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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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Python Supports These 5 Native Data types

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Python supports five native data types. The Data types are such that a Programmer can use to write the logic and get the output. Many beginners may not aware of native data types. So I am adding a short note on that here. Native means as is Python supported data types.


Python Five Key Native Data Types
Python Five Key Native Data Types

Python Native Data Types

In Python, you can find five types of native data types. Here is a quick list for you. Those are Number, String, List, Tuple, Set, and Dictionary.


1. Number

For all the numeric values,  you can use this data type.


2. String

It handles all Characters, Special-symbols, and Alphanumeric values.


3. List

It is something like sequential data. A program can do Sort, Merge, etc. on this data.


4. Tuple

Data is a little different from the List.


5. Set

This kind of Data-type helps you to do set operations. Those are like Intersection, Difference, etc.


6. Dictionary

Here, the Dictionary something like a group of List kinds of data. But, each value has a key associated with it.


References

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