[python] What are the differences between Pandas and NumPy+SciPy in Python?

They both seem exceedingly similar and I'm curious as to which package would be more beneficial for financial data analysis.

This question is related to python numpy scipy pandas

The answer is


Numpy is required by pandas (and by virtually all numerical tools for Python). Scipy is not strictly required for pandas but is listed as an "optional dependency". I wouldn't say that pandas is an alternative to Numpy and/or Scipy. Rather, it's an extra tool that provides a more streamlined way of working with numerical and tabular data in Python. You can use pandas data structures but freely draw on Numpy and Scipy functions to manipulate them.


Pandas offer a great way to manipulate tables, as you can make binning easy (binning a dataframe in pandas in Python) and calculate statistics. Other thing that is great in pandas is the Panel class that you can join series of layers with different properties and combine it using groupby function.


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