In [1]:

    

!pip install pixiedust


    

    




Collecting pixiedust
  Downloading pixiedust-1.0.10.tar.gz (129kB)
    100% |################################| 133kB 3.0MB/s ta 0:00:01
Collecting mpld3 (from pixiedust)
  Downloading mpld3-0.3.tar.gz (788kB)
    100% |################################| 798kB 851kB/s eta 0:00:01
Collecting lxml (from pixiedust)
  Downloading lxml-3.8.0-cp35-cp35m-manylinux1_x86_64.whl (7.2MB)
    100% |################################| 7.2MB 96kB/s  eta 0:00:01
Collecting geojson (from pixiedust)
  Downloading geojson-2.0.0-py2.py3-none-any.whl
Building wheels for collected packages: pixiedust, mpld3
  Running setup.py bdist_wheel for pixiedust ... done
  Stored in directory: /home/jupyter/.cache/pip/wheels/27/ad/40/25418dfd6c7101fd7d3f25569ef80838e018f0ac378f7257ea
  Running setup.py bdist_wheel for mpld3 ... done
  Stored in directory: /home/jupyter/.cache/pip/wheels/69/bc/68/7ca3b696749d183e998968fc24b0ff3c5e119d9e68bf495b07
Successfully built pixiedust mpld3
Installing collected packages: mpld3, lxml, geojson, pixiedust
Successfully installed geojson-2.0.0 lxml-3.8.0 mpld3-0.3 pixiedust-1.0.10

In [3]:

    

import pixiedust


    

    




Pixiedust database opened successfully
Table VERSION_TRACKER created successfully






    






        

            
                
            
            Pixiedust version 1.0.10
        
        






    




Pixiedust runtime updated. Please restart kernel
Table USER_PREFERENCES created successfully
Table service_connections created successfully

In [7]:

    

homes = pixiedust.sampleData(6)


    

    




Downloading 'Million dollar home sales in NE Mass late 2016' from https://openobjectstore.mybluemix.net/misc/milliondollarhomes.csv
Downloaded 102051 bytes
Creating pandas DataFrame for 'Million dollar home sales in NE Mass late 2016'. Please wait...
Loading file using 'pandas'
Successfully created pandas DataFrame for 'Million dollar home sales in NE Mass late 2016'

In [8]:

    

display(homes)


    

    





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