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https://github.com/mgobeaalcoba/python_postgresql
Examples of connecting to Postgres to exploit data and creating tables in Postgres directly from Python
https://github.com/mgobeaalcoba/python_postgresql
data-engineering database-management dotenv postgresql psycopg2 python3
Last synced: about 2 months ago
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Examples of connecting to Postgres to exploit data and creating tables in Postgres directly from Python
- Host: GitHub
- URL: https://github.com/mgobeaalcoba/python_postgresql
- Owner: Mgobeaalcoba
- Created: 2024-06-10T01:51:14.000Z (7 months ago)
- Default Branch: master
- Last Pushed: 2024-06-27T20:45:54.000Z (7 months ago)
- Last Synced: 2024-06-27T23:40:33.881Z (7 months ago)
- Topics: data-engineering, database-management, dotenv, postgresql, psycopg2, python3
- Language: Jupyter Notebook
- Homepage:
- Size: 26.4 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Connecting and Manipulating PostgreSQL with Python
This repository contains a Jupyter Notebook with examples of how to connect Python with PostgreSQL and how to create and manipulate tables in PostgreSQL using Python.
## Content
- **Connection to PostgreSQL**: Examples of how to establish a connection with a PostgreSQL database using `psycopg2` and `SQLAlchemy`.
- **Loading Data into a DataFrame**: How to load data from PostgreSQL into a Pandas DataFrame.
- **Data Manipulation**: Examples of data manipulation using Pandas.
- **Creating Tables in PostgreSQL**: How to create new tables in PostgreSQL from manipulated DataFrames.
- **Credential Management**: Using a `.env` file to manage credentials securely.
## Requirements
-Python 3.x
- Jupyter Notebook
- Pandas
- psycopg2
-SQLAlchemy
- python-dotenv
## Facility
1. Clone this repository:
```bash
git clone https://github.com/Mgobeaalcoba/python_postgresql
```
2. Create a virtual environment and install dependencies:
```bash
python -m venv venv
source venv/bin/activate # On Windows use `venv\Scripts\activate`
pip install -r requirements.txt
```
3. Create a `.env` file in the project root directory with the following content, replacing the values with your PostgreSQL credentials:
```bash
POSTGRES_DB=database_name
POSTGRES_USER=user_name
POSTGRES_PASSWORD=your_password
POSTGRES_HOST=localhost
POSTGRES_PORT=5432
```
4. Start Jupyter Notebook:
```bash
jupyter notebook
```
5. Open the `conexión de jupyter a postgres sql.ipynb` notebook and follow the examples.
## Use
The notebook includes detailed examples on how to:
- Connect to a PostgreSQL database.
- Execute SQL queries and load the results into a Pandas DataFrame.
- Manipulate the data in the DataFrame.
- Create a new table in PostgreSQL and save the manipulated data in it.
## Grades
- Make sure the `.env` file is in your `.gitignore` to avoid uploading your credentials to the repository.
- Review and adjust configurations and credentials based on your development and production environment.
## Contributions
Contributions are welcome! Feel free to open an issue or submit a pull request.
## License
This project is licensed under the MIT License. See the `LICENSE` file for details.