Basedash supports a wide variety of chart types to help you visualize your data effectively. Our AI automatically selects the most appropriate chart type based on your data and requirements, but you can also specify the chart type in your natural language requests.

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How AI chooses chart types

Basedash AI analyzes your request and data structure to determine the optimal visualization:
  • Data type analysis: Examines column types (dates, numbers, categories, etc.)
  • Query intent: Understands what you’re trying to show (trends, comparisons, distributions, etc.)
  • Data volume: Considers the number of data points and categories
  • Best practices: Applies visualization best practices automatically
  • SQL generation: Creates appropriate SQL queries to fetch the required data

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Chart type categories

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Data visualization charts

Perfect for analyzing and presenting data:

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Data display components

For presenting information in various formats:

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Specialized visualizations

For specific use cases and data types:

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Requesting specific chart types

You can specify chart types in your natural language requests:
  • “Show me monthly revenue as a line chart”
  • “Create a pie chart of sales by region”
  • “Display customer satisfaction scores as a horizontal bar chart”
  • “Show conversion rates in a funnel chart”
  • “Display total revenue as a number”
  • “Show me user activity patterns as an activity chart”

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Adding breakdowns

Use the “broken down by” syntax to slice your data into multiple series:
  • “Show me user signups broken down by email domain”
  • “Display sales broken down by product category”
  • “Create a chart of visitors broken down by page”
  • “Show me revenue over time broken down by region”
See Breakdowns for more examples and best practices.

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Best practices for chart selection

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Choose based on your goal

  • Trends over time: Line charts, timebar charts
  • Comparisons: Horizontal bar charts
  • Proportions: Pie charts
  • Conversions: Funnel charts
  • Single metrics: Number displays
  • Activity patterns: Activity charts
  • Geographic data: Map visualizations

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Consider your data

  • Small datasets (< 10 categories): Pie charts work well
  • Large datasets (> 20 categories): Horizontal bar charts are better
  • Time series: Line charts for continuous trends
  • Categorical data: Horizontal bar charts
  • Single values: Number displays
  • Geographic data: Map visualizations

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Design principles

  • Keep it simple - avoid unnecessary complexity
  • Use appropriate colors and contrast
  • Include clear titles and labels
  • Consider your audience’s familiarity with chart types

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Customizing chart appearance

Once a chart is created, you can customize:
  • Colors and themes
  • Axis labels and formatting
  • Chart titles and descriptions
  • Data formatting (currency, percentages, etc.)
  • Legend positioning and styling

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Next steps

Explore individual chart type pages to learn:
  • When to use each chart type
  • Example queries and use cases
  • Best practices and tips
  • Common pitfalls to avoid