chain-ops-python
data_algebra
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chain-ops-python | data_algebra | |
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2 | 5 | |
0 | 113 | |
- | 0.9% | |
10.0 | 8.5 | |
over 1 year ago | 5 months ago | |
Python | ||
- | BSD 3-clause "New" or "Revised" License |
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chain-ops-python
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Modern Pandas (Part 2): Method Chaining
You don't need pandas to do chaining. It's a one-liner in pure python: https://github.com/tpapastylianou/chain-ops-python
Not to mention, it's a lot more debuggable this way (which is generally the biggest downside to most specialised chaining approaches).
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More Intuitive Partial Function Application in Python
This is great. I will use it with my python chaining approach: https://github.com/tpapastylianou/chain-ops-python
My only grief is that decorator, which forces you to wrap existing functions anyway (same way I had to define lambdas in my example anyway).
Do you have any insight on that?
data_algebra
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Modern Pandas (Part 2): Method Chaining
There are a number of packages in Python specializing in variations of piped processing in Pandas. My own is this one: https://github.com/WinVector/data_algebra .
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Siuba – A Dplyr Port to Python
Neat. I've been working on my own "piped-Codd" style system I call the "data algebra" https://github.com/WinVector/data_algebra
I use method chaining as the composing notation.
What are some alternatives?
dataiter - Python classes for data manipulation
siuba - Python library for using dplyr like syntax with pandas and SQL
mito - The mitosheet package, trymito.io, and other public Mito code.
pandas-profiling - Create HTML profiling reports from pandas DataFrame objects [Moved to: https://github.com/ydataai/pandas-profiling]
polars - Dataframes powered by a multithreaded, vectorized query engine, written in Rust
ydata-profiling - 1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.