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Mastering flat_map in Python with List Comprehension

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Introduction In Python, when working with nested lists or iterables, one common challenge is flattening them into a single list while applying transformations. Many programming languages provide a built-in flatMap function, but Python does not have an explicit flat_map method. However, Python’s powerful list comprehensions offer an elegant way to achieve the same functionality. This article examines implementation behavior using Python’s list comprehensions and other methods. What is flat_map ? Functional programming  flatMap is a combination of map and flatten . It transforms the collection's element and flattens the resulting nested structure into a single sequence. For example, given a list of lists, flat_map applies a function to each sublist and returns a single flattened list. Example in a Functional Programming Language: List(List(1, 2), List(3, 4)).flatMap(x => x.map(_ * 2)) // Output: List(2, 4, 6, 8) Implementing flat_map in Python Using List Comprehension Python’...
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Aws QuickSight quick tutorial

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aws quicksight

Amazon QuickSight is a very fast, cloud-powered business intelligence (BI) service that makes it easy for all employees to build visualizations, perform ad-hoc analysis, and quickly get business insights from their data.

Amazon QuickSight Architecture uses a new, Super-fast, Parallel, In-memory Calculation Engine (“SPICE”) to perform advanced calculations and render visualizations rapidly.

Amazon QuickSight integrates automatically with AWS data services, enables organizations to scale to hundreds of thousands of users, and delivers fast and responsive query performance to them via SPICE’s query engine.

At one-tenth the cost of traditional solutions, Amazon QuickSight enables you to deliver rich BI functionality to everyone in your organization.

  1. Easily connect Amazon QuickSight to AWS data services, including Amazon Redshift, Amazon RDS, Amazon Aurora, Amazon EMR, Amazon DynamoDB, Amazon S3, and Amazon Kinesis; upload CSV, TSV and spreadsheet files; or connect to third-party data sources such as Salesforce.
  2. Amazon QuickSight automatically infers data types and relationships and provides suggestions for the best possible visualizations, optimized for your data, to help you get quick, actionable business insights.
  3. Amazon QuickSight uses SPICE – a Super-fast, Parallel, In-memory optimized Calculation Engine built from the ground up to generate answers on large datasets.
  4. Securely share your analysis with others in your organization by building interactive stories for collaboration using the storyboard and annotations. 
  5. Recipients can further explore the data and respond back with their insights and knowledge, making the whole organization efficient and effective.

Related: AWS - Cloud computing online Training

Amazon QuickSight provides partners a simple SQL-like interface to query the data stored in SPICE so that customers can continue using their existing BI tools from AWS BI Partners while benefiting from the faster performance delivered by SPICE.

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