Quick Start: Use Go language functions to implement simple data visualization scatter plot display

Quick Start: Use Go language functions to implement simple data visualization scatter plot display

Introduction:
Data visualization is an indispensable part of modern data analysis. It can help us understand the distribution, patterns and relationships of data more clearly. In this article, we will introduce how to use the Go language to write a simple function to achieve a visual scatter plot display of data. Through this example, readers will learn how to use Go language libraries for data processing and graphics drawing.

1. Data preparation:
First, we need to prepare some data for visual display. We chose a simple two-dimensional scatter plot as an example. The data set is as follows:

X values: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
Y value: [5, 10, 15, 7, 8, 13, 6, 9, 11, 14]

This set of data represents the position of ten points on the two-dimensional coordinate system.

2. Import the necessary libraries:
Before we start writing code, we need to import some necessary libraries. Here we will use the go-chart library for chart drawing. Install the library through the following command:

go get -u github.com/wcharczuk/go-chart

Import the required library:

package main

import (
    "fmt"
    "github.com/wcharczuk/go-chart"
    "os"
)

3. Code implementation :
First, we write a function to realize the drawing of data visualization scatter plot. The input parameters of this function are X values ​​and Y values, and the output is the completed scatter plot. The code is as follows:

func drawScatterChart(xValues []float64, yValues []float64) {
    points := []chart.Point{}

    for i := 0; i < len(xValues); i++ {
        points = append(points, chart.Point{
            X: xValues[i],
            Y: yValues[i],
        })
    }

    graph := chart.Chart{
        XAxis: chart.XAxis{
            Name: "X",
        },
        YAxis: chart.YAxis{
            Name: "Y",
        },
        Series: []chart.Series{
            chart.ContinuousSeries{
                Style: chart.Style{
                    Show:        true,
                    StrokeColor: chart.ColorBlue,
                },
                XValues: xValues,
                YValues: yValues,
            },
        },
    }

    f, _ := os.Create("scatter_chart.png")
    defer f.Close()
    graph.Render(chart.PNG, f)
    fmt.Println("Scatter chart generated successfully!")
}

In the above code, we first use a loop to assemble the X value and Y value into the chart.Point type and add it to the points slice. Then, we create a Chart type variable graph, and set the names of the X-axis and Y-axis, the data series to be drawn, and the drawing style. Finally, we call the Render method of the chart to save the result as a PNG format image file, and print out a success message.

4. Call the function:
Now, we can write a main function to call the function we just wrote to draw the scatter plot. The code is as follows:

func main() {
    xValues := []float64{1, 2, 3, 4, 5, 6, 7, 8, 9, 10}
    yValues := []float64{5, 10, 15, 7, 8, 13, 6, 9, 11, 14}
    drawScatterChart(xValues, yValues)
}

In the main function, we create two slice variables xValues ​​and yValues ​​and assign the previously prepared sample data to them. Then, we call the drawScatterChart function to draw the scatter plot.

5. Running code:
After completing the writing of the above code, we can use the following command to run the program:

go run main.go

The program is completed After that, a scatter chart file named scatter_chart.png will be generated.

6. Summary:
Through this simple example, we learned how to use the Go language to write functions to achieve a visual scatter chart display of data. In practical applications, we can change the data set and drawing style as needed to achieve more complex data visualization requirements. The Go language provides a wealth of libraries and functions to help us process data and draw graphics more easily. I hope that readers can have a preliminary understanding of data visualization in Go language through this article, and can further explore more functions and applications.

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