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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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Big data real role to help Real estate business

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How big data helps real estate is trending today. When people buy real estate and its dependencies you can get from analytics

Advantages of Big-data in Real estate

  1. Study the data from real estate consume
  2. Understand the buyers
  3. Loan dependencies and role of consumers
  4. Sale activities by agents
  5. Sales boost

Role of Big Data

Real estate agents need to check lot of data sources to identify sales pitch and formula to boost sales. The first point is agents should understand the requirements of consumers or buyers of real estate.

References

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