You have the tools to create fungal charts, but how do you create a good one?
If you don’t have a spreadsheet, then it’s really easy to get lost in your own little world of data visualization.
For this tutorial, I’ll be using a chart of the number of new infections reported in India last year.
The charts are generated by a script from PandemicTech, a popular data visualization tool.
PandemicTech has also produced this tutorial for you, if you want to make one yourself.
The basic approach is simple.
You import the data from the chart into Pandemic, and you select a chart type (such as the number or number per 100,000), and a scale (the number of pixels in a chart, and how big they are).
Then you open up the chart in Pandemic.
You’ll notice that the chart is scaled down, so that it looks like the image above.
Next, you have to import the dataset.
It’s a little tricky, because the data comes in a CSV file.
Pandemic automatically creates these files for you.
Once you have the CSV file, you can import it into Pandemia.
Each chart has a name, a type, and a scaling scale.
The name of the chart tells you what it is, and the type tells you its scale.
Then you can use the chart as a reference for a visualization.
To make the chart bigger, you could choose a higher scale, but if you scale the chart to a smaller scale, it will look even smaller.
Finally, the name of each chart tells Pandemic what the number should be.
There are lots of charts with this name, so the name tells you the chart’s type.
This is important, because a chart is not just a single line of data.
As you can see from the image below, there are multiple charts with different names.
One chart with a name of “100 million infections” has a scaling factor of 10, while another with a naming that doesn’t appear on the chart has an average of 100.
If the name is wrong, Pandemic can’t find the chart, so it just goes away.
So what does Pandemic say when you import it?
Pandemia says that it needs a chart name and a name type that you can choose from the drop-down menu.
In other words, you need a name that is a subset of a chart’s data type.
I chose to use the name “100,000 infections.”
The chart is about 100 pixels wide, and it is about 10 pixels tall.
Then, you select the chart type, select the scaling scale, and click Import.
And there you go!
Now you can plot the data and make a fungal chart with it.