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🎬 Dive into our blog on #data #wrangling & #exploratory #analysis with JupySQL. Prep for an end-to-end Ploomber pipeline & gear up for recommendation systems! 🔍
📖 Read here: https://ploomber-sql.readthedocs.io/en/latest/mini-projects/recommendation-system/eda-with-jupyter.html
Enjoyed it? Star JupySQL: https://github.com/ploomber/jupysql
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🚀 Explore our movie recommendation system! Learn to:
Write a #Python script for Movie Database API 📽️
Populate #DuckDB 🦆
Package with Ploomber for future upgrades 🐍
📖 Dive in:
https://ploomber-sql.readthedocs.io/en/latest/mini-projects/recommendation-system/setting-up-etl.html🔜 Next: Data #analysis & #wrangling in #Jupyter with #SQL & JupySQL 📊
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🚀 🚀 🚀Just published a comprehensive new blog post on dockerizing your #Python-based ETL pipelines!
Delve into the varied benefits and detailed instructions of Docker packaging with us.
⚡ Learn how to create a virtual environment, and package a Python pipeline.
⚡ Learn about procedure of building and running Docker images while emphasizing the importance of distinct virtual environments for each project. -
🤔 Ever wondered how we can manage and load data into a DuckDB instance? Check out the next blog in our SQL course!
Built around Python and SQL, this guide delves deep into numerous Python libraries such as 'requests', 'pandas' and DuckDB's Python API to guide you through the process.
🔗 Read about it here:
https://ploomber-sql.readthedocs.io/en/latest/packaging-your-sql-project/intro-to-etl-pipelines-with-python-and-sql.html#DataEngineering #DataAnalytics #Python #SQL #ETLPipeline #DuckDB #Pandas #DataTransformation #GitHub #DataScience
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📣 New ETL pipeline course module out! Grasp the difference between .pyscript & Jupyter notebooks and master Python script drafting best practices.
Dive into function definitions, modularization, code documentation, and Python script packaging. We also introduce Pandas and DuckDB Python API for efficient data handling. Discover more at
#Python #DataScience #SQLAlchemy #Pandas #Automation #Modularization.
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🚀 🚀 Congratulations, SangGyu (David) An, on merging your work to the JupySQL project! SangGyu contributed a fix to the %sqlrender magic - this allows users to see their saved queries. He also ensured our compatibility page is up to date.
JupySQL's now supports
🌟 DuckDB
⚡ Pandas
🌟 Polars
⚡ MySQL
🌟 Microsoft SQL Server
⚡ MariaDB
🌟 Snowflake
⚡ Clickhouse
🌟 Mindsdb
⚡ PostgreSQL
🌟 Compatibility
⚡ QuestDB
🌟 Oracle Database
⚡ Trino
#DB #Engine #Connectivity #DataWorkflow