Use visualizations in notebooks

Visualizations are a key component of effective notebooks, helping transform raw query results into clear, compelling charts that support your data narrative. Notebooks support all the same visualization options available in the New Relic query builder.

Available chart types

Choose the right visualization for your data and story:

Line charts

Perfect for showing trends over time and comparing multiple metrics.

Best for: Time series data, performance trends, comparing metrics over time

Example query:

SELECT average(duration) AS 'Response Time'
FROM Transaction
WHERE appName = 'MyApp'
TIMESERIES 5 minutes
SINCE 6 hours ago

Area charts

Show volume and composition changes over time with filled areas under the line.

Best for: Cumulative data, showing total volume with breakdowns, resource usage over time

Example query:

SELECT count(*) FROM Transaction
WHERE appName = 'MyApp'
FACET host
TIMESERIES 10 minutes
SINCE 2 hours ago

Bar charts

Compare values across different categories or dimensions.

Best for: Comparing values across categories, top N lists, error breakdowns

Example query:

SELECT count(*) AS 'Request Count'
FROM Transaction
WHERE appName = 'MyApp'
FACET name
SINCE 1 hour ago
ORDER BY count(*) DESC
LIMIT 10

Pie charts

Display proportional data and percentage breakdowns.

Best for: Showing parts of a whole, percentage distributions, simple category breakdowns

Example query:

SELECT count(*) FROM Transaction
WHERE appName = 'MyApp'
FACET httpResponseCode
SINCE 1 hour ago

Tables

Present detailed data in rows and columns for precise values.

Best for: Detailed data, exact values, lists with multiple attributes, debugging

Example query:

SELECT timestamp, name, duration, httpResponseCode
FROM Transaction
WHERE appName = 'MyApp' AND duration > 5
SINCE 1 hour ago
ORDER BY duration DESC
LIMIT 20

Billboards

Highlight single important metrics prominently.

Best for: Key performance indicators, summary statistics, single important values

Example query:

SELECT average(duration) AS 'Avg Response Time (ms)'
FROM Transaction
WHERE appName = 'MyApp'
SINCE 1 hour ago

Customize your visualizations

Chart settings

Access chart customization options by clicking the Chart settings icon in your query block:

1. Colors: Choose custom colors for your data series
2. Axes: Customize axis labels, ranges, and formatting
3. Legend: Show/hide legend, adjust positioning
4. Thresholds: Add horizontal lines for targets or alerts
5. Units: Format numbers, percentages, time values

Color schemes

Choose colors that support your narrative:

• Default palette: Standard New Relic colors for consistency
• Custom colors: Match your organization's branding
• Accessible colors: High contrast for better readability
• Status colors: Green for healthy, red for errors, yellow for warnings

Formatting options

Format your data for clarity:

• Numbers: Add thousands separators, decimal places
• Percentages: Show as percentages rather than decimals
• Time values: Display in hours, minutes, or seconds
• Bytes: Show in KB, MB, GB as appropriate

Visualization best practices

Choose the right chart type

• Time series data: Use line or area charts
• Comparisons: Use bar charts
• Proportions: Use pie charts (but limit to 5-7 categories)
• Exact values: Use tables
• Key metrics: Use billboards

Design for clarity

Chart titles and labels

Always add descriptive titles and labels:

SELECT average(duration) AS 'Average Response Time (ms)',
       percentile(duration, 95) AS '95th Percentile (ms)'
FROM Transaction
WHERE appName = 'E-commerce API'
SINCE 24 hours ago
TIMESERIES 1 hour

Use consistent formatting

• Keep similar charts using the same time ranges
• Use consistent color schemes across related charts
• Apply the same formatting rules throughout your notebook

Highlight important information

• Use thresholds to show targets or SLA boundaries
• Choose colors that draw attention to problems (red for errors)
• Size billboards appropriately for their importance

Context and storytelling

Add explanatory text

Use Markdown blocks to provide context for your visualizations:

## Response Time Analysis

The chart below shows a significant spike in response times at 2:30 PM,
corresponding with the deployment of version 2.1.4. The 95th percentile
reached 2.8 seconds, well above our 500ms SLA target.

### What this means:
- 5% of users experienced unacceptable delays
- The issue was resolved by rolling back the deployment
- We need better performance testing before releases

Tell a story with multiple charts

Arrange your visualizations to build a narrative:

1. Overview chart: Start with high-level metrics
2. Drill-down charts: Show specific aspects or segments
3. Root cause charts: Display underlying causes
4. Resolution charts: Show improvement or fixes

Advanced visualization techniques

Using variables for dynamic charts

Create reusable visualizations with variables:

{{appName = "production-api"}}
{{timeRange = "6 hours ago"}}

SELECT count(*) AS 'Requests',
       average(duration) AS 'Avg Duration'
FROM Transaction
WHERE appName = '{{appName}}'
TIMESERIES 5 minutes
SINCE {{timeRange}}

Comparative analysis

Show before and after or period comparisons:

SELECT average(duration) AS 'Response Time'
FROM Transaction
WHERE appName = 'MyApp'
TIMESERIES 1 hour
SINCE 7 days ago
COMPARE WITH 1 week ago

Multi-faceted analysis

Break down metrics by multiple dimensions:

SELECT count(*) FROM Transaction
WHERE appName = 'MyApp'
FACET host, httpResponseCode
SINCE 2 hours ago

Troubleshooting visualizations

Common issues

Chart shows no data:

• Check your time range includes data
• Verify your WHERE clauses are correct
• Ensure you have permission to access the data

Chart is too cluttered:

• Use LIMIT to reduce the number of series
• Consider breaking into multiple charts
• Use aggregation to combine less important categories

Data looks wrong:

• Check for timezone issues in time series
• Verify your math in calculated fields
• Look for filtering that might exclude expected data

Performance optimization

• Use appropriate time ranges for your analysis
• Add specific WHERE clauses to limit data volume
• Use sampling for very large datasets
• Consider using approximation functions for better performance

What's next?

• Learn about sharing notebooks with your team
• Explore notebook examples for visualization inspiration
• Check out the chart types guide for detailed information about all available visualizations