@@ -4,12 +4,33 @@ slug: scipy | |||
| 4 | 4 | sortorder: 0319 | |
| 5 | 5 | toc: False | |
| 6 | 6 | sidebartitle: SciPy | |
| 7 | - meta: SciPy | ||
| 7 | + meta: SciPy is an umbrella project for many open source data analysis libraries such as NumPy, pandas and Matplotlib. | ||
| 8 | 8 | ||
| 9 | 9 | ||
| 10 | 10 | # SciPy | |
| 11 | + [SciPy](https://www.scipy.org/) is a collection of open source code libraries | ||
| 12 | + for math, science and engineering. [NumPy](/numpy.html), | ||
| 13 | + [Matplotlib](/matplotlib.html) and [pandas](/pandas.html) are libraries | ||
| 14 | + that fall under the SciPy project umbrella. | ||
| 15 | + | ||
| 16 | + [Blaze](http://blaze.pydata.org/) is a similar, but separate, ecosystem | ||
| 17 | + with additional tools for wrangling, cleaning, processing and analyzing data. | ||
| 11 | 18 | ||
| 12 | 19 | ||
| 13 | 20 | ### SciPy resources | |
| 14 | - * [SciPy Lecture notes](http://www.scipy-lectures.org/) | ||
| 21 | + Take a look at the individual pages for [NumPy](/numpy.html), | ||
| 22 | + [Matplotlib](/matplotlib.html) and [pandas](/pandas.html) for tutorials | ||
| 23 | + specific to those projects. The following resources are broader walkthroughs | ||
| 24 | + for the SciPy ecosystem: | ||
| 25 | + | ||
| 26 | + * [SciPy Lecture notes](http://www.scipy-lectures.org/) goes into the | ||
| 27 | + overall Python scientific computing ecosystem and how to use it. | ||
| 28 | + | ||
| 29 | + * The [SciPy Cookbook](http://scipy-cookbook.readthedocs.io/) contains | ||
| 30 | + instructions for various SciPy packages that were previously hosted | ||
| 31 | + on the SciPy wiki. | ||
| 15 | 32 | ||
| 33 | + * [Lectures in Quantitative Economics: SciPy](https://lectures.quantecon.org/py/scipy.html) | ||
| 34 | + provides a good overview of SciPy compared to the specific NumPy | ||
| 35 | + project, as well as explanations for the wrappers SciPy provides | ||
| 36 | + over lower-level FORTRAN libraries. | ||
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