Can Julius Make This Type Of Plot For Me? (Almost) Always

Introduction

Julius has proven to be highly capable when it comes to creating a wide range of data visualizations, including some quite unusual plot types. While there are already great guides on data visualizations with Julius on this forum, such as this comprehensive starting point and an exploration of baseball data visualizations, this post aims to dive into less common chart types and assess Julius’s ability to create them.

The idea for this post originated from a user’s question about different chart types in another thread. To determine if Julius can plot these less common chart types, the best approach is to ask it directly. In this experiment, various unusual chart types were requested to evaluate Julius’s understanding and ability to create them. While the examples provided are simple and may not be as visually striking as those found through a Google search, they serve to demonstrate Julius’s capabilities. It’s important to note that the most effective charts often require a clever combination of chart types, an understanding of user needs, and artistic sensibility. Julius can assist with the majority of the process, but these final touches still require human input.

Unusual Plots with Julius

Here are some examples of the requested chart types, the expected output, and what Julius generated.

Sankey Plot

Common use cases: Visualizing flow and transfer between different states or conditions, such as energy flow, material flow, or customer journeys.

Expectation:

Julius:

Julius understood it really well. It has several inputs that branch out into several outputs. The user can now ask for a lot of refinements as desired to achieve the look of the expected chart, but that should not be an issue.

Network Graph

Common use cases: Representing relationships and connections between entities, such as social networks, computer networks, or biological networks.

Expectation:

plot_network

Julius:

Again, no problems. The nodes and the linkages between them are present and that’s all I wanted to see.

Pareto Chart

Common use cases: Identifying the most significant factors contributing to a particular outcome, such as quality control, cost analysis, or process improvement.

Expectation:

plot_pareto

Julius:

Excellent!

Chord Diagram

Common use cases: Visualizing the inter-relationships between entities, such as migration patterns, trade flows, or gene interactions.

Expectation:

Julius:

Not quite. Julius clearly understands the Sankey-like features present in this chart, but it failed to generate the proper circle around it.

Heatmap

Common use cases: Representing the magnitude of a phenomenon in a matrix format, such as gene expression, geographic data, or correlation matrices.

Expectation:

Julius:

Perfect!

Polar Area Chart

Common use cases: Comparing multiple variables with cyclical or directional aspects, such as wind direction, seasonal data, or daily activity patterns.

Expectation:

Julius:

Honesty, great. Can be edited more to suit specific needs.

Streamgraph

Common use cases: Visualizing the evolution of multiple time series that sum up to a constant total, such as market share, music genres, or topic popularity over time.

Expectation:

plot_streamgraph

Julius:

It’s okay. It would need some more conversation to get where I expect it to be, but Julius is aware and can do as best as it can with data generated on the spot.

Circular Tree Map

Common use cases: Representing hierarchical data in a circular layout, such as disk space usage, budget allocation, or population distribution.

Expectation:

plot_circular_tree_map

Julius:

Did not manage to get it. Again, the issue seems to lie with circular designs.

Hexbin Plot

Common use cases: Visualizing the density distribution of large datasets, such as geographic data, scatterplots, or bivariate histograms.

Expectation:

Julius:

Perfect!

Violin Plot

Common use cases: Comparing the distribution of multiple datasets, similar to box plots but with additional information about the probability density.

Expectation:

plot_violin

Julius:

Incredible!

Polar Scatterplot

Common use cases: Plotting data with cyclical or directional aspects, such as wind direction, animal migration patterns, or periodic phenomena.

Expectation:

Julius:

Great work.

Waterfall Chart

Common use cases: Illustrating the cumulative effect of sequentially introduced positive or negative values, such as changes in financial statements, cost analysis, or population changes.

Expectation:

plot_waterfall

Julius:

Perfect.

Sunburst Chart

Common use cases: Visualizing hierarchical data in a radial layout, such as website traffic, product categories, or file system structures.

Expectation:

plot_sunburst

Julius:

Lol, no. Again, circular design.

Funnel Chart

Common use cases: Representing stages in a process and measuring their conversion rates, such as sales pipelines, user retention, or website navigation.

Expectation:

plot_funnel

Julius:

Julius actually did better. I don’t like when these are designed such that the smaller funnel areas are not aligned with the y-axis.

Ribbon Plot

Common use cases: Comparing the evolution of multiple time series with an emphasis on their rank order, such as sports rankings, market positions, or popularity trends.

Expectation:

plot_ribbon

Julius:

Eh, it’s okay, I bet I could get it there by talking about it some more with Julius.

Box-and-Whiskers Plot

Common use cases: Comparing the distribution of multiple datasets using quartiles and outliers, such as test scores, sales figures, or sensor measurements.

Expectation:

Julius:

Not that unusual of a plot, but Julius does it great. Worth mentioning because it’s a useful one.

Dendrogram

Common use cases: Visualizing the hierarchical clustering of data points, such as genetic relationships, document similarity, or customer segmentation.

Expectation:

plot_dendrogram

Julius:

Okay here Julius did so well that the generated image was too high of a resolution (8K) and I couldn’t post it to this forum before resizing it.

Ternary Plot

Common use cases: Plotting the composition of three-component mixtures, such as soil types, chemical compositions, or market share.

Expectation:

Julius:

Works for me. We could make this one look great easily.

Violin Swarm Plot

Common use cases: Combining the advantages of violin plots and swarm plots to show the distribution and individual data points simultaneously.

Expectation:

plot_violin_swarm

Julius:

Same as with the Dendrogram. Julius generated a great plot with a really high resolution that I had to resize to post. Incredible work.

Word Tree

Common use cases: Exploring the context and usage patterns of specific words or phrases in a text corpus, such as customer reviews, social media posts, or literature analysis.

Expectation:

Julius:

There’s a specific library for creating these using nested dictionaries, however, Julius did not use that and just made a Word Cloud. Did not work out in the end.

Parallel Coordinates Plot

Common use cases: Visualizing multivariate data and identifying patterns or clusters, such as product comparisons, customer profiles, or performance metrics.

Expectation:

Julius:

Great work. I love this type of chart in general.

Ridge Plot

Common use cases: Comparing the distribution of multiple datasets in a visually appealing and space-efficient manner, similar to violin plots but without the mirroring.

Expectation:

plot_ridge

Julius:

Amazing.

Hexagonal Binning Heatmap

Common use cases: Visualizing the density distribution of large datasets while reducing overplotting and emphasizing high-density regions.

Expectation:

Julius:

No comment. Great.

Slopegraph

Common use cases: Comparing changes in values between two points in time or two categories, such as before-and-after measurements, or differences between groups.

Expectation:

Julius:

Great.

Circular Histogram

Common use cases: Visualizing the distribution of a cyclical variable, such as time of day, compass direction, or periodic phenomena.

Expectation:

Julius:

Hey, we got a circular one to work great on the first try!

Bubble Matrix

Common use cases: Comparing the values of multiple variables across different categories using the size and color of bubbles, such as market share, performance indicators, or survey responses.

Expectation:

plot_bubble_matrix

Julius:

Not quite. Need to work on anchoring the bubbles more.

Voronoi Treemap

Common use cases: Visualizing hierarchical data while optimizing the aspect ratio of the cells, useful for displaying large datasets or irregular hierarchies.

Expectation:

plot_voronoi_treemap

Julius:

Amazing work.

Hive Plot

Common use cases: Visualizing network structures and relationships between entities, such as social networks, transportation networks, or interaction patterns.

Expectation:

Julius:

I think it worked but I need to give it better data.

Conclusion

Julius demonstrates an impressive ability to generate a wide range of plot types, including many unusual ones. Not only do the plots look accurate, but they are also consistently high-resolution. While Julius struggles with certain circular designs like chord diagrams and circular treemaps, it’s worth noting that these charts can be challenging to create and often require careful manual implementation.

Overall, Julius proves to be a highly capable tool for plotting data. If there are any additional unusual chart types not covered in this post, please mention them in the replies, and we can explore Julius’s ability to create them as well.


Keywords: data visualization, unusual plots, AI-generated charts, Julius, GPT, Claude, Sankey plot, network graph, Pareto chart, chord diagram, heatmap, polar area chart, streamgraph, circular tree map, hexbin plot, violin plot, polar scatterplot, waterfall chart, sunburst chart, funnel chart, ribbon plot, box-and-whiskers plot, dendrogram, ternary plot, violin swarm plot, word tree, parallel coordinates plot, ridge plot, hexagonal binning heatmap, slopegraph, circular histogram, bubble matrix, Voronoi treemap, hive plot.

5 Likes

the hex plots are sweet! my favorite is the ridge plot though — I didn’t know those existed. those are such an aesthetically appealing way to visualize distributions. thanks for making this!

2 Likes

I love the hexagonal binning heatmap, it looks like the universe! This is so neat! OH YOU HAVE A POLAR PLOT, I LOVE TO SEE IT!

1 Like

Love these! For me the tough part is, when it’s not quite there, talking back to Julius and making it make it better for me. Sometimes my counter-prompts when dealing with graphs are not so good :frowning: . Any tips?

1 Like

The graph customization is pretty good, but if that does not work you can always try and re-prompt. Additionally, if you know the portion in the code that changes the format, you can go in and edit the code directly. You can add a line of code that will change the format, or just make slight tweaks to the code itself (i.e. if it’s a colour adjustment just change the name of the colour).
Hope this helps :slight_smile: