['tfidf'][0])


    

    
Out[27]:





0.9791305844747478

In [28]:

    

knn_model = graphlab.nearest_neighbors.create(people,features=['tfidf'],label='name')


    

    




PROGRESS: Starting brute force nearest neighbors model training.

In [29]:

    

knn_model.query(obama)


    

    




PROGRESS: Starting pairwise querying.
PROGRESS: +--------------+---------+-------------+--------------+
PROGRESS: | Query points | # Pairs | % Complete. | Elapsed Time |
PROGRESS: +--------------+---------+-------------+--------------+
PROGRESS: | 0            | 1       | 0.00169288  | 22.978ms     |
PROGRESS: | Done         |         | 100         | 498.922ms    |
PROGRESS: +--------------+---------+-------------+--------------+






    
Out[29]:





    

        
query_label
        
reference_label
        
distance
        
rank
    
    

        
0
        
Barack Obama
        
0.0
        
1
    
    

        
0
        
Joe Biden
        
0.794117647059
        
2
    
    

        
0
        
Joe Lieberman
        
0.794685990338
        
3
    
    

        
0
        
Kelly Ayotte
        
0.811989100817
        
4
    
    

        
0
        
Bill Clinton
        
0.813852813853
        
5
    

[5 rows x 4 columns]

In [28]:

    

swift = people[people['name'] == 'Taylor Swift']


    

In [29]:

    

knn_model.query(swift)


    

    




PROGRESS: Starting pairwise querying...
PROGRESS: +--------------+---------+-------------+--------------+
PROGRESS: | Query points | # Pairs | % Complete. | Elapsed Time |
PROGRESS: +--------------+---------+-------------+--------------+
PROGRESS: | 0            | 1       | 0.00169288  | 17.804ms     |
PROGRESS: | Done         |         | 100         | 135.698ms    |
PROGRESS: +--------------+---------+-------------+--------------+






    
Out[29]:





    

        
query_label
        
reference_label
        
distance
        
rank
    
    

        
0
        
Taylor Swift
        
0.0
        
1
    
    

        
0
        
Carrie Underwood
        
0.76231884058
        
2
    
    

        
0
        
Alicia Keys
        
0.764705882353
        
3
    
    

        
0
        
Jordin Sparks
        
0.769633507853
        
4
    
    

        
0
        
Leona Lewis
        
0.776119402985
        
5
    

[5 rows x 4 columns]

In [30]:

    

jolie = people[people['name'] == 'Angelina Jolie']


    

In [31]:

    

knn_model.query(jolie)


    

    




PROGRESS: Starting pairwise querying.
PROGRESS: +--------------+---------+-------------+--------------+
PROGRESS: | Query points | # Pairs | % Complete. | Elapsed Time |
PROGRESS: +--------------+---------+-------------+--------------+
PROGRESS: | 0            | 1       | 0.00169288  | 20.841ms     |
PROGRESS: | Done         |         | 100         | 447.341ms    |
PROGRESS: +--------------+---------+-------------+--------------+






    
Out[31]:





    

        
query_label
        
reference_label
        
distance
        
rank
    
    

        
0
        
Angelina Jolie
        
0.0
        
1
    
    

        
0
        
Brad Pitt
        
0.784023668639
        
2
    
    

        
0
        
Julianne Moore
        
0.795857988166
        
3
    
    

        
0
        
Billy Bob Thornton
        
0.803069053708
        
4
    
    

        
0
        
George Clooney
        
0.8046875
        
5
    

[5 rows x 4 columns]

In [32]:

    

arnold = people[people['name'] == 'Arnold Schwarzenegger']


    

In [33]:

    

knn_model.query(arnold)


    

    




PROGRESS: Starting pairwise querying.
PROGRESS: +--------------+---------+-------------+--------------+
PROGRESS: | Query points | # Pairs | % Complete. | Elapsed Time |
PROGRESS: +--------------+---------+-------------+--------------+
PROGRESS: | 0            | 1       | 0.00169288  | 22.653ms     |
PROGRESS: | Done         |         | 100         | 460.209ms    |
PROGRESS: +--------------+---------+-------------+--------------+






    
Out[33]:





    

        
query_label
        
reference_label
        
distance
        
rank
    
    

        
0
        
Arnold Schwarzenegger
        
0.0
        
1
    
    

        
0
        
Jesse Ventura
        
0.818918918919
        
2
    
    

        
0
        
John Kitzhaber
        
0.824615384615
        
3
    
    

        
0
        
Lincoln Chafee
        
0.833876221498
        
4
    
    

        
0
        
Anthony Foxx
        
0.833910034602
        
5
    

[5 rows x 4 columns]

In [36]:

    

elton_john = people[people['name'] == 'Elton John']


    

In [37]:

    

elton_john


    

    
Out[37]:





    

        
URI
        
name
        
text
        
word_count
    
    

        
<http://dbpedia.org/resou
rce/Elton_John> ...
        
Elton John
        
sir elton hercules john
cbe born reginald ken ...
        
{'all': 1, 'least': 1,
'producer': 1, 'heavi ...
    


    

        
tfidf
    
    

        
{'all':
1.6431112434912472, ...
    

[? rows x 5 columns]
Note: Only the head of the SFrame is printed. This SFrame is lazily evaluated.
You can use len(sf) to force materialization.

In [39]:

    

#stack('word_count', new_column_name = ['word','count'])
elton_john_wc_table = elton_john[['word_count']].stack('word_count',new_column_name = ['word','count'])
elton_john_wc_table


    

    
Out[39]:





    

        
word
        
count
    
    

        
social
        
1
    
    

        
champion
        
1
    
    

        
be
        
1
    
    

        
2014
        
1
    
    

        
legal
        
1
    
    

        
became
        
1
    
    

        
2005
        
1
    
    

        
december
        
2
    
    

        
21
        
2
    
    

        
furnish
        
2
    

[255 rows x 2 columns]
Note: Only the head of the SFrame is printed.
You can use print_rows(num_rows=m, num_columns=n) to print more rows and columns.

In [40]:

    

elton_john_wc_table.sort('count',ascending=False)


    

    
Out[40]:





    

        
word
        
count
    
    

        
the
        
27
    
    

        
in
        
18
    
    

        
and
        
15
    
    

        
of
        
13
    
    

        
a
        
10
    
    

        
has
        
9
    
    

        
john
        
7
    
    

        
he
        
7
    
    

        
on
        
6
    
    

        
award
        
5
    

[255 rows x 2 columns]
Note: Only the head of the SFrame is printed.
You can use print_rows(num_rows=m, num_columns=n) to print more rows and columns.

In [42]:

    

elton_john_tfidf_table = elton_john[['tfidf']].stack('tfidf',new_column_name= ['tf-idf','count'])
elton_john_tfidf_table.sort('count',ascending=False)


    

    
Out[42]:





    

        
tf-idf
        
count
    
    

        
furnish
        
18.38947184
    
    

        
elton
        
17.48232027
    
    

        
billboard
        
17.3036809575
    
    

        
john
        
13.9393127924
    
    

        
songwriters
        
11.250406447
    
    

        
tonightcandle
        
10.9864953892
    
    

        
overallelton
        
10.9864953892
    
    

        
19702000
        
10.2933482087
    
    

        
fivedecade
        
10.2933482087
    
    

        
aids
        
10.262846934
    

[255 rows x 2 columns]
Note: Only the head of the SFrame is printed.
You can use print_rows(num_rows=m, num_columns=n) to print more rows and columns.

In [43]:

    

vic_beckham = people[people['name'] == 'Victoria Beckham']


    

In [44]:

    

graphlab.distances.cosine(elton_john['tfidf'][0],vic_beckham['tfidf'][0])


    

    
Out[44]:





0.9567006376655429

In [46]:

    

paul_m = people[people['name']== 'Paul McCartney']


    

In [47]:

    

graphlab.distances.cosine(elton_john['tfidf'][0],paul_m['tfidf'][0])


    

    
Out[47]:





0.8250310029221779

In [48]:

    

knn_model_tfidf = graphlab.nearest_neighbors.create(people,features=['tfidf'],label='name',distance='cosine')


    

    




PROGRESS: Starting brute force nearest neighbors model training.

In [49]:

    

knn_model_wc= graphlab.nearest_neighbors.create(people,features=['word_count'],label = 'name',distance='cosine')


    

    




PROGRESS: Starting brute force nearest neighbors model training.

In [50]:

    

knn_model_wc.query(elton_john)


    

    




PROGRESS: Starting pairwise querying.
PROGRESS: +--------------+---------+-------------+--------------+
PROGRESS: | Query points | # Pairs | % Complete. | Elapsed Time |
PROGRESS: +--------------+---------+-------------+--------------+
PROGRESS: | 0            | 1       | 0.00169288  | 16.728ms     |
PROGRESS: | Done         |         | 100         | 319.004ms    |
PROGRESS: +--------------+---------+-------------+--------------+






    
Out[50]:





    

        
query_label
        
reference_label
        
distance
        
rank
    
    

        
0
        
Elton John
        
2.22044604925e-16
        
1
    
    

        
0
        
Cliff Richard
        
0.16142415259
        
2
    
    

        
0
        
Sandro Petrone
        
0.16822542751
        
3
    
    

        
0
        
Rod Stewart
        
0.168327165587
        
4
    
    

        
0
        
Malachi O'Doherty
        
0.177315545979
        
5
    

[5 rows x 4 columns]

In [51]:

    

knn_model_tfidf.query(elton_john)


    

    




PROGRESS: Starting pairwise querying.
PROGRESS: +--------------+---------+-------------+--------------+
PROGRESS: | Query points | # Pairs | % Complete. | Elapsed Time |
PROGRESS: +--------------+---------+-------------+--------------+
PROGRESS: | 0            | 1       | 0.00169288  | 22.186ms     |
PROGRESS: | Done         |         | 100         | 454.898ms    |
PROGRESS: +--------------+---------+-------------+--------------+






    
Out[51]:





    

        
query_label
        
reference_label
        
distance
        
rank
    
    

        
0
        
Elton John
        
-2.22044604925e-16
        
1
    
    

        
0
        
Rod Stewart
        
0.717219667893
        
2
    
    

        
0
        
George Michael
        
0.747600998969
        
3
    
    

        
0
        
Sting (musician)
        
0.747671954431
        
4
    
    

        
0
        
Phil Collins
        
0.75119324879
        
5
    

[5 rows x 4 columns]

In [52]:

    

knn_model_wc.query(vic_beckham)


    

    




PROGRESS: Starting pairwise querying.
PROGRESS: +--------------+---------+-------------+--------------+
PROGRESS: | Query points | # Pairs | % Complete. | Elapsed Time |
PROGRESS: +--------------+---------+-------------+--------------+
PROGRESS: | 0            | 1       | 0.00169288  | 15.532ms     |
PROGRESS: | Done         |         | 100         | 314.267ms    |
PROGRESS: +--------------+---------+-------------+--------------+






    
Out[52]:





    

        
query_label
        
reference_label
        
distance
        
rank
    
    

        
0
        
Victoria Beckham
        
-2.22044604925e-16
        
1
    
    

        
0
        
Mary Fitzgerald (artist)
        
0.207307036115
        
2
    
    

        
0
        
Adrienne Corri
        
0.214509782788
        
3
    
    

        
0
        
Beverly Jane Fry
        
0.217466468741
        
4
    
    

        
0
        
Raman Mundair
        
0.217695474992
        
5
    

[5 rows x 4 columns]

In [53]:

    

knn_model_tfidf.query(vic_beckham)


    

    




PROGRESS: Starting pairwise querying.
PROGRESS: +--------------+---------+-------------+--------------+
PROGRESS: | Query points | # Pairs | % Complete. | Elapsed Time |
PROGRESS: +--------------+---------+-------------+--------------+
PROGRESS: | 0            | 1       | 0.00169288  | 21.814ms     |
PROGRESS: | Done         |         | 100         | 455.019ms    |
PROGRESS: +--------------+---------+-------------+--------------+






    
Out[53]:





    

        
query_label
        
reference_label
        
distance
        
rank
    
    

        
0
        
Victoria Beckham
        
1.11022302463e-16
        
1
    
    

        
0
        
David Beckham
        
0.548169610263
        
2
    
    

        
0
        
Stephen Dow Beckham
        
0.784986706828
        
3
    
    

        
0
        
Mel B
        
0.809585523409
        
4
    
    

        
0
        
Caroline Rush
        
0.819826422919
        
5
    

[5 rows x 4 columns]

In [ ]: