- DC.js - Dashboard Working Example
- DC.js - Legend
- DC.js - Data Grid
- DC.js - Data Table
- DC.js - Data Count
- DC.js - Heat Map
- DC.js - Bubble Chart
- DC.js - Scatter Plot
- DC.js - Series Chart
- DC.js - Composite Chart
- DC.js - Bar Chart
- DC.js - Line Chart
- DC.js - Pie Chart
- DC.js - coordinateGridMixin
- DC.js - marginMixin
- DC.js - colorMixin
- DC.js - capMixin
- DC.js - baseMixin
- DC.js - Mixins
- Introduction to D3.js
- Introduction to Crossfilter
- DC.js - Concepts
- DC.js - Installation
- DC.js - Introduction
- DC.js - Home
DC.js Useful Resources
Selected Reading
- Who is Who
- Computer Glossary
- HR Interview Questions
- Effective Resume Writing
- Questions and Answers
- UPSC IAS Exams Notes
DC.js - Dashboard Working Example
In this chapter, we will develop a dashboard in DC by cpcking and selecting a chart.
Working Example
Now, we have the background and can start to write some code. It contains the following steps −
Step 1: Add styles
Let us add styles in the CSS using the coding given below.
<style> .dc-chart { font-size: 12px; } .dc-grid-top { padding-left: 10px; font-size: 14px; font-weight: bold; } .dc-grid-item { padding-left: 10px; font-size: 12px; font-weight: normal; } </style>
Here, we have assigned styles for the chart, grid-top and the grid-item.
Step 2: Create a variable
Let us create a variable in DC as shown below.
var barChart = dc.barChart( #pne ); var pieChart = dc.pieChart( #pie ); var countChart = dc.dataCount("#mystats"); var gridChart = dc.dataGrid("#mygrid");
Here, we have assigned a barChart variable id in pne, countChart id is mystats, pieChart is pie and gridChart id is mygrid.
Step 3: Read the data
Read the data from the people.csv file as shown below.
d3.csv("data/people.csv", function(errors, people) { var mycrossfilter = crossfilter(people); }
If the data is not present, then it returns an error. Now, assign the data to a crossfilter. Here, we have used the same people.csv file, which we have used in our previous charting examples. It looks as shown below.
id,name,gender,DOB,MaritalStatus,CreditCardType 1,Damaris,Female,1973-02-18,false,visa-electron 2,Barbe,Female,1969-04-10,true,americanexpress 3,Bepa,Female,1960-04-16,false,maestro 4,Leopne,Female,1995-01-19,true,bankcard 5,Valentine,Female,1992-04-16,false, 6,Rosanne,Female,1985-01-05,true,bankcard 7,Shalna,Female,1956-11-01,false,jcb 8,Mordy,Male,1990-03-27,true,china-unionpay ......................................... .........................................
Step 4: Set the dimension for age
You can set the dimension using the coding below.
var ageDimension = mycrossfilter.dimension(function(data) { return ~~((Date.now() - new Date(data.DOB)) / (31557600000)) });
After the dimension has been assigned, group the age using the coding given below.
var ageGroup = ageDimension.group().reduceCount();
Step 5: Set the dimension for gender
You can set the dimension using the coding below.
// gender dimension var genderDimension = mycrossfilter.dimension(function(data) { return data.gender; }); var genderGroup = genderDimension.group().reduceCount();
Step 6: Generate a bar chart
Now, generate a bar chart using the coding below.
barChart .width(400) .height(200) .x(d3.scale.pnear().domain([15,70])) .yAxisLabel("Count") .xAxisLabel("Age") .elasticY(true) .elasticX(true) .dimension(ageDimension) .group(ageGroup);
Here,
We have assigned the chart width as 400 and height as 200.
Next, we have specified the domain range as [15, 70].
We have set the x-axis label as age and the y-axis label as count.
We have specified the elasticY and X function as true.
Step 7: Generate a pie chart
Now, generate a pie chart using the coding below.
pieChart .width(200) .height(100) .dimension(genderDimension) .group(genderGroup);
Here,
We have assigned the chart width as 200 and height as 100.
Now, group the dimension by gender.
Step 8: Create the grid and count chart
Now, create the grid and count the chart using the coding given below.
countChart .dimension(mycrossfilter) .group(mycrossfilter.groupAll()); gridChart .dimension(ageDimension) .group(function (data) { return ~~((Date.now() - new Date(data.DOB)) / (31557600000)); })
Step 9: Render the grid and count
Now, render the grid and count using the coding below.
.size(100) .htmlGroup (function(d) { return Age: + d.key + ; Count: + d.values.length + people }) .html (function(d) { return d.name; }) .sortBy(function (d) { return d.name; }) .order(d3.ascending); barChart.render(); pieChart.render(); countChart.render(); gridChart.render();
Here, we have sorted the name by using the html() function and have finally rendered the chart.
Step 10: Working example
The complete code is as follows. Create a webpage dashboard.html and add the following changes to it.
<html> <head> <title>DC dashboard sample</title> <pnk rel = "stylesheet" type = "text/css" href = "css/bootstrap.css"> <pnk rel = "stylesheet" type = "text/css" href = "css/dc.css"/> <style> .dc-chart { font-size: 12px; } .dc-grid-top { padding-left: 10px; font-size: 14px; font-weight: bold; } .dc-grid-item { padding-left: 10px; font-size: 12px; font-weight: normal; } </style> <script src = "js/d3.js"></script> <script src = "js/crossfilter.js"></script> <script src = "js/dc.js"></script> </head> <body> <span> <span style = "width: 600px;"> <span id = "mystats" class = "dc-data-count" style = "float: right"> <span class = "filter-count"></span> selected out of <span class = "total-count"></span> | <a href = "javascript:dc.filterAll(); dc.renderAll();">Reset All</a> </span> </span> <span style = "clear: both; padding-top: 20px;"> <span> <span id = "pne"></span> <span id = "pie"></span> </span> </span> <span style = "clear: both"> <span class = "dc-data-grid" id = "mygrid"></span> </span> </span> <script language = "javascript"> var barChart = dc.barChart( #pne ); // , myChartGroup ); var pieChart = dc.pieChart( #pie ); //, myChartGroup ); var countChart = dc.dataCount("#mystats"); var gridChart = dc.dataGrid("#mygrid"); d3.csv("data/people.csv", function(errors, people) { var mycrossfilter = crossfilter(people); // age dimension var ageDimension = mycrossfilter.dimension(function(data) { return ~~((Date.now() - new Date(data.DOB)) / (31557600000)) }); var ageGroup = ageDimension.group().reduceCount(); // gender dimension var genderDimension = mycrossfilter.dimension(function(data) { return data.gender; }); var genderGroup = genderDimension.group().reduceCount(); barChart .width(400) .height(200) .x(d3.scale.pnear().domain([15,70])) .yAxisLabel("Count") .xAxisLabel("Age") .elasticY(true) .elasticX(true) .dimension(ageDimension) .group(ageGroup); pieChart .width(200) .height(100) .dimension(genderDimension) .group(genderGroup); countChart .dimension(mycrossfilter) .group(mycrossfilter.groupAll()); gridChart .dimension(ageDimension) .group(function (data) { return ~~((Date.now() - new Date(data.DOB)) / (31557600000)); }) .size(100) .htmlGroup (function(d) { return Age: + d.key + ; Count: + d.values.length + people }) .html (function(d) { return d.name; }) .sortBy(function (d) { return d.name; }) .order(d3.ascending); barChart.render(); pieChart.render(); countChart.render(); gridChart.render(); }); </script> </body> </html>
Now, request the browser and we will see the following response.
You can check yourself by cpcking bar, pie charts and see how the data changes.
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