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Merge pull request #276 from jrleeman/mapes_about
Add about notebooks
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ideas.md

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- xray
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- xarray
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- GIS
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- Expand on some of the more interesting aspects of what we do in the cartopy tutorial
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- Fun things that can be done with Shapely

notebooks/ABOUT_THESE_NOTEBOOKS.md

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# Suggestions for exploring the notebook collection
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Each notebook is a self-contained document, and they can be explored in any order. But their real power is as a set of resources you can adjust and adapt. Once you understand them, you can learn to mix-and-match the examples demonstrated here to construct your own notebooks.
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A few suggestions for possible user approaches are offered here. A complete listing can be found at the bottom.
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--------------
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## Beginner's approach
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A good place to start is on Jupyter itself, from the **Jupyter_Notebooks** folder.
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- Jupyter's own Help menu is excellent. Be sure to notice its features.
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- For Python code, notice the power of
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- _tab_ key for autocomplete suggestions after a period . showing an object's _attributes and methods_
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- _shift + tab_ keys for documentation on any object whose name the cursor is placed within
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**Primer** notebooks are oriented to beginners.
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**Pythonic_Data_Analysis** and **Time_Series_Analysis** are good early lessons on code-to-figures workflow.
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**Bonus/What to do when things go wrong.ipynb** can help users throughout their journey.
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For meteorology work, get oriented with **Metpy_Introduction/Introduction to MetPy.ipynb**
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--------------
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## Building your own analyses: suggestions organized by workflow stages
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### Inputting data
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- Basic text data
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- Pythonic_Data_Analysis
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- NetCDF files
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- netCDF/netCDF-Reading.ipynb
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- Meteorology grids and streams
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- Siphon/Siphon Overview.ipynb
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- Bonus/Downloading GFS with Siphon.ipynb
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- Bonus/Siphon_XARRAY_Cartopy_HRRR.ipynb
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- Model_Output/Downloading model fields with NCSS.ipynb
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- Satellite_Data/Working with Satellite Data.ipynb
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- Weather observations
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- Skew_T/Upper Air and the Skew-T Log-P.ipynb
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- Surface_Data/Surface Data with Siphon and MetPy.ipynb
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### Analysis: derived quantities and statistical summarizations
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- NumPy/Numpy Basics.ipynb and NumPy/Intermediate Numpy.ipynb
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- Primer/Numpy and Matplotlib Basics.ipynb
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### Graphical outputs:
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- Animation/Creating Animations.ipynb
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- CartoPy/CartoPy.ipynb
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- GOES_RGB_Demo/GOES_RGB_Image.ipynb
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- Matplotlib/Matplotlib Basics.ipynb
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- Satellite_Data/GOES_Interactive_Plot.ipynb
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- Skew_T/Upper Air and the Skew-T Log-P.ipynb
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### File outputs
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- netCDF/netCDF-Writing.ipynb
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