SciPy
This chapter works through SciPy Introduction, the anchor topic behind SciPy Tutorial.
SciPy is a scientific computation library that uses NumPy underneath.
SciPy is a scientific computation library that uses NumPy underneath.
If you have Python and PIP already installed on a system, then installation of SciPy is very easy.
As SciPy is more focused on scientific implementations, it provides many built-in scientific constants.
Optimizers are a set of procedures defined in SciPy that either find the minimum value of a function, or the root of an equation.
Sparse data is data that has mostly unused elements (elements that don't carry any information ).
Graphs are an essential data structure.
Spatial data refers to data that is represented in a geometric space.
We know that NumPy provides us with methods to persist the data in readable formats for Python. But SciPy provides us with interoperability with Matlab as well.
Interpolation is a method for generating points between given points.
In statistics, statistical significance means that the result that was produced has a reason behind it, it was not produced randomly, or by chance.