Notebooks

Overview
You can use your favourite Jupyter Notebooks on Sprinkle. Through the navigation panel 🖱
click on Notebooks.
The Jupyter Notebook 📔
is an open-source web application that allows you to create and share documents that contain live code, narrative text, equations, and visualizations📊
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Use notebooks for data cleaning, transformations, numerical simulation, statistical modelling, data visualization & machine learning.
Feature Walkthrough 🚶
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Import data from sprinkle’s explore and segment reports to the notebook
Sprinkle created a library named “sprinkleSdk” to import data from the reports. The below script imports the library and imports data into the data frame.
Import sprinkle SDK
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from sprinkleSdk import SprinkleSdk as sp
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Read Segment
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df = sp.read_segment('<segment_id>')
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Read Explore
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df = sp.read_explore('<explore_id>')
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Once data is imported, you can run all kinds of analyses like descriptive, predictive, prescriptive, diagnostic analysis using these data.
Create a table and update an existing table in Sprinkle post-analysis?
Create a table or update existing table  in the warehouse using a data frame
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sp.create_or_update_table('user_defined_name', df)
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How to work on Spark session operations?
Get spark session with default configurations
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spark = sp.getOrCreate()
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Change spark app name while creating default spark session
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spark = sp.appName('some-name').getOrCreate()
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Get spark session where the user can customise your configuration
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spark = sp.sparkBuilder()
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appName('some-name')
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.config("spark.some.config.option1", "some-value")
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.config("spark.some.config.option2", "some-value")
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.getOrCreate()
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