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Showing posts with the label Key-value Data

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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 Access Dictionary Key-Value Data in Python

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Use for-loop to read dictionary data in python. Here's an example of reading dictionary data. It's helpful to use in real projects. Python program to read dictionary data yearly_revenue = {    2017 : 1000000,    2018 : 1200000,    2019 : 1250000,    2020 : 1100000,    2021 : 1300000,  } total_income = 0 for year_id in yearly_revenue.keys() :   total_income+=yearly_revenue[year_id]   print(year_id, yearly_revenue[year_id]) print(total_income) print(total_income/len(yearly_revenue)) Output 2017 1000000 2018 1200000 2019 1250000 2020 1100000 2021 1300000 5850000 1170000.0 ** Process exited - Return Code: 0 ** Press Enter to exit the terminal Explanation The input is dictionary data. The total revenue sums up for each year. Notably, the critical point is using the dictionary keys method. References Python in-depth and sample programs
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