---
title: Exploring your data
category: Explore and Visualize
slug: exploring-data
blurb: Explore your dataset with charts, pivots, and powerful filters—including multiple filters combined with AND and OR logic.
order: 2
---
# Exploring your data

AddMaple is built for exploration. When you open a project, every column is summarized on the Chart Dashboard. From there you can expand charts, pivot columns together, drill into rows, and—most importantly—**filter** your data to focus on the audience or segment you care about.

Filters in AddMaple are **instant** and **global**: once applied, they update every chart, table, pivot, statistical test, and related-column calculation across your project.

## Ways to explore

| View | What it's for |
|------|----------------|
| **Chart Dashboard** | See every column at a glance; expand, filter, and pivot from any chart |
| **Pivot charts** | Compare two or more columns side by side |
| **Table** | Scan responses; click values to filter |
| **Row by row** | Read individual records in full, with cohort context |

Toggle between views from the top of the workspace. For a full survey-analysis walkthrough, see [How to analyze a survey](how-to-analyze-a-survey).

## Add a filter

There are several ways to start filtering:

### 1. Filter button

From the Chart Dashboard, table, or row view, click **Filter** at the top of the screen—or press **/** on your keyboard.

![AddMaple Filter button](https://prismic-io.s3.amazonaws.com/addmaple/c8e5664a-5455-4783-9ebe-872fac864ac3_addmaple-action-menu.png)

Choose a column, then choose how to filter. The options depend on the column type—for example, categorical columns support **is** and **is not**, while numeric columns support **greater than**, **less than**, and **between**.

![AddMaple Filter Select menu](https://prismic-io.s3.amazonaws.com/addmaple/2f62207c-720a-4128-bde4-3271f34bcc97_addmaple-filter-select-menu.png)

![AddMaple filter by country](https://prismic-io.s3.amazonaws.com/addmaple/023b5e7c-2468-4064-bb41-57aa694166c2_addmaple-filter-by-country.png)

### 2. From a chart

Expand a column, then hover over a bar (or segment) and click **Filter by this value**.

![Horizontal bar chart with filter in popover](https://images.prismic.io/addmaple/bdd4272d-5721-471f-8df2-3509687ba396_chart-filter.png?auto=compress,format)

### 3. From a date chart

Click a bar on a date chart to filter to that date range.

![Date chart](https://images.prismic.io/addmaple/6da4945f-c257-4bb5-b9ce-80f26f6c5939_date-chart.png?auto=compress,format)

### 4. From the table

In table view, click any categorical value in a row to add it as a filter.

![AddMaple Table View](https://images.prismic.io/addmaple/d8a90989-53a6-4bb4-b7fe-a262d68cf847_addmaple-table-view.png?auto=compress,format)

You can also add filters from the sentence builder when pivoting. See [Adding a filter](../sentence-builder/addfilterdashboard).

## Combine multiple filters with AND and OR

AddMaple supports **advanced filtering**: stack multiple filters and control how they combine. This is one of the most powerful ways to explore subgroups in your data.

### How AND and OR work

- The **first filter** always uses **AND** logic.
- Each additional filter can stay on **AND** (narrow further) or switch to **OR** (broaden the match).
- **AND** filters narrow your audience: respondents must match **all** AND conditions.
- **OR** filters broaden a condition: respondents can match **any** OR option within that group.

AddMaple groups filters automatically: all **AND** conditions must be satisfied together, while **OR** conditions within the same column group create a broader match.

### Examples

**Narrow with AND** — respondents who match every condition:

- `Department` **is** `Sales` **AND**
- `Age Group` **is** `25–34` **AND**
- `Overall satisfaction` **is greater than or equal to** `4`

Result: a tight segment of satisfied sales employees aged 25–34.

**Broaden with OR** — respondents who match any of several values:

- `Country` **is** `United Kingdom` **OR**
- `Country` **is** `Ireland`

Result: respondents from either country.

**Mix AND and OR** — common in real analysis:

- `Work location` **is** `Remote` **OR** `Work location` **is** `Hybrid` **AND**
- `Tenure` **is greater than or equal to** `2` years

Result: remote or hybrid workers with at least two years' tenure.

### What updates when you filter

Filters remove rows **before** any calculation runs. When you apply or change filters:

- All charts and tables update instantly
- Pivot percentages and counts recalculate
- [Related columns](../stats/related-columns) and [statistical tests](../frequently-asked-questions/statisticalcalculations) recalculate for the filtered audience
- Exports and dashboards reflect the filtered data

To see exactly which rows are included, check the status line above your pivot. See [Filtering vs hiding](../pivot-chart-and-table/filtering-vs-hiding).

## Filter types by column type

AddMaple offers different filter operators depending on whether a column is numeric, categorical, multi-select, text, or a date. Examples include:

- **Numeric** — equal to, between, greater than, less than
- **Single-select categorical** — is, is not, has more than (minimum count threshold)
- **Multi-select** — includes any, includes all, doesn't include, count operators
- **Text** — contains, doesn't contain (with optional whole-word matching)
- **Date** — is between (click a bar on a date chart to pre-fill a range)

For the full reference table, see [Use filter types](../pivot-chart-and-table/filter-types).

## Filters vs hiding

**Filters** remove respondent rows from the entire project. **Hiding** removes categories from a single chart without dropping rows from the dataset. Both can be active at once—the status line shows filtered rows, hidden categories, and weighted counts.

See [Filtering vs hiding in pivot charts](../pivot-chart-and-table/filtering-vs-hiding).

## Build reusable audience segments

If you need a segment you'll reuse across charts—for example **Detractors**, **Enterprise buyers**, or **Remote staff**—create a [custom variable](../data-types/create-segment) instead of stacking filters each time. Custom variables appear as columns you can filter, pivot, and analyze like any other field.

For focused client views built from filters and segments, see [Subgroup views](subgroup-views).

## Related guides

- [Filter your data](../frequently-asked-questions/filter-your-data) — quick FAQ summary
- [Use filter types](../pivot-chart-and-table/filter-types) — full operator reference
- [Filtering vs hiding](../pivot-chart-and-table/filtering-vs-hiding) — rows, results, and the status line
- [Exploring related columns](../stats/related-columns) — find statistically meaningful relationships to explore next
- [How to pivot your data](../frequently-asked-questions/how-to-pivot-your-data)
- [Subgroup views](subgroup-views) — reusable audience cuts for client deliverables

---

### Key points

- Filters apply instantly across your entire project
- Stack multiple filters and combine them with **AND** and **OR**
- Filter from the top menu, charts, tables, dates, or the sentence builder
- Related columns and stats recalculate when filters change
- Use custom variables for segments you reuse often