Alteryx Designer Knowledge Base

Definitive answers from Designer experts.
AlteryxSpatialPluginsEngine.dll could not be loaded: The specified module could not be found
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Suppose you have a datetime stamp in a dataset for the timezone where you are. This dataset includes data for locations in timezones other than the one you're in and you want to convert your datetime stamp to reflect the local time zones of the locations in your data.
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A part of the Spatial Tools Category, the Distance Tool calculates how far apart spatial objects are.
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Clustering analysis has a wide variety of use cases, including harnessing spatial data for grouping stores by location, performing customer segmentation or even insurance fraud detection. Clustering analysis groups individual observations in a way that each group (cluster) contains data that are more similar to one another than the data in other groups. Included with the Predictive Tools installation, the K-Centroids Cluster Analysis Tool allows you to perform cluster analysis on a data set with the option of using three different algorithms; K-Means, K-Medians, and Neural Gas. In this Tool Mastery, we will go through the configuration and outputs of the tool.
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One of the perennial challenges of creating high-quality maps is working with data sets where the spatial data is too spread out to make a useful map. The general solution for this challenge is to create a Map Book. A Map Book is a series of maps that show a subset of the data at a more detailed resolution. This article demonstrates methods for creating a Map Book in Alteryx.\n  
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Customers using pre 2019.4 Designer and Insights Data need to update to the Mapbox maps or they will see this issue with Digital Globe maps.
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This article is part of the CS Macro Development Series. The goal of this series is to communicate tips, tricks, and the thought process that goes into developing good, dynamic macros.
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Don’t know the area of your polygon? Need the length of your line? Do you want your spatial object’s X and Y coordinates? Don’t Panic! The Spatial Info tool can translate all that information and more!
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Imagine this – you’re on vacation. You’re on a sandy beach where the sun has been relentless all day. It’s hot and you need something to cool you off. Ice cream would be perfect! The Find Nearest tool can help!
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The Report Map tool allows the user to define theme settings/ranges and to modify the size, icon, and color of the display for each range, and this can be done rather easily. First, in the Map tool on the Data tab, pick which column you would like to theme off in the Thematic Field selection area:                            Once this column is selected, go to the Layers tab in the Map tool and expand the layer options for your theme layer. Click on the Theme and options will appear on the right. For the purpose of defining your own theme settings, you will want the Tile Method to be on Unique Value, which gives the Specific Values area.                             The Specific Values area is where you list what you want to theme on. For this example, we are theming off the DMA_Name so you would enter each of the DMA names you would like to theme. If you have a lot of ranges, you could also use a Summarzie tool in your module and  Group By your theme column, thus giving you a list of your theme values. Run the module once to populate the Browse tool and you can then click and hold on the first row and drag down to the row of your choosing, selecting them all. Ctrl+C will copy the rows and you can paste them into the Specific Values area using Ctrl+V                             Once the values are entered, click on Refresh and a layer option will show up for each of the theme values you set.                           Now that the theme values are layers, you can go to the Style option under each layer and change the Point Style , bring in a Custom Point , change the  Size , Color , modify the Outline Color and Outline Size .                           If you don't define all the values that are contained in the data you are bringing thru, the Map tool also provides options on what to do with these.                           This can also be done with number ranges with a few small changes. For Tile Method , choose Manual Tile . Enter in the cutoff for each range that you would like to be able to theme.                          Hit Refresh and the new layers for the theme ranges will be displayed, allowing you to modify each one. Also note that layers are created for the ranges below and above what you specify in the Cutoff Values area.                         
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Copy:  In a Browse tool, under the map tab, right click on any point on the map.  The Latitude and Longitude for that location will be displayed.  If you click on “Copy Point …” you will have copied that Latitude Longitude value to your clipboard. Paste:  Right click on the module canvas, select “Paste” and a Text Input tool will be added to your module, with the values of your copied point already populated in the tool.
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Buffer – This tool was designed to work primarily with Lines and Polygons, but is effective with Points as well Trade Area – Only works with Points.  If you create a trade area around a polygon, the Trade Area tool will use the polygon’s centroid as the basis for creating the trade area.  The Trade Area tool should only be used with point spatial objects. Non-Overlapping – Points Only.  To create non-overlapping buffers around Point spatial objects, use the Trade Area tool instead of the Buffer tool, and check the “Eliminate Overlap” checkbox.  It is not possible to create a non-overlapping trade area from line or polygon spatial objects.    
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The purpose of this process is to demonstrate the use of the bounding rectangle as a means of processing spatial data. 
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In its spatial tools, Alteryx includes an option to create a convex hull polygon from a series of points. However, depending on the type of analysis requested, it can be more ideal to create a concave hull instead. An example of this would be the need to group customer points into trade areas thematically based on store location. If the standard method of convex hull polygon creation were used, it would be possible to create polygons that overlap, which would not be the desired outcome. A demostration of this is shown below. Module attached. Example: To avoid this, one can first project non-overlapping trade areas from the points and spatially combine them to eliminate the overlap. To then remove the excess area projected, the object can be trimmed to the original convex hull boundaries. To further process and remove the resulting holes, spatial generalization can then be used.
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The addition of a reference map can bring your report to another level of utility.  This is a technique that is often used when a module is developed to produce a multitude of maps; each zoomed-in upon a small area.  For users who may be unfamiliar with the area displayed in the primary map view, a reference map provides a rapid means of orientation. The key to creating a reference map is making use of the bounding rectangle sourced from your primary map.  The bounding rectangle will be used as a display feature (layer) in the reference map.
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How To: Combine Date Ranges with a Macro This module (and embedded batch macro) will provide a comprehensive timeline or date range(s) using multiple, overlapping date ranges.       The macro converts date ranges into spatial objects in order to use the spatial functions in Alteryx to group overlapping or adjacent ranges. This ensures that ranges A and C get are grouped together when A and C do not overlap but both A and C overlap range B (and so forth for larger chains of ranges).           It also allows for “jumping” a user-determined number of days in order to combine regions that do not overlap but are within a specified number of days of one another.      
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Business Problem: Thematic maps are often used to display data geographically with colored or shaded themes, but sometimes users wish to see the data differently. For this purpose, dot density mapping has become a frequently requested feature for map rendering in Alteryx. Dot density creation is possible with the inclusion of the spatial function within the formula tool. This function, ST_Random Point, will randomly disperse a point within a given polygon. Utilizing this tool, anyone can create a macro to produce the data required to generate a dot density map. Actionable Results: Easily create dot density thematic maps Overview: It can often be convenient to view thematic maps as clustered points. This type of visual output is a logical and accurate representation of data occurring in a non-continuous distribution. Vertical: Any Key Tools Used: Formula Tool (ST_Random Point spatial function), Generate Rows Required Input: As inputs, the Dot Density macro requires two fields: geography with an associated value and a configuration of the number of dots per value. Determining the appropriate number of dots per value may require some trial and error to produce desirable results. Knowing the min, max, and median values associated with the base geographies would help you to determine and optimal dots per value. This coupled with the size of dots on the map will greatly affect the aesthetic of the mapping.  
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Convert Polygons to Polylines This macro can be used to convert Polygons into Polylines. In order to use the macro you must specify a spatial field (polygon) as an input. After running the module all the polygons in the selected spatial field will be converted to polylines. This macro is very useful for when you are putting polygons on an ALTERYX base map and want their boundaries to appear on top of the base map roads. An example would be the mapping of census based Trade Areas. As census Geographies tend to follow roads, they are often obscured by the Alteryx base map. Before Example After Example  
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Alteryx users who have purchased the TomTom Alteryx Maps data set have the ability to extract layers into various formats using the Alteryx Street Analytic App. Installs from TomTom 2011 Q3 Alteryx Maps forward, include the Street App within the install.  The App replaces what was previously known as the StreetWare product.  The Alteryx Street App is an extraction tool which allows the user to extract TomTom layers into various file formats such as .tab, .shp, .yxdb to name a few. The App is specific to the data install vintage of TomTom Alteryx Maps Data and is located in the, AlteryxDataProductsAlteryxMapTomTom_US_xxxx_Qx directory.  To run the Street App (TomTom_US_yyyy_Qx.yxwz) you will need to browse to the location above and select it. Under the Geography Selection tab, select the Geographies you would like data for. You may select all, single or multiple Geographies as shown below: Under the Layer Selection tab, you may select the individual layers you would like to install for the Geographies that you selected. The Output Options tab allows you to select the file format you wish to create and the Destination directory you wish to install the data to.  There is also an option to merge the geographies.   One feature of the wizard that was not present in the StreetWare product is the ability to create seamless .tab files.  This feature allows the user the ability to bypass the 2 GB limitation that .tab files have. Please note .shp files also have a 2 GB file size limitation but do not offer the same seamless ability that is incorporate in the extraction of .tab files When .tab file format is selected a folder is created containing the referenced .tab tables, the seamless .tab files are visible below this folder.  As Shown Below:   The seamless .tab files will be opened and viewed in MapInfo as normal.  The individual .tab files that are referenced by the Seamless files can be found in the SeamlessTabFiles folder. We hope our users find that the Street App will be an easy-to-use utility to extract the desired map layers for use in their preferred applications.
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Often, we get support requests asking if we can do a quick session on best practices for a particular tool or set of tools.  The Spatial Match Tool is certainly no stranger to this request.  Even though Alteryx is extremely fast and efficient with spatial processing, there are instances where a slight change in settings could speed up your total module runtime. For example, let us assume that we have 10,000 records that we are trying to perform a spatial match against.  Upon looking at our data, we notice that the points were derived from the centroid of another polygon, but the previous polygon field was still in the data stream.  Removing the unnecessary spatial field is one of the first steps in optimizing your data stream.  Why?  If you don't need the data, why are you pushing it all the way through your module?  That extra data consumes memory, so removing it from your data stream reduces that consumption, increasing the available resources on your computer.   Ultimately, this practice can be used in any aspect of your data, but it is especially relevant with spatial processing.  For more tips and tricks regarding your spatial match process, download the included zip package.  It contains information that can help you optimize your modules that utilize the Spatial Match tool.   Special thanks to Paul Treece for helping out with the module! Until next time! - Chad  Follow me on Twitter! @AlteryxChad    
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I have no doubts that many of you have attempted to geocode a set of records, only to find that your records show up in the middle of the ocean on the other side of the world.  I certainly have, and the result is always that I accidentally reversed my non-descriptive latitude and longitude fields just before the Alteryx Create Points Tool.  If I had taken a quick look at my data, I would have known that my field with a non-zero hundreds digit (100+) is my longitude field, and setting it properly would have saved me valuable processing time.   While the above example is common, there are many others that are equally as common that can be fixed or avoided completely with a bit of additional knowledge.  The main question of the article (How accurate does my data need to be?) all depends on your use case.  For example, in many point-in-polygon cases you may only need 5 digits of precision rather than 6.  Why?  5 decimal places are accurate at 1.1 meters, while 6 decimals are accurate to 0.11 meters.  This may seem like a big difference, but when you are trying to search for entire buildings based on a trade area, 5 decimals should do the trick. If you are interested in learning more, please take a look at the StackExchange article How to Measure Accuracy of Latitude and Longitude.  This breaks down the difference between accuracy and precision, and goes into detail about each decimal in a latitude and longitude point (with examples!).   Big thanks goes out to our very own Paul Treece for his help with the article.  Until next time! Chad Follow me on Twitter! @AlteryxChad
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