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
from sprinkleSdk import SprinkleSdk as sp
Read Segment
df = sp.read_segment('<segment_id>')
Read Explore
df = sp.read_explore('<explore_id>')
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
sp.create_or_update_table('user_defined_name', df)
How to work on Spark session operations?
Get spark session with default configurations
spark = sp.getOrCreate()
Change spark app name while creating default spark session
spark = sp.appName('some-name').getOrCreate()
Get spark session where the user can customise your configuration
spark = sp.sparkBuilder()
appName('some-name')
.config("spark.some.config.option1", "some-value")
.config("spark.some.config.option2", "some-value")
.getOrCreate()