{"id":154,"date":"2019-10-10T20:44:55","date_gmt":"2019-10-11T01:44:55","guid":{"rendered":"http:\/\/qlikwithfriends.com\/?p=154"},"modified":"2019-12-04T03:49:01","modified_gmt":"2019-12-04T08:49:01","slug":"using-advanced-set-analysis-operators-to-power-your-visualizations","status":"publish","type":"post","link":"https:\/\/qlikwithfriends.com\/index.php\/2019\/10\/10\/using-advanced-set-analysis-operators-to-power-your-visualizations\/","title":{"rendered":"Using Advanced Set Analysis Operators To Power Your Visualizations"},"content":{"rendered":"\t\t
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In this post, I\u2019m going to talk about the differences between some of the set analysis operators. \u2026 Okay, I\u2019ll agree that the world probably doesn\u2019t need another blog post on set analysis, but I\u2019m going to focus specifically on the four operators that I think are underused. I get a lot of questions from users about set analysis and this topic has come up three or four times in the past month. I\u2019ve even answered a few community posts on this very topic.<\/p>

The operators are\u00a0\u00a0 +=\u00a0\u00a0\u00a0\u00a0 *=\u00a0\u00a0\u00a0\u00a0 -=\u00a0\u00a0\u00a0\u00a0 \/=<\/p>

If you\u2019ve never used these, or if you wonder why you might use them then this post is for you.<\/p>

Let\u2019s look at a very simple example that I\u2019ll be using to illustrate these.<\/p>

I\u2019ve loaded a Qlik Sense app with the following animal names (and unique IDs to use as a dimension values).<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\"All\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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Here are two simple tables that display those values. My dimension is \u201cID\u201d and my measure is MaxString([Animal]). There\u2019s only one value of [Animal] for each ID, but I\u2019ve used MaxString so that I can demonstrate some set analysis expressions.<\/p>

In the first table, I\u2019ve just listed all the animals. In the second table I\u2019ve used the following set analysis expression.<\/p>

[Animal] = {“Dog”,”Fish”,”Turtle”}
\u201conly values of [Animal] that are \u201cDog\u201d or \u201cFish\u201d or \u201cTurtle\u201d<\/em><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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So far, it\u2019s simple\u2014this is the basic set analysis that we use most often. But, let\u2019s examine what happens when the user filters some values. I\u2019ve selected five of the animals below.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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Table #1 shows exactly what we expect but look again at table #2. The values don\u2019t match the filtered values I\u2019ve selected. Some of the selected values are missing and one of the values displayed is the one I excluded.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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This is where the users were confused. Is something wrong? What\u2019s going on in table #2?<\/p>

Answer: Exactly what is supposed to be going on\u2014this is how set analysis works.\u00a0 The \u201c=\u201d (equal sign) in the expression:<\/p>

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 [Animal] = {“Dog”,”Fish”,”Turtle”}<\/p>

means, \u201conly values of [Animal] that are Dog or Fish or Turtle, no matter what values are filtered<\/strong>.\u201d<\/em> In other words, using only the equal sign overrides the filter criteria with only the values in the set analysis expression<\/u>.<\/p>

Most of the time, this is exactly what we want it to do, however, in many cases we actually do<\/span> want to consider both the filters and<\/u> set analysis. This is exactly what those users wanted to happen and it\u2019s what confused them.<\/p>

Fortunately, Qlik provides a solution for this.<\/p>

Back to those operators\u00a0\u00a0 +=\u00a0\u00a0\u00a0\u00a0 *=\u00a0\u00a0\u00a0\u00a0 -=\u00a0\u00a0\u00a0\u00a0 \/=\u00a0\u00a0 that I mentioned earlier. These are what we use when we also want to consider the filtered values.<\/p>

Stand back, because we\u2019re about to put the \u201cSet\u201d<\/em> in \u201cSet Analysis\u201d<\/em>\u2014and YES\u2014there will be Venn diagrams.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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Set Analysis Operators To The Rescue<\/u><\/strong><\/p>

Think about the following set analysis expression<\/p>

{< [Animal] += {“Dog”,”Fish”,”Turtle”} >}<\/p>

as<\/p>

{<\u00a0\u00a0 [Field]\u00a0 operator\u00a0 {Comparison Values} \u00a0\u00a0>}<\/p>

Or, in other words<\/p>

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 {<\u00a0 Filtered Values<\/em><\/strong> on the left of the \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 operator \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Comparison Values<\/em><\/strong> on the right\u00a0 >}<\/p>

\u00a0<\/p>

Filtered Values<\/em><\/strong> is the set<\/em> of all the values for a field that we\u2019ve selected in a filter for that field. If nothing has been filtered, then it contains all the values. In the filter shown below, those values are<\/p>

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Bird, Cat, Dog, Fish, Frog<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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Comparison Values<\/em><\/strong> is the set<\/em> of all the values that are specified in the set analysis expression. In the examples below, these will be<\/p>

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Dog, Fish, Turtle<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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Set Analysis Operators<\/u><\/strong><\/p>

Now let\u2019s look at those four operators and learn about what they do.<\/p>

+=<\/strong> \u00a0\u00a0The Union operator
<\/u>Definition: \u201cReturn the set<\/em> containing the values that belong to any<\/em> of the Filtered Values<\/em> or Comparison Values<\/em>.\u201d<\/p>

In English: \u201cI want the result to include all of the filtered values and<\/em> the comparison values.\u201d<\/p>

So, If the expression is<\/p>

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 MaxString({< [Animal] += {“Dog”,”Fish”,”Turtle”} >})<\/p>

This is the diagram that represents the set analysis expression.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\"Union\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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This is the resulting table. The items in the table are the ones that are shaded green in the diagram above.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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-=<\/strong> \u00a0\u00a0The Exclusion operator
<\/u>Definition: \u201cReturn the set<\/em> containing the values that belong to the Filtered Values<\/em> only if the value is not part of the set of Comparison Values<\/em>.\u201d<\/p>

In English: \u201cI want the result to include all of the filtered values except for those that are<\/em> the comparison values.\u201d<\/p>

So, If the expression is<\/p>

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 MaxString({< [Animal] -= {“Dog”,”Fish”,”Turtle”} >})<\/p>

This is the diagram that represents the set analysis expression.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\"Exclusion\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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This is the resulting table. The items in the table are the ones that are shaded green in the diagram above.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\"Exclusion\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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*=<\/strong> \u00a0\u00a0The Intersection operator
<\/u>Definition: \u201cReturn the set<\/em> containing the values that belong to both<\/em> the Filtered Values<\/em> and Comparison Values<\/em>.\u201d<\/p>

In English: \u201cI want the result to include only the filtered values that are also specified in<\/em> the comparison values.\u201d<\/p>

So, If the expression is<\/p>

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 MaxString({< [Animal] *= {“Dog”,”Fish”,”Turtle”} >})<\/p>

This is the diagram that represents the set analysis expression.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\"Intersection\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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This is the resulting table. The items in the table are the ones that are shaded green in the diagram above.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\"Intersection\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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\/=<\/strong> \u00a0\u00a0The Symmetric Difference (XOR) operator
<\/u>Definition: \u201cReturn the set<\/em> containing the values that belong to either, but not both of<\/em> the Filtered Values<\/em> and Comparison Values<\/em>.\u201d<\/p>

In English: \u201cI want the result to include all of the filtered values and comparison values that do not match<\/em>.\u201d<\/p>

So, If the expression is<\/p>

\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 MaxString({< [Animal] \/= {“Dog”,”Fish”,”Turtle”} >})<\/p>

This is the diagram that represents the set analysis expression.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\"Symmetric\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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\n\t\t\t\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t

This is the resulting table. The items in the table are the ones that are shaded green in the diagram above.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

\n\t\t\t\t\t\t
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\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\"Symmetric\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
\n\t\t\t\t\t\t
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\n\t\t\t\t
\n\t\t\t\t\t\t\t

All of this may seem confusing at first but learning how to use these operators will enable you to deliver much more robust features in your visualizations. Try them out on your own data sets. Please post any questions or area that you\u2019d like to see explained further in the comments below.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"

In this post, I\u2019m going to talk about the differences between some of the set analysis operators. \u2026 Okay, I\u2019ll agree that the world probably doesn\u2019t need another blog post on set analysis, but I\u2019m going to focus specifically on the four operators that I think are underused. I get …<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_exactmetrics_skip_tracking":false,"_exactmetrics_sitenote_active":false,"_exactmetrics_sitenote_note":"","_exactmetrics_sitenote_category":0,"footnotes":""},"categories":[6,11,7],"tags":[],"class_list":["post-154","post","type-post","status-publish","format-standard","hentry","category-qliksense","category-qlikview","category-visualizations"],"_links":{"self":[{"href":"https:\/\/qlikwithfriends.com\/index.php\/wp-json\/wp\/v2\/posts\/154","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/qlikwithfriends.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/qlikwithfriends.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/qlikwithfriends.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/qlikwithfriends.com\/index.php\/wp-json\/wp\/v2\/comments?post=154"}],"version-history":[{"count":3,"href":"https:\/\/qlikwithfriends.com\/index.php\/wp-json\/wp\/v2\/posts\/154\/revisions"}],"predecessor-version":[{"id":170,"href":"https:\/\/qlikwithfriends.com\/index.php\/wp-json\/wp\/v2\/posts\/154\/revisions\/170"}],"wp:attachment":[{"href":"https:\/\/qlikwithfriends.com\/index.php\/wp-json\/wp\/v2\/media?parent=154"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/qlikwithfriends.com\/index.php\/wp-json\/wp\/v2\/categories?post=154"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/qlikwithfriends.com\/index.php\/wp-json\/wp\/v2\/tags?post=154"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}