notebook.community

Edit and run



In [1]:

    
%matplotlib inline
import pandas as pd



In [2]:

    
from IPython.core.display import HTML
css = open('style-table.css').read() + open('style-notebook.css').read()
HTML('<style>{}</style>'.format(css))









    Out[2]:



In [7]:

    
titles = pd.DataFrame.from_csv('data/titles.csv', index_col=None,encoding='utf-8')
titles.head()









    Out[7]:






  
    
      
      title
      year
    
  
  
    
      0
      The Rising Son
      1990
    
    
      1
      Ashes of Kukulcan
      2016
    
    
      2
      The Thousand Plane Raid
      1969
    
    
      3
      Crucea de piatra
      1993
    
    
      4
      The 86
      2015



In [7]:

    
chardet.detect?



In [8]:

    
type(rawdata)









    Out[8]:





_io.TextIOWrapper



In [16]:

    
import glob
glob.glob('*.csv')









    Out[16]:





['sales2.csv', 'sales1.csv']



In [19]:

    
import glob
from chardet.universaldetector import UniversalDetector

detector = UniversalDetector()
for filename in glob.glob('*.csv'):
    print( filename.ljust(60)),
    detector.reset()
    for line in file(filename, 'rb'):
        detector.feed(line)
        if detector.done: break
    detector.close()
    print( detector.result)









    



sales2.csv                                                  






    



---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-19-51b03ca5ab5e> in <module>()
      6     print( filename.ljust(60)),
      7     detector.reset()
----> 8     for line in file(filename, 'rb'):
      9         detector.feed(line)
     10         if detector.done: break

NameError: name 'file' is not defined



In [ ]:



In [22]:

    
import chardet
from io import StringIO
rawdata=open('data/cast.csv').read()
chardet.detect(StringIO(rawdata))









    



---------------------------------------------------------------------------
MemoryError                               Traceback (most recent call last)
<ipython-input-22-ff0df6818d27> in <module>()
      2 from io import StringIO
      3 rawdata=open('data/cast.csv').read()
----> 4 chardet.detect(StringIO(rawdata))

MemoryError:



In [10]:

    
cast = pd.DataFrame.from_csv('data/cast.csv', index_col=None)
cast.head()









    Out[10]:






  
    
      
      title
      year
      name
      type
      character
      n
    
  
  
    
      0
      Suuri illusioni
      1985
      Homo $
      actor
      Guests
      22
    
    
      1
      Gangsta Rap: The Glockumentary
      2007
      Too $hort
      actor
      Himself
      NaN
    
    
      2
      Menace II Society
      1993
      Too $hort
      actor
      Lew-Loc
      27
    
    
      3
      Porndogs: The Adventures of Sadie
      2009
      Too $hort
      actor
      Bosco
      3
    
    
      4
      Stop Pepper Palmer
      2014
      Too $hort
      actor
      Himself
      NaN

What are the ten most common movie names of all time?



In [7]:

    
titles['title'].value_counts()[:10]









    Out[7]:





Hamlet                  19
Macbeth                 14
Carmen                  14
The Three Musketeers    12
Maya                    11
She                     11
Eva                     10
Temptation              10
Karma                   10
Honeymoon               10
dtype: int64



In [ ]:

Which three years of the 1930s saw the most films released?



In [8]:

    
titles[(titles['year']<1940)&(titles['year']>=1930)]['year'].value_counts()









    Out[8]:





1937    1187
1936    1129
1938    1115
1939    1055
1935    1039
1934     955
1932     931
1933     880
1931     872
1930     814
dtype: int64



In [ ]:

Plot the number of films that have been released each decade over the history of cinema.



In [29]:

    
dec=((titles['year']//10)*10)
print(dec.max())
print(dec.min())
dec.hist(bins=(dec.max()-dec.min())/10+1)









    



2020
1890






    Out[29]:





<matplotlib.axes.AxesSubplot at 0x7f7dde262a90>

Plot the number of "Hamlet" films made each decade.



In [35]:

    
hamdec=titles[titles['title']=="Hamlet"]
hamdec['year']=(hamdec['year']//10)*10
hamdec['year'].hist(bins=(hamdec['year'].max()-hamdec['year'].min())/10+1)









    



/usr/local/lib/python3.4/dist-packages/ipykernel/__main__.py:2: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
  from ipykernel import kernelapp as app






    Out[35]:





<matplotlib.axes.AxesSubplot at 0x7f7dde0e2400>



In [34]:

    
hamdec

Plot the number of "Rustler" characters in each decade of the history of film.



In [36]:

    
hamdec=cast[cast['character']=="Rustler"]
hamdec['year']=(hamdec['year']//10)*10
hamdec['year'].hist(bins=(hamdec['year'].max()-hamdec['year'].min())/10+1)









    



/usr/local/lib/python3.4/dist-packages/ipykernel/__main__.py:2: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
  from ipykernel import kernelapp as app






    Out[36]:





<matplotlib.axes.AxesSubplot at 0x7f7dddfabf28>



In [ ]:

Plot the number of "Hamlet" characters each decade.



In [37]:

    
hamdec=cast[cast['character']=="Hamlet"]
hamdec['year']=(hamdec['year']//10)*10
hamdec['year'].hist(bins=(hamdec['year'].max()-hamdec['year'].min())/10+1)









    



/usr/local/lib/python3.4/dist-packages/ipykernel/__main__.py:2: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
  from ipykernel import kernelapp as app






    Out[37]:





<matplotlib.axes.AxesSubplot at 0x7f7dde533a90>



In [ ]:

What are the 11 most common character names in movie history?



In [39]:

    
cast['character'].value_counts()[:11]









    Out[39]:





Himself        18857
Dancer         11200
Extra           9268
Reporter        7676
Doctor          6895
Policeman       6534
Student         6415
Nurse           6217
Bartender       6205
Party Guest     6005
Minor Role      5943
dtype: int64



In [ ]:

Who are the 10 people most often credited as "Herself" in film history?



In [9]:

    
cast[cast['character']=='Herself']['name'].value_counts()[:10]









    Out[9]:





Joyce Brothers         14
Queen Elizabeth II     11
Margaret Thatcher       8
Lili?n Garc?a           7
Joan Rivers             7
Mary Jo Pehl            7
Sally Jessy Raphael     5
Chris Evert             5
Juhi Chawla             5
Bunny Yeager            5
dtype: int64



In [ ]:

Who are the 10 people most often credited as "Himself" in film history?



In [42]:

    
cast[cast['character']=='Himself']['name'].value_counts()[:10]









    Out[42]:





Adolf Hitler             93
Richard Nixon            39
Ronald Reagan            31
John F. Kennedy          25
Ron Jeremy               25
Bill Clinton             20
Franklin D. Roosevelt    20
George W. Bush           20
Winston Churchill        20
Benito Mussolini         18
dtype: int64



In [ ]:

Which actors or actresses appeared in the most movies in the year 1945?



In [43]:

    
cast[cast['year']==1945]['name'].value_counts()[:10]









    Out[43]:





Emmett Vogan        39
Sam (II) Harris     30
Bess Flowers        28
Harold Miller       28
Nolan Leary         27
Frank O'Connor      26
Franklyn Farnum     25
Tom London          24
Charles Sullivan    24
Edmund Cobb         24
dtype: int64



In [ ]:

Which actors or actresses appeared in the most movies in the year 1985?



In [44]:

    
cast[cast['year']==1985]['name'].value_counts()[:10]









    Out[44]:





Mammootty        19
Shakti Kapoor    19
Sukumari         17
Lou Scheimer     15
Aruna Irani      14
Rajesh Khanna    13
Deven Verma      13
Mohanlal         13
Raj Babbar       13
Om Shivpuri      12
dtype: int64



In [ ]:

Plot how many roles Mammootty has played in each year of his career.



In [49]:

    
cast[cast['name']=='Mammootty'].hist(column='year')









    Out[49]:





array([[<matplotlib.axes.AxesSubplot object at 0x7f7dddbca128>]], dtype=object)



In [46]:

    
cast.hist?



In [ ]:

What are the 10 most frequent roles that start with the phrase "Patron in"?



In [52]:

    
cast[cast['character'].str.startswith('Patron in')]['character'].value_counts()[:10]









    Out[52]:





Patron in Frisky Rabbit         16
Patron in Chinese Restaurant     9
Patron in the Coffee House       9
Patron in Billiard Parlor        5
Patron in Bar                    4
Patron in restaurant             3
Patron in Restaurant             3
Patron in Club                   3
Patron in cabaret                3
Patron in Audience               2
dtype: int64

What are the 10 most frequent roles that start with the word "Science"?



In [54]:

    
cast[cast['character'].str.startswith('Science')]['character'].value_counts()[:10]









    Out[54]:





Science Teacher         54
Science Student          9
Science Fair Student     8
Science Club Member      5
Science Reporter         5
Science Promo Cadet      4
Science Fair Judge       4
Science Kid              4
Science Officer          3
Science Fair Kid         3
dtype: int64



In [ ]:

Plot the n-values of the roles that Judi Dench has played over her career.



In [55]:

    
cast[cast['name']=='Judi Dench'].plot(kind='scatter',x='year',y='n')









    Out[55]:





<matplotlib.axes.AxesSubplot at 0x7f7dddda5710>



In [ ]:

Plot the n-values of Cary Grant's roles through his career.



In [ ]:



In [ ]:

Plot the n-value of the roles that Sidney Poitier has acted over the years.



In [56]:

    
cast[cast['name']=='Sidney Poitier'].plot(kind='scatter',x='year',y='n')









    Out[56]:





<matplotlib.axes.AxesSubplot at 0x7f7ddd9c3978>



In [ ]:

How many leading (n=1) roles were available to actors, and how many to actresses, in the 1950s?



In [60]:

    
cast[(cast['n']==1)&(cast['type']=='actor')&(cast['year']<1960)&(cast['year']>=1950)].shape[0]









    Out[60]:





6390



In [61]:

    
cast[(cast['n']==1)&(cast['type']=='actress')&(cast['year']<1960)&(cast['year']>=1950)].shape[0]









    Out[61]:





2818

How many supporting (n=2) roles were available to actors, and how many to actresses, in the 1950s?



In [63]:

    
cast[(cast['n']==2)&(cast['type']=='actor')&(cast['year']<1960)&(cast['year']>=1950)].shape[0]









    Out[63]:





4388



In [62]:

    
cast[(cast['n']==2)&(cast['type']=='actress')&(cast['year']<1960)&(cast['year']>=1950)].shape[0]









    Out[62]:





4406



In [ ]:

	title	year
5571	Hamlet	1940
26280	Hamlet	2010
37562	Hamlet	2010
42436	Hamlet	1990
43711	Hamlet	1910
68563	Hamlet	1950
86177	Hamlet	1970
88221	Hamlet	1980
88412	Hamlet	2000
92180	Hamlet	1920
114784	Hamlet	1960
155367	Hamlet	1910
164427	Hamlet	2000
170820	Hamlet	1960
187902	Hamlet	1990
193741	Hamlet	2010
195956	Hamlet	1910
206810	Hamlet	1970
208799	Hamlet	2010

	title	year
0	The Rising Son	1990
1	Ashes of Kukulcan	2016
2	The Thousand Plane Raid	1969
3	Crucea de piatra	1993
4	The 86	2015

	title	year	name	type	character	n
0	Suuri illusioni	1985	Homo $	actor	Guests	22
1	Gangsta Rap: The Glockumentary	2007	Too $hort	actor	Himself	NaN
2	Menace II Society	1993	Too $hort	actor	Lew-Loc	27
3	Porndogs: The Adventures of Sadie	2009	Too $hort	actor	Bosco	3
4	Stop Pepper Palmer	2014	Too $hort	actor	Himself	NaN