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How-To Geek on MSNPython Beginner's Guide to Processing DataThe main reason to use Python is that you get a lot more options than what's included in most spreadsheets. Spreadsheets are ...
Python libraries like Pandas, NumPy, SciPy, and Matplotlib streamline data cleaning, statistical analysis, and visualization directly within Excel.
Numpy made a change to their repr and pandas continues to return Numpy types as before, only the repr has changed and that should not really be considered a pandas issue. However, to be fair, many ...
Python, being one of the most dynamic landscape in data science, has become a force to be reckoned with, with its uniform set of libraries that are tailored for data manipulation, analysis and ...
Want to get better performance with Python? Here's how to use NumPy to toe the 'invisible line' of data and memory transfers and optimize efficiency.
Here’s how to use Cython to accelerate array iterations in NumPy. NumPy gives Python users a wickedly fast library for working with data in matrixes.
Want to start a large project? Keep away from Python. On a large scale it isn’t as awesome as you think — here's what to use instead.
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