# Tables and Pivot Tables

View and analyze your data in flexible tabular formats

Tables provide a direct view of your data, while pivot tables let you summarize and cross-tabulate dimensions. Both are essential tools for understanding what's in your dataset.

# Data Tables

By default, when you select a table it displays your data by time (usually by snapshot or load date):

![](https://docs.scoopanalytics.com/assets/legacy/c8a06a6-image-4d9629d8e6.png)

## Time Series Toggle

Click the **Time Series** slider to change how data is aggregated:

![](https://docs.scoopanalytics.com/assets/legacy/2a77599-image-cdc7f516b8.png)

| Mode | Description |
|------|-------------|
| **Time Series ON** | Groups data by date, shows trends over time |
| **Time Series OFF** | Aggregates across all dates into summary |

## Time Range Selection

By default the time range is set to "Most Recent", limiting to the latest load. You can extend this:

- **Most Recent**: Latest snapshot only
- **Last 7 Days**: Rolling week
- **Last 30 Days**: Rolling month
- **Custom Range**: Specify start and end dates
- **All Time**: Complete history

This is especially useful for non-snapshot (transactional) datasets where you want to analyze all historical records.

## Table Features

| Feature | How To |
|---------|--------|
| **Sort** | Click column header |
| **Multi-sort** | Shift+click additional columns |
| **Filter** | Use Filter tab in left panel |
| **Show/Hide Columns** | Uncheck in column list |
| **Export** | Click Export button for CSV/Excel |

# Pivot Tables

Pivot tables let you summarize data by grouping rows and pivoting columns. Click the table bar to the right of your table to open pivot options:

<Image align="center" width="300px" src="https://docs.scoopanalytics.com/assets/legacy/4b70c75-image-4db7a71537.png" />

## Enabling Pivot Mode

Click the **Pivot Mode** slider to enable two key capabilities:

<Image align="center" width="400px" src="https://docs.scoopanalytics.com/assets/legacy/35d9600-image-d1a9647baa.png" />

- **Row Grouping**: Nest dimensions hierarchically
- **Column Pivoting**: Spread an attribute across column headers

## Row Grouping

With row grouping, you can expand and collapse individual items to progressively drill into your data:

<Image align="center" width="400px" src="https://docs.scoopanalytics.com/assets/legacy/db52a7c-image-f302addeeb.png" />

**To create row groups:**
1. Enable Pivot Mode
2. Drag columns to the row grouping area
3. Order determines nesting (top = outermost)
4. Click expand (+) icons to drill down

**Example hierarchy:**
```
Region (outer)
  └── State (middle)
        └── City (inner)
```

## Column Pivoting

Drag an attribute to the column labels area to pivot it across columns. For example, dragging "Channel" creates column headers for each channel value:

<Image align="center" width="650px" src="https://docs.scoopanalytics.com/assets/legacy/44fc4b2-image-dc2f7f8f33.png" />

**Best practices for column pivoting:**
- Choose dimensions with 3-10 unique values
- High cardinality columns (100+ values) create too many columns
- Time periods (Quarter, Month) work well as column pivots

## Pivot Table Metrics

At each intersection of row and column, Scoop calculates your selected metric:

| Aggregation | Best For |
|-------------|----------|
| **Sum** | Revenue, quantities, totals |
| **Count** | Number of records |
| **Average** | Rates, percentages, scores |
| **Min/Max** | Ranges, outliers |
| **Distinct** | Unique counts |

# Common Pivot Patterns

## Sales by Region and Quarter

**Configuration:**
- Row Groups: Region, Rep
- Column Pivot: Quarter
- Value: Sum of Revenue

**Result:**
```
                Q1        Q2        Q3        Q4
West        $450K     $520K     $480K     $610K
  Sarah     $180K     $210K     $190K     $240K
  Mike      $150K     $170K     $160K     $200K
  Lisa      $120K     $140K     $130K     $170K
Central     $380K     $410K     $420K     $520K
```

## Pipeline by Stage and Owner

**Configuration:**
- Row Groups: Stage
- Column Pivot: Owner
- Value: Sum of Amount, Count of Deals

**Result:** See pipeline distribution across reps at each stage

## Conversion by Source and Month

**Configuration:**
- Row Groups: Lead Source
- Column Pivot: Month
- Value: Count of Leads, Count of Customers, Conversion Rate

**Result:** Track which sources convert best over time

# Working with Large Datasets

## Performance Tips

1. **Filter first**: Narrow data before pivoting
2. **Limit dimensions**: Use Top N for high-cardinality columns
3. **Date rollups**: Group by month vs day
4. **Pre-aggregate**: Create blended datasets for common analyses

## Row Limits

| Context | Limit |
|---------|-------|
| Preview | 1,000 rows |
| Full view | Up to 10,000 rows |
| Export | Unlimited |

# Exporting Tables

## Export Options

Click **Export** to download:

| Format | Use For |
|--------|---------|
| CSV | Data processing, imports |
| Excel | Offline analysis, pivot tables |

Export includes:
- Current filters
- Sorting
- All visible columns
- Full data (not just visible rows)

## Adding to Canvases

To embed tables in presentations:

1. Configure your table in Explorer
2. Click **Save** and name it
3. Open your canvas
4. Add the saved table as an object
5. Table updates when data syncs

# Troubleshooting

## Table Shows No Data

- Check active filters
- Verify time range includes data
- Confirm dataset has synced
- Look at column selection

## Pivot Totals Don't Match

- Check for null values in grouping columns
- Verify aggregation type
- Some rows may be excluded by filters
- Compare to ungrouped table view

## Slow Performance

- Add filters to reduce data
- Limit pivot dimensions
- Use monthly vs daily grouping
- Consider pre-aggregated datasets

# Related Topics

- [Filtering Data](filtering-data) - Narrow your results
- [Charting Time Series Data](charting-time-series-data) - Visualize trends
- [Non-Time Series Data](non-time-series-data) - Aggregate analysis
- [Visual Themes](visual-themes) - Style your tables