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Customizable Bins in Plots: Adjust the number of bins in your plots to tailor data granularity and enhance visualization precision, enabling more flexible data analysis.
Resizable Canvas with Interactive Ratio Adjustment: Customize the canvas size and adjust the aspect ratio interactively for a more tailored and precise plotting experience.
Log Scale Configuration for Scatter Plots: Enable log scale on scatter plots to better visualize data across wide value ranges, enhancing data interpretation and clarity.
📊 Focus on What Matters - Top/Bottom N Categories:
🌈 Customizable Plot Colors:
Now, you can add a personal touch to your plots by choosing any color you like. This is perfect for aligning your visualizations with your company's branding or simply picking a color that fits the mood of your presentation. It's a small change, but we believe it can make a big difference in how your data is perceived and understood.
📊 Focus on What Matters - Top/Bottom N Categories:
We understand that sometimes less is more. That's why we're introducing the ability to show just the top or bottom N categories in your plots. This feature will help you create cleaner, more focused visualizations, making it easier for your audience to get the key takeaways without getting lost in the details.
We can't wait to see the amazing visualizations you'll create with these new tools. As always, we're here to listen to your feedback and make Graphext even better for you.
Direct Renaming: You can now rename categories directly within our interface. This straightforward functionality allows for quick adjustments to your dataset, ensuring that your categories accurately reflect your data.
Efficient Merging: When you name two categories the same, Graphext will automatically combine them into one. This is particularly useful for cleaning up datasets where the same item might be listed under different names, like various job titles (Product Manager, PM, Product Mgmt, etc…) that essentially mean "Product Manager."
Coming soon! The Future is ✨AI-Powered:
We're not stopping here! Get ready for an upcoming feature where our AI will suggest merging similar concepts. Imagine the AI detecting and suggesting merging "Advisor" and "Adviser" or "E-mail" and "Email," helping you to further clean and organize your data efficiently.
Seamless Integration:
These new category management tools are designed to fit smoothly into your existing Graphext workflow. Renaming and merging are straightforward, quick, and won’t interrupt your data analysis.
We hope these updates make your data work more efficient and straightforward. Your feedback is always welcome as we continue to improve Graphext.
Say hi to interactive plot resizing! At Graphext, we understand that the impact of a good visualization is not just in the data it represents, but also in how it's presented. Recognizing that different visualizations require different aspect ratios for optimal clarity and impact, we've now made it possible for you to adjust the size of your plots interactively.
What's New?
Interactive Resizing: You can now click and drag the edge of your plots to resize them. This means you can easily switch between landscape and portrait orientations or fine-tune the dimensions to get just the right ratio for your data visualization needs.
Adaptable Visuals: Whether your data looks best in a wide, landscape format or a tall, vertical orientation, you have complete control over how your plots are displayed. This flexibility ensures that you can present your data in the most effective and visually appealing way.
Why This Matters:
We've all been there – tweaking numbers, trying to get the visualization size just right, only to end up with a format that doesn't quite do the data justice. It can be a frustrating and time-consuming process. That's why we prioritized developing a solution that not only saves time but also enhances your ability to present data in the best light possible.
Seamless Exporting:
Once you've configured the perfect size for your plot, exporting it is just as straightforward. This seamless transition from customization to export means your workflow is smoother and faster, allowing you to share your insights with others more efficiently.
This week at Graphext, we're introducing a series of keyboard shortcuts designed to make your filtering process in the cross filters significantly more efficient. We understand that working with data often involves dealing with variables that have a wide range of categories and selecting or deselecting these manually can be time-consuming. That's why we've implemented these shortcuts to streamline your workflow.
What's New?
Selecting a Range of Categories: Now, you can easily select all categories between two points with just a couple of clicks. Click on the first category, then click on the last category while holding down the SHIFT key. This will select both categories and everything in between.
Adding or Removing Categories: To add or remove a single category from your selection, simply hold down the CMD key (on Mac) or the CTRL key (on Windows) while clicking the category. This feature is particularly handy when you want to maintain most categories but exclude just a few, especially with variables that have a high number of categories.
Why This Matters:
These enhancements are all about saving you time and making your data analysis workflow smoother. By allowing for quicker selection and deselection of categories, we hope to significantly reduce the time you spend on manual tasks, freeing you up to focus on the more critical aspects of your analysis.
We're rolling out an update to the correlations section, now called Correlations 2.0, for all our Graphext users. Here's a quick refresher on what the correlations section does: It's a handy tool within Graphext that lets you pick a variable you're interested in, and then it shows you how that variable correlates with others in your dataset, sorting the results by the highest correlation. This feature is pretty neat because it works with all kinds of variables, including categorical ones, thanks to the mutual information algorithm we use.
What's New in Version 2.0?
Pearson Coefficient: We've added the Pearson coefficient to our toolbox, so now you have another way to measure how variables relate to each other, especially useful for linear relationships between continuous variables.
More Ways to Visualize Data: Besides the bubble charts we had before, you can now use boxplots and heatmaps for a different look at the correlations in your data. These should give you more insights and make the correlations easier to understand at a glance.
Why We Made These Changes:
We wanted to give you more options and better tools to see and understand the relationships in your data. The Pearson coefficient is a classic statistical tool for a reason, and we think it's a great complement to the mutual information algorithm. As for the new visualizations, we know that a good chart can sometimes tell you more at a glance than a bunch of numbers, so we're excited to offer you more choices there.
Try It Out:
The updated correlations section is ready for you to explore. Check out the new features and see how they can help with your data analysis. We're here for any questions or feedback you might have.
1. Visualize Relationships at a Glance: Say hello to Scatter Plots and Bubble Charts, offering a rapid, intuitive way to understand the connections between your variables. See correlations, trends, outliers, and clusters with a simple glance.
2. Multi-variable Mapping: Take control by mapping not just one or two, but up to four variables simultaneously! Size and color your bubbles based on these variables, unlocking deeper insights within a single visualization.
3. Dynamic Regression Insights: Watch as the regression line dynamically adapts in real-time. Whether you're adjusting categories, filtering data, or modifying variables, the regression line instantly recalculates, aiding in a deeper understanding of your dataset.
4. Instant Statistical Insights: Dive into your data's depth with instant calculations of Pearson and R-squared coefficients. Uncover the strength and direction of relationships between your variables.
5. Tailored Customization: Personalize your visualizations to fit your exact needs. From customizing tooltips to adjusting size ranges and colors, wield complete control over how your data is presented.
Welcome to the world of Scatter Plots and Bubble Charts with Graphext! 🚀
Just follow the magic star 🌟 and ask away. It will enable you to perform tasks such as extracting the name of the weekday, the month, or the time of day from a date column. We understand the challenges of working with dates in Python... That's why we have made it incredibly easy!
But that's not all. With free text, you can change variable types, perform operations between variables, create segmentations, and much more. Go ahead, give it a try, and let us know what you think.
This is just the start, we are creating a user interface powered by artificial intelligence to provide the best data analysis experience. Stay tuned!
