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Step-by-Step Guide to Reading Different Files in Python

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 In the world of data science, automation, and general programming, working with files is unavoidable. Whether you’re dealing with CSV reports, JSON APIs, Excel sheets, or text logs, Python provides rich and easy-to-use libraries for reading different file formats. In this guide, we’ll explore how to read different files in Python , with code examples and best practices. 1. Reading Text Files ( .txt ) Text files are the simplest form of files. Python’s built-in open() function handles them effortlessly. Example: # Open and read a text file with open ( "sample.txt" , "r" ) as file: content = file.read() print (content) Explanation: "r" mode means read . with open() automatically closes the file when done. Best Practice: Always use with to handle files to avoid memory leaks. 2. Reading CSV Files ( .csv ) CSV files are widely used for storing tabular data. Python has a built-in csv module and a powerful pandas library. Using cs...

SAP HANA top Career Options to Find in Job Market

SAP HANA converges database and application platform capabilities in-memory to transform transactions, analytics, text analysis, predictive and spatial processing so businesses can operate in real-time. I have listed the areas on available careers for SAP HANA.

SAP HANA 

It has completely transformed the database industry by combining database, data processing, and application platform capabilities in a single in-memory platform.

The platform also provides libraries for predictive, planning, text processing, spatial, and business analytics -- all on the same architecture.

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Operational Analytics

With transactional and analytical data stored together, SAP HANA provides on-the-fly analysis so you can make real-time decisions.

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Crunch petascale data volumes for quick, accurate answers to sophisticated business problems.

Predictive, Spatial and Text Analysis

A powerful suite of predictive, spatial and text analytics libraries can run across multiple data sources

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