Not long ago, I met up for coffee with a mate of mine with whom I'm working on some Python scripts. He asked, "Have you seen this James Eeagle guy on LinkedIn?" "No," I replied, "What about him?" "He creates amazing charts of financial data... you'd love it."
So, I naturally took a look and stumbled upon this beauty of an animation: interest rates predicted by the market over time. Have a look:
Immediately, I thought it would be cool to have a similar animation but for the oil price as predicted by the futures market (a chart called "term structure"). So, I asked him directly in his LinkedIn post (link to post):
I decided to take the challenge upon myself, as I thought it would be a good use case to demonstrate an example of how to go about creating a cool animation like this one for data visualization.
Do not get hung up on the specific data being shown here. The point is that there are better, more visually appealing ways to present information that may entice your audience and capture their attention. With the tools available today, anyone can do it.
There are various alternatives for creating an animated chart like the one above, but I’ll focus on two tools: Excel/VBA and Python.
With either, it obviously helps to have a clear idea in mind of what you want and how to work with the data sequentially. However, if you have little expertise in coding, or even if you have some but want to speed up the process, you can leverage ChatGPT, as I have consistently emphasized in previous editions.
The first step is to obtain the data and format it for use. Now, depending on the data, accessing and downloading it can be either easy or difficult. It might be publicly available for free, or it could be behind a paywall. In this case, I obtained the data from Bloomberg, a well-known financial database.
Below is a brief excerpt from the database, once in my Excel spreadsheet:
The table displays dates in the first column, followed by 12 prices, one for each futures contract maturity over the next 12 months. This indicates the current price of a barrel of oil for future delivery. The futures market enables buyers and sellers to hedge against volatility in the oil price. If this sounds too complex, simply think of the price of a futures contract as the market's prediction of what the oil price will be in the future.
Let's create a simple line chart from the first two columns, date and front month (consider this the spot price, for simplicity). Without any formatting, this is what we get:
Now, what we aim to do is add a new series to the chart for each futures curve, each consisting of 12 prices, one for each month. We need to determine which date corresponds to each of the 12 futures contract maturities, enabling us to plot them on the same Price vs Date chart.
Additionally, we want to add a futures curve to the chart only at the end of each month, rather than on every single date (daily granularity), to prevent the chart from becoming too cluttered and too heavy for the animation we plan to create. Here are the steps:
This is what the chart looks like at an intermediate step:
To create the animation, we aim to export each step as a separate image file, allowing us to combine them into a movie. Specifically, at the end of every month, we add the futures curve series to the chart and save that chart as an image.
Because doing this manually for many data points is impractical, we use a macro to automate the process over the entire range. The simplest approach is to record a macro while performing a few steps manually, and then edit the macro in the VBA editor.
If you're not very familiar with VBA, this is where ChatGPT can become your invaluable advisor!
Once you have all your images, there are many ways to stitch them together. For this example, I've used Python, with guidance from ChatGPT, as usual.
Prompt:
“I got 150 .png image files and a .mp3 audio file. Write me a python script to turn the sequence of images into a movie, with the mp3 as background music.”
We follow the instructions provided, and once the process is complete, this is the final animated video we obtain as a result:
Let's be honest: coding enhances your capabilities—there's no doubt about it. If you know how to code, you have an edge.
However, I want to emphasize again that you can leverage ChatGPT not only to learn coding but also to accelerate your coding process, troubleshoot issues, and more. Dive in and start experimenting!
In this example, I intentionally approached the process from a no-coder's perspective, aiming to obtain as many step-by-step instructions as possible and to communicate in the simplest English possible.
I can’t share the ChatGPT instance as sharing chats with images is not supported yet, but here are the general principles of my querying process:
The chat screenshots below illustrate the principles mentioned above, giving you an idea of how the conversation progressed in simple spoken English:
.. And so the conversation continues until I converge on the desired solution.
The chart, axis, legends, text, logo, and background music were all created using Python.
However, for the fun of it, I added one extra step: I took the resulting .mp4 video to Microsoft Clipchamp, a free video editor in Windows 11, and added some floating text boxes to annotate three key historical events that underpin the price behavior in these periods.
This video-editing game can easily draw you in, as there’s always some extra touch that can be added, and it’s really fun. However, for the sake of this demo, this will do.
The animation includes:
Here is the end product (sound on):
What do you think?
Give me a shout if you'd like to have these files for your own experimentation, including the Excel workbook with the VBA code and/or the Python scripts mentioned above.
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Alan Mourgues is a Petroleum Reservoir Engineering Consultant with 25 years of international experience. He is the founder of CrowdField — the go-to hub for Oil & Gas subsurface professionals to upskill, freelance, and monetize their expertise. CrowdField brings together a global community through: i) Freelance marketplace for niche talent and task-based solutions; ii) Digital Store & Vault of engineering tools, workflows, and resources; iii) AI Hub showcasing startups, workflows, and use cases; iv) Learning resources including webinars, blogs, and curated datasets. Alan’s mission is to empower professionals to turn knowledge into income and future-proof their careers as the energy transition unfolds.
