sspipe VS siuba

Compare sspipe vs siuba and see what are their differences.

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sspipe siuba
1 25
145 1,101
0.0% -
0.0 7.5
almost 2 years ago 8 months ago
Python Python
MIT License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.

sspipe

Posts with mentions or reviews of sspipe. We have used some of these posts to build our list of alternatives and similar projects.

siuba

Posts with mentions or reviews of siuba. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-04-04.

What are some alternatives?

When comparing sspipe and siuba you can also consider the following projects:

tsflex - Flexible time series feature extraction & processing

Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

kindleServer - This project serve HTML files (and a few more) saved in your computer with a UI suitable for Kindle web browser. On top of that, it include a Read Mode (thanks to ReadabiliPy) to display the text in a comfortable size without have to use the 'Article Mode' in Kindle web browser.

dtale - Visualizer for pandas data structures

concrete-numpy - Concrete-Numpy: A library to turn programs into their homomorphic equivalent.

Altair - Declarative statistical visualization library for Python

seaborn - Statistical data visualization in Python

q - q - Run SQL directly on delimited files and multi-file sqlite databases

data-science-ipython-notebooks - Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

vinum - Vinum is a SQL processor for Python, designed for data analysis workflows and in-memory analytics.

Dask - Parallel computing with task scheduling

DataFramesMeta.jl - Metaprogramming tools for DataFrames