onestation 0.1.0

This package aims to carry out a preprocessing of conventional weather stations

Onestation 0.1.0

Pre-processing data from conventional weather stations

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Topics

• Project description

• Functionalities

• Application

• Tools used

• Project access

• Install and run the package

• Developer

Project description

The project under development is a library/package in Python with the purpose of pre-processing conventional weather station data. One station is a Python package that has the main objective of helping developers or professionals who seek to treat and clean weather station data and apply it to a Machine Learning model aimed exclusively at precision irrigation.

The package is available on [Pypisistema](https://pypi.org/project/onestation/) it will allow the daily, continuous and remote pre-processing of the collections carried out by conventional meteorological stations, allowing professionals and developers to apply them in their work in a fast and applied way.

Application

Understand data pre-processing concepts and techniques used to transform raw data into an applicable format. Visit the link and learn more https://brain-mentors.com/concepts-of-data-pre-processing.

☑️Note: This work is being finalized and will facilitate the process of processing data from conventional meteorological stations and can also be applied or converted to automatic meteorological stations.

Functionalities

:heavy_check_mark: Functionalities 1: Perform data cleaning.

:heavy_check_mark: Functionalities 2: Perform data transformation.

:heavy_check_mark: Functionalities 3: Apply data reduction.

Tools used

Project access

You may access the project source code or access the project on PyPi at the link https://pypi.org/project/onestation/

Install and run the package

To install the package you must use Pycharm or Jupyter Notebook. For this, you must have the latest version of Python installed on your machine:

User installation

The easiest way to install onestation is with pip

pip install onestation

If you are having difficulty installing the correct package versions, you can set up a virtual environment like this:

1- pip install virtualenv

2- virtualenv env

3- source env/bin/activate

4- curl https://bootstrap.pypa.io/get-pip.py | python3

5- pip install onestation

6- pip install ipykernel

7- ipython kernel install --user --name=env

8- jupyter notebook

9- When finished, deactivate your virtualenv with deactivate

Use

For a complete tutorial on how the package is used in Jupyter notebooks, see our Jupyter notebook demo https://colab.research.google.com/github/IRkernel/IRkernel/blob/master/example-notebooks/Demo.ipynb

For more information about the database used in the tests and to be able to download the dataset, see the link: https://www.kaggle.com/datasets/rogerioifpr/brazil-weather-conventional-stations-19612019

Help and Support

For help with using or installing the package, contact Rogerio Pereira do Santos [e-mail]

Developer

_{Rogério Santos}