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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...
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Why MySQL You Need to Master for Data Analytics Jobs

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MySQL Before you can start analysing data, you are going to actually have to have some data on hand. That means a database – preferably a relational one. If you had your sights set on a non-relational, NoSQL database solution, you might want to step back and catch your breath. NoSQL databases are unique because of their independence from the Structured Query Language (SQL) found in relational databases. Relational databases all use SQL as the domain-specific language for ad hoc queries, whereas non-relational databases have no such standard query language, so they can use whatever they want –including SQL. Non-relational databases also have their own APIs designed for maximum scalability and flexibility. When You Need to Learn NoSQL Databases? NoSQL databases are typically designed to excel in two specific areas: speed and scalability. But for the purposes of learning about data concepts and analysis, such super-powerful tools are pretty much overkill. In other words, you...
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