semvec/pypi-packages huggingface dataset:
xldiff 0.1.0
A dead-simple command line diffing of datasets stored in Excel
Requires Python: >=3.6

# XL Diff

A dead-simple command line diffing of datasets stored in Excel
format (.xlsx).

## Usage

```
python -m xldiff file_left.xlsx file_right.xlsx
```

If the datasets match then the program will exit successfully
and produce no output. If they do not match then the first
non-matching row from the "left" and the "right" versions will
be printed and the program will terminate with a non-zero
exit code.

**OK, but what's it for?** Mostly to make it easier to verify
that data has been moved successfully from one system to another
or that a new "version" of a dataset has actually changed.
compass-ts 0.0.13
Python module dealing with univariate and multivariate time series forecasting.
Requires Python: >=3.6

# Compass-TS Library
![Project Status: WIP â€“ Initial development is in progress, but there has not yet been a stable, usable release suitable for the public.](https://www.repostatus.org/badges/latest/wip.svg)

Compass-TS is a `Python module` dealing with **univariate and multivariate time series forecasting**. It provides classes and functions that allows ease of application of commonly used visualisation, statistical or machine learning packages for time series forecasting that include `sklearn, xgboost, statsmodel, tsfresh, matplotlib and seaborn`. Steps in time series forecasting are made easier with functions that can be called for data visualisation and exploration, data transformation, feature engineering, model validation, model prediction and model evaluation.
TensorMap 0.0.1
Data Visualizer
Requires Python: >=3.6

# TensorMap

[![PyPI Version](https://img.shields.io/badge/Version-0.0.1-3775A9?style=plastic&logo=PyPi)](https://pypi.org/project/pylearn/)
[![Code Coverage](https://img.shields.io/badge/CodeCoverage-99p-F01F7A?style=plastic&logo=CodeCov)](https://github.com/social-learning/pylearn)
[![Github](https://img.shields.io/badge/GitHub-PyLearn-181717?style=plastic&logo=GitHub)](https://github.com/social-learning/pylearn)
[![LinkedIn](https://img.shields.io/badge/GitHub-CodeForAll-0077B5?style=plastic&logo=LinkedIn)](https://www.linkedin.com/company/codeforall/)
[![TensorFlow](https://img.shields.io/badge/TensorFlow-2.3.1-FF6F00?style=plastic&logo=TensorFlow)](https://https://www.tensorflow.org/)
[![TensorFlow](https://img.shields.io/badge/OpenAIGym-0.12.5-0081A5?style=plastic&logo=OpenAI-Gym)](https://gym.openai.com/)
[![SciKitLearn](https://img.shields.io/badge/PyTorch-1.6.0-EE4C2C?style=plastic&logo=PyTorch)](https://pytorch.org/)
gis-lab 0.0.1
A small example package
Requires Python: >=3.6

# GIS-Lab

[![PyPI Version](https://img.shields.io/badge/Version-0.0.1-3775A9?style=plastic&logo=PyPi)](https://pypi.org/project/pylearn/)
[![Code Coverage](https://img.shields.io/badge/CodeCoverage-99p-F01F7A?style=plastic&logo=CodeCov)](https://github.com/social-learning/pylearn)
[![Github](https://img.shields.io/badge/GitHub-PyLearn-181717?style=plastic&logo=GitHub)](https://github.com/social-learning/pylearn)
[![LinkedIn](https://img.shields.io/badge/GitHub-CodeForAll-0077B5?style=plastic&logo=LinkedIn)](https://www.linkedin.com/company/codeforall/)
[![TensorFlow](https://img.shields.io/badge/TensorFlow-2.3.1-FF6F00?style=plastic&logo=TensorFlow)](https://https://www.tensorflow.org/)
[![TensorFlow](https://img.shields.io/badge/OpenAIGym-0.12.5-0081A5?style=plastic&logo=OpenAI-Gym)](https://gym.openai.com/)
[![SciKitLearn](https://img.shields.io/badge/PyTorch-1.6.0-EE4C2C?style=plastic&logo=PyTorch)](https://pytorch.org/)
santa-7imbrook 0.1
A secret santa matcher
Requires Python: >=3.6

Secret Santa
=============

Simple cli to match your friends or family up for secret santas!

Add people to your group, set a location to exclude households or partners. People in the same location wont get each other.

```shell
./santa.py add-person <name> <phone-number> <location>
```

You can test out your matches with `--dry-run`

```shell
./santa.py shuffle --dry-run
```

Then send it off! (without `--dry-run`) There's no way to track back who got who after the program quits so it's one shot.
gis-kit 0.0.1
A small example package
Requires Python: >=3.6

# PyLearn

[![PyPI Version](https://img.shields.io/badge/Version-0.0.1-3775A9?style=plastic&logo=PyPi)](https://pypi.org/project/pylearn/)
[![Code Coverage](https://img.shields.io/badge/CodeCoverage-99p-F01F7A?style=plastic&logo=CodeCov)](https://github.com/social-learning/pylearn)
[![Github](https://img.shields.io/badge/GitHub-PyLearn-181717?style=plastic&logo=GitHub)](https://github.com/social-learning/pylearn)
[![LinkedIn](https://img.shields.io/badge/GitHub-CodeForAll-0077B5?style=plastic&logo=LinkedIn)](https://www.linkedin.com/company/codeforall/)
[![TensorFlow](https://img.shields.io/badge/TensorFlow-2.3.1-FF6F00?style=plastic&logo=TensorFlow)](https://https://www.tensorflow.org/)
[![TensorFlow](https://img.shields.io/badge/OpenAIGym-0.12.5-0081A5?style=plastic&logo=OpenAI-Gym)](https://gym.openai.com/)
[![SciKitLearn](https://img.shields.io/badge/PyTorch-1.6.0-EE4C2C?style=plastic&logo=PyTorch)](https://pytorch.org/)