10/4/2017 0 Comments How To Install Postal 2 MapsHow to create geographic maps using Power BIThe project. This is the first article of a series dedicated to discovering geographic maps in Power BI. Remember that Power BI is a product undergoing constant evolution; new features are added every month at a fast pace. And over the time Power BI has gained more mapping capabilities compared to the starting point. They are based on Bing map engine. Bing simply recognizes addresses, coordinates or any geographic attribute and plots it on a map. Behind the scenes, Bing converts the input into geographic coordinates (latitude and longitude) to be passed to the page. A well- known process called geocoding. Nevertheless, it’s advisable to follow some “best practices” in order to get a valid result. I’ll go more in detail later on. The project This is the first article of a series dedicated to discovering geographic maps in Power BI. My goal is to illustrate to you the different visuals. Get maps, driving directions and distances, coordinates (latitude/longitude) all for free. Easily switch from one mapping service (Google Maps, Bing Maps, and. Launch a webmap and explore Campbell River! Our new and improved webmap is now faster and easier to use, with more tools to help explore neighbourhoods and create maps. Irish and Celtic TrueType fonts from Ireland free to download suitable for MAC and PC. The latest PC gaming hardware news, plus expert, trustworthy and unbiased buying guides. Provides many maps of the world, world regions, countries and cities for download. Uses native browser technologies like JavaScript, CSS, HTML, SVG or VML. Enter the data as shown in the picture below. Call the column Address, call the table bing. You get the following result. The Bing engine is clever enough to identify locations although of a different kind; two addresses, a bridge, an airport, a volcano (!). But it didn’t recognize a building, Teatro San Carlo a theater in Naples and placed the point somewhere else. We will address the issue later on. Click here, to download the full dataset with over 1. Download the file in either . Click Get Data - > Text/CSV. Power BI loads the file and shows you a data preview, based on file code page and delimiter. For this demo click Load and the dataset is imported into Power BI. To be sure that Power BI recognizes correctly the data, let’s force the data category. So we are sure that data format is correctly evaluated by the Bing map. Enlarge the visual to fit the page size. If you want to have more details, for example, the airport name, add the Airport. Name field to the tooltip or the legend in the visualization toolbox. How to install Windows 8. Here are tips on how to install the Windows 8 RTM (Release to Manufacturer), or regular version. You can zoom in and out or scroll around the world, but you can’t change the map type. Let’s say we want to know which is the world’s busiest airport and the amount of passenger traffic for each one in our list. Wikipedia provides the info we need. In the pop- up window insert the following URL. List. Click Load to import data into your model. Click Transform - > Split Column - > By delimiter. In the dialog window select Custom as the delimiter and insert the “/” symbol into the empty field. Leave the selection for “At each occurrence of the delimiter” and click OK. Rename both columns by right- clicking on the heading and choosing Rename . If you wish, you can change the name of the table, by clicking in the Name field under the PROPERTIES window. I called mine “passengers traffic statistics”. Numbers from the Wikipedia page are formatted in the English notation, with commas as the thousands separator. But my operating system, for example, is set to Italian and comma is the decimal delimiter. So Power BI treats the field as a text. If you are in the same situation, select the column Total passengers, click on the Transform tab and choose Replace values. Replace the comma with an empty space as showed in the figure and click OK. In order to convert it to a number click on Data Type- > Whole Number. The symbol in the column heading switches to a number, meaning that Power BI has changed the data type. Click on the Relationships icon. Power BI tries to set up a relationship basis on similarity in data fields, but in this case, it doesn’t work for us. Now the bubbles are filled with a lighter or darker color, based on the passengers number. It overlays regions with polygons and boundaries; again we have to pass an attribute that can be recognized as a significant geographic name. For example a city, a state, a country, postal code, etc. Latitude and longitude are not applicable as filled map works with areas, not points. Therefore we must train Power BI to identify one of our fields as a geographic location. Make sure that the field Country in the dataset “passengers traffic statistics” is selected. Click Modeling tab - > Data category - > Country. Power BI marks the country name as geographic spot. Expand the dataset “passengers traffic statistics” and add the field Country to the Location bucket. Power BI recognizes the countries and displays the filled regions on the map. As in the previous example, you got a color saturation scale. Note that Power BI automatically groups and sums the total number of passengers by country, so you don’t have to perform aggregations before plotting data. But, if you don’t use precise geographic references, some ambiguity can occur and the likelihood of retrieving an exact result decreases. Do you expect a city or a state? Or if you search for Paris, Cambridge, Georgia, etc.? When it happens, Power BI warns you with an icon in the top left corner of your visual indicating that the map needs more location data to accurately plot values. If they aren’t available, try to make your location as distinguishing as possible. For example set the Data Category in the modeling tab as a geographic attribute (Address, City. Continent, Country/Region, Zip. For example “Paris, France”, rather than “Paris, Texas” or “Cambridge, Cambridgeshire, UK”. Use the DAX function CONCATENATE to bind multiple fields together and use to geocode locations. This internationally adopted code helps to properly recognize some locations. Do not use localized names or abbreviations. They are quick and easy to use. No previous knowledge is requested. Both are based on Bing maps geocoding engine and both allow cross- filtering between the map elements and the other visuals in the report. According to the data you’re displaying, size and color saturation of the bubbles may vary. A solid polygon is plotted over the related area. Polygon’s color saturation may vary, depending on the data. Mark your spot as a geographic attribute from the Data Category menu in Power BI. Alternatively, concatenate data from multiple columns, to pass to Power BI an unambiguous value. If available, for bubble maps use latitude and longitude. Focused in IT support for Human Resources management. Common tasks: Database development and monitoring, data warehousing, creating BI solutions and reporting, data analysis. MCTS certificated: SQL Server Developer. Speaker at SQL Saturdays, and other conferences in Europe. Author for SQLShack and UGISS (User Group Italiano SQL Server). Latest posts by Andrea Martorana Tusa (see all). Ways to Add Places to Google Maps. Provide the following information. You should see a file with the following nine column headers: Store Code, Name, Address Line 1, City, State, Postal Code, Country, Primary Phone, and Primary Category. Place each business location on one row, filling out the information under the appropriate headers. Google provides detailed guidelines on its website, but here are the most important tips. For example, if all of your businesses are coffee shops that share the same name, designate each Store Code as Joe. Coffee. 1, Joe. Coffee. Avoid special characters and leading or trailing spaces. Some fields have a 6. If your postal code begins with 0, make sure your spreadsheet formatting does not delete that digit. You may use the full name of your country, or look up its ISO 3.
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