While Pandas covers some basic calculations, SciPy is better suited for more complicated tasks, such as confirming if distributions are significantly different, calculating confidence intervals, and comparing multiple datasets. Statistical analysis made easy in Python with SciPy and pandas DataFrames (Randy Olson) - This will give you a good idea of when to switch over from pandas to SciPy for statistical analysis.In addition to the library and stack of tools, SciPy also refers to the SciPy community and a group of conferences dedicated to scientific computing in Python-such as SciPy or EuroSciPy. SciPy is a set of numerical operations built on top of NumPy's ndarray. SciPy is most commonly used in academic fields such as earth science and astronomy, but data scientists might find its linear algebra module useful.Īlthough SciPy and NumPy are sometimes referred to interchangeably, they're not the same. This environment is known as the SciPy stack, and includes NumPy, matplotlib, and pandas. It was created by Travis Oliphant, Eric Jones, and Pearu Peterson in 2001 as part of the effort to create a complete scientific computing environment in Python. SciPy is a Python library used for scientific computing and statistical analysis.
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