Contour Map
Chart overview
Contour maps represent three-dimensional surfaces on a two-dimensional plane using lines that connect points of equal value (isolines).
Key points
- These visualizations are essential in physics and engineering for showing electromagnetic field distributions, heat flow patterns, and pressure gradients.
- In geosciences, they display terrain elevation and atmospheric data.
- Filled contour plots enhance readability by using color gradients between contour lines, making it easy to identify regions of high and low values.
Example Visualization
Create This Chart Now
Generate publication-ready contour maps with AI in seconds. No coding required β just describe your data and let AI do the work.
View example prompt
"Create a professional contour map showing the electromagnetic field distribution in a rectangular waveguide operating in TEββ mode (dominant mode). Generate a 2D grid representing the cross-section of a waveguide (10cm Γ 6cm). Calculate the electric field intensity pattern using the wave equation: E = sin(Οx/a) Γ exp(-0.3y/b) Γ cos(0.5x - 0.3y), where a=10 (width) and b=6 (height). Use 25 filled contour levels with the 'plasma' colormap for vibrant visualization. Overlay 12 white contour lines (linewidth 0.5, alpha 0.6) and label them with field intensity values. Add a colorbar labeled 'Electric Field Intensity (V/m)'. Include axis labels: 'Waveguide Length (cm)' and 'Waveguide Width (cm)'. Title: 'Electromagnetic Field Distribution in Rectangular Waveguide (TEββ Mode)'. Add a subtle grid for reference."
How to create this chart in 30 seconds
Upload Data
Drag & drop your Excel or CSV file. Plotivy securely processes it in your browser.
AI Generation
Our AI analyzes your data and generates the Contour Map code automatically.
Customize & Export
Tweak the design with natural language, then export as high-res PNG, SVG or PDF.
Python Code Example
Console Output
Maximum field intensity: 0.821 V/m Minimum field intensity: -0.819 V/m Mean field intensity: 0.001 V/m Field intensity range: 1.640 V/m
Common Use Cases
- 1Electromagnetic field analysis in waveguides and antennas
- 2Heat distribution and thermal analysis
- 3Terrain elevation and topographic mapping
- 4Pressure and velocity field visualization in fluid dynamics
- 5Geophysical data analysis (seismic, gravitational fields)
- 6Meteorological data (temperature, pressure systems)
Pro Tips
Use filled contours (contourf) for better visual clarity with color gradients
Label contour lines for precise value reading
Choose colormaps appropriate for your data (sequential for one direction, diverging for bidirectional)
Increase contour levels for smoother gradients (20-30 levels recommended)
Add grid lines to help readers locate specific regions
Scientific Chart Selection Cheat Sheet
Not sure whether to use a Violin Plot, Box Plot, or Ridge Plot? Download our single-page reference mapping the most-used scientific chart types, exactly when to use them, and the core Matplotlib/Seaborn functions.