Top Tweets for #JupySQL
Check out my @DuckDB talk from @SciPyConf 2023! See how #Python folks in #DataScience can get the power of a database with none of the hassle. The demo includes @ProjectJupyter & #JupySQL.
I haven't given a talk in a while - I'd love your advice!
https://t.co/0XUJFfE2OH
๐#JupySQL v0.9.0 is out!๐
Load config from pyproject.toml, resolve CTEs with new 'with_' feature & enjoy more control over scripts with parameterized queries. Plus, many more features & bug fixes!
Learn more: https://t.co/Iys5cN2Quo
๐ Show some love: https://t.co/fq1jJmU68f
Learn how to integrate @deepset #Haystack, an open-source framework for building NLP systems, with #JupySQL and #JupyterNotebooks.
๐ Learn how to build your custom nodes and combine them with agents.
https://t.co/UGNVXn60kT
#ML #AI #Python #NLP #GenerativeAI
Excited to share our new tutorial on product analytics using #SQL! Dive into crucial metrics like user growth and retention, explore practical examples, and learn about #JupySQL for seamless analytics tasks.
โก๏ธhttps://t.co/t5mjohGq3m
#DataAnalytics #ProductAnalytics #Ecommerce
๐ NEW RELEASE: In JupySQL 0.7.5, we've worked on documenting %sqlcmd tables/%sqlcmd columns for your ease.
Dive into our updated documentation today to explore and understand these features more efficiently.
Link https://t.co/AuZH5nitR2
#JupySQL #Documentation
๐ NEW RELEASE: With our latest 0.7.5 release, we've fixed the default value of %config SqlMagic.displaylimit to 10 for a more manageable output.
Plus, you can now set the display limit to unlimited by inputting 0 or None.
More power to you! #JupySQL #SqlMagic #DataHandling
๐ NEW RELEASE: With the 0.7.5 release, you'll now get enhanced error messages when a function used in the plotting API is unsupported by the DB driver.
This way, it's easier than ever to identify and resolve issues swiftly.
#JupySQL #ErrorHandling #DataVisualization
๐ NEW RELEASE! JupySQL 0.7.5 now allows the use of the native DuckDB .df() method when autopandas is in action.
This integration ensures more efficient performance and seamless operation between DuckDB and pandas.
Check it out!
#JupySQL #DuckDB #Pandas #DataAnalysis
Learn to streamline ETL processes and supercharge your data management - through Jupyter! - with this guide from Ido Michael on @kdnuggets!
Automate it with #GitHub actions. Dive in!: ๐https://t.co/82qQysJuiL ๐๐ก
Image https://t.co/TuLL5bjWik. #ETL #JupySQL #DataScience
New Post
Schedule & Run ETLs with Jupysql and GitHub Actions
This blog provided you with a comprehensive overview of ETL and JupySQL, including a brief introduction to ETLs and JupySQL.
https://t.co/yeeby0l2wj
#github #etl #jupysql #jupyter #jupyternotebook
Dive into our latest tutorial: Analyzing #Github #Data with #JupySQL + #DuckDB!
Learn how to query the Github REST API and perform in-depth analysis using JupySQL and DuckDB in Jupyter Notebooks.
Check out the tutorial:
https://t.co/jnWkL9LOjg
#DataAnalysis #CodingTips
Did you know that with #JupySQL, you can harness the power of #ggplot for your #data visualizations?
With the ggplot API you can create stunning #visualizations using SQL table names instead of datasets.
Explore our tutorial: https://t.co/wMiaOJ1nRt
Introducing our new blog: Schedule #ETLs with #JupySQL and #GitHub Actions!
Learn the basics of ETLs and JupySQL, work with the public Penguins dataset, and schedule your ETL using GitHub Actions!
Get started today:
https://t.co/PCjHdff37t
#JupyterNotebook #DataWorkflow
Use #SQL keyword autocompletion in your #Jupyter notebooks with #JupySQL! ๐
Simply press tab while typing to get suggestions!
Give it a try and share your feedback with us on Slack! Install JupySQL now:
https://t.co/IZM49F7TxR
#Autocompletion #SQL #NewFeature
Easily export SQL result sets to CSV with JupySQL! ๐
Simply provide a filename, and let JupySQL handle the rest!
Get started with JupySQL and enhance your data exporting experience today! https://t.co/KsJhfCcxAd
#JupySQL #SQL #CSVExport #DataScience #JupyterNotebook
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