Lifestyle Data Visualization With D3 And Angularjs Pdf


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Create Dynamic Visualizations with AngularJS chapter, we'll go over what D3 is and what makes it such a powerful tool for data visualization. Learn how to create dynamic and interactive data visualizations with D3 and AngularJS. Build dynamic and interactive visualizations from real-world data with D3 on AngularJS In Detail Using, the powerful JavaScript toolkit for creating.

Data Visualization With D3 And Angularjs Pdf

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where he developed data dashboards using for visualizing social Did you know that Packt offers eBook versions of every book published, with PDF and . Build dynamic and interactive visualizations from real-world data with D3 on AngularJS. Build dynamic and interactive visualizations from real-world data with D3 on PDF下载地址( MB) We'll reach top-notch reusability and testability by combining D3 graphics with our favorite web application framework, AngularJS.

Last updated on D3 is a powerful library for creating data visualizations for the web. With it, you can create compelling visual presentations of your data while writing relatively little code. In combination with AngularJS, the two can be used to create highly sophiticated, dynamic and interactive data visualizations. An emphasis is placed on screenshots and live code examples linked to from within the text. But don't just take our word for it. Have a look at some of the examples the authors have created utilizing the combination of D3 and AngularJS.

Array helpers 82 Other non-linear scales D3 includes other scales than simply linear mappings. For instance, we can create a logarithmic scale using the d3. We can create a new power scale by using the d3. The logarithmic scale is useful for translating data that increases exponentially. The power scale, like the logarithmic scale is useful for translating data that increases exponentially.

These two scales output format are slightly different in their computation of the output range. All of these scales work very similar to each other, with slight differences. One easy way we can simply convey this type of data is by using Axes in our visualizations.

D3 provides fantastic helper functions that help us construct the necessary annotations that combine to form an axis, such as tick marks, labels and reference lines.

As long as we properly create our scale and use it to build our axis, D3 can take care of constructing the building function. Creating an axis To create an axis, we can use the d3. This is because the position of the circles depends on the data being a flat array of integers, as well as our call to d3. In our case, this is the second element of our array.

D3 offers a variety of different formatters we can use to pass into tick- Format for our axis. Our formatter, d3. Lets update our scale to instead start at the first data point instead of zero. That change is as simple as changing our scales domain from [0, d3. These techniques lay the foundation for things like live updating, real-time data visualizations. Transitions At the heart of almost all animated data visualizations built with D3 our transitions.

Transitions make it effortless for us to apply a smooth, animated, transition over a collection of selected elements. We took a circle and animated with the addition of only a single line of code! We can adjust how long a transition takes by using the. Working from the above example, we can adjust the animation to take 4 seconds ms , instead of ms, by using transition.

Easing lets us fiddle with how the transition should accelerate. This would be a "linear" easing type. If, instead, we drop a hammer, it will accelerate down, going faster and faster. This would be an "exp" easing type. By default, D3 uses "cubic-in-out" which is how most physical objects move in the real world. They first speed up, then, when they approach their target, they slow down, like a car speeding up after a stop sign and then slowing down as it approaches a red light at an intersection.

This is the same transition illustrated in the above example. By default, all easing types are in so just cubic is the same as cubic-in and we can fiddle with the easing type by appending either -out or -in-out.

Events Events allow our visualizations to be interactive. Using them, we specify what should happen when a user performs an action, like clicking, or moving the mouse, or pressing the keyboard. HTML on its own has a variety of different interactive events we can opt to be notified of using callbacks. D3 simply makes it easier to set them up using selections instead of having to deal with individual DOM elements directly.

We can do all this just using the on selection method, passing it the name of the event we want to listen for and a callback function which should be called when that event occurs. Different event listeners are being applied to all the elements in the selection. Just like most other selection methods, our callback will get called with the first two arguments set to the clicked elements datum and index in the selection, respectively.

Event listener will only be setup once per element, event if we re-setup the listener. If, for some reason, we want to remove all the event listeners for a selection, we can call on with null as the second argument. Animation and interaction 93 1 d3. A click events are fired when a user presses and then releases the mouse button. The objective is to avoid moving asteroids circles from colliding with our spaceship mouse.

Animation and interaction 94 1 update ; 2 setInterval update, ; When an asteroid circle collides with our spaceship mouse , game over! Alert the user that they lost and reset the level counter. We just made a video game in 15 lines of JavaScript. Getting data into the browser All the examples up until this point used hard-coded data values directly in our code. This is fine when working with very small, unchanging, data sets but quickly becomes unmanageable when the amount of data increases or our data changes frequently.

This problem can be solved with a few D3 helper functions that allow us to load data in different formats from a separate files, instead of being in our code. Specifically, we can use d3. All we need to give each is the name of the file to load, and a callback to be called once the file has been loaded.

Data Visualization with D3 and AngularJS

Loading CSV data episodes. Loading data from local file Most modern browsers impose security restrictions that prevent HTML files loaded from your computer frommaking requests for other local file resources. This security restriction prevents normal browser users from mistakingly opening a downloaded HTML file and having it snoop other files off of their hard drive.

To circumvent this restriction, the simplest solution is to run a web server using python -m SimpleHTTPServer from the command line in the directory from which you want to run your server. Then we can access our-file. Data Parsing and Formatting 98 Common Gotcha: One key difference is that JSON object keys must be in double quotes. The same is true for string values. Working with data Often the hardest part of data visualization is just getting the data we want to visualize into a meaningful format.

Notice how in the above example the dates are formatted as strings and contain a -? With it, we can create a new date format object to parse our funky dates. This chapter will cover additional resources and stepping off points for continued exploration of D3. Maps Built into D3 is an extensive collection of utility methods that make working with geographic data much easier. A common use case is in the creation of choropleths and other thematic maps commonly used in data visualization.

D3 does not provide methods like createPieChart. Instead, D3 offers functions that make creating them from scratch easier. Lets walk though a quick pie chart example to show this in action.

The pie layout simply takes data and produces the necessary parameters that arc expects. One of the most interesting among them is the d3. About Angular Angular is a framework that makes it easier to create web applications but it lends it self well to interactive visualization.

It does this by forcing us to break up our application into pieces that perform specific types of tasks. Splitting our code up this way allows components to be easily swapped out for other components. It also helps with connecting our components to other components allowing one visualization to be driven by each other or update themselves automatically when their underlying data changes.

Directives make it easier to create reusable visualizations. If we had created a directive that contained our pie chart, this would be simple. If we write our visualizations in directives, we also get a lot of other advantages for free. It does this by allowing us to reuse the same visualization a variable number of times. This is often useful when creating visualizations that depend on the state of some other visualization or when, say, you wanted two different visualizations to update whenever a slider was moved.

We can think of them in the following way: The information our application wants to show or allow to be modified. In Angular, for the most part, our viewers and models are automatically connected.

Hello Angular! This app will update a template whenever the value of an input tag changes. At the time of writing, the newest version is 1.

Just know that it contains the information of our application. Angular will take care of wiring everything up for us automatically using two way data binding.

All of our directives will live on this module. We only have one directive right now so it seems pointless to put it into a module but when we have many, this will help us group related directives. First, we give it a name. Angular will take care of converting that to the proper HTML tag name with - dashes instead of capital letters.

It contains everything that should happen every time the element appears in the HTML. Angular will call our link method with a few arguments. Next is the element the directive on. The third is an object hash of all the elements properties. The restrict: We could also indicate something is a directive using its class name by using 'C' instead of 'E'.

Korner C. Data Visualization with D3 and AngularJS (PDF + Code)

Directives for reusable visualizations 1 myApp. Because the link method gets called for every new directive instance, our code for modifying the directive will go inside of the link method.

Now when Angular loads our app, it will check our HTML for any directives and invoke all the link functions on them. In the link function, we can copy and paste in all of the original pie chart code.

Doing element[0] gives us just the plain old DOM element. An isolate scope will allow us to pass our data into the directive using an attribute.

It just means that Angular takes care of updating the DOM whenever data changes. Similarly, it automatically updates our data when the DOM changes. All we need to specify is the relationship between our data and DOM elements. When we drag one, all the others are updated automatically. This saves us the trouble of having to manually set up event listeners on all of the sliders as well as taking care of updating their values.

It might help to think of Angular as having written all that code for us. The scope works a lot like the DOM tree. If we create a new scope on a DOM element, all of the child elements will have access to the variables on that new scope.

This is the scope the ourRangeValue is created on. Controllers are normally used to modify scope variables programmatically in JavaScript. Whenever we create and use a new controller, a new scope is also created for it. Working from our previous example, lets see what it looks like to create and use a controller to create new scopes.

We first need to create a module to put our controller on. One for the first HelloController and another one for the second. This has the effect of binding the first two range slides to the value of ourRangeValue on the first scope and the second two range sliders to the value of ourRangeValue on the second scope. Inner scopes inherit from their outer scopes. Scope inheritance ng-init is used to initialize properties on the scope of the current element.

In the following example, a property called foobar on the root scope is given the value The HelloController is unchanged from the previous examples. We might expect that all of the range sliders would now be bound to the same foobar element in the outer scope but they are not. Instead, a new foobar property is created on each of the inner HelloController scopes. Its progress scope property will be a number that represents the loading bars progression from 0 to percent.

Then, the scope. For example, we could copy and paste our directive a few times and watch as changes to the range slider updates all of the progress bars. It just has a different value for its first element. But it always has to have the same number of slices as it started with. It would be better if we could instead add or remove elements from the chart array and have the donut chart appropriately add or remove slices.

If some of this syntax is still a bit unclear, refer back to chapter 2 for a refresher on how selections work in D3. For this, we can use two buttons, one for adding elements to chart, another for removing elements. For this, we can use an ng-repeat. Angular throws an error: The chart array is not being modified by the slider values. This is another reincarnation of scope inheritance we mentioned earlier in this chapter. Doing so, we can safely modify its properties without having to worry about shadowing properties from the parent scope.

Because the pie layout is the only thing that uses data directly, we can give pie a value accessor and it will take care of plucking the pie chart value out of each object in the data array.

The most common being the d3. If used properly, we can continue to use these same functions but Angular also offers its own alternatives for loading in data. We would either need to edit our existing donut chart directive by changing the url it was fetching data from or create a new directive, almost exactly like the original that loaded data in from the scope instead of putting d3.

A better alternative would be for our directive to care nothing about where it gets its data. The controller is where the logic should go that ties together our application. The first step to do doing this is defining our controller.

Angular will do this for us automatically. In fact, Angular almost always knows when to check the scope. A detailed overview of DI and how it works is beyond the scope of this book. In the mean, just know that Angular is smart enough to check what arguments it should call your controllers initialization method with by looking at the variable names of the arguments.

Our directive will take care of the rest. Our directives have always been responding to data changes, never the other way around. It can often be a very modular technique to update data on our directives scope and then optionally listen for changes to that variable in some other place in our application or even in other directives.

This makes our directives more reusable because they no longer need to know anything about each other. As a concrete example, imagine we created a scatter plot directive and wanted to add the ability to see the details of an individual point whenever the mouse is placed over the top of this point. There are a few ways to achieve this, some more modular than others. Which is fine until we need another type of scatter plot that does something slightly different.

Possibly displaying the details in a slightly different way than the first. If we were to stick with our first strategy, we would now need a completely new directive, almost identical to the first expect in the way it displayed its detail content.

A better approach would be to have a single directive that displays a scatter plot that is not responsible for displaying any details about the selected point. All it has is a new scope variable named selectedPoint. Then, when a point is moused over, it will set the selectedPoint scope property to the data of the newly moused over point.

Data Visualization with D3 and AngularJS | PACKT Books

In the the wild, our visualizations are often drastically more complicated. This chapter will cover some of the general best practices the authors have come across when creating directives that are general purpose and reusable. A good strategy is to always take some time up front to consider if a visualization needs to be generalized.

Does the visualization need to be used in multiple places? Accessor functions In Angular, a scope expression is a code snippet, similar to a function, that can be configured on the directive as an attribute. Our directive will evaluate this expression when accessing each element in our data. By making the accessors configurable, we avoid having a directive that assumes a particular input format. This means our directive can accept any type of data array so long as we tell it out to pluck the specific values out of the data using the accessor expression.

We'll reach top-notch reusability and testability by combining D3 graphics with our favorite web application framework, AngularJS. This book teaches the basics of vector graphics, D3, and AngularJS integration, and then dives into controlling, manipulating, and filtering data.

You will learn about the testability of components and how to implement custom interactions, filters, and controllers; discover how to parse and map data in D3. After reading the last few chapters, you'll be able to bring life to your visualizations with more features of D3. You will finish your journey by implementing a parser for different server application logs and display them on a Google Analytics style interactive dashboard.

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