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---
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title: "Pandas Extending & Plotting"
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numberOfPeople: "5-10" # How many people you expect to be able to accommodate.
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pythonLevel: "Intermediate" # Any, Beginner, Intermediate, or Advanced.
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contactPerson: # The main person to reach out to regarding the sprint.
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name: "Julian Harbeck"
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email: harbeck@tu-berlin.de
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github: https://github.com/Julian-Harbeck
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twitter:
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links: # Add as many links as relevant.
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- title: "Project pandas GitHub repo"
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url: "https://github.com/pandas-dev/pandas/"
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- title: "Project astropy GitHub repo"
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url: "https://github.com/astropy/astropy"
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- title:
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"Project astropy-pandas GitHub repo (extending pandas with astropy object
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support)"
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url: "https://github.com/janpipek/pandas-units-extension"
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- title:
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"Project skyfield-pandas GitHub repo (extending pandas with skyfield
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object support)"
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url: "https://github.com/Julian-Harbeck/pandas-skyfield-extension"
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---
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Pandas has a powerful extension API that allows other libraries to create their
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own dtype and ExtensionArray (EA) and define their behaviour, e.g. arithmetic
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operation with scalars and arrays. In the past year I have both worked on the
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pandas EA API (e.g. adding a plotting API) and implementing/updating EA for
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other packages (astropy, skyfield, see links above). In `astropy-pandas` we have
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implemented an EA supporting `Quantity` objects, arrays with a physical unit
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attached to them. This includes arithmetic operations, but also unit conversions
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(`ft` -> `m`) or reductions like `.mean()`, more examples can be found in
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[doc/units.ipynb](https://github.com/janpipek/pandas-units-extension/blob/main/doc/units.ipynb).
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`skyfield-pandas` implements an EA wrapper for the Skyfield library for orbit
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propagation of satellites and fast vectorized operations on them (exampels see
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[doc/skyfield_position.ipynb](https://github.com/Julian-Harbeck/pandas-skyfield-extension/blob/main/doc/skyfield_position.ipynb)).
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For this sprint I am open to work on one or more of the following topics
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depending where the most interested is in:
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- Conitinue working on one of the two existing extensions, giving an
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introduction how they work and implement smaller new features (e.g. JSON
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serialization, accumulative operations) including tests.
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- Start the development of an entirely new EA. Which array-like object did you
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always wanted to be compatible with pandas including vectorized operations?
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Let's develop a first working prototype of an EA supporting the basic
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functionallity.
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- Working on pandas directly, how to write a good first issue, how to implement
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and test a new feature locally and how to create a good PR. I am not an export
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on the whole pandas package yet as I have only joined the team recently, but I
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have worked especially on the ExtensionArray and plotting API.

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