Input parameters are a core, unique part of Hex. Input parameters can be created in the Notebook view and then added, optionally, to an app.
Izzy Miller
With Hex, you can easily dive into cohort analysis using Python and unlock insights about your customer groups. Explore their behavior over time, spot retention patterns, and discover valuable nuggets of information. By defining cohorts based on shared characteristics, like the month of their first purchase, you'll gain a deeper understanding of how different customer sets behave. Hex empowers you to make smarter decisions and optimize your business strategies by leveraging the power of cohort analysis.
Understand how collective user tastes can be used to find products that are similar to each other and make personalized recommendations based on purchase history. Hex makes it easy to build a recommendation engine using collaborative filtering with Python, and then deploy it as an interactive web app.
This project demonstrates a simple network graph analysis using data from the Silk Road forums, the igraph package, and Hex. Most network analyses and community data analysis projects are done as static point-in-time analyses, but Hex makes it easy to provide an interactive window into the data and let users explore the network graph themselves. WARNING: This dataset contains information about illegal activity as well as a lot of bad language. Explore the raw data at your own risk!
Period over period analysis in a notebook has never been easier or more flexible. With a powerful Python workspace that also supports SQL, you can build a fully interactive report for anyone, and give them the tools to customize their timeframes and periods of interest. When you're done, just click "Publish" and your results are instantly shareable.
Reduce customer churn with predictive insights. Discover how our Random Forest model can forecast potential customer drop-offs before they happen, saving you the higher costs of acquiring new clients. Dive into our project to see how we turn data into retention strategies for your business.
Izzy Miller, Dev Advocate at Hex
Hex is your go-to platform for flexible time series forecasting directly with your data warehouse, enabling you to construct powerful predictive time series models using Python and SQL, without any needless data shuffling. It's particularly handy when integrated with libraries like Prophet for detailed daily temperature forecasting. Once you've nailed your model, it's simple to add interactive elements, making your forecasts not just informative, but engaging. You can take your model straight from creation to production, all from within the intuitive Hex interface. No fuss, no extra steps - just efficient, effective data science at your fingertips.
Building a natural language processing app that uses Hex, HuggingFace, and a simple TF-IDF model to do sentiment analysis, emotion detection, and question detection on natural language text.
Exploratory data analysis in Hex is like no other tool you've used before. SQL, Python, rich text, and a library of no-code tools are right at your fingertips in the same workspace. When you're done, just click "Publish" and your results are instantly shareable.
Discover how Hex data scientists and analysts use Hex for everything from dashboards to deep dives.
Table display cells are a way to visualize, filter, and format tabular data without writing any code. Simply choose a dataframe and use the Table display settings to apply any fitlers, change the data format of any column, hide any column, wrap text.
Hex’s first-class Python support unlocks a world of opportunity for data exploration.
Query your warehouse, uploaded files, or dataframes directly with SQL.
Map cells let you visualize geographic data in a customizable interactive map.
Chart cells let you visualize and explore the dataframes in a Hex project, without writing code.
Text and Markdown cells let you add narrative, explanations, and context to your data project.