

In [1]:

    
import pixiedust









    



Pixiedust database opened successfully






    





        
            
                
            
            Pixiedust version 0.74
        
        






    



/Users/rajrsingh/anaconda/lib/python2.7/site-packages/bokeh/core/json_encoder.py:52: DeprecationWarning: parsing timezone aware datetimes is deprecated; this will raise an error in the future
  NP_EPOCH = np.datetime64('1970-01-01T00:00:00Z')



In [2]:

    
pixiedust.sampleData()









    





  
    
      Id
      Name
      Topic
      Publisher
    
  
  
  
    
        1
        Car performance data
        transportation
        IBM
    
  
    
        2
        Airbnb Data for Analytics: Washington D.C. Listings
        Economy & Business
        IBM Cloud Data Services
    
  
    
        3
        Total population by country
        Society
        IBM Cloud Data Services
    
  
    
        4
        GoSales Transactions for Naive Bayes Model
        Leisure
        IBM
    
  
    
        5
        Election results by County
        Society
        IBM
    
  
    
        6
        Million dollar home sales in NE Mass late 2016
        Economy & Business
        IBM



In [3]:

    
popdf = pixiedust.sampleData(3)









    



Downloading 'Total population by country' from https://apsportal.ibm.com/exchange-api/v1/entries/889ca053a19986a4445839358a91963e/data?accessKey=657b130d504ab539947e51b50f0e338e






    





                
                    Starting download...
                    
                






    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    














    



Creating pySpark DataFrame for 'Total population by country'. Please wait...
Successfully created pySpark DataFrame for 'Total population by country'



In [4]:

    
display(popdf)









    




Hey, there's something awesome here! To see it, open this notebook outside GitHub, in a viewer like Jupyter

            
270,437,212,523

Million dollar home sales

Home sales of $1million and above in Northeastern Massachusetts for the 3 months prior to Jan. 27, 2017. Downloaded from Redfin.com on Jan. 27, 2017.



In [5]:

    
homesdf = pixiedust.sampleData(6)









    



Downloading 'Million dollar home sales in NE Mass late 2016' from https://openobjectstore.mybluemix.net/misc/milliondollarhomes.csv






    





                
                    Starting download...
                    
                






    














    














    














    














    














    














    














    














    














    














    














    














    














    



Creating pySpark DataFrame for 'Million dollar home sales in NE Mass late 2016'. Please wait...
Successfully created pySpark DataFrame for 'Million dollar home sales in NE Mass late 2016'

Map display

The first time you run the main pixiedust visualization command, display(), you get the default visualization, which is a table. Then, from the drop-down menu select "Map", and populate the options dialog as follows:

Keys: put your latitude and longitude fields here. They must be floating values. These fields must be named latitude, lat or y and longitude, lon or x.
Values: the field you want to use to thematically color the map. Only one field can be used.
Mapbox Access Token: The token you get from your Mapbox account here: https://www.mapbox.com/studio/signup/



In [6]:

    
display(homesdf)









    




Hey, there's something awesome here! To see it, open this notebook outside GitHub, in a viewer like Jupyter

            PixieDust map with Mapbox

Id	Name	Topic	Publisher
1	Car performance data	transportation	IBM
2	Airbnb Data for Analytics: Washington D.C. Listings	Economy & Business	IBM Cloud Data Services
3	Total population by country	Society	IBM Cloud Data Services
4	GoSales Transactions for Naive Bayes Model	Leisure	IBM
5	Election results by County	Society	IBM
6	Million dollar home sales in NE Mass late 2016	Economy & Business	IBM