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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...

Data analyst in FMCG sector the real opportunities

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[Demand for data analytics in FMCG] Data analyst is a great demanding career in FMCG sector. The below are the key areas where data analytics can be applied in FMCG sector. There are many areas in FMCG sector one can get great insights. I have given some most useful thought that are being used in FMCG industry. The data engineer /Scientist must have great business knowledge to get true insights. However, as a software developer, this is just a working on analytics software as per guidelines prescribed by data scientists. Consumers  Business questions: Where are your consumers? Can you identify the characteristics that bond your consumers to the brands they buy? Can you segment your consumers using those characteristics and create a consumer purchase decision tree? Can you access and translate the sentiment that your customers are saying about your company, your products and your customer service? Can you share data with your retail and convenience store customers o...