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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: How to Work With Various File Formats

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Here is Python logic that shows Parse and Read Different Files in Python. The formats are XML, JSON, CSV, Excel, Text, PDF, Zip files, Images, SQLlite, and Yaml. Python Reading Files import pandas as pd import json import xml.etree.ElementTree as ET from PIL import Image import pytesseract import PyPDF2 from zipfile import ZipFile import sqlite3 import yaml Reading Text Files # Read text file (.txt) def read_text_file(file_path):     with open(file_path, 'r') as file:         text = file.read()     return text Reading CSV Files # Read CSV file (.csv) def read_csv_file(file_path):     df = pd.read_csv(file_path)     return df Reading JSON Files # Read JSON file (.json) def read_json_file(file_path):     with open(file_path, 'r') as file:         json_data = json.load(file)     return json_data Reading Excel Files # Read Excel file (.xlsx, .xls) def read_excel_file(file_path):    ...
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