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For the past year, we've been heads down talking to Data Scientists to help them find a better way to share their analyses with others, maximise their impact, and demonstrate their value.
As a result, we've shipped dozens of features to make this easier, including allowing Data Scientists to convert any Jupyter notebook into an app with a single line of code and share it in seconds.
We've also launched features enhancing Jupyter itself, like making data sets interactive with dp.DataTable and other inline blocks.
Why does this matter?
By using Datapane to transform a notebook into something beautiful, interactive, and shareable, Data Scientists can maximise the impact of their analyses and demonstrate their value in a format that saves them time and wows stakeholders.
Thank you for using and contributing to Datapane this year. We're delighted to have you as part of our growing community.
Jupyter to App conversion, interactive DataTables, PyData meetups, and more!
Welcome back to Datapane's monthly update.
Read on for a jam-packed monthly recap of all things Datapane, including product updates, quick tutorials, upcoming events, and more. We'll cover:
Transform DataFrames with dp.DataTable
DataFrames are essential for exploring data in Python, but presenting them to others can be lacklustre.
Datapane's dp.DataTable transforms DataFrames into something interactive that end-users can sort, search, filter, export, and run SQL queries against without writing Python.
Check it out in detail here, or here 👇
A data app in one line of code? yep.
In the past month, we've rolled out some key features that enable Data Scientists to convert a notebook into an app with a single line of code.
Just run the code below.
(make sure you've installed and logged into Datapane and saved your notebook!)
Transforming a notebook into something beautiful, interactive, and shareable enables Data Scientists to maximise the impact of their analyses and demonstrate their value in a format that saves time and wows stakeholders.
Check it out in detail here.
See you at a PyData meetup soon?
Jo-Fai Chow recently joined the Datapane team as our new resident Data Science Evangelist.
Joe joins us from H2O.ai where he helped build one of the world's biggest data science communities.
Joe was in London this week for the PyData meetup. He'll be a frequent visitor and speaker at future events and would love to say hi!
Let us know if you're coming along, and we might just bring some Datapane swag 🤩
⚡️ Quick guide to dp.BigNumber
A single number can often be the most important thing in your data analyses.
Use Datapane's BigNumber to present KPIs, changes, and stats in a user-friendly way.
See our docs for more detail here, or watch it here 👇
Python package of the month.... emailsanta!
Inspired by PyData, we've launched a new feature promoting a python package each month.
This month, we're deferring to our friends over at PyData who we think called it with this seasonally appropriate one: emailsanta.
emailsanta lets users send a letter to Santa and receive a reply!
Note that this library is for entertainment purposes only and does not provide a real interaction with Santa Claus.
1) You can read about the rest of the team behind Datapane here.
2) Follow our latest product updates as they happen here.
3) Come say hi 👉 on our Discord, GitHub, Twitter, LinkedIn.
Thanks for reading, and have a great holiday period from the team behind Datapane.