Preparing your data
The spreadsheet shape every data-driven project expects, the header rows that attach logos and colours, and how gaps are handled.
The shape
Every race reads the same layout: one column per item, one row per period, and the first column holding the date.
Reading across a row gives you every item's value at one moment; reading down a column gives you one item's history. That is exactly the shape an animation needs, which is why the format is strict about it.
If your data currently has one row per item and one column per date, it is transposed — rotate it before importing.
Header rows
Above the data rows sit optional header rows, and they carry most of what makes a chart look finished.
An image row attaches a logo, flag, or portrait to each column. A colour row gives each item its own bar colour, overriding the chart default. A category row groups items so they can share a colour or be filtered together.
Images can be uploaded files, URLs, country flags, or emoji. For a column of uploaded images, select the first empty image cell and upload the whole set at once — files are sorted by filename and filled down the column, so 01.jpg through 100.jpg land on the rows you expect.
Dates and periods
The first column's dates must match the period chosen when the project was created. An annual project expects one row per year; a monthly project expects one row per month.
This is the single most common import problem, and it is worth saying plainly to a new team: the period cannot be changed after data is entered without re-entering the rows. Decide it first.
Gaps and missing values
Gaps are expected and handled. If an item has no value for a period, leave the cell empty — missing points are interpolated, so items can join the race partway through and drop out later.
Do not fill gaps with zeros unless the value genuinely is zero. A zero is a real data point and will animate as a bar collapsing to nothing, which tells a different and usually wrong story.
Where data can come from
You can paste directly from Excel or Google Sheets, upload a CSV, or type into the spreadsheet by hand.
There is also a built-in statistics library of prepared datasets — population, GDP, YouTube channels, and more — which is useful for training and for prototyping a layout before your own data is ready.
One thing worth telling your team early: projects built on your own data perform substantially better than projects left on sample data. If the goal is real work rather than practice, import real data as early as possible.
Frequently Asked Questions
How many items can we chart?
The spreadsheet will hold far more than you should display. On screen, ten to twelve bars stay readable at 1080p; past fifteen the labels are too small to read on a phone. Use Visible Item Count to show the top slice of a much larger dataset — the rest still drive the race, they just are not all on screen.
Our data steps unevenly. Is that a problem?
It animates, but it can look abrupt where the gaps are large. Adding intermediate periods, or lengthening the per-period duration, gives each transition more time to play out.
Can we update a chart when new data arrives?
Yes. Edit the spreadsheet behind an existing project, add the new rows, and re-render. The layout, styling, and layers are all preserved, which is what makes a recurring monthly video cheap to produce after the first one.
What about currency or unit formatting?
Store the raw numbers and format them for display. The Value settings carry a prefix, a postfix, decimals, a thousands format, and a multiplier — so you can keep exact figures in the sheet and still display them as millions with a leading dollar sign.
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