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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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How to Read CSV file Data in Python

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Here is a way to read  CSV files  in Python pandas. The packages you need to import are numpy and pandas. On the flip side, f or Text files, you don't need to import these special libraries since python by default support it. Python pandas read_csv >>> import numpy as np >>> import pandas as pd To see how pandas handle this kind of data, we'll create a small CSV file in the working directory as ch05_01.csv. white, red, blue, green, animal 1,5,2,3,cat  2,7,8,5,dog  3,3,6,7,horse  2,2,8,3,duck  4,4,2,1,mouse Since this file is comma-delimited , you can use the read_csv() function to read its content and convert it to a dataframe object. >>> csvframe = pd.read_csv('ch05_01.csv') >>> csvframe white red blue green animal 0 1 5 2 3 cat 1 2 7 8 5 dog 2 3 3 6 7 horse 3 2 2 8 3 duck 4 4 4 2 1 mouse Python reading text files Sinc...
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