Create charts and data visualizations. Produces PNG or SVG images from data specs using matplotlib.
Creates data visualizations (bar, line, pie charts) from structured data using matplotlib.
The input is a JSON object:
{
"chart_type": "bar",
"title": "Chart Title",
"labels": ["Label 1", "Label 2", "Label 3"],
"datasets": [
{"label": "Series A", "data": [10, 20, 30]},
{"label": "Series B", "data": [15, 25, 35]}
],
"x_label": "X Axis Label (optional)",
"y_label": "Y Axis Label (optional)"
}
| Field | Type | Required | Description |
|---|---|---|---|
chart_type | string | yes | bar, line, or pie |
title | string | yes |
| Chart title |
labels | array[string] | yes | X-axis labels (or pie slice labels) |
datasets | array | yes | Data series array |
datasets[].label | string | no | Series name (shown in legend) |
datasets[].data | array[number] | yes | Numeric values (must match labels length) |
x_label | string | no | X-axis label |
y_label | string | no | Y-axis label |
bar — Grouped bar chart. Multiple datasets shown side-by-side. X-axis labels rotated 45° for readability.line — Line chart with markers. Each dataset is a separate line.pie — Pie chart. Uses first dataset only. Shows percentage labels.png — Raster image at 150 DPI. Best for embedding in presentations and emails.svg — Vector image. Best for web display and scaling.{
"type": "chart",
"input": {
"chart_type": "bar",
"title": "Quarterly Revenue",
"labels": ["Q1", "Q2", "Q3", "Q4"],
"datasets": [
{"label": "2025", "data": [1200, 1350, 1100, 1500]},
{"label": "2026", "data": [1380, 1600, null, null]}
],
"y_label": "Revenue ($K)"
},
"output_format": "png"
}
{
"type": "chart",
"input": {
"chart_type": "line",
"title": "Weekly Active Users",
"labels": ["W1", "W2", "W3", "W4", "W5"],
"datasets": [{"label": "Users", "data": [100, 120, 115, 140, 160]}],
"y_label": "Users"
},
"output_format": "svg"
}