cortanaanalytics
================
This a Python library for using Microsoft Azure Datamarket and Cortana Analytics Services.
Installation
------------
To install, use pip:
.. code:: shell
pip install cortanaanalytics
You can also get the development versions directly from the GitHub repo: http://github.com/crwilcox/cortanaanalytics
Getting Started
---------------
Cortana Analytics has many different packages. Please look at each section for the library you are interested in.
Also, you will need `obtain an access key <https://datamarket.azure.com/account/keys>`__ from the Azure Datamarket and subscribe to the service you wish to use.
Text Analytics
--------------
https://datamarket.azure.com/dataset/amla/text-analytics
.. code:: python
from cortanaanalytics.textanalytics import TextAnalytics
key = '1abCdEFGh/ijKlmN/opq234r56st/UvWXYZabCD7EF8='
ta = TextAnalytics(key)
score = ta.get_sentiment("hello world")
scores = ta.get_sentiment_batch([{"Text":"hello world", "Id":0}, {"Text":"hello world again", "Id":2}])
Recommendations
---------------
https://datamarket.azure.com/dataset/amla/recommendations
.. code:: python
from cortanaanalytics.recommendations import Recommendations
email = 'email@outlook.com'
key = '1abCdEFGh/ijKlmN/opq234r56st/UvWXYZabCD7EF8='
rs = Recommendations(email, key)
# create model
model_id = rs.create_model('groceries' + datetime.now().strftime('%Y%m%d%H%M%S'))
# import item catalog
catalog_path = os.path.join('app', 'management', 'commands', 'catalog.csv')
rs.import_file(model_id, catalog_path, Uris.import_catalog)
# import usage information
transactions_path = os.path.join('app', 'management', 'commands', 'transactions.csv')
rs.import_file(model_id, transactions_path, Uris.import_usage)
# build model
build_id = rs.build_fbt_model(model_id)
status = rs.wait_for_build(model_id, build_id)
if status != BuildStatus.success:
print('Unsuccessful in building the model, failing now.')
return
# update model active build (not needed unless you are rebuilding)
rs.update_model(model_id, None, build_id)
print('Built a model. Model ID:{} Build ID:{}'.format(model_id, build_id))
Anomaly Detection
-----------------
https://datamarket.azure.com/dataset/aml_labs/anomalydetection
.. code:: python
from cortanaanalytics.anomalydetection import AnomalyDetection
key = '1abCdEFGh/ijKlmN/opq234r56st/UvWXYZabCD7EF8='
ad = AnomalyDetection(key)
data = [
(datetime(2014, 9, 21, 11, 5, 0), 3),
(datetime(2014, 9, 21, 11, 10, 0), 9.09),
(datetime(2014, 9, 21, 11, 15, 0), 0)
]
result = ad.score(test_data)
or you can also use strings
.. code:: python
from cortanaanalytics.anomalydetection import AnomalyDetection
key = '1abCdEFGh/ijKlmN/opq234r56st/UvWXYZabCD7EF8='
ad = AnomalyDetection(key)
data = "9/21/2014 11:05:00 AM=3;9/21/2014 11:10:00 AM=9.09;9/21/2014 11:15:00 AM=0;"
params = "SpikeDetector.TukeyThresh=3; SpikeDetector.ZscoreThresh=3"
result = ad.score_raw(data, params)
