How to import JSON data into Google Sheets to create a live COVID-19 chart

…in 5 minutes. Without code.

feature image

Today we’re bringing you a guest post from German data journalist Simon Haas, who recently wrote about how to use live-updating JSON data in Google Sheets and Datawrapper – without any code. We were intrigued. Here’s Simon article in an extended version:

There are tons of APIs out there that provide near real-time data that you can use to create automated charts and maps with free tools like Datawrapper, like coronavirus case data or stock market data.

Those APIs usually provide data in JSON format, like in this API by Muhammad Mustadi that provides data about coronavirus cases, collected by the Johns Hopkins University:

screenshot Mathdroid API

This article explains how you can import this JSON data into a Google Sheets table and make sure that it gets updated automatically. There’s no coding or web server required, plus people can collaborate in your spreadsheet and collect data from other sources.

The table I created for the German public-service TV broadcaster ZDF. Find it in its natural habitat here.

Eventually, we create a nice-looking Datawrapper table (the one above) showing the worst-hit countries by the novel coronavirus based on data by Johns Hopkins, including:

  • confirmed cases
  • COVID-19 related deaths
  • a seven-day average of the daily confirmed new cases and deaths
  • and how that average changed compared to the prior seven days

Let’s start:

Step 1: Copy sample sheet and scripts

  • Go to this Google Sheet file I prepared for you.
  • In Google Sheets, click on File → Make a copy. This will also copy two scripts, ImportJSON and triggerAutoRefresh that you can find in Tools → Script Editor.

The spreadsheet should become available in your Google Drive. Thanks to the ImportJSON script, it’s now possible to populate your Google Spreadsheet with JSON data from the API.

Just replace the URL in the corresponding sheet with your API of choice.

screenshot Google Docs

In the sample spreadsheet you find these in cell A1 of the allCountriesCases sheet:

"/", "noTruncate;noInherit", doNotDelete!$A$1)

and in cell J2 in topCountriesTimeline:

""; "/US";
"noInherit,noTruncate,noHeaders"; doNotDelete!$A$1))

The last formula imports the pomber/covid19 API and automatically switches its rows with columns (= “transposes”).

Brad Jasper, the developer behind ImportJSON, explains its option parameter here.

Step 2: Set up a Google “trigger”

Almost done! Next step: Set up a script that generates a random number every x minutes, thus triggering an auto-refresh in your Google sheet.

  1. Go to
  2. Open the menu (three vertical dots) next to ImportJSON
  3. Click on Triggers. This will open a new page.
  4. Click on the blue button in the bottom right, Add Trigger. A pop-up will open in which you can decide on settings for your trigger:
    • Choose which function to run should be set to triggerAutoRefresh
    • Select event source should be set to Time-driven
    • Select type of time-based trigger should be set to Minutes timer
    • Select minute interval: 15 might be a reasonable value in our case

Step 3: Prepare the data for your visualization

The first sheet datawrapper will be used for your visualization. I recommend to import the JSONs in other sheets, do calculations there, then pull them from the first sheet.

If you’re wondering where the arrows in the Trend column come from: Those are calculated in the sheet topCountriesTimeline starting at cell I3.

=IF(AND(H3>=-0.0449, H3<=0.0449), "➙", 
IF(AND(H3>=0.045),"➚", "➘"))

Just change the numbers if you prefer other thresholds.

The Cases column gets calculated like so:


This results in 760,520 ^+29,110^ (probably a higher number by the time you’re reading this), which is the total number of confirmed coronavirus cases in the United States and how many new cases got reported since yesterday. Datawrapper will notice the two ^‘s and make two lines out of it.

What does the formula do? First of all, if there’s an error (IFERROR – e.g. if the JSON is broken), the text in the cell will become “server error”. But if everything is ok, Google Sheets will pull the case numbers from two different columns in the topCountriesSorted sheet.

Because you will show two numbers per cell in your final Datawrapper table, Datawrapper recognizes them as text instead of numbers. Adjusting the number format in Datawrapper won’t be possible anymore. You can transform the numbers to text in the right number format with TEXT(D7, "#,##0") before importing them to Datawrapper.

Step 4: Visualize your data

That’s it! You can now visualize your data with Datawrapper and embed the result on your website. To do so, create a new chart, then select Link external data source (not Import Google Spreadsheet) in step 1: Upload data.

Now paste the Google Sheets URL. Make sure your Google sheet is set to Anyone with the link can view when you click the green Share button. You can find a detailed explanation in this Datawrapper Academy article.

Once that’s done, go to step 2: Check & Describe and select English (en-US) as your Output locale. In step 3: Visualize, tick Parse markdownMerge with emtpy cells and Add first row to header to properly display the table.

Flags can be displayed with Replace country codes with flags. The Countries column is for desktopCountry for mobile only.

This is how your final table looks like:

How it works

Two scripts in your Google spreadsheet are doing all the work for you: ImportJSON.​gs and triggerAutoRefresh.​gs. The latter one generates a random number in cell A1 of your sheet doNotDelete each time it gets triggered. If you change the sheet’s name, you’ll need to change the function in, too. You can access both scripts in Google Sheets in Tools → Script Editor.

This article is based on a tutorial by Vadorequest. The table is inspired by & The APIs used in the sample sheet come from pomber/covid19 & mathdroid/covid-19-api.


This article is based on a tutorial by Vadorequest. The table is inspired by & The APIs used in the sample sheet come from pomber/covid19 & mathdroid/covid-19-api.

Thanks for this great guest post, Simon! Make sure to follow Simon on Twitter (@simondhaas) and find other projects he worked on over at If you’re learning something and would like to teach it to others, get in touch with Lisa at – we’re always looking for data- and Datawrapper-related guest posts.



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