Python Perf: Adding performance resources related to Pandas, Numpy an…

…d Numba
yml-blog · Aug 14, 2020 · 81ef4e9 · 81ef4e9
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@@ -196,6 +196,40 @@ See [Machine Learning Testing](./details/julia-python-and-r.md#testing)
 - [Python and performance](https://github.com/ameroueh/performance)
 - [NumPy aware dynamic Python compiler using LLVM ](https://github.com/ameroueh/numba) | [Numba](http://numba.pydata.org/)
 - [Profiling in Python](https://github.com/mkunesch/profiling-talk) - by [Markus Kunesch](https://github.com/mkunesch)
+  - Profiling: [Profiling with Pycharm 1](https://stackoverflow.com/questions/32926847/profiling-a-python-program-with-pycharm-or-any-other-ide#32926882) | [Profiling with Pycharm 2](https://softwaretester.info/python-profiling-with-pycharm-community-edition/) | [PyCharm and cProfile](https://intellij-support.jetbrains.com/hc/en-us/community/posts/115000057970-Is-there-a-way-to-force-PyCharm-to-use-cProfile-) | [Call tree with Python Profilers](https://stackoverflow.com/questions/4544784/how-can-you-get-the-call-tree-with-python-profilers)
+- Speed up Python/Pandas
+  - [How to optimise your Pandas code](https://kanoki.org/2019/01/09/how-to-optimize-your-pandas-code/)
+  - [Python Itertools: For a faster and memory efficient code](https://kanoki.org/2019/02/08/python-itertools/)
+  - [Python/Pandas performance](https://www.youtube.com/results?search_query=%2Bpython+%2Bpandas+%2Bperformance) ([notebook](https://github.com/softhints/python/blob/master/notebooks/pandas/How_to_Optimize_and_Speed_Up_Pandas.ipynb))
+  - [High-Performance Pandas: eval() and query()](https://jakevdp.github.io/PythonDataScienceHandbook/03.12-performance-eval-and-query.html)
+  - [Fast, Flexible, Easy and Intuitive: How to Speed Up Your Pandas Projects](https://realpython.com/fast-flexible-pandas)
+  - [Using Cython Nuitka Numba ShedSkin Pythran Transonic](https://twitter.com/ianozsvald/status/1226436048428900353)
+  - [using Dask / Vaex / Modin to speed up Pandas-like operations](https://twitter.com/ianozsvald/status/1225748724363780096)
+- Misc
+  - [lambda functions or nested functions ('def')?](https://stackoverflow.com/questions/134626/which-is-more-preferable-to-use-lambda-functions-or-nested-functions-def)
+  - Pandas GroupBy speedup
+    - [Improving the performance of Pandas Group](https://stackoverflow.com/questions/47392758/improving-the-performance-of-pandas-groupby)
+    - [Pandas groupby](https://realpython.com/pandas-groupby/)
+    - [Faster pandas with parallel processing](https://towardsdatascience.com/faster-pandas-with-parallel-processing-cudf-vs-modin-f2318c594084)
+    - [Optimize Custom Grouping Function](https://medium.com/dunder-data/pandas-challenge-001-optimize-custom-grouping-function-44a9f2f321f8)
+    - [Speed up pandas 4x](https://www.kdnuggets.com/2019/11/speed-up-pandas-4x.html)
+- Vectorizations
+  - [Python & Vectorization](https://towardsdatascience.com/python-vectorization-5b882eeef658?fbclid=IwAR0sS8uNZlf_iiXw3_qwvUXxh-0UlrJ_nNIFlPJ0hBSHFvGtW2y2fFETqsQ)
+  - [SO: what-is-vectorization?](https://stackoverflow.com/questions/1422149/what-is-vectorization)
+  - [numpy.vectorize()](https://numpy.org/doc/stable/reference/generated/numpy.vectorize.html)
+  - [Array Programming With NumPy: What is Vectorization?](https://realpython.com/numpy-array-programming/#what-is-vectorization)
+  - [numba.vectorize()](https://numba.pydata.org/numba-doc/dev/user/vectorize.html)
+  - [Fast, Flexible, Easy and Intuitive: How to Speed Up Your Pandas Projects](https://realpython.com/fast-flexible-pandas/) (**See Vectorization section**)
+- [numba](http://numba.pydata.org/)
+  - [Using numba](https://tedboy.github.io/pandas/enhancingperf/enhancingperf2.html)
+  - [Performance Tips](http://numba.pydata.org/numba-doc/latest/user/performance-tips.html)
+    - [njit explained](https://github.com/numba/numba/issues/3523)
+  - [Compiling Python code with @jit](https://numba.pydata.org/numba-doc/latest/user/jit.html)
+    - [Automatic parallelization with @jit](https://numba.pydata.org/numba-doc/latest/user/parallel.html#numba-parallel)
+  - [numba.vectorize()](https://numba.pydata.org/numba-doc/dev/user/vectorize.html)
+
+
+
 - High Performance Python talk by [Ian Oszvald](https://twitter.com/ianozsvald/): Blogs: [1](https://ianozsvald.com/2019/11/16/higher-performance-python-at-pydatacambridge-2019/) o [2](https://ianozsvald.com/2019/11/22/higher-performance-python-odsc-2019/)  | [Slides](https://speakerdeck.com/ianozsvald/higher-performance-python-odsc-2019) | [Useful resources shared](https://twitter.com/DataChaz/status/1197608275606413312)
   - [Making Pandas Fly (EuroPython 2020)](https://speakerdeck.com/ianozsvald/making-pandas-fly-europython-2020) | [Blog](https://ianozsvald.com/2020/07/24/making-pandas-fly-at-europython-2020/)
   - [Making Pandas Fly (PyDataAmsterdam 2020)](https://speakerdeck.com/ianozsvald/making-pandas-fly-pydataamsterdam-2020) | [Blog](https://ianozsvald.com/2020/06/23/making-pandas-fly-for-pydataamsterdam-2020/)