cortanaanalytics
This a Python library for using Microsoft Azure Datamarket and Cortana Analytics Services.
Installation
To install, use pip:
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 from the Azure Datamarket and subscribe to the service you wish to use.
Text Analytics
https://datamarket.azure.com/dataset/amla/text-analytics
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
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
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
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)
