semvec/pypi-packages huggingface dataset:
csv2drf 4.7.0
Utility to convert G2 raw data from CSV to DRF
License: MIT
Requires Python: <4.0,>=3.9

# CSV2DRF

This program is built for the Personal Space Weather Station project. Originally, the Grape2 stations store raw data in CSV format. This program converts it to the DigitalRF format.

For documentation, refer to the Wiki at
pydbsmgr 1.0.2
Python package for database control and DataFrame processing
License: MIT
Requires Python: >=3.10

![pydbsmgr](https://raw.githubusercontent.com/jzsmoreno/pydbsmgr/main/pydbsmgr.png)

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# pydbsmgr

Python package for database control and administration as well as for DataFrame processing. Also contains a simpler [Python SDK for Azure Cloud tools](https://learn.microsoft.com/en-us/azure/developer/python/sdk/azure-sdk-overview) such as uploading `.parquet`, `.csv` and `.xlsx` files, downloading them and DataFrame cleansing, for more information review our [`documentation`](https://jzsmoreno.github.io/pydbsmgr/).

## Prerequisites

Before you begin, ensure you have met the following requirements:

- You have a _Windows/Linux/Mac_ machine running [Python 3.10+](https://www.python.org/).
- You have installed the latest versions of [`pip`](https://pip.pypa.io/en/stable/installing/) and [`virtualenv`](https://virtualenv.pypa.io/en/stable/installation/) or `conda` ([Anaconda](https://www.anaconda.com/distribution/)).

## Installation

This package can be easily installed with pip:

```bash
pip install pydbsmgr
```

## Installation from GitHub

If you prefer, you can do it in this other way:

```bash
pip install git+https://github.com/jzsmoreno/pydbsmgr
```

## You can contribute to this repository

Through the following steps:

1. Clone this repository (requires `git`):

```
git clone https://github.com/jzsmoreno/pydbsmgr.git
cd pydbsmgr
```

1. Create and activate a python virtual environment (The activation may vary depending on your OS here is the example for Linux):

```
python3 -m venv venv
source ./venv/bin/activate
```

3. Install all the `requirements`:

```
pip3 install -r requirements.txt
```

4. Now you can test it with any python file you want. But you can also use it in a jupyter notebook, just install [jupyterlab](https://pypi.org/project/jupyterlab/)

```
pip3 install jupyterlab
```

5. Open the jupyter lab instance (you can see that already exists an `example.ipynb`, where you can see some of the things you can do):

```
jupyter lab
```