Create Chart from Query Task?

Create Chart from Query Task?

I need to create a chart from the result of a query task using Esri JS API. Note, the chart does not have to be created with Esri API, but the query runs in that. The result is written to the DOM and can be displayed using an .innerHTML.

So I basically have a number (Query Result) that is given to the DOM that I would like to use to build a chart. The fun thing is that its a time aware DynamicService and this makes great use of the timeslider widget to create a great visualization of development over time. I now wish to add to this with a statistical review. I am able to return a total built number to the DOM and display that in a DIV, as shown in the JSFIDDLE. So its a cool visualization and provides some stats. the query is running on the same same source data, but on a REST that is not M-enabled.

What I am looking for is to provide a line chart that adds records to it as the number increases - query results returned to the DOM. I have no idea where to start.

You could try to use the mediaInfos charts like this example:

Off-panel widgets are widgets that are not in a panel. They can be turned on or off and can be added to the controller. The off-panel widgets embedded in a theme display when the Widget tab is activated. The following is a list of off-panel widgets:

  • 3DFx—Provides you with a collection of 3D animation approaches to visualize and analyze geographic information in an intuitive and interactive 3D environment.
  • Attribute table—Displays a tabular view of operational layers' attributes. Currently, layers from a map service, feature service, and feature collection in the map are supported.
  • Compass—Click to reorient the scene north.
  • Coordinate—Displays coordinates in the current map projection when moving the pointer on the map or in other coordinate systems by clicking the map.
  • Extent Navigate— Allows you to navigate the map to its previous or next extent.
  • Full Screen—Enables you to start the app in full screen mode.
  • Home Button—Click to zoom to the map's initial extent.
  • Incident Analysis—Defines an area of interest and notes what is happening around the area, such as current weather, demographic information, and features close to the area.
  • My Location—Detects your physical location and zooms to it on the map.
  • Navigate—Allows you to rotate and pan the scene.
  • Overview Map—Shows the current spatial extent of the map display as a gray rectangle relative to the entire spatial extent of the basemap service.
  • Scale bar—Displays a scale bar on the map.
  • Search—Replaces the existing Geocoder widget with support for searching and suggestions on multiple sources.
  • Situation Awareness—Allows you to locate an incident on the map and analyze information from different feature layers within a specified incident area.
  • Slides—Shows different views of the scene based on the slides captured in the web scene.
  • Splash—Displays content on the splash screen.
  • Summary—Dynamically summarizes numeric attributes for features based on the map extent.
  • Swipe—Shows a portion of a layer or layers on top of the map.
  • Time Slider—Visualizes content within a map that contains time-aware layers.
  • Zoom Slider—Provides interactive zoom controls in the map display.

To turn on or off a widget, hover over the widget and click the eye icon.

The Cloud Console has three main sections, shown in the following screenshot:

Navigation menu

The navigation menu contains a list of BigQuery resources that you can view:

The SQL workspace section displays your datasets, tables, views, and other BigQuery resources. This is where you can create and run queries, work with tables and views, see your BigQuery job history, and perform other common BigQuery tasks.

The Transfers section opens the BigQuery Data Transfer Service page.

The Scheduled queries section displays your scheduled queries.

The Reservations section displays slot commitments, reservations, and reservation assignments.

The BI Engine section opens the BigQuery BI Engine page.

To collapse the navigation menu so that only the icons are visible, click Hide BigQuery navigation menu. To temporarily expand the menu again, hold the pointer over the menu. To expand the menu so that the labels remain visible, click Show BigQuery navigation menu.

Explorer panel

The Explorer panel is visible when you select SQL workspace in the navigation menu. This panel contains a list of your current project plus any pinned projects. To view the datasets that you have access to in a project, expand the project. To view tables, views, and functions in that dataset, expand the dataset.

You can also use the search box to search for resources by name (project, dataset, table, or view name) or search for resources by label. The search box finds the resources that match, or contain matches, within your current and pinned projects.

To use search and autocomplete powered by Data Catalog (beta), in the Try search and autocomplete powered by Data Catalog dialog, click Enable. With this feature enabled, BigQuery loads your results on demand for searches in the Explorer panel and for autocomplete in SQL queries. If you have a large number of resources, Data Catalog improves the Cloud Console's performance. It also lets you search for resources outside of your current and pinned projects.

Details panel

The details panel shows information about your BigQuery resources. When you select a dataset, table, view, or other resource in the Explorer panel, the Cloud Console opens a new tab in the details panel with information about the resource. From these tabs, you can create tables and views, modify table schemas, export data, and perform other actions.

Working Methods of GIS Explained By GIS Assignment Expert

A GIS is a computer-based programming tool used to map and analyse things that exist on the earth. GIS is a technology integrated with few database operations like statistical analysis and queries with geographic analysis and unique visualisation.


Mapping is generally a geographic container for data analytics and data layers. The maps created by GIS can be embedded and shared easily in apps which are accessible by anyone, anywhere. We all know the importance of Maps. Everyone understands and evaluates a good map. GIS users make and work on the development of maps to provide basic experience and best interface for the application of GIS. Maps offer a critical context as they are artistic and analytical which allows you to discover and explore and interpret patterns.

Maps Need Data

The Geography Information System organisations work with a fundamental mission - area to focus, reasons to exist and support their mandate. Such organisations are engaged to develop key data layers that support their focused mission. This work includes the involvement of data layers, operational data, and standard base map layers for application and geographies. The creation of data includes user authored data, Esri authored data and partner authored data.

Geographic Analysis

Have you ever explored any type of information such as parks, school, or figure out the areas of high crime rates? You may have noticed that we naturally use maps as a source of information by finding routes, patterns, assessing trends, etc. This process is known as spatial analysis. Spatial analysis is one of the most remarkable and intriguing aspects of the Geography Information System. It is used to compile information from different sources and results as a new set of information with the use of spatial operators. The set of spatial operators broadens the ability to solve spatial questions.

With the availability of smartphones, laptop computers, tablets, and other internet-based devices, apps have attracted the world's attention. GIS applications have changed the way people think about geography. The apps are comprised of a user-interface and user-interface which brings a specific map into use.

So, these were the steps involved in the working process of GIS. Want to know more? Avail help from GIS assignment experts.

Geographical heat mapping: Essential features

In addition to an intuitive and simple-to-understand user interface and experience, eSpatial offers some more key features for geographical heat mapping:

  • The ability to use your own data, or a dataset from the eSpatial datastore. Even if you don’t quite have your own regional dataset established, you can still use the heat mapping feature using an available dataset.
  • Street address mapping. Whereas Excel doesn’t support this, eSpatial enables you to plot out relevant street addresses, displayed as pins on regional heat maps.
  • Simple sharing and publishing. eSpatial makes it easy to share and collaborate on geographic heat maps, so you can show this data to the entire team.

If Excel is limiting your heat mapping activities, you could benefit from a dedicated enterprise solution like eSpatial.

Liam Costello

Liam is an eSpatial account manager and mapping expert. He specializes in helping businesses solve problems and increase sales through mapping visualization, territory management, route optimization and more. Liam holds a Master's Degree in Geographical Information Systems (GIS) and Remote Sensing.

Create 3D Map

Now that the data is loaded, it is ready to use. For our purposes, we won’t worry about doing the typical preliminary steps of data exploration or cleansing prior to generating the map. Instead, we will proceed directly to creating a heatmap of the number of incidents, with the ability to filter by offense type. Here are the steps to creating the heatmap:

  1. To load the data into the map, select the 3D map icon in the Insert Tab. You should see the following image:

2. From the Field list, drag latitude and longitude over to the Location box.

3. Drag the General Offence Number over to the Height box.

4. In the Height box, select “Count” as the aggregate function.

5. Drag Offence Type to the Filter box

6. Select the Heatmap Icon (4 th from left) under Data in the Layer panel

7. Change the name “Layer 1” to “Offenses.”

8. Zoom into the Seattle area and view the heatmap.

Filter the Data

If you are interested in seeing a map that only includes the various types of assault, then the filter checkboxes can be used to filter the data and display the corresponding heatmap.

Strategy at the Movies

Office Space

How much work can a man accomplish with eight bosses breathing down his neck? For Peter Gibbons, an employee at information technology firm Initech in the 1999 movie Office Space, the answer was zero. Initech’s use of a matrix structure meant that each employee had multiple bosses, each representing a different aspect of Initech’s business. High-tech firms often use matrix to gain the flexibility needed to manage multiple projects simultaneously. Successfully using a matrix structure requires excellent communication among various managers—however, excellence that Initech could not reach. When Gibbons forgot to put the appropriate cover sheet on his TPS report, each of his eight bosses—and a parade of his coworkers—admonished him. This fiasco and others led to Gibbons to become cynical about his job.

Simpler organizational structures can be equally frustrating. Joanna, a waitress at nearby restaurant Chotchkie’s, had only one manager—a stark contrast to Gibbons’s eight bosses. Unfortunately, Joanna’s manager had an unhealthy obsession with the “flair” (colorful buttons and pins) used by employees to enliven their uniforms. A series of mixed messages about the restaurant’s policy on flair led Joanna to emphatically proclaim—both verbally and nonverbally—her disdain for the manager. She then quit her job and stormed out of the restaurant.

Office Space illustrates the importance of organizational design decisions to an organization’s culture and to employees’ motivation levels. A matrix structure can facilitate resource sharing and collaboration but may also create complicated working relationships and impose excessive stress on employees. Chotchkie’s organizational structure involved simpler working relationships, but these relationships were strained beyond the breaking point by a manager’s eccentricities. In a more general sense, Office Space shows that all organizational structures involve a series of trade-offs that must be carefully managed.

Figure 9.13: Within a poorly organized firm like Initech, simply keeping possession of a treasured stapler is a challenge.

Create new workbooks

You can create a new workbook from scratch or use a built-in workbook as the basis for your new workbook.

To create a new workbook from scratch, select Workbooks and then +New workbook.

Select the subscription the workbook is created in and give it a descriptive name. Each workbook is an Azure resource like any other, and you can assign it roles (Azure RBAC) to define and limit who can access.

To enable it to show up in your workbooks to pin visualizations to, you have to share it. Click Share and then Manage users.

Use the Check access and Role assignments as you would for any other Azure resource. For more information, see Share Azure workbooks by using Azure RBAC.

Group strategies

Curate featured content using groups and promote a set of groups as the organization’s Featured Groups. (Assign this task to other staff if possible.) If your organization decides to use basemaps other than the default Esri basemaps, create and maintain a group for the basemap gallery.

Groups do not consume credits, so group maintenance is simply good housekeeping however, cleaning up groups may also help you clean up old content items that are consuming storage credits.

Identify stagnant groups or groups that are no longer in use, especially public and organizational groups.

  1. View your organization’s groups (click Groups > My Organization's Groups ) and reverse the sort order to list oldest groups first.
  2. For each group, view its Content tab to determine the most recently modified items.
  3. Open item pages for the group content and review the Usage tab for activity statistics.

4 Answers 4

Natural language querying poses very many intricacies which can be very difficult to generalize. From a high level, I would start with trying to think of things in terms of nouns and verbs.

So for the sentence: How many books were sold last month?

You would start by breaking the sentence down with a parser which will return a tree format similar to this:

You can see that there is a subject books, a compound verbal phrase indicating the past action of sell, and then a noun phrase where you have the time focus of a month.

We can further break down the subject for modifiers: "how many" for books, and "last" for month.

Once you have broken the sentence down you need to map those elements to sql language e.g.: how many => count, books => book, sold => sales, month => sales_date (interval), and so on.

Finally, once you have the elements of the language you just need to come up with a set of rules for how different entities interact with each other, which leaves you with:

Select count(*) from sales where item_type='book' and sales_date >= '5/1/2014' and sales_date <= '5/31/2014'

This is at a high level how I would begin, while almost every step I have mentioned is non-trivial and really the rabbit hole can be endless, this should give you many of the dots to connect.