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Python Regex: The 5 Exclusive Examples

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 Regular expressions (regex) are powerful tools for pattern matching and text manipulation in Python. Here are five Python regex examples with explanations: 01 Matching a Simple Pattern import re text = "Hello, World!" pattern = r"Hello" result = re.search(pattern, text) if result:     print("Pattern found:", result.group()) Output: Output: Pattern found: Hello This example searches for the pattern "Hello" in the text and prints it when found. 02 Matching Multiple Patterns import re text = "The quick brown fox jumps over the lazy dog." patterns = [r"fox", r"dog"] for pattern in patterns:     if re.search(pattern, text):         print(f"Pattern '{pattern}' found.") Output: Pattern 'fox' found. Pattern 'dog' found. It searches for both "fox" and "dog" patterns in the text and prints when they are found. 03 Matching Any Digit   import re text = "The price of the
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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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