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In [1]:



    


import graphlab as gl



    











In [2]:



    


url = 'http://s3.amazonaws.com/dato-datasets/millionsong/song_data.csv'
song = gl.SFrame.read_csv(url)



    


















    






[INFO] This non-commercial license of GraphLab Create is assigned to iliassweb@gmail.comand will expire on September 22, 2016. For commercial licensing options, visit https://dato.com/buy/.

[INFO] Start server at: ipc:///tmp/graphlab_server-16203 - Server binary: /home/zax/anaconda/lib/python2.7/site-packages/graphlab/unity_server - Server log: /tmp/graphlab_server_1443512832.log
[INFO] GraphLab Server Version: 1.6.1










    






PROGRESS: Downloading http://s3.amazonaws.com/dato-datasets/millionsong/song_data.csv to /var/tmp/graphlab-zax/16203/d84209ef-feb0-4d66-9dbb-6b5ce9e9937e.csv
PROGRESS: Finished parsing file http://s3.amazonaws.com/dato-datasets/millionsong/song_data.csv
PROGRESS: Parsing completed. Parsed 100 lines in 1.49752 secs.
------------------------------------------------------
Inferred types from first line of file as 
column_type_hints=[str,str,str,str,int]
If parsing fails due to incorrect types, you can correct
the inferred type list above and pass it to read_csv in
the column_type_hints argument
------------------------------------------------------
PROGRESS: Read 637410 lines. Lines per second: 435946
PROGRESS: Finished parsing file http://s3.amazonaws.com/dato-datasets/millionsong/song_data.csv
PROGRESS: Parsing completed. Parsed 1000000 lines in 1.71802 secs.

















In [4]:



    


song.show()



    


















    






Canvas is accessible via web browser at the URL: http://localhost:51504/index.html
Opening Canvas in default web browser.

















In [5]:



    


song.head()



    


















    
Out[5]:








    

        song_id
        title
        release
        artist_name
        year
    

    

        SOQMMHC12AB0180CB8
        Silent Night
        Monster Ballads X-Mas
        Faster Pussy cat
        2003
    

    

        SOVFVAK12A8C1350D9
        Tanssi vaan
        Karkuteillä
        Karkkiautomaatti
        1995
    

    

        SOGTUKN12AB017F4F1
        No One Could Ever
        Butter
        Hudson Mohawke
        2006
    

    

        SOBNYVR12A8C13558C
        Si Vos Querés
        De Culo
        Yerba Brava
        2003
    

    

        SOHSBXH12A8C13B0DF
        Tangle Of Aspens
        Rene Ablaze Presents
Winter Sessions ...		
        Der Mystic
        0
    

    

        SOZVAPQ12A8C13B63C
        Symphony No. 1 G minor
"Sinfonie ...		
        Berwald: Symphonies Nos.
1/2/3/4 ...		
        David Montgomery
        0
    

    

        SOQVRHI12A6D4FB2D7
        We Have Got Love
        Strictly The Best Vol. 34
        Sasha / Turbulence
        0
    

    

        SOEYRFT12AB018936C
        2 Da Beat Ch'yall
        Da Bomb
        Kris Kross
        1993
    

    

        SOPMIYT12A6D4F851E
        Goodbye
        Danny Boy
        Joseph Locke
        0
    

    

        SOJCFMH12A8C13B0C2
        Mama_ mama can't you see
? ...		
        March to cadence with the
US marines ...		
        The Sun Harbor's Chorus-
Documentary Recordings ...		
        0
    



[10 rows x 5 columns]



















In [6]:



    


song['year'].mean()



    


















    
Out[6]:








1030.3256520000118

Transforming columns





In [9]:



    


song['num_words']= song['title'].apply(lambda x : len(x.split(' ')))
song



    


















    
Out[9]:








    

        song_id
        title
        release
        artist_name
        year
        num_words
    

    

        SOQMMHC12AB0180CB8
        Silent Night
        Monster Ballads X-Mas
        Faster Pussy cat
        2003
        2
    

    

        SOVFVAK12A8C1350D9
        Tanssi vaan
        Karkuteillä
        Karkkiautomaatti
        1995
        2
    

    

        SOGTUKN12AB017F4F1
        No One Could Ever
        Butter
        Hudson Mohawke
        2006
        4
    

    

        SOBNYVR12A8C13558C
        Si Vos Querés
        De Culo
        Yerba Brava
        2003
        3
    

    

        SOHSBXH12A8C13B0DF
        Tangle Of Aspens
        Rene Ablaze Presents
Winter Sessions ...		
        Der Mystic
        0
        3
    

    

        SOZVAPQ12A8C13B63C
        Symphony No. 1 G minor
"Sinfonie ...		
        Berwald: Symphonies Nos.
1/2/3/4 ...		
        David Montgomery
        0
        9
    

    

        SOQVRHI12A6D4FB2D7
        We Have Got Love
        Strictly The Best Vol. 34
        Sasha / Turbulence
        0
        4
    

    

        SOEYRFT12AB018936C
        2 Da Beat Ch'yall
        Da Bomb
        Kris Kross
        1993
        4
    

    

        SOPMIYT12A6D4F851E
        Goodbye
        Danny Boy
        Joseph Locke
        0
        1
    

    

        SOJCFMH12A8C13B0C2
        Mama_ mama can't you see
? ...		
        March to cadence with the
US marines ...		
        The Sun Harbor's Chorus-
Documentary Recordings ...		
        0
        6
    



[1000000 rows x 6 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.

Agregation





In [10]:



    


song.groupby('artist_name', {'total':gl.aggregate.COUNT})



    


















    
Out[10]:








    

        artist_name
        total
    

    

        Gary Lewis & The Playboys
        45
    

    

        The Dells
        54
    

    

        DJ Konnat
        1
    

    

        VULTURE WHALE
        11
    

    

        Martha Argerich/Kathia
Buniatishvili/Dora ...		
        1
    

    

        S.S featuring Jp_ Mar Da
Cigar Splitter ...		
        1
    

    

        Ian Astbury
        11
    

    

        Big L / Kool G Rap
        1
    

    

        Son House
        106
    

    

        Lil Wayne / BG
        1
    



[72664 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.

Regresssion model





In [13]:



    


url = 'http://s3.amazonaws.com/dato-datasets/regression/Housing.csv'
x = gl.SFrame.read_csv(url)
model = gl.linear_regression.create(x, target='price')



    


















    






PROGRESS: Downloading http://s3.amazonaws.com/dato-datasets/regression/Housing.csv to /var/tmp/graphlab-zax/16203/3e472d59-83ab-4cf8-8a1a-b8fbeb638439.csv
PROGRESS: Finished parsing file http://s3.amazonaws.com/dato-datasets/regression/Housing.csv
PROGRESS: Parsing completed. Parsed 100 lines in 0.049366 secs.
------------------------------------------------------
Inferred types from first line of file as 
column_type_hints=[int,int,int,int,int,int,str,str,str,str,str,int,str]
If parsing fails due to incorrect types, you can correct
the inferred type list above and pass it to read_csv in
the column_type_hints argument
------------------------------------------------------
PROGRESS: Finished parsing file http://s3.amazonaws.com/dato-datasets/regression/Housing.csv
PROGRESS: Parsing completed. Parsed 546 lines in 0.018493 secs.
PROGRESS: Creating a validation set from 5 percent of training data. This may take a while.
          You can set ``validation_set=None`` to disable validation tracking.

PROGRESS: Linear regression:
PROGRESS: --------------------------------------------------------
PROGRESS: Number of examples          : 518
PROGRESS: Number of features          : 12
PROGRESS: Number of unpacked features : 12
PROGRESS: Number of coefficients    : 13
PROGRESS: Starting Newton Method
PROGRESS: --------------------------------------------------------
PROGRESS: +-----------+----------+--------------+--------------------+----------------------+---------------+-----------------+
PROGRESS: | Iteration | Passes   | Elapsed Time | Training-max_error | Validation-max_error | Training-rmse | Validation-rmse |
PROGRESS: +-----------+----------+--------------+--------------------+----------------------+---------------+-----------------+
PROGRESS: | 1         | 2        | 1.003654     | 97059.006065       | 34861.599338         | 15799.058155  | 16005.847610    |
PROGRESS: +-----------+----------+--------------+--------------------+----------------------+---------------+-----------------+

















In [16]:



    


gl.canvas.set_target('ipynb')
song.show(view="Scatter Plot", x="year", y="release")



    


















    



























In [ ]:

Content source: ledrui/Predicting-House-Prices

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