plydata
Pandas
plydata | Pandas | |
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2 | 399 | |
274 | 42,039 | |
- | 0.7% | |
0.0 | 10.0 | |
8 months ago | 5 days ago | |
Python | Python | |
BSD 3-clause "New" or "Revised" License | BSD 3-clause "New" or "Revised" License |
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plydata
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datar: the dplyr in python
from datar import f from datar.dplyr import mutate, filter, if_else from datar.tibble import tibble # or # from datar.all import f, mutate, filter, if_else, tibble df = tibble( x=range(4), y=['zero', 'one', 'two', 'three'] ) df >> mutate(z=f.x) """# output x y z 0 0 zero 0 1 1 one 1 2 2 two 2 3 3 three 3 """ df >> mutate(z=if_else(f.x>1, 1, 0)) """# output: x y z 0 0 zero 0 1 1 one 0 2 2 two 1 3 3 three 1 """ df >> filter(f.x>1) """# output: x y 0 2 two 1 3 three """ df >> mutate(z=if_else(f.x>1, 1, 0)) >> filter(f.z==1) """# output: x y z 0 2 two 1 1 3 three 1 """ Works with plotnine # example grabbed from https://github.com/has2k1/plydata import numpy from datar.base import sin, pi from plotnine import ggplot, aes, geom_line, theme_classic df = tibble(x=numpy.linspace(0, 2*pi, 500)) (df >> mutate(y=sin(f.x), sign=if_else(f.y>=0, "positive", "negative")) >> ggplot(aes(x='x', y='y')) + theme_classic() + geom_line(aes(color='sign'), size=1.2)) https://preview.redd.it/w0hs4m8fyf771.png?width=697&format=png&auto=webp&s=eadd7473a9e3393c2d58531c0b2b12f849c27e5e Easy to integrate with other libraries import klib from pipda import register_verb from datar.datasets import iris from datar.dplyr import pull dist_plot = register_verb(func=klib.dist_plot) iris >> pull(f.Sepal_Length) >> dist_plot() https://preview.redd.it/w8b8ouagyf771.png?width=892&format=png&auto=webp&s=3cc8f04e63be710f593b2b6128073f65cf7ffaa4 For more detailed and advanced usage, see https://pwwang.github.io/datar/
df = tibble( x=range(4), y=['zero', 'one', 'two', 'three'] ) df >> mutate(z=f.x) """# output x y z 0 0 zero 0 1 1 one 1 2 2 two 2 3 3 three 3 """ df >> mutate(z=if_else(f.x>1, 1, 0)) """# output: x y z 0 0 zero 0 1 1 one 0 2 2 two 1 3 3 three 1 """ df >> filter(f.x>1) """# output: x y 0 2 two 1 3 three """ df >> mutate(z=if_else(f.x>1, 1, 0)) >> filter(f.z==1) """# output: x y z 0 2 two 1 1 3 three 1 """ ``` Works with plotnine ```python example grabbed from https://github.com/has2k1/plydata import numpy from datar.base import sin, pi from plotnine import ggplot, aes, geom_line, theme_classic df = tibble(x=numpy.linspace(0, 2*pi, 500)) (df >> mutate(y=sin(f.x), sign=if_else(f.y>=0, "positive", "negative")) >> ggplot(aes(x='x', y='y')) + theme_classic() + geom_line(aes(color='sign'), size=1.2)) ``` ![plotnine](https://github.com/pwwang/datar/raw/master/example.png) Easy to integrate with other libraries ```python import klib from pipda import register_verb from datar.datasets import iris from datar.dplyr import pull dist_plot = register_verb(func=klib.dist_plot) iris >> pull(f.Sepal_Length) >> dist_plot() ``` ![klib](https://github.com/pwwang/datar/raw/master/example2.png) For more detailed and advanced usage, see https://pwwang.github.io/datar/
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[1]: https://github.com/pandas-dev/pandas/issues/53999
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Exploring Open-Source Alternatives to Landing AI for Robust MLOps
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What are some alternatives?
datar - A Grammar of Data Manipulation in python
Cubes - [NOT MAINTAINED] Light-weight Python OLAP framework for multi-dimensional data analysis
Dask - Parallel computing with task scheduling
tensorflow - An Open Source Machine Learning Framework for Everyone
brain-brew - Automated Anki flashcard creation and extraction to/from Csv
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Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Keras - Deep Learning for humans
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
pyexcel - Single API for reading, manipulating and writing data in csv, ods, xls, xlsx and xlsm files
SymPy - A computer algebra system written in pure Python