How-to guides

AddMaple has an intelligent engine for detect multi-select columns, however it is not possible to always detect this accurately.

AddMaple is one of the few cloud based software tools that can read SPSS (or SAV) data files. They have an unusual format and can't be opened by standard spreadsheets.

Discover how to open .sav files without SPSS. We show you how to convert .sav files to excel or .csv, as well as how you can instantly explore and analyze .sav files in the cloud without SPSS.

Below is a guide for how to work with an AI research Co-Pilot to analyze text.

AddMaple makes it easy to merge categories or tags into a single value. This is especially useful for combining smaller categories or creating custom groupings. In this example, we’ll show you how to merge Sweden, Norway, Finland, and Denmark into a single category called “Scandinavia.”

With AddMaple, you can easily rename categories without altering your original data. The changes are saved in your project settings, so the original data remains untouched.

AddMaple supports grouping columns with overlapping categories, which is especially useful for aligning data across similar questions. This grouping often happens automatically for opinion scales, but you can also manage it manually when needed.

Analyzing open-ended survey responses, such as brand, product, or artist mentions, can be challenging due to variations in spelling and phrasing. With AddMaple’s “Merge Similar Mentions” feature, you can clean and organize this data in seconds.

After you've created a new column with thematic codes, you can add or edit codes via the table view.

Learn how we use OpenAI, but how your data is not stored or used for training new models.

In large datasets you may want to search on your chart dashboard for a particular column.

AddMaple understands that sometimes you will have personally identifiable information (PII) or sensitive data in your dataset. Rather than expect you to remove sensitive columns and join it back later (which could lead to scrambling or other issues), we simply let you encrypt the sensitive columns while keeping the dataset intact.

In survey data, you might have a column with many small categories that only have a few responses each. For example, a global survey with a country question could include many countries with very few respondents. Filtering out these smaller categories can be helpful because:

AddMaple allows you to aggregate one column by another. For example if you have a numeric column - Salary, and a categorical column - Age Range, you can use AddMaple to view median salary by age range.

AddMaple detects numeric data and automatically creates bins/buckets so that you can visualise the data in a histogram.

Our multi-select data type is for columns where there can be more than one result. This could be a "select all that apply" question in a survey, or a set of tags exported from a database.

This is the main categorical column type that we have in AddMaple. It will show up with turquoise bars in the chart dashboard

You can let viewers of your report also explore your data using AddMaples tools.

You can change the title of a column by clicking on it from the Chart Dashboard. An input box will appear where you can make your changes. Click the green tick button or press "enter" to save.

To add a filter you can either click the kebab menu (or press the / key) and select "Add Filter"

Reports are unpublished by default. To publish, simply click the "Publish" button - the url of your published report will then be made visible.

To add a chart to your report, simply navigate to the chart you want to add, click the options menu and click "Add To Report".

In row by row view you can navigate between rows through the Next and Previous buttons.

This view allows you to see a single "row" from you data in a vertical view. This is a lot easier than a traditional spreadsheet (table) view and allows you to dive into a specific row to see the results for all columns for that row.

You can add a filter by clicking on the value for a particular column

You can add a filter by clicking on the value that you would like to filter by in the table. For example when viewing an "Age" column, clicking on the "65+" value from one of the rows will filter the entire table to only show rows where the "Age" is "65+".

To explore a single row, simply click on the row number (in the left column)

All columns in the table view are sortable. Simple click on the sort icon next to the column title. Clicking again will toggle between ascending and descending order.

This is done via the multi select box in the sentence builder.

While viewing any chart in AddMaple, whether a single or multiple pivot, you can get an AI powered explanation.

When viewing a text column, you will see a button: Get AI Summary

If AddMaple detects columns that are significantly related to your selected column they will show up in the Stats tab:

Where AddMaple detects multiple opinion scale columns next to each other we group them together.

When you expand a opinion scale column it will be displayed as a standard AddMaple bar chart.

AddMaple runs chi-square tests for you automatically to determine whether there is a significant relationship between two categorical columns and the strength of that relationship.

AddMaple will automatically run an ANOVA test when you pivot by a categorical column and a numeric column.

AddMaple performs a 2-sided T-Test automatically when you pivot by a numeric column and a categorical column with only 2 categories. If you want to run a T-Test on a column with more than 2 categories, you first need to filter down to only look at 2 categories.

AddMaple allows you to create new columns with custom "segments". These segments can be as simple or as complex as you need. You can create fine-grained personas from multiple filters or just create a simple single filter segment.

AddMaple automatically calculates appropriate "bins" or groups for numeric and date data. These are re-calculated automatically based on your dataset and the filters you have applied.

You can add a pivot no matter what screen you are on in AddMaple by using the Options menu

When you pivot by a categorical column and a numeric column, and the categorical column contains 2 or more categories with less than 4 results, AddMaple will use the Kruskal-Wallis test rather than ANOVA.

These are run automatically when pivoting by 2 numeric columns. Pearson’s correlation is applied if the data is normally distributed, while Spearman’s correlation is used if the data is not normally distributed. These tests measure the strength and direction of the relationship between the two numerical variables.

From detecting data types, to automatic numeric binning, we explain how automation makes AddMaple fast and breezy to use

Find out how to use AddMaple's stats engine and how it works

AddMaple analyses your data in your browser without uploading it to the cloud. We use modern web APIs to read and process your files all within your browser.

AddMaple makes it simple and intuitive to pivot your data. We help you cross-tabulate, pivot and aggregate your data without any complicated settings.

Generate interactive graphs from your raw survey data and embed them in a report

AddMaple detects many different column types automatically including numbers, currency, dates, categories, etc.

AddMaple supports powerful instant filters that are applied across your entire dataset. Filters can be applied directly from charts.

AddMaple is designed to work with any data source - this includes data where column names or items of data may be long, or where there are many possible values for a column.

AddMaple automatically analyses your data from a file and generates charts for you.

AddMaple can read large data files - including files that will crash a spreadsheet. On a modern computer AddMaple can easily read in data files of up to 200MB...