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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.
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.
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
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!
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!
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.
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.
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.
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.
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.
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.
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.