dython
A set of data tools in Python (by shakedzy)
pycopent
Estimating Copula Entropy (Mutual Information), Transfer Entropy (Conditional Mutual Information), and the statistics for multivariate normality test and two-sample test, and change point detection in Python (by majianthu)
dython | pycopent | |
---|---|---|
2 | 1 | |
490 | 134 | |
- | - | |
7.7 | 6.0 | |
4 months ago | 12 days ago | |
Python | Python | |
MIT License | GNU General Public License v3.0 only |
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.
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.
dython
Posts with mentions or reviews of dython.
We have used some of these posts to build our list of alternatives
and similar projects.
-
How to interpret scatterplot regarding customer purchasing habits
Make a categorical heatmap instead (example see https://github.com/shakedzy/dython/issues/2)
-
Time series prediction problem
to answer question one try just running a simple correlation matrix among your yearly and the average of your daily figures For years 2012+ when you have all four inputs. I frequently use the small convenience library Dython Dython in Github. If your features are very independent then you will not be able to fill in missing values and will need to find other surrogates such as “is my crop largely a fixed percentage of overall exports and are overall exports available for missing years?” If your features are highly dependent then essentially you don’t need them all - both XGBoost and LightGBM have simple fill-in-with-the-mean type imputation of missing values - run across all your data with imputation on and removing low impact features will remove all but one highly interdependent features.
pycopent
Posts with mentions or reviews of pycopent.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-10-19.
-
[P] the copent package v0.2.1 now on PyPI
GitHub: https://github.com/majianthu/pycopent/
What are some alternatives?
When comparing dython and pycopent you can also consider the following projects:
RocketPy - Next generation High-Power Rocketry 6-DOF Trajectory Simulation
DeepPoseKit - a toolkit for pose estimation using deep learning
flopy - A Python package to create, run, and post-process MODFLOW-based models.
transferentropy - Code for the paper "Estimating Transfer Entropy via Copula Entropy"
dash - Data Apps & Dashboards for Python. No JavaScript Required.
taylor - Taylor will tell you why your project is SO late
Machine-Learning-for-Asset-Managers - Implementation of code snippets, exercises and application to live data from Machine Learning for Asset Managers (Elements in Quantitative Finance) written by Prof. Marcos López de Prado.
viper - Simple, expressive pipeline syntax to transform and manipulate data with ease