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| author | Marcel Ribeiro-Dantas <ribeirodantasdm@gmail.com> | 2024-06-21 02:11:51 -0300 |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2024-06-21 02:11:51 -0300 |
| commit | 30edebae889893e1b657b1a2326576450f2f56d4 (patch) | |
| tree | 3af5406b8c1e08c9ffac81a9db86cb7b62dffbf6 /pythonstatcomp.html.markdown | |
| parent | 7611e1f1904619b58333a8c564500d9cb2b584d9 (diff) | |
| parent | 790a78e3cf1ec8610699ed34255d459f84a92a18 (diff) | |
Merge pull request #4969 from verhovsky/remove-bare-links
Remove bare links
Diffstat (limited to 'pythonstatcomp.html.markdown')
| -rw-r--r-- | pythonstatcomp.html.markdown | 9 |
1 files changed, 5 insertions, 4 deletions
diff --git a/pythonstatcomp.html.markdown b/pythonstatcomp.html.markdown index 38bffd88..1e8a12b8 100644 --- a/pythonstatcomp.html.markdown +++ b/pythonstatcomp.html.markdown @@ -13,7 +13,7 @@ This is a tutorial on how to do some typical statistical programming tasks using """ To get started, pip install the following: jupyter, numpy, scipy, pandas, matplotlib, seaborn, requests. Make sure to do this tutorial in a Jupyter notebook so that you get - the inline plots and easy documentation lookup. The shell command to open + the inline plots and easy documentation lookup. The shell command to open one is simply `jupyter notebook`, then click New -> Python. """ @@ -227,8 +227,9 @@ sns.lmplot("BirthY", "EstAge", data=hre) If you want to learn more, get _Python for Data Analysis_ by Wes McKinney. It's a superb resource and I used it as a reference when writing this tutorial. -You can also find plenty of interactive IPython tutorials on subjects specific to your interests, like Cam Davidson-Pilon's <a href="http://camdavidsonpilon.github.io/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/" Title="Probabilistic Programming and Bayesian Methods for Hackers">Probabilistic Programming and Bayesian Methods for Hackers</a>. +You can also find plenty of interactive IPython tutorials on subjects specific to your interests, like Cam Davidson-Pilon's [Probabilistic Programming and Bayesian Methods for Hackers](http://camdavidsonpilon.github.io/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/). Some more modules to research: - - text analysis and natural language processing: nltk, http://www.nltk.org - - social network analysis: igraph, http://igraph.org/python/ + + - text analysis and natural language processing: [nltk](http://www.nltk.org) + - social network analysis: [igraph](http://igraph.org/python/) |