*Table chart

Create and configure table charts in the Polyteia Platform.

Table charts are perfect for displaying your data in an organized list format - like a digital filing system for your information. Think of it like creating a clean report that you could present at a city council meeting or health department briefing.

You can use table charts in two ways:

• Regular tables - Simple lists of your data with custom columns and groupings

• Pivot tables - Advanced cross-tabular analysis that organizes data by categories

When to use table charts

Table charts work well when you want to:

• Show detailed information that doesn't fit well in other chart types

• Present data to colleagues who need to see specific numbers

• Create reports for government meetings or public presentations

• Display lists like "Districts by vaccination rate" or "Emergency response times by neighborhood"

Example uses:

• Public health officials showing vaccination rates by district and age group

• Emergency services displaying call types by neighborhood and time

• Budget managers listing expenses by department and quarter

Creating table charts

1

Set up your table

1. Go to the Chart tab in the right sidebar

2. Select Table from the Chart type menu

3. Your data will appear in a clean table layout with sortable columns (enabled by default)

All columns are sortable by default - users can click any column header to sort the data ascending or descending.

2

Choose and organize your columns

In the Metrics section on the right:

• Click "Add metric" to include more information from your data

• Remove columns using the small ✕ next to them

• Rename any column by clicking the three dots ••• and changing the "Title"

• Switch which data column is displayed if needed

• Drag columns to reorder them in your table

3

Create column groups (optional)

Organize related columns under group headings for better organization:

1. In the table settings, look for "Column groups"

2. Click "Add group" and enter a descriptive name (like "Q1 Data" or "Demographics")

3. Drag columns into the group to organize them

4. Reorder groups and columns as needed

Example groupings:

• "Financial": Budget, Actual_Spending, Variance

• "Demographics": Age_Group, Gender, Population_Count

• "Performance": Response_Time, Success_Rate, Satisfaction

This creates clean section headers that make large tables easier to read.

4

Customize column appearance

Make important data stand out:

1. Click the three dots ••• next to any column

2. Choose display options:

   • Column colors: Apply heatmap or text coloring based on values

   • Number formatting: Set decimal places, add currency symbols

   • Sortable: Disable sorting for specific columns (enabled by default)

3. Preview your changes in the table display

5

Set pagination and display options

Control how much data is shown at once:

• Show all rows - Display everything (good for small datasets)

• 5, 10, 25, or 50 rows per page - Break large datasets into manageable sections

• Navigation buttons appear automatically when pagination is used

Chart title and description:

• Title - What your table shows (like "District Vaccination Rates Q1 2024")

• Description - Explain what the data represents for viewers

Creating pivot tables

For advanced cross-tabular analysis, you can create pivot tables that organize data by categories.

To create a pivot table:

1. Set up your pivot structure first in the query builder - see our comprehensive Pivot Tables guide for full step-by-step instructions

2. Once your pivot table is configured in the data preview, come to the Chart tab

3. Select Table as your chart type to display your pivot analysis

The pivot table will show your data in a grid format with:

• Rows: Categories down the left side (like states, districts, departments)

• Columns: Categories across the top (like months, age groups, service types)

• Values: Totals or counts at each intersection

Pro tip: Pivot tables work especially well as table charts because you can see all the cross-tabulated data clearly, use column groups to organize complex analysis, and apply sorting to find patterns quickly.

Advanced table features

Column groups in detail

Column groups help organize complex tables with many columns:

In regular tables:

• Group related metrics (like "Financial Metrics", "Performance Indicators")

• Create logical sections that match how people think about the data

• Make wide tables easier to scan and understand

In pivot tables:

• Group time periods (Q1, Q2, Q3, Q4 under "2024 Quarters")

• Organize demographic breakdowns (age groups under "Demographics")

• Separate different metric types ("Counts" vs "Percentages")

How to use groups effectively:

1. Start with your most important grouping

2. Use clear, descriptive group names

3. Limit to maximum 3-4 groups for readability

4. Order groups by importance or logical flow

Column coloring

Make data patterns visible with automatic coloring:

Heatmap coloring:

• Background colors based on values (higher values = darker colors)

• Perfect for quickly identifying outliers and patterns

• Good for budget variances, performance metrics, population density

Text coloring:

• Text color changes based on values

• Useful for status indicators, positive/negative values

• Less visually overwhelming than background colors

Differences between table and data table

Table charts (Chart tab)

• Purpose: Clean, polished presentations for reports and sharing

• Features: Custom titles, descriptions, pagination, column groups, coloring

• Sorting: All columns sortable by default, can be disabled per column

• Best for: Final reports, dashboards, presentations to stakeholders

Data tables (Data tab)

• Purpose: Interactive exploration and analysis of raw data

• Advanced features:

  • Interactive headers with inline column renaming

  • Advanced filtering with multiple operators per column

  • Column management (add, remove, reorder columns)

  • Copy-to-clipboard functionality for any cell

  • Row limit controls up to 15,000 rows with performance optimization

  • Type-aware cell rendering for dates, numbers, and text

  • Filter status indicators showing active filters and sorting

• Best for: Data exploration, pattern discovery, understanding data quality

Troubleshooting common issues

"My table shows no data"

• Check data source: Verify your insight has data in the Data tab

• Review filters: Make sure filters aren't excluding all your data

• Verify columns: Ensure selected columns contain values

• See also: Create insight for data configuration help

"Columns are too narrow/wide"

• Auto-sizing: Most columns automatically adjust based on content

• Manual adjustment: Drag column borders in the preview to resize

• Content length: Very long text may need manual width setting

• See also: Visualization settings for general chart customization

"Too many columns to see clearly"

• Use column groups: Organize related columns under group headings

• Remove unnecessary columns: Focus on only the most important metrics

• Consider multiple tables: Break complex data into focused table charts

• Export option: Use data export for full dataset access

• See also: Data export for downloading complete data

"Pivot table shows empty cells"

• Check data combinations: Not every row/column combination may have data

• Filter data: Reduce scope to focus on relevant combinations

• Verify relationships: Ensure your row and column categories actually match

• See also: Pivot tables for detailed pivot troubleshooting

"Table loads too slowly"

• Add pagination: Break large datasets into smaller pages

• Filter data first: Reduce the amount of data being displayed

• Limit columns: Show only essential information

• Consider aggregation: Use summarized data instead of raw datasets

• See also: Aggregation for data summarization techniques

"Sorting doesn't work as expected"

• Data types: Make sure numbers are stored as numbers, not text

• Mixed data: Columns with mixed data types might sort unexpectedly

• Custom sorting: Some data may need specific sorting logic

• See also: Data types for understanding data formats

Remember: Table charts are most effective when your data is already well-organized and clean. If you're having display issues, the problem might be in the data preparation phase rather than the chart configuration.