semvec/pypi-packages huggingface dataset:
indonesia-earthquake 0.0.4
the latest earthquake from BMKG | Indonesia
Requires Python: >=3.6

# Latest Indonesia Earthquake
Do you need the latest earthquake from BMKG | Indonesia Meteorological, Climatological, and Geophysical Agency

## Guidance
This package will scrape the latest earthquake data from [BMKG](https://www.bmkg.go.id/).

1. Install package from https://pypi.org/project/indonesia-earthquake/
2. Install module from https://pypi.org/project/requests/
3. Install module from https://pypi.org/project/beautifulsoup4/
4. Run your main.py with this code

```
import last_earthquake

if __name__ == '__main__':
    result = last_earthquake.data_extraction()
    last_earthquake.show_data(result)
```

# Author
Arsenius Anom Permadi
mlcm 0.0.1
Multi-Label Confusion Matrix
Requires Python: >=3.6

# MLCM creates a 2D Multi-Label Confusion Matrix
Please read the following paper for more information:\
M. Heydarian, T. Doyle, and R. Samavi, MLCM: Multi-Label Confusion Matrix,\
IEEE Access, Feb. 2022, DOI: 10.1109/ACCESS.2022.3151048\
For other projects please see https://biomedic.ai/


Please cite the paper if you are using the MLCM.\
This work is licensed under a Creative Commons Attribution 4.0 License.\
For more information, see https://creativecommons.org/licenses/by/4.0/

# An example on how to use MLCM package:
% Importing libraries
>> from mlcm import mlcm\
>> import numpy as np

% Creating random input (multi-label data)
>> number_of_samples = 1000\
>> number_of_classes = 5\
>> label_true = np.random.randint(2, size=(number_of_samples, number_of_classes))\
>> label_pred = np.random.randint(2, size=(number_of_samples, number_of_classes))

% Calling mlcm and illustrating the results
>> conf_mat,normal_conf_mat = mlcm.cm(label_true,label_pred)\
>> print('\nRaw confusion Matrix:')\
>> print(conf_mat)\
>> print('\nNormalized confusion Matrix (%):')\
>> print(normal_conf_mat)

>> one_vs_rest = mlcm.stats(conf_mat)
infima-client 0.287.0
A client library for accessing Infima
Requires Python: >=3.7.1,<4.0.0

# infima_client

A client library for accessing Infima. It will manage the HTTP REST requests for you.

## System requirements

The infima_client requires Python 3.7+. It is multi-platform, and the goal is to make
it work equally well on Windows, Linux and OSX.

## Installation

The library is published in PyPi.

```shell
pip install infima_client
```

## Usage

Contact [Support](support@infima.io) for an access token.

```python
from infima_client import InfimaClient

token = "..."
client = InfimaClient(token=token)
client.demo()
```

Alternatively, the token can be configured with the `INFIMA_TOKEN` environment variable.

## More Information

See the [Docs](http://docs.infima.io/) for more information.

Contact [Support](support@infima.io) if you have any questions.
dfplanner 0.0.2
Using Pyccolo to optimize Pandas query plans holistically
Requires Python: >=3.6

dfplanner
=========
[![License: BSD3](https://img.shields.io/badge/License-BSD3-maroon.svg)](https://opensource.org/licenses/BSD-3-Clause)

This project uses flit. To get started with an editable install:

```bash
python -m pip --upgrade pip
python -m pip install flit
flit install -s --extras dev
```