| # Creating Plots | |
| Gradio is a great way to create extremely customizable dashboards. Gradio comes with three native Plot components: `gr.LinePlot`, `gr.ScatterPlot` and `gr.BarPlot`. All these plots have the same API. Let's take a look how to set them up. | |
| ## Creating a Plot with a pd.Dataframe | |
| Plots accept a pandas Dataframe as their value. The plot also takes `x` and `y` which represent the names of the columns that represent the x and y axes respectively. Here's a simple example: | |
| $code_plot_guide_line | |
| $demo_plot_guide_line | |
| All plots have the same API, so you could swap this out with a `gr.ScatterPlot`: | |
| $code_plot_guide_scatter | |
| $demo_plot_guide_scatter | |
| The y axis column in the dataframe should have a numeric type, but the x axis column can be anything from strings, numbers, categories, or datetimes. | |
| $code_plot_guide_scatter_nominal | |
| $demo_plot_guide_scatter_nominal | |
| ## Breaking out Series by Color | |
| You can break out your plot into series using the `color` argument. | |
| $code_plot_guide_series_nominal | |
| $demo_plot_guide_series_nominal | |
| If you wish to assign series specific colors, use the `color_map` arg, e.g. `gr.ScatterPlot(..., color_map={'white': '#FF9988', 'asian': '#88EEAA', 'black': '#333388'})` | |
| The color column can be numeric type as well. | |
| $code_plot_guide_series_quantitative | |
| $demo_plot_guide_series_quantitative | |
| ## Aggregating Values | |
| You can aggregate values into groups using the `x_bin` and `y_aggregate` arguments. If your x-axis is numeric, providing an `x_bin` will create a histogram-style binning: | |
| $code_plot_guide_aggregate_quantitative | |
| $demo_plot_guide_aggregate_quantitative | |
| If your x-axis is a string type instead, they will act as the category bins automatically: | |
| $code_plot_guide_aggregate_nominal | |
| $demo_plot_guide_aggregate_nominal | |
| ## Selecting Regions | |
| You can use the `.select` listener to select regions of a plot. Click and drag on the plot below to select part of the plot. | |
| $code_plot_guide_selection | |
| $demo_plot_guide_selection | |
| You can combine this and the `.double_click` listener to create some zoom in/out effects by changing `x_lim` which sets the bounds of the x-axis: | |
| $code_plot_guide_zoom | |
| $demo_plot_guide_zoom | |
| If you had multiple plots with the same x column, your event listeners could target the x limits of all other plots so that the x-axes stay in sync. | |
| $code_plot_guide_zoom_sync | |
| $demo_plot_guide_zoom_sync | |
| ## Making an Interactive Dashboard | |
| Take a look how you can have an interactive dashboard where the plots are functions of other Components. | |
| $code_plot_guide_interactive | |
| $demo_plot_guide_interactive | |
| It's that simple to filter and control the data presented in your visualization! |