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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...

Google Analytics - Training.PDF

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Google Analytics can track data from a shopping cart on your own or other, domains with the addition of some code. If your website initiates a purchase checkout process on a separate store site (for example, if you send customers from www.mystore.com to www.securecart.com), you just have to add some tracking code to your store site and the shopping cart pages on the host site. The specific code can be found in the Analytics Help Center in the article titled, “How do I use Google Analytics to track a 3rd-party shopping cart?” Read more here: http://static.googleusercontent.com/media/www.google.com/en//grants/education/Google_Analytics_Training.pdf