Canvas tutorial - Turn SVG scatterplot into Canvas - Normal level

This scatterplot is made with d3.js and SVG - For the canvas tutorial it is now your job to turn this scatterplot into one uses canvas for the visual part (the drawing of the circles). You can still use d3's helper functions for things such as scales, d3.select, etc.

See the other two levels here: Medium level and Extreme level

If you're completely stuck (and please, for your own benefit, only then) you can look at the solution here

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forked from nbremer's block: Canvas tutorial - Turn SVG scatterplot into Canvas - Normal level

<!DOCTYPE html>

<body>
    <script>
        ////////////// Create the SVG //////////////

//****** Delete the SVG and create a canvas instead ******// 
      
        let width = 1000,
            height = 800

//Create the SVG container
        let svg = d3.select("body")
            .append("svg")
            .attr("width", width)
            .attr("height", height)

////////////// Create scales //////////////

//****** Keep all of these scales as-is ******//

const x_scale = d3.scaleLinear() //rating
            .range([0, width])

const y_scale = d3.scaleLog() //budget
            .domain([500, 500e6]) //in dollars
            .range([height, 0])

const r_scale = d3.scaleSqrt() //profit ratio = revenue / budget
            .domain([0, 6])
            .range([0, 10])

//Make the movies that have the highest profit ratio less visible
        //to balance their increased size
        const opacity_scale = d3.scaleLinear() //profit ratio = revenue / budget
            .domain([0, 100])
            .range([0.2, 0.01])
            .clamp(true)

//A linear color scale to give an idea about when a movie was made
        const color_scale = d3.scaleSequential(d3.interpolateViridis) //release year

////////////// Read in the data //////////////

//Data based on dataset from 
        //https://data.world/popculture/imdb-5000-movie-dataset
        d3.csv("imdb-movies.csv", function (error, data) {
            if (error) throw error

////////////// Final data prep //////////////

//****** Keep as-is ******//

//Make the number columns actually numeric
            data.forEach(d => {
                d.release_year = +d.release_year
                d.budget = +d.budget
                d.revenue = +d.revenue
                d.rating = +d.rating
                d.num_voted_users = +d.num_voted_users
                d.profit_ratio = +d.profit_ratio
            })

////////////// Adjust scales //////////////

//****** Keep as-is ******//

//Set the range for the scales now that the data is read in
            x_scale.domain(d3.extent(data, d => d.rating)).nice()
            color_scale.domain(d3.extent(data, d => d.release_year))

////////////// Create circles //////////////

//*** Replace this section with a loop that goes over all ***// 
            //*** the data and creates a canvas circle for each movie ***//
            //*** using the correct x, y, radius, color and opacity for each ***//

let circle_group = svg.append("g").attr("class", "circle-group")

let circles = circle_group.selectAll(".movie")
                .data(data)
                .enter().append("circle")
                .attr("class", "movie")
                .attr("cx", d => x_scale(d.rating))
                .attr("cy", d => y_scale(d.budget))
                .attr("r", d => r_scale(d.profit_ratio))
                .style("fill", d => color_scale(d.release_year))
                .style("opacity", d => opacity_scale(d.profit_ratio))

})//d3.csv

</script>
</body>

https://d3js.org/d3.v4.min.js