at.Py - bite-sized Python tips for atmosci
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Introducing at.Py
Bite-sized tips about Python, tailored for atmospheric scientists!
Dec 4, 2022
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at.Py
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131. 🐼 pandas for all your datetime needs
📆 Don't write your own date string parser; simply use pandas to parse it for you!
Sep 21, 2023
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at.Py
1
130. Speed up loading chunks of data with zarr
In the previous example, we rendered the satellite imagery from a TIF file.
Sep 20, 2023
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at.Py
129. 10848x10848 pixels, high-res satellite image taking forever to render?
You may not need the full resolution rendered on a global extent.
Sep 19, 2023
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at.Py
128. Want to compare YTD precipitation to climatology?
🐼 #pandas has a built-in cumsum method that will calculate the cumulative sum, grouped by year.
Sep 15, 2023
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at.Py
127. Unsure of when to use threads or processes?
Use threads for IO tasks (reading/writing to disk, downloading data) or subprocesses.
Sep 14, 2023
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at.Py
126. Want to interpolate an xarray Dataset?
🌟 The `interp` method is user-friendly!
Sep 13, 2023
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at.Py
2
125. Want to get all the unique station names without any imports?
Eliminate loops, which are extremely inefficient for large lists, and ifs when handling duplicates by using the built-in data type, `set`.
Sep 12, 2023
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at.Py - bite-sized Python tips for atmosci
Bite-sized tips about Python, tailored for atmospheric scientists! Subscribe for highlights on data ingestion, processing, analysis, and visualization!
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at.Py - bite-sized Python tips for atmosci
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