Add Maple

Instant Automatic Data Analysis

From detecting data types, to automatic binning, we explain the features that make AddMaple fast and easy to use

Automatic data cleansing and interpretation

When you load a data file into AddMaple, a lot of calculations happen instantly in your browser. Below are the details for the major ones - all of which save you time and enable you to start exploring your data without manually cleaning your data or configuring columns.

Data Type Detection

AddMaple automatically detects your data types for you. We detect numbers, currencies, percentages, dates, opinion scales, categorical data, tags, etc.

This happens instantly even on large datasets and is an important feature as it enables us to provide instant summaries of your data which differ depending on the detected data type.

AddMaple automatically cleans your data for you, for example if you have the values:

  • 130
  • N/A
  • 110
  • 120

AddMaple will understand it as a numeric column even though some of the values have the text "N/A".

Tag Detection

Dealing with tags or survey questions that can have multiple responses to the same question is difficult to do in spreadsheets.

This is where AddMaple shines. We automatically detect this data type whether the data is separated by commas (,), semicolons (;), colons (:), or pipes (|). In a spreadsheet a common approach of dealing with this data would be to separate it using formulas into mutiple columns - but that makes filtering and pivoting much harder.

In AddMaple the data stays in the same column and you can easily explore, filter and pivot.

Instant Summaries

After a data set has been loaded and the data types automatically detected, AddMaple produces instant summaries of each column. This enables you to see an overview of your data at a glance.

Because the column types are automically detected, we can display different summaries for each data type.

AddMaple Instant Summaries

Number Bucketing

AddMaple performs intelligent bucketing (binning or grouping) of numeric data.

Our algorithm handles large, small and negative numeric ranges. The buckets that we create are rounded to sensible values and are not distorted by outliers.

As filters are applied the buckets are recalculated in an instant making it easy to dive into a particular range.

The below data was imported as raw numeric values, but AddMaple automatically grouped it into ranges.

AddMaple Numeric Data
Bar Chart

Written by Ange

User Researcher and Founder of AddMaple

Bar Chart

Other Articles

Bar Chart