Plotly
- Create interactive visualizations (e.g., scatter plots, bar charts, line plots, box plots, heat maps) with hover interactions and toggles.
- Customize visual appearance (colors, sizes, axis labels, titles, annotations, shapes, text) and add elements like trendlines or legends.
- Integrates with programming languages such as Python, R, and JavaScript to generate and share plots directly from code.
Definition
Section titled “Definition”Plotly is a data visualization and analytics platform that enables users to create interactive charts, graphs, and maps.
Explanation
Section titled “Explanation”Users input their data into Plotly, select a chart type, and the platform generates the plot, which can then be customized. Customization options include changing colors, sizes, axis labels, titles, and adding annotations, shapes, and text. Interactivity features allow hovering over data points or bars to reveal values, toggling between data sets, and adding elements such as trendlines or legends. Plotly also integrates with programming languages (Python, R, JavaScript), enabling plots to be created from code and shared or embedded for presentations and reports.
Examples
Section titled “Examples”Scatter plot
Section titled “Scatter plot”A scatter plot uses dots to represent data points and shows the relationship between two variables. In Plotly, users input their data, select the scatter plot type, and the platform generates the plot. The plot can be customized (dot color and size, axis labels, title) and made interactive so users can hover over dots to see data values or add a trendline to show an overall pattern.
Bar chart
Section titled “Bar chart”A bar chart uses horizontal or vertical bars to represent data and compares values across categories. In Plotly, users input their data, select the bar chart type, and the platform generates the chart. The chart can be customized (bar color, axis labels, title) and made interactive so users can hover over bars to see values or add a legend to indicate what each bar represents.
Use cases
Section titled “Use cases”- Interactive visualizations for presentations or reports to help audiences explore and understand data.
- Creating and sharing plots directly from code via integrations with Python, R, and JavaScript, including embedding plots into websites or exporting standalone files.
Related terms
Section titled “Related terms”- Scatter plot
- Bar chart
- Line plot
- Box plot
- Heat map
- Trendline
- Legend
- Annotations
- Shapes
- Text
- Interactive plots