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here I use ~/.bash_profile).\n\n\techo 'export PATH=$HOME/anaconda3/bin:$PATH' \u003e\u003e ~/.bash_profile\n\nSource (install) your ~/.bash_profile or ~/.bashrc\n\n\tsource ~/.bash_profile\n\nFor those who need Python 2.7\n\n\tconda create -n py2 python=2.7\n\nTo activate the environment\n\n   \t source activate py2\n\nInstall additional packages using pip or conda install\n\n\tconda install -c conda-forge cartopy\n\n\tpip install geopandas\n\n### How to start using Jupyter notebooks\n\nChange the port number between 7000 and 8000, and in a terminal input the following\n\n\tjupyter notebook --no-browser --port=####\n\nFor your convenience, add a shortcut called \"jupy\" to your ~/.bash_profile to activate\n\n    echo \"alias jupy='jupyter notebook --no-browser --port=####'\" \u003e\u003e ~/.bash_profile\n\n\nPort forwarding with Putty to access remote server's Jupyter notebook on local browser\n\n![Port Forwarding in Putty](https://github.com/ahuang11/gogopy/blob/master/putty_config.png \"Port Forwarding in Putty\")\n\n1. If you use putty, before connecting to the session, on the left, follow these tabs\n\n\tConnection \u003e SSH \u003e Tunnels\n\n2. In source port replace #### with the port number you chose earlier between 7000 and 8000\n\n\t####\n\n3. In destination add localhost:#### replacing #### with the port number you chose earlier\n\n\tlocalhost:####\n\n4. Click Add\n\n5. Now you should see it in the list\n\n    L####       localhost:####\n\n6. BEFORE CLICKING OPEN, head back to the Session on the left\n\n7. Click the corresponding saved sesssion, and press Save so you don't have to repeat!\n\nNow in your browser input the URL that `jupyter notebook --no-browser --port=####` displayed and you have access!\n\n\tCopy/paste this URL into your browser when you connect for the first time,\n\t    to login with a token:\n\t\thttp://localhost:####/?token=????????????????????????????????????????????????\n\n### Potentially useful packages\n- numpy (np) - essential number crunching and transformation; found in most packages\n- pandas (pd) - extremely useful labeled tabular data processor\n- cartopy (ccrs) - succeeding `basemap` for geographic map projections\n- holoviews (hv) - high level plotting API on top of `matplotlib` and `bokeh`\n- geoviews (gv) - high level plotting API on top of `holoviews` for geographical maps\n- datashader - big data plotter, capable of handling millions of data points\n- dask - scalable, multiprocessing and easy to use wrapper\n- xarray - multidimensional data structure processor bult on top of `netCDF4` and `pandas`\n- geopandas - GIS processor built on top of `fiona`, `pandas`, and `shapely`\n- matplotlib (plt) - old fashion, but robust, data plotter\n- bokeh - low level interactive data plotter\n- scikit-learn - machine learning for regression, classification, clustering\n- keras - high level deep learning API on top of `tensorflow` and `theano`\n- metpy - collection of tools for meteorology\n- xesmf - high level geospatial regridding and interpolation on top of `esmpy`\n\n#### Demonstration topics\nSee some of these packages demonstrated [here!](https://github.com/ahuang11/gogopy/blob/master/random_examples.pdf)\n- Why not jet\n- Read csv\n- High level plotting\n- Interactive plotting\n- Read unformatted tables\n- Read netcdf\n- Get climatology\n- Get daily anaomalies\n- Interactive map\n- Read grib\n- Read plain binary / flatfiles\n- Read shapefile\n- Geographical maps\n\n#### `pip install` vs `conda install`\n- `pip install` runs much quicker than than `conda install`\n- `pip install` works best for standalone packages that doesn't require complex compiling\n- `conda install` is useful with packages that require complex compiling (e.g. cartopy, gdal)\n- In most cases, follow the `Installation Instructions` page from documentation\n- Or just try doing `pip install packagename`\n- If that fails, `conda install packagename` or `conda install -c conda-forge packagename`\n\n### Additional Resources\n\nFor a wonderfully written data science handbook\n\nhttps://jakevdp.github.io/PythonDataScienceHandbook/\n\nFor standard Python styling guidelines\n\nhttps://www.python.org/dev/peps/pep-0008/\n\nUseful Jupyter magic\n\n    %timeit\n    %load some_file.py\n\nMake Jupyter notebook aware of other virtual environments\n\n    source activate some_environment\n    pip install ipykernel\n\nAdd Jupyter extensions\n\n    conda install -c conda-forge jupyter_contrib_nbextensions\n\nMake Jupyter cell width take up whole screen\n\n    from IPython.core.display import display, HTML\n    display(HTML(\"\u003cstyle\u003e.container { width:100% !important; }\u003c/style\u003e\"))\n\nFor those who need grib\n\n    conda create --name pynio --channel conda-forge/label/dev python=3.6 xarray pynio\n    conda install libgdal\n    source activate pynio\n\nMy philosophy: personalize your setup; it'll make coding that much more enjoyable!\n\nHere's my setup:\n- Jupyter notebook (interactive prototyping)\n- Sublime Text 3 (production code scripting; [demonstration GIF](https://www.sublimetext.com/))\n- MobaXterm (side by side SSH and WinSCP and tabs)\n\nIdeas for personalizing:\n- Set up your favorite keyboard shortcuts (like ctrl + v for pasting in terminal)\n- Write aliases for common commands (see my [.bash_profile](https://github.com/ahuang11/gogopy/blob/master/.bash_profile))\n- Configure settings (see my [.screenrc](https://github.com/ahuang11/gogopy/blob/master/.screenrc) and [ipython_config.py](https://github.com/ahuang11/gogopy/blob/master/ipython_config.py))\n\n### Acknowledgements\nSome credits goes to the weather overlord chilly T (bill-turner) for taking ahuang11 under his wing and\nletting him flourish into the beautiful coding butterfly that he is today. :)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fahuang11%2Fgogopy","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fahuang11%2Fgogopy","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fahuang11%2Fgogopy/lists"}