Quick Start¶
Get up and running with Charted in 5 minutes.
Installation¶
pip install charted
Requirements: Python 3.10+
Your First Chart¶
Create a bar chart in 3 lines:
from charted import BarChart
chart = BarChart(
data=[120, 180, 210],
labels=["Q1", "Q2", "Q3"],
title="Sales by Quarter"
)
chart.save("sales.svg")
That’s it! You now have a sales.svg file ready to use in presentations, websites, or documentation.
Try Different Chart Types¶
Charted supports 14 chart types with a consistent API:
from charted import BarChart, ColumnChart, LineChart, PieChart, RadarChart
# Bar chart (horizontal bars)
BarChart(data=[120, 180, 210], labels=["A", "B", "C"]).save("bar.svg")
# Column chart (vertical bars)
ColumnChart(data=[120, 180, 210], labels=["A", "B", "C"]).save("column.svg")
# Line chart
LineChart(data=[120, 180, 210], labels=["A", "B", "C"]).save("line.svg")
# Pie chart
PieChart(data=[120, 180, 210], labels=["A", "B", "C"]).save("pie.svg")
# Radar chart
RadarChart(data=[120, 180, 210], labels=["A", "B", "C"]).save("radar.svg")
Multi-Series Charts¶
Compare multiple data series:
from charted import ColumnChart
data = [
[120, 180, 210, 150], # 2023
[130, 190, 220, 160], # 2024
]
chart = ColumnChart(
data=data,
labels=["Q1", "Q2", "Q3", "Q4"],
series_names=["2023", "2024"],
title="Sales Comparison"
)
chart.save("multi.svg")
Load Data from CSV¶
No pandas needed:
from charted import load_csv, BarChart
x, y, labels = load_csv("sales.csv", x_col="Quarter", y_col="Revenue")
chart = BarChart(data=y, labels=x, title=labels[0])
chart.save("sales.svg")
CSV Format:
Quarter,Revenue
Q1,120
Q2,180
Q3,210
Q4,150
Jupyter Integration¶
Charts render inline automatically:
from charted import BarChart
# Just create a chart, it displays inline
BarChart(
data=[120, 180, 210, 150],
labels=["Q1", "Q2", "Q3", "Q4"],
title="Sales by Quarter"
)
Apply a Theme¶
from charted import BarChart
# Built-in themes
chart = BarChart(
data=[120, 180, 210],
labels=["Q1", "Q2", "Q3"],
theme="dark" # or "light", "high-contrast"
)
# Or custom theme
chart = BarChart(
data=[120, 180, 210],
labels=["Q1", "Q2", "Q3"],
theme={
"colors": ["#FF6B6B", "#4ECDC4", "#45B7D1"],
}
)
Use the CLI¶
Create charts without writing Python:
# From CSV
python -m charted create bar sales.svg --data sales.csv
# Batch process
python -m charted batch ./data ./output
# See options
python -m charted --help
Next Steps¶
Explore Chart Types: See all 14 chart types
Theming Guide: Customize colors and styles
Configuration: Global settings and defaults
Need help? Check the full documentation or report an issue.