|
| 1 | +# Suggestions for exploring the notebook collection |
| 2 | + |
| 3 | +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. |
| 4 | + |
| 5 | +A few suggestions for possible user approaches are offered here. A complete listing can be found at the bottom. |
| 6 | + |
| 7 | +-------------- |
| 8 | +## Beginner's approach |
| 9 | + |
| 10 | +A good place to start is on Jupyter itself, from the **Jupyter_Notebooks** folder. |
| 11 | + - Jupyter's own Help menu is excellent. Be sure to notice its features. |
| 12 | + - For Python code, notice the power of |
| 13 | + - _tab_ key for autocomplete suggestions after a period . showing an object's _attributes and methods_ |
| 14 | + - _shift + tab_ keys for documentation on any object whose name the cursor is placed within |
| 15 | + |
| 16 | +**Primer** notebooks are oriented to beginners. |
| 17 | + |
| 18 | +**Pythonic_Data_Analysis** and **Time_Series_Analysis** are good early lessons on code-to-figures workflow. |
| 19 | + |
| 20 | +**Bonus/What to do when things go wrong.ipynb** can help users throughout their journey. |
| 21 | + |
| 22 | +For meteorology work, get oriented with **Metpy_Introduction/Introduction to MetPy.ipynb** |
| 23 | + |
| 24 | + |
| 25 | +-------------- |
| 26 | +## Building your own analyses: suggestions organized by workflow stages |
| 27 | + |
| 28 | +### Inputting data |
| 29 | + - Basic text data |
| 30 | + - Pythonic_Data_Analysis |
| 31 | + |
| 32 | + - NetCDF files |
| 33 | + - netCDF/netCDF-Reading.ipynb |
| 34 | + |
| 35 | + - Meteorology grids and streams |
| 36 | + - Siphon/Siphon Overview.ipynb |
| 37 | + - Bonus/Downloading GFS with Siphon.ipynb |
| 38 | + - Bonus/Siphon_XARRAY_Cartopy_HRRR.ipynb |
| 39 | + - Model_Output/Downloading model fields with NCSS.ipynb |
| 40 | + - Satellite_Data/Working with Satellite Data.ipynb |
| 41 | + |
| 42 | + - Weather observations |
| 43 | + - Skew_T/Upper Air and the Skew-T Log-P.ipynb |
| 44 | + - Surface_Data/Surface Data with Siphon and MetPy.ipynb |
| 45 | + |
| 46 | +### Analysis: derived quantities and statistical summarizations |
| 47 | + |
| 48 | + - NumPy/Numpy Basics.ipynb and NumPy/Intermediate Numpy.ipynb |
| 49 | + - Primer/Numpy and Matplotlib Basics.ipynb |
| 50 | + |
| 51 | +### Graphical outputs: |
| 52 | + |
| 53 | + - Animation/Creating Animations.ipynb |
| 54 | + - CartoPy/CartoPy.ipynb |
| 55 | + - GOES_RGB_Demo/GOES_RGB_Image.ipynb |
| 56 | + - Matplotlib/Matplotlib Basics.ipynb |
| 57 | + - Satellite_Data/GOES_Interactive_Plot.ipynb |
| 58 | + - Skew_T/Upper Air and the Skew-T Log-P.ipynb |
| 59 | + |
| 60 | +### File outputs |
| 61 | + - netCDF/netCDF-Writing.ipynb |
| 62 | + |
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