notebook.community

Edit and run 





In [2]:



    


%matplotlib inline
import pandas as pd



    











In [3]:



    


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



    


















    
Out[3]:























In [4]:



    


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



    


















    
Out[4]:










  
    

      
      title
      year
    

  
  
    

      0
      Ligaw na daigdig
      1962
    

    

      1
      Sluby ulanskie
      1934
    

    

      2
      The House of the Seven Gables
      1940
    

    

      3
      Mandala - Il simbolo
      2008
    

    

      4
      Shi bian
      1958
    

  




















In [5]:



    


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



    


















    
Out[5]:










  
    

      
      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 [6]:



    


titles.title.value_counts().head(10)



    


















    
Out[6]:








Hamlet                  19
Macbeth                 15
Carmen                  14
The Three Musketeers    12
Maya                    11
Love                    10
She                     10
Paradise                10
Temptation              10
Kismet                  10
Name: title, dtype: int64

















In [ ]:

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





In [7]:



    


titles[(titles["year"]>=1930) & (titles["year"]<1940)].title.value_counts().head(3)



    


















    
Out[7]:








Big Business            3
Temptation              3
The Three Musketeers    3
Name: title, dtype: int64

















In [ ]:

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





In [8]:



    


t = titles
(t.year // 10 * 10).value_counts().sort_index().plot(kind='bar')



    


















    
Out[8]:








<matplotlib.axes._subplots.AxesSubplot at 0x7f508315d208>










    
























In [ ]:

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





In [9]:



    


t = titles[titles.title == 'Hamlet']
(t.year // 10 * 10).value_counts().sort_index().plot(kind='bar')



    


















    
Out[9]:








<matplotlib.axes._subplots.AxesSubplot at 0x7f505a2b84a8>










    
























In [ ]:

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





In [10]:



    


t = cast[cast.character == 'Rustler']
(t.year // 10 * 10).value_counts().sort_index().plot(kind='bar')



    


















    
Out[10]:








<matplotlib.axes._subplots.AxesSubplot at 0x7f508203df28>










    
























In [ ]:

Plot the number of "Hamlet" characters each decade.





In [11]:



    


t = cast[cast.character == 'Hamlet']
(t.year // 10 * 10).value_counts().sort_index().plot(kind='bar')



    


















    
Out[11]:








<matplotlib.axes._subplots.AxesSubplot at 0x7f5081fd0198>










    
























In [ ]:

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





In [12]:



    


cast.character.value_counts().head(11)



    


















    
Out[12]:








Himself        18553
Dancer         11338
Extra           9328
Reporter        7726
Doctor          6968
Policeman       6582
Student         6534
Nurse           6236
Bartender       6203
Party Guest     6185
Minor Role      6052
Name: character, dtype: int64

















In [ ]:

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





In [15]:



    


cast[cast.character == "Herself"].name.value_counts().head(10)



    


















    
Out[15]:








Joyce Brothers        14
Queen Elizabeth II    11
Margaret Thatcher      8
Lili?n Garc?a          8
Joan Rivers            7
Mary Jo Pehl           7
Hillary Clinton        5
Caroline Rhea          5
Rekha                  5
Juhi Chawla            5
Name: name, dtype: int64

















In [ ]:

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





In [16]:



    


cast[cast.character == "Himself"].name.value_counts().head(10)



    


















    
Out[16]:








Adolf Hitler             95
Richard Nixon            41
Ronald Reagan            32
John F. Kennedy          26
Ron Jeremy               24
Franklin D. Roosevelt    20
Winston Churchill        20
Bill Clinton             20
George W. Bush           20
Martin Luther King       19
Name: name, dtype: int64

















In [ ]:

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





In [20]:



    


cast[cast.year == 1945].name.value_counts().head(1)



    


















    
Out[20]:








Emmett Vogan    39
Name: name, dtype: int64

















In [ ]:

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





In [21]:



    


cast[cast.year == 1985].name.value_counts().head(1)



    


















    
Out[21]:








Mammootty    20
Name: name, dtype: int64

















In [ ]:

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





In [32]:



    


# (cast[cast.name == "Mammootty"].character // 1 * 1).value_counts().sort_index().plot(kind='bar')

cast[cast.name == 'Mammootty'].year.value_counts().sort_index().plot()



    


















    
Out[32]:








<matplotlib.axes._subplots.AxesSubplot at 0x7f5081cca978>










    
























In [ ]:

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





In [36]:



    


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



    


















    
Out[36]:








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

















In [ ]:

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





In [38]:



    


cast[cast.character.str.startswith("Science")].character.head(10)



    


















    
Out[38]:








10860         Science Student
29725             Science Kid
36888         Science Student
80438            Science Monk
124653    Science Performer 3
127689        Science Teacher
136976        Science Teacher
139631        Science Teacher
167672    Science Promo Cadet
171221    Science Fair Patron
Name: character, dtype: object

















In [ ]:

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





In [43]:



    


char = cast[cast.name == "Judi Dench"].sort("year")
char = char[char.n.notnull()]
char.plot(x="year",y ="n", kind="scatter")



    


















    






/home/ubuntu/miniconda3/lib/python3.5/site-packages/ipykernel/__main__.py:1: FutureWarning: sort(columns=....) is deprecated, use sort_values(by=.....)
  if __name__ == '__main__':










    
Out[43]:








<matplotlib.axes._subplots.AxesSubplot at 0x7f506b7e1a58>










    
























In [ ]:

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





In [44]:



    


char = cast[cast.name == "Cary Grant"].sort("year")
char = char[char.n.notnull()]
char.plot(x="year",y ="n", kind="scatter")



    


















    






/home/ubuntu/miniconda3/lib/python3.5/site-packages/ipykernel/__main__.py:1: FutureWarning: sort(columns=....) is deprecated, use sort_values(by=.....)
  if __name__ == '__main__':










    
Out[44]:








<matplotlib.axes._subplots.AxesSubplot at 0x7f5081f15908>










    
























In [ ]:

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





In [45]:



    


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



    


















    
Out[45]:








<matplotlib.axes._subplots.AxesSubplot at 0x7f506b7171d0>










    
























In [ ]:

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





In [61]:



    


c = cast
c = c[c.year // 10 == 195]
c = c[(c.n == 1) ]
c.type.value_counts()



    


















    
Out[61]:








actor      6430
actress    2858
Name: type, dtype: int64

















In [ ]:

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





In [60]:



    


c = cast
c = c[c.year // 10 == 195]
c = c[(c.n == 2) ]
c.type.value_counts()



    


















    
Out[60]:








actress    4435
actor      4431
Name: type, dtype: int64

















In [ ]:

Content source: climberwb/pycon-pandas-tutorial

Similar notebooks:

notebook.community | gallery | about