> ## Documentation Index
> Fetch the complete documentation index at: https://docs.nrev.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Filter Data

> Apply flexible filters to your dataset—combine conditions, use logic rules, and reference other columns to control what passes through.

## What It Does

* **Filters rows** based on one or more conditions
* **Combines filters using AND/OR logic**
* **Supports text, number, boolean, and blank checks**
* **Allows dynamic comparisons between columns**
* **Returns only the rows that match your rules** — with all columns intact

***

## 🏁 Getting Started

<Frame>
  <img src="https://mintcdn.com/nurturev/OitEIaKlfl7lCKCJ/images/Filter%20Data%20node%20configuration%20screenshot.png?fit=max&auto=format&n=OitEIaKlfl7lCKCJ&q=85&s=512006975f743be86c63d37f86af70e7" alt="Filter Data node configuration screenshot" style={{ borderRadius: '0.5rem', width: '100%', margin: '1.5rem 0' }} width="1178" height="1664" data-path="images/Filter Data node configuration screenshot.png" />
</Frame>

<Steps>
  <Step title="Add the Node">
    Drag in the **Filter Data** node from the panel.
  </Step>

  <Step title="Connect an Input">
    Use any upstream node that outputs the dataset you'd like to filter.
  </Step>

  <Step title="Set Filter Conditions">
    Select a column, choose a condition (e.g., “is equal to”), and enter a value or reference another column.
  </Step>

  <Step title="Set Combination Logic">
    Use **AND** to require all conditions to match, or **OR** to allow any.
  </Step>

  <Step title="Run the Node">
    The output will include only rows that pass your filters.
  </Step>
</Steps>

***

## Inputs

### 🛠️ Required Fields

* **Filter Logic (✅)**\
  Choose whether filters are combined with `AND` or `OR`.\
  *Why it matters:* Defines how strict or flexible the matching will be.

* **Filter Conditions (✅)**\
  Add one or more conditions to define which rows should pass.\
  *Why it matters:* Each condition filters your data by value or structure.

<Note>
  Only existing columns are available — missing fields are automatically excluded.
</Note>

***

## Available Conditions

| Condition          | Description                                   |
| ------------------ | --------------------------------------------- |
| `is_equal_to`      | Matches exactly to a given value              |
| `is_not_equal_to`  | Matches anything except a specific value      |
| `is_greater_than`  | Only allows rows with higher numeric values   |
| `is_less_than`     | Only allows rows with lower numeric values    |
| `is_empty`         | Matches blank or missing fields               |
| `is_not_empty`     | Matches any field that has a value            |
| `is_true`          | Matches `true` booleans                       |
| `is_false`         | Matches `false` booleans                      |
| `contains`         | Field includes a substring (case-insensitive) |
| `does_not_contain` | Field does **not** include a substring        |

<Note>
  Use “value from another column” to create **row-level dynamic comparisons**.
</Note>

***

## Output

Returns a filtered version of your dataset.

* All columns are preserved
* Row order remains unchanged
* Only rows that satisfy the rules will be passed forward

***

## How It Works

1. Loads your input data
2. Applies each condition to the selected column
3. Combines rules using AND or OR
4. Returns only matching rows

***

## 🚀 Example Use Cases & Prompts

| Use Case                  | Filter Example                                         |
| ------------------------- | ------------------------------------------------------ |
| Clean out test records    | `email contains test`, `status is not equal to active` |
| Filter by ICP segment     | `tier is in Strategic,Enterprise`                      |
| Focus on high-score leads | `score is greater than 85`                             |
| Row-level match           | `region equals value from assigned_region column`      |

***

## ✨ Pro Tips

<Tip>
  Use `is in` with comma-separated values (e.g., `IT,Marketing`) to include multiple options at once.
</Tip>

<Tip>
  Reference other columns for powerful **row-level logic**—great for matching teams, regions, or reps dynamically.
</Tip>

<Tip>
  Try OR logic to broaden results if you're getting too few matches.
</Tip>

***

## ⚠️ Important Considerations

<Warning>
  Only columns from your input data can be used in filters—no risk of referencing a missing field.
</Warning>

<Warning>
  Make sure the condition matches the field type: numeric filters for numbers, text filters for strings.
</Warning>

<Warning>
  Dynamic comparisons only work when both columns exist in every row.
</Warning>

***

## 🛠 Troubleshooting & Gotchas

| Symptom                  | Likely Cause                             | Suggested Fix                         |
| ------------------------ | ---------------------------------------- | ------------------------------------- |
| No rows in output        | Filters are too strict                   | Try OR logic or relax your conditions |
| “Type mismatch” error    | Comparing number to text (or vice versa) | Update to compatible filter type      |
| Dynamic rule not working | Referenced field doesn’t exist in a row  | Adjust logic or use default fallback  |

***

## 📝 FAQ

<AccordionGroup>
  <Accordion title="Can I add multiple filter conditions?">
    Yes — add as many as you need, and combine them with AND/OR logic.
  </Accordion>

  <Accordion title="Can I compare one column to another?">
    Absolutely — select “value from another column” for dynamic comparisons.
  </Accordion>

  <Accordion title="Can I check for blank values?">
    Yes — use `is_empty` or `is_not_empty` to handle missing fields.
  </Accordion>
</AccordionGroup>

***

## 💰 Pricing

> The Filter Data node is **free** — no credits required.

***

<p style={{ fontSize: '1rem', fontWeight: 'bold', marginTop: '1.5rem' }}>
  Filter with precision — apply logic, narrow results, and keep only what matters to your GTM plays.
</p>