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Makeovermonday 43

For week 43 for makeovermonday we had this table How Frequent Is My Type My problem is: - I don't know what are all this abbreviation mean - It is difficult to find the most frequent type - Even if I know what all this abbreviation mean, I need some time in order to find my type - It is difficult to understand, what does the information on the left side mean This is my first work ever for makeovermonday: It was important for me to understand all abbreviations. I also put filter in order to give the user a possibility to discover their type step by step. With the color on the table I see what is the highest / lowest frequency for each type.
Letzte Posts

I want to understand RegEx! (Part2)

It is already two weeks ago since my last blog post. This two weeks I spent in Scotland. It is a very beautiful country with unforgettable landscaps. However, it is not the topic I want to talk about. In this blog I will continue the topic about the RegEx and its using in Tableau. Tableau offers you four different uses cases of RegEx: REGEXP_EXTRACT If you have data like this: aspirin_20_mg_oral_tablet and you would like to extract onliy 20_mg. What I do is I check my RegEx on this web site: http://regexr.com/ If it is ok, put this RegEx in Tableau function: REGEXP_EXTRACT([0-9][0-9]+[_]+[a-z]+) and extract all "20_mg" REGEXP_EXTRACT_NTH The same like the function before but here you can limit your extract to Nth index. Image you have data like this: aspirin_20565435 and you want to extract only "aspirin_20". So your formula should be: REGEXP_EXTRACT_NTH([a-z]+[0-9], 2) REGEXP_MATCH It is very easy one: Using REGEXP_MATCH we can find if ...

I want to understand RegEx! (Part1)

Have you ever been a witness of such dialogues? Have you ever understood what the people talking about if they mention RegEx? Do you want to speak this language? Then, read this series of the blogs about RegEx. RegEx is a huge part and we can talk about it a long time. There are a lot of good blogs and videos to this topic and it takes a lot of time to understand all of them. In this article I want to give you a short introduction into "RegEx-World". I want you to understand what this mean and how you can use it. And If you decide to became a RegEx professional then you need to read more blogs or books also to watch more videos :). But let's start step by step Idea of RegEx: Imagine you have data like this: website.com/domain/orderpage.html?productcat=shoes&brand=12345 Moin St.&shoenumber=12345&color= black . www.blue website.com /domain/orderpage.html?=M ichle /productcat=shoes&brand= 3456 Silvester St .&shoenumber=5678&color= www...

Tableau Logical Functions: IF, IIF, IFNULL

Have you ever had the situations when you would like to add some conditions as a text or as a number in one separate column? And you got stuck on it. The solution is “IF”, “IIF”, and “IFNULL” functions. IF With the function IF you can add three or more conditions to your calculation: IF test1 THEN value1 ELSEIF test2 THEN value2 ELSE else END EXAMPLE IF SUM([Profit])>5000 then "Profit" ELSEIF SUM([Profit])<4999 and SUM([Profit])>2000 then "Breakeven" ELSE "Loss" END Note! If you create this formula, use exact the aggregation in the text field. In the example above the aggregation is SUM([Profit]), thus I used this aggregation in the formula and NOT just [Profit]. IIF If you want to run a calculation with TWO conditions, e.g. : If I have “XY”, then give me “Z”, otherwise give me “AB” (two conditions!), then use the function IIF. EXAMPLE Assume, we have this data set: I would like to calculate the Conversi...

Tableau Table Calculation Function: WINDOW - Functions

The functions which begin with „WINDOW_...“ are also common used in Tableau. Remember! The “WINDOW_” function stays for the offset in data set, so-called WINDOW. It can look like this: 1) You can see the “WINDOW” clearly because of separation line between rows: 2) You limit the “Window” by giving the information about the first and the last row number. In this case, you give Tableau the information about the data offset. Let's have a look at the example with WINDOW_SUM I created a sample with data from Superstore. I would like to have a total sum of Sales in every row. In order to do this I created a calculation field: WINDOW_SUM(SUM([Sales]), FIRST(), LAST()) With this formula I said to Tableau: “Hey Tableau, calculate the total sum of sales from the first till the last row in the data set” And this is the result: Tableau wrote the result (total sum of Sales) in every row. As another option you can cumulate the result in each row and...

Tableau Logical Function: CASE

Today I would like to discuss about my favorite function in Tableau: CASE I like this function because the using is many-sided and you can create both dimensions and numbers. Example 1: Rename (Dimension) If you would like to rename some data set, not using the option “Alias”, then you can use the CASE Here Tableau looks at data items in “Category”, compare it and if it finds any match, it renames them into the labels I entered. Example 2: 5 Total sum (Number) If you would like to calculate the rate for each items in the Category, then you can also use the Case function. Here Tableau looks at data items in “Category”, compare it and if it finds any match, it gives % Total sum ([Anzahl der Datensätze]/9994). If you have any questions left, let me know…..

Level of Detail Expressions (LoD) in Tableau: FIXED

The last keyword of LoD I am talking to is FIXED. Remember! By the function INCLUDE we included some numbers into the calculation even though we don't visualize this number. By the function EXCLUDE we exclude some numbers from the calculation even though we visualize them. With the function FIXED we “freeze” some numbers in our calculation, i.e. we can run calculation of all art, but the “fixed” dimension remains unchanged. This is the structure of FIXED function: With this function we can e.g calculate a frequency of customer's orders, calculate unique customers from month to month as the cumulative value etc.. Let us have a look to an example, where we analyze sub-categories: I created a simple cross table with the data from Superstore: I would like to see this numbers in a hint text, if I analyze sub-categories. I created a stucked bar chart, which shows sales in each region. I also highlighted sub-categories with different color, as I would ...