A plotting toolkit for Go · v0.1

From a slice of data
to a clearer picture.

Build charts for exploratory analysis, reports, and web pages with a small Go API. Render crisp vectors, portable images, and self-contained HTML.

Explore the gallery ↓Start with Go ↗

$ go get github.com/Alifarid0011/chartframe

Six ways to explore your data

Rendered by this Go package · synthetic, reproducible examples

Line · Scatter · Linear fit

Find the signal

Monthly observations, their connected path, and an ordinary least-squares fit. Synthetic values show a gradual upward trend.

Open or download

SVG PNG HTML

View runnable Go example

package main

import (
	cf "github.com/Alifarid0011/chartframe"
	"log"
)

func main() {
	x := []float64{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}
	y := []float64{12, 16, 15, 22, 24, 23, 30, 32, 31, 38, 40, 43}
	c := cf.New("Monthly observations").
		Line("observed", x, y).
		Scatter("samples", x, y).
		LinearFit("least-squares", x, y).
		Labels("Month", "Response")
	if err := c.Save("trend.svg"); err != nil {
		log.Fatal(err)
	}
}

Grouped bar

Compare the groups

Two measurement periods across four regions. Matching category labels keep the series aligned; the vertical axis includes zero.

Open or download

SVG PNG HTML

View runnable Go example

package main

import (
	cf "github.com/Alifarid0011/chartframe"
	"log"
)

func main() {
	labels := []string{"North", "South", "East", "West"}
	c := cf.New("Regional comparison").
		Bar("baseline", labels, []float64{42, 35, 48, 38}).
		Bar("current", labels, []float64{54, 44, 57, 51}).
		Labels("Region", "Units")
	if err := c.Save("categories.svg"); err != nil {
		log.Fatal(err)
	}
}

Histogram

See the distribution

Thirty-six synthetic measurements in eight equal-width bins. Every sample is counted, including observations on the final edge.

Open or download

SVG PNG HTML

View runnable Go example

package main

import (
	cf "github.com/Alifarid0011/chartframe"
	"log"
)

func main() {
	values := []float64{18, 22, 25, 26, 27, 28, 29, 30, 30, 31, 32, 33, 34, 34, 35, 36, 36, 37, 38, 38, 39, 40, 40, 41, 42, 42, 43, 44, 45, 46, 47, 48, 49, 50, 52, 56}
	c := cf.New("Measurement distribution").
		Histogram("samples", values, 8).
		Labels("Measurement", "Count")
	if err := c.Save("distribution.svg"); err != nil {
		log.Fatal(err)
	}
}

Box plot

Put spread in context

Three small cohorts compared by median, quartiles, and spread. Quartiles use sorted linear interpolation (R type 7).

Open or download

SVG PNG HTML

View runnable Go example

package main

import (
	cf "github.com/Alifarid0011/chartframe"
	"log"
)

func main() {
	c := cf.New("Cohort spread").
		Box("A", []float64{20, 22, 23, 24, 24, 25, 26, 27, 29, 32}).
		Box("B", []float64{24, 25, 27, 28, 29, 30, 31, 33, 35, 39}).
		Box("C", []float64{19, 21, 22, 23, 24, 25, 26, 28, 31, 36}).
		Labels("Cohort", "Measurement")
	if err := c.Save("summary.svg"); err != nil {
		log.Fatal(err)
	}
}

Heatmap

Spot the pattern

A labeled weekday-by-time matrix. Color encodes relative activity; the color legend gives the numerical range.

Open or download

SVG PNG HTML

View runnable Go example

package main

import (
	cf "github.com/Alifarid0011/chartframe"
	"log"
)

func main() {
	days := []string{"Mon", "Tue", "Wed", "Thu", "Fri"}
	times := []string{"09:00", "12:00", "15:00", "18:00"}
	values := [][]float64{[]float64{12, 18, 15, 22, 19}, []float64{32, 41, 35, 44, 38}, []float64{24, 30, 28, 36, 32}, []float64{16, 22, 18, 25, 21}}
	c := cf.New("Activity by weekday and time").
		Heatmap("Activity", days, times, values).
		Labels("Weekday", "Time")
	if err := c.Save("matrix.svg"); err != nil {
		log.Fatal(err)
	}
}

Empirical CDF

Read the whole sample

The same measurements as a cumulative step curve. Read the fraction of observations at or below a chosen measurement.

$The same measurements as a cumulative step curve. Read the fraction of observations at or below a chosen measurement.$

Open or download

SVG PNG HTML

View runnable Go example

package main

import (
	cf "github.com/Alifarid0011/chartframe"
	"log"
)

func main() {
	values := []float64{18, 22, 25, 26, 27, 28, 29, 30, 30, 31, 32, 33, 34, 34, 35, 36, 36, 37, 38, 38, 39, 40, 40, 41, 42, 42, 43, 44, 45, 46, 47, 48, 49, 50, 52, 56}
	c := cf.New("Cumulative measurements").
		ECDF("samples", values).
		Labels("Measurement", "Cumulative fraction")
	if err := c.Save("cumulative.svg"); err != nil {
		log.Fatal(err)
	}
}

One figure, six views

Take the notebook with you.

Compose the same charts with cf.Grid and export a complete research sheet. The HTML includes local viewport pan, zoom, reset, and SVG download.

SVG sheet PDF report Open HTML ↗

Go in, charts out.

Line, scatter, categorical bar, histogram, box plot, heatmap, and ECDF. Add labels, compare series, or compose a dashboard.

Small analysis helpers.

Fit a least-squares line, describe a sample with interpolated quartiles, or create validated histogram bins. Read CSV columns without silently dropping missing values.

Built on Gonum Plot.

Gonum Plot provides the rendering and typography. Chartframe adds validated builders, statistics, export, and dashboard composition.