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With the rapid development of data analysis and artificial intelligence, data visualization has become an increasingly important tool. Data visualization not only helps people understand data more intuitively, but also helps people better discover the information and patterns hidden in the data. The Go language is also a very good tool in this regard. As a high-performance programming language, Go language has many features. This article will introduce how to use Go language for data visualization.
Before introducing the use of Go language for data visualization, we need to first understand the characteristics of Go language. The following are the main features of Go language.
Go language is a programming language based on concurrent operations. It achieves high concurrency performance through mechanisms such as Goroutine, Channel and Mutex. This makes it easy to write efficient concurrent programs.
Go language provides a very rich standard library, covering network programming, I/O, file processing, etc. With the support of these standard libraries, we can easily develop programs.
Go language is a statically typed programming language. Static typing can check the type of code in advance and avoid some type errors.
Go language supports cross-compilation, which allows us to easily compile programs into executable files for different platforms. This allows development and deployment for different platforms.
In Go language, we can use third-party libraries and tools to quickly achieve data visualization. Here are the steps for data visualization using Go language.
Before we start, we need to install some necessary libraries and tools. The following are the libraries and tools that need to be installed:
You can use the following command to install these libraries and tools:
go get -u github.com/wcharczuk/go-chart go get -u github.com/gin-gonic/gin go get -u github.com/jinzhu/gorm
Before doing data visualization, we need to prepare the data first . Here is an example CSV file:
日期,收入,支出 2020-01-01,10000,8000 2020-01-02,12000,9000 2020-01-03,11000,10000 2020-01-04,13000,8000 2020-01-05,14000,12000
We can use Gorm to read this CSV file into a database. The following is an example code:
package main import ( "bufio" "encoding/csv" "io" "log" "os" "time" "github.com/jinzhu/gorm" _ "github.com/jinzhu/gorm/dialects/sqlite" ) type Record struct { gorm.Model Date time.Time `gorm:"not null"` Income int `gorm:"not null"` Expense int `gorm:"not null"` } func main() { db, err := gorm.Open("sqlite3", "test.db") if err != nil { log.Fatal(err) } defer db.Close() db.AutoMigrate(&Record{}) file, err := os.Open("data.csv") if err != nil { log.Fatal(err) } defer file.Close() reader := csv.NewReader(bufio.NewReader(file)) for { line, err := reader.Read() if err == io.EOF { break } else if err != nil { log.Fatal(err) } date, err := time.Parse("2006-01-02", line[0]) if err != nil { log.Fatal(err) } income, err := strconv.Atoi(line[1]) if err != nil { log.Fatal(err) } expense, err := strconv.Atoi(line[2]) if err != nil { log.Fatal(err) } record := Record{ Date: date, Income: income, Expense: expense, } db.Create(&record) } }
With the data, we can start generating charts. In Go language, we can use GoChart to generate charts. The following is a sample code to generate a line chart:
package main import ( "net/http" "strconv" "github.com/gin-gonic/gin" "github.com/wcharczuk/go-chart" "github.com/jinzhu/gorm" _ "github.com/jinzhu/gorm/dialects/sqlite" ) func main() { db, err := gorm.Open("sqlite3", "test.db") if err != nil { log.Fatal(err) } defer db.Close() r := gin.Default() r.GET("/", func(c *gin.Context) { var records []Record db.Find(&records) var xvalues []time.Time var yvalues1 []float64 var yvalues2 []float64 for _, record := range records { xvalues = append(xvalues, record.Date) yvalues1 = append(yvalues1, float64(record.Income)) yvalues2 = append(yvalues2, float64(record.Expense)) } graph := chart.Chart{ Title: "收入支出", XAxis: chart.XAxis{ Name: "日期", Ticks: []chart.Tick{ {Value: chart.TimeToFloat64(xvalues[0]), Label: xvalues[0].Format("2006-01-02")}, {Value: chart.TimeToFloat64(xvalues[len(xvalues)-1]), Label: xvalues[len(xvalues)-1].Format("2006-01-02")}, }, }, YAxis: chart.YAxis{ Name: "金额", }, Series: []chart.Series{ chart.TimeSeries{ Name: "收入", XValues: xvalues, YValues: yvalues1, }, chart.TimeSeries{ Name: "支出", XValues: xvalues, YValues: yvalues2, }, }, } buffer := bytes.NewBuffer([]byte{}) graph.Render(chart.PNG, buffer) c.Data(http.StatusOK, "image/png", buffer.Bytes()) }) r.Run(":8080") }
With the chart, we can start the Web server. In Go language, we can use Gin to start the web server. The following is a sample code:
func main() { db, err := gorm.Open("sqlite3", "test.db") if err != nil { log.Fatal(err) } defer db.Close() r := gin.Default() r.GET("/", func(c *gin.Context) { var records []Record db.Find(&records) // 生成图表的代码 // ... c.Data(http.StatusOK, "image/png", buffer.Bytes()) }) r.Run(":8080") }
Now, we can visit http://localhost:8080 in the browser to view the generated line chart.
Go language, as a high-performance programming language, can help us easily perform data visualization. In this article, we introduce how to use the Go language to quickly generate charts and use Gin to start a web server to display these charts. If you are interested in data visualization, using Go language for data visualization is a very good choice.
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