Data Formatting and Precision

In general, Superchart will adopt the same data formatting and precision as provided by the data source.

The following sections describe which elements Superchart will inherit from the data source automatically and some common steps to ensure the data in Superchart matches the source.

Number Precision

Precision is the measure of exactness that can be expressed with a specific number of digits or decimal places. Number precision is an important factor in data visualization, because it helps ensure accuracy in the representation of data. Superchart will interpret and inherit number precision from the source data.

Google Sheets Number Precision

If you have a number column but haven't touched the formatting, there is a good chance it is set to 'Automatic' (as shown below). When running aggregate calculations on 'Automatic' number formatting, Superchart will attempt to be as accurate as possible. This can lead to results with many decimals (i.e. an average of 12.343209342304 in a pivot table instead of a rounded value).

If you want to adjust that precision, there are a few ways. Choose 'Custom Number Format' as shown below or choose from one of their pre-formatted number/precision options.

Excel users are generally most familiar with the quick option in the top menu. This has the same effect, setting the format and precision for the number.

There are a number of other options for changing precision and number formatting. If you've already started building a visualization in Superchart, make sure to refresh the data in your visualization after making any modifications to precision or formatting on numbers.

Airtable Number Precision

In Airtable, number formatting is generally more explicit. See the example below for the configuration around number precision in Airtable:

Again, if you've already started building a visualization in Superchart, make sure to refresh the data in your visualization after making any modifications to precision or formatting on numbers.

Beyond general number data types, there are a couple of other common fields that adopt formatting and precision. Next, we'll touch on currency.

Currency

Currency is generally a specific data type in a database, as it allows users to store and work with monetary values. Operations and data display are slightly unique for currency or monetary data.

Google Sheets Currency Precision

With a plethora of preconfigured currency number formats, you'll most likely want to select a from the Google Sheets predefined list. Be sure to refresh the data in Superchart if you've made any modifications to the formatting of Google Sheets currency data.

Airtable Currency Precision

Similar to number precision, Airtable takes a fairly explicit approach to currency precision. You can see in the screenshot below the configuration options for currency precision in Airtable:

Once you've formatted the currency type and precision for the value in Airtable or Sheets, Superchart will adopt that same configuration. Refresh the data in Superchart if you've made any modifications to the currency formatting in Airtable.

Percentages

Percentage values are often stored in a particular field type in a database to ensure accuracy and precision when performing calculations. Operations and data display are slightly unique for a percentage.

Google Sheets Percentage Precision

Similar to other number formats, Google Sheets allows you to modify the precision and display of percentage fields. See the screenshot below on custom number formatting for percentages:

If you've already synced data to Superchart and subsequently change field formatting in Google Sheets, make sure to refresh the data in Superchart.

Airtable Percentage Precision

Once again, Airtable is more explicit when dealing with percentages. There is a field type for percentages and you can set the precision as follows:

Be sure to refresh the data in Superchart if you've made any modifications to the formatting of Airtable number types.

Messy Data

It's not as easy as it sounds to read data formatting from the data source. Charting and visualization tools rely on "clean data"; Google Sheets, Airtable, and other flexible no code tools support some pretty messy data. We do our best, but Superchart is no exception to that "clean data" rule. If you're having trouble with a specific data set in either Airtable or Google Sheets, here are some basics to check:

• Empty Cells - It sounds obvious, but it's a remarkably easy to have patches of missing data in a large data set. Rows with partial or adjusted data (i.e. empty cell shifts, incorrect delimiters during csv imports, etc.) can make the data near impossible to interpret or aggregate. Make sure you don't have missing data or any obvious formatting issues in the data.
• Column Header but No Data - If you have a bunch of empty columns with header text, you probably want to remove that at the visualization stage. Generally, visualization tools don't love empty data sets.
• Empty Header Rows - Sometimes exports or other spreadsheets have a empty rows at the top, either for formatting or containing limited data related to the export. You'll want to remove these 'empty' rows before trying to visualize the rest of the data in the sheet.
• Columns with Multiple Data Types - If you have a currency value, number value, and percentage all in the same column you may want to transpose your data. Visualization tools, Superchart included, prefer data in structured and consistent row-oriented formats.

To steal inspiration from some of the greatest skiing instruction content ever created... If you mix data formats in the same column and try to run aggregations, you're gonna have a bad time. Reach out to us via hello@superchart.io if you've having particular issues with data formatting or data causing errors in Superchart.