tidypolars
redframes
tidypolars | redframes | |
---|---|---|
7 | 10 | |
309 | 295 | |
- | - | |
8.0 | 1.4 | |
3 months ago | about 1 year ago | |
Python | Python | |
MIT License | BSD 2-clause "Simplified" License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
tidypolars
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Modern Polars: a side-by-side comparison with Pandas
I recommend trying tidypolars
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Modern Polars: an extensive side-by-side comparison of Polars and Pandas
There’s a tidypolars package that appears to be well-maintained https://github.com/markfairbanks/tidypolars
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R Tidyverse / dplyr is life changing!
tidypolars is one I’ve seen. Still very new, but it’s built on top of polars (which is a little more like dplyr to begin with), so it’s much faster than pandas.
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Introducing tidypolars - a Python data frame package with syntax familiar to R tidyverse users
If I misunderstood your question - feel free to open a discussion with a small code example and we can talk through how you can do it in tidypolars.
- Introducing tidypolars - a Python data frame package for R tidyverse users
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Tidyverse appreciation thread
Try out tidypolars. It's really close to tidyverse syntax and it's a lot faster than pandas as well
redframes
- What is something you wish there was a Python module for?
- Redframes: General Purpose Data Manipulation Library
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Modern Polars: an extensive side-by-side comparison of Polars and Pandas
I'm not GP, but I find the pandas API incredibly inconsistent and difficult to remember how to do simple transformations. For example, it sometimes overloads operators because it doesn't use built in language features like lambdas. There are reasons for the inconsistency, but using the alternatives like R's tidyverse or Julia's DataFramess.jl is like night and day for me.
I found RedFrames [1] recently which wraps Pandas dataframes with a more consistent interface, it's probably what I'd use if I had to write data transformations that had to be compatible with Pandas.
[1] https://github.com/maxhumber/redframes
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Ask HN: How you maintain your daily log?
[2022-10-23 14:11:15]: Question []: should we use Red Frames (https://github.com/maxhumber/redframes) in addition to Pandas? Criteria for decision? @me #projectLion
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Python 3.11.0 final is now available
If you like writing chain-able pandas, you should check out: https://github.com/maxhumber/redframes
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Add your own custom methods to third-party types with this pattern
I intend to use this pattern in my redframes library to hijack some pd.DataFrame methods.
- GitHub - maxhumber/redframes: [re]ctangular[d]ata[frames]
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Ask HN: What are you doing this weekend?
I'm dog-fooding my new Python data manipulation library, redframes: https://github.com/maxhumber/redframes
To help me prep for my Fantasy Hockey Draft next week!
- redframes, a new data manipulation library for ML and visualization
- Show HN: Redframes, a Python data manipulation library like dplyr
What are some alternatives?
polars - Dataframes powered by a multithreaded, vectorized query engine, written in Rust
xgboost - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
tidytable - Tidy interface to 'data.table'
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
dtplyr - Data table backend for dplyr
Keras - Deep Learning for humans
db-benchmark - reproducible benchmark of database-like ops
tensorflow - An Open Source Machine Learning Framework for Everyone
extendr - R extension library for rust designed to be familiar to R users.
MLflow - Open source platform for the machine learning lifecycle
Apache Arrow - Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing
pydeep - Deep learning in Python