Big walls, cities, computing, and design.
Published
Edited
Apr 28, 2019
5 forks
12 stars
height = 500
// height = 20
{
let firstNumber = 55
return firstNumber + 10
}
function addingNumbers(number3, number4){
let number5 = number3 + number4
return number5
}
bosData = d3.csv("https://gist.githubusercontent.com/jdev42092/46071bf3284265c37ea07d6328ef7a3a/raw/cc7bfc53f3853437749906ccf7d2cac49c43c9a2/neigh_311.csv", ({neighborhood, num_311}) => ({neighborhood: neighborhood, calls: +num_311}))
{
var margin = ({top: 15, right: 10, bottom: 25, left: 30})
// Initialize SVG object (using our pre-defined width and height)
const svg = d3.select(DOM.svg(width, height));
// Get length of dataset
let arrayLength = bosData.length; // length of dataset
let maxValue = d3.max(bosData, d=> d.calls); // get max value of our dataset
let x_axisLength = (width - margin.right - margin.left); // length of x-axis in our layout
let y_axisLength = (height - margin.top - margin.bottom); // length of y-axis in our layout
// Use a scale for the height of the visualization
const yScale = d3.scaleLinear()
.domain([0, d3.max(bosData, d=> d.calls)])
.range([margin.bottom, height - margin.top])
// Select and generate rectangle elements
svg.selectAll( "rect" )
.data( bosData )
.enter()
.append("rect")
.attr( "x", (d,i) => (i*(x_axisLength/arrayLength) + margin.left))
// Set x coordinate of each bar to index of data value (i) times dynamically calculated bar width.
// Add left margin to account for our left margin.
.attr( "y", d => (height - yScale(d.calls)) )
// Set y coordinate using yScale.
.attr( "width", (x_axisLength/arrayLength) - 1 )
// Set bar width using length of array, with 1px gap between each bar.
.attr( "height", d => yScale(d.calls) - yScale(0))
// Set height of rectangle to data value, accounting for bottom margin.
.attr( "fill", "steelblue");
// Create y-axis, beginning at the top margin and ending at the bottom margin
svg.append("line")
.attr("x1", margin.left)
.attr("y1", margin.top)
.attr("x2", margin.left)
.attr("y2", height - margin.bottom)
.attr("stroke-width", 2)
.attr("stroke", "black");
// Create x-axis beginning at the left margin, and ending at the right margin
svg.append("line")
.attr("x1", margin.left)
.attr("y1", height - margin.bottom)
.attr("x2", width - margin.right)
.attr("y2", height - margin.bottom)
.attr("stroke-width", 2)
.attr("stroke", "black");
// Add a Label
// y-axis label
svg.append("text")
.attr("class", "y label")
.attr("text-anchor", "end")
.text("No. of 311 Calls")
.attr("transform", "translate(20, 20) rotate(-90)");
return svg.node();
}
margin = ({top: 15, right: 10, bottom: 25, left: 30})
// Initialize SVG object (using our pre-defined width and height)
svg = d3.select(DOM.svg(width, height));
// Get length of dataset
arrayLength = bosData.length; // length of dataset
maxValue = d3.max(bosData, d=> d.calls); // get max value of our dataset
x_axisLength = (width - margin.right - margin.left); // length of x-axis in our layout
y_axisLength = (height - margin.top - margin.bottom); // length of y-axis in our layout
// Use a scale for the height of the visualization
yScale = d3.scaleLinear()
.domain([0, d3.max(bosData, d=> d.calls)])
.range([margin.bottom, height - margin.top])
// Select and generate rectangle elements
svg.selectAll( "rect" )
.data( bosData )
.enter()
.append("rect")
.attr( "x", (d,i) => (i*(x_axisLength/arrayLength) + margin.left))
// Set x coordinate of each bar to index of data value (i) times dynamically calculated bar width.
// Add left margin to account for our left margin.
.attr( "y", d => (height - yScale(d.calls)) )
// Set y coordinate using yScale.
.attr( "width", (x_axisLength/arrayLength) - 1 )
// Set bar width using length of array, with 1px gap between each bar.
.attr( "height", d => yScale(d.calls) - yScale(0))
// Set height of rectangle to data value, accounting for bottom margin.
.attr( "fill", "steelblue");
// Create y-axis, beginning at the top margin and ending at the bottom margin
svg.append("line")
.attr("x1", margin.left)
.attr("y1", margin.top)
.attr("x2", margin.left)
.attr("y2", height - margin.bottom)
.attr("stroke-width", 2)
.attr("stroke", "black");
// Create x-axis beginning at the left margin, and ending at the right margin
svg.append("line")
.attr("x1", margin.left)
.attr("y1", height - margin.bottom)
.attr("x2", width - margin.right)
.attr("y2", height - margin.bottom)
.attr("stroke-width", 2)
.attr("stroke", "black");
// Add a Label
// y-axis label
svg.append("text")
.attr("class", "y label")
.attr("text-anchor", "end")
.text("No. of 311 Calls")
.attr("transform", "translate(20, 20) rotate(-90)");
svg.node();
One platform to build and deploy the best data apps
Experiment and prototype by building visualizations in live JavaScript notebooks. Collaborate with your team and decide which concepts to build out.
Use Observable Framework to build data apps locally. Use data loaders to build in any language or library, including Python, SQL, and R.
Seamlessly deploy to Observable. Test before you ship, use automatic deploy-on-commit, and ensure your projects are always up-to-date.