I have this data in Tableau:
KPI_NAME Value Date
------------------------
A 2 1-Jan
B 4 1-Jan
A 6 2-Jan
B 7 2-Jan
and I want it like this:
A B Date
------------------------
2 4 1-Jan
6 7 2-Jan
So I want it to convert each distinct value in the column KPI_NAME to a separate row, this can be done in the visualization part in Tableau but I want to do that in the data preparation because I want to use it in calculated field
Any help is appreciated.
Most tableau functionality is designed to consume more granular, flattened, and tidy data in the form of your first set. As such, the data prep functionality has a feature to unpivot column values into rows. I don't believe that reverse functionality is built into the data prep capability in the same way.
Not knowing your end use case, potentially a work around would be to:
Create a calculated field with an IF statement to return the value
when record is listed as A, otherwise return NULL.
Although you will still have the same number of records, you should be able to perform many of the calculations available with this type of data structure
Alternatively, you could perform you pivot outside of Tableau.
Related
I am trying to create the derived column based on the condition that met the value and trying to do the summation of multiple matching column values dynamically. So I am using reduce function in ADF derived column mapping data flow. But the column is not getting created even the transformation is correct.
Columns from source
Derived column logic
Derived column data preview without the new columns as per logic
I could see only the fields from source but not the derived column fields. If I use only the array($$) I could see the fields getting created.
Derived column data preview with logic only array($$)
How to get the derived column with the summation of all the fields matching the condition?
We are getting data of 48 weeks forecast and the data to be prepared on monthly basis.
eg: Input data
Output data:
JAN
----
506 -- This is for first record i.e. (94 + 105 + 109 + 103 + 95)
The problem is that the array($$) in the reduce function has only one element, so that the reduce function can not accumulate the content of the matching columns correctly.
You can solve this by using two derived columns and a data flow parameter as follows:
Create derived columns with pattern matching for each month-week you did it before, but put the reference $$ into the value field, instead of the reduce(...) function.
This will create derived columns like jan0, jan1, etc. containing the copy of the original values. For example Week 0 (1 Jan - 7 Jan) => 0jan with value 95.
This step gives you a predefined set of column names for each week, which you can use to summarize the values with specific column names.
Define Data Flow parameters for each month containing the month-week column names in a string array, like this:
ColNamesJan=['0jan' ,'1jan', etc.] ColNamesFeb=['0feb' ,'1feb', etc.] and so on.
You will use these column names in a reduce function to summarize the month-week columns to monthly column in the next step.
Create a derived column for each month, which will contain the monthly totals, and use the following reduce function to sum the weekly values:
reduce(array(byNames($ColNamesJan)), 0, #acc + toInteger(toString(#item)),#result)
Replace the parameter name accordingly.
I was able to summarize the columns dynamically with the above solution.
Please let me know if you need more information (e.g. screenshots) to reproduce the solution.
Update -- Here are the screenshots from my test environment.
Data source (data preview):
Derived columns with pattern matching (settings)
Derived columns with pattern matching (data preview)
Data flow parameter:
Derived column for monthly sum (settings):
Derived column for monthly sum (data preview):
I have 3 tables on mysqlworkbench, 1 table need to combine with 2 data ch(17million row) and cl(9million row) suppose to be one table, other table name alldoc.(121k)
Basically i need to combine ch and cl as one table, and compare with alldoc data. Technically they are suppose to be same but people made mistake that why i need to compare. 100 column
enter image description here
enter image description here
I plan to write query till i hit to 100 because i have 100 columns in all data. Just rows sizes are different.
Thank you from advance. I know complicated but i really need to compare these two data writing query
I am not sure what the technical term for what I am trying to do is.
Hoping raw data and output below will clearly define the use case.
Raw data :
This is what my raw data looks like
Output 1 :
this is what I am trying extract first
Here I am trying to get a table where the first column has the name of the guests and 2nd column has the count of times they have featured in the table as a guest.
Output 2 :
this what I am trying extract next
Here I am trying to map months against names and see how many nights one has collected in which month.
One way to achieve this would be to create a temp table with 5 columns,column 1 with Guest names,
column 2 with count of occurrence in guest 1 column in raw data table,
column 3 with count of occurrence in guest 2 column in raw data table,
column 4 with count of occurrence in guest 3 column in raw data table,
column 5 with total of previous 3 columns.
But I am trying to find a proper solution through tableau, if possible. Because this way would not help me achieve Output 2.
Plain text raw data if you'd like to work on it :
booking by,Guest 1,Guest 2,Guest 3,stay start,stay end,hotel code
Ram,Seema,Ram,,May 1 2018,May 2 2018,BBST
Karan,Ram,Seema,,May 6 2018,May 7 2018,BRRLY
Mahesh,Mahesh,Seema,Ram,June 2 2018,June 4 2018,BBST
Krishna,Krishna,,,June 2 2018,June 3 2018,BRRLY
Seema,Seema,,,June 7 2018,June 8 2018,BRRLY
I am quite new to Tableau, so have patience with me :)
I have two tables,
Table one (T1) contains all my data with the first row being Year-Week, like 2014-01, 2014-02, and so on. Quick question regarding this, how do I make Tableau consider this as a date, and not as string?
T1 contains a lot of data that looks like this:
YearWeek Spend TV Movies
2014-01 5000 42 12
2014-02 4800 41 32
2014-03 2000 24 14
....
2015-24 7000 45 65
I have another table (T2) that contains information regarding some values I want to multiply with the T1 columns, T2 looks like:
NAME TV Movies
Weight 2 5
Response 6 3
Ad 7 2
Version 1 0
I want to create a calculated field (TVNEW) that takes the values from T1 of TV, and adds Response(TV) to it, and times it with the weight(TV),
So something like this:
(T1[TV]+T2[TV[Response]])*T2[TV[Weight]]
This looks like this for the rows:
(42+6)*2
(41+6)*2
(24+6)*2
...
(45+6)*2
So the calculation should take a specific value from T2, and do the calculation for each value in T1[TV]
Thanks in advance
The easy answer to your question will be: No, not natively.
What you want to do sounds like accessing a 2 dimensional array and that's not really the intention of Tableau. Additionally you have 2 completely independent tables without a common attribute to JOIN on. Tableau is just not meant to work that way.
I cannot think of a way to dynamically extract that value (I assume your example is just that, an example; and in your case you don't just use two values in the calculation, otherwise you could create 2 parameters that you can use in your calculated fields)
When I look at your tables it looks like you could transpose and join them that they ideally look like this: (Edit: Comment says transposing is not an option)
Medium Value YearWeek Spend
Movies 12 2014-01 5,000
Movies 32 2014-02 4,000
Movies 14 2014-03 2,000
Movies 65 2015-24 7,000
TV 42 2014-01 5,000
TV 41 2014-02 4,000
TV 24 2014-03 2,000
TV 45 2015-24 7,000
and
Medium Weight Response Ad Version
TV 2 6 7 1
Movies 5 3 2 0
Depending on the systems you work with you could already put it in one CSV or table so you wouldn't have to do a JOIN in Tableau.
Now you can create the first table natively in Tableau (from Version 9.0 onwards), if you open your data source, in the Data Source Preview choose the columns TV and Movies, click on the small triangle and then on Pivot. (At this point you can also choose the YearWeek column click on the triangle and Split to create a seperate field for Year and Week. You won't be able to assign the type date to it put that shouldn't give you any disadvantages.)
For the second table I can think of two possibilities:
you have access to a tool that can transpose your table (Excel can do that see: Convert matrix to 3-column table ('reverse pivot', 'unpivot', 'flatten', 'normalize') Once you have done that you can open it in Tableau and join the two tables on Medium
You could create calculated fields depending on the medium:
Field: Weight
CASE [Medium]
WHEN 'TV' THEN 2
WHEN 'Movies' THEN 5
END
And accordingly for Response, Ad and Version
Obviously that is only reasonable if you really just need a handfull of values.
Once this is done it's only a matter of creating a calculated field with
([Value]+[Response])*[Weight]
And this will calculate all the values for your table
I want to create a monthly report, calculating the % from the previous 2 month average from the previous 12 months average. Basically I want to see which shops have dropped in sales in the previous 2 months, and hopefully only show the shops that have decreased 20% in sales.
So i believe the columns need to be like this
Shop|Products|Avg of 12 months|Avg of 2 months| %
Since i have many entries for the sales, i also need to sum the previous 12 months and then average it... as well as sum the previous 2 months and average it
I have thought of some ways to do it, but it didnt seem to work and seems all too complicated and complex.
Im hoping if there is a simpler solution to this? Do i need to use pivot table?
I'm using PostGres 9.1 on Visual Studio 10
Thanks a bunch
When something seems too complicated to resolve with a single query, I create and populate a DataTable runtime and pass it to ReportViewer.
In this case you can:
create a DataTable with Shop and Product as a PK (if you want print the report for a period of months you can also add Month as PK). The other 2 columns will be Avg12Months and Avg2Months
insert a record for each combination of Shop/Product (and eventually Month)
for each record Shop/Product calculate and save the results for Avg12Months and Avg2Months
pass your DataTable to ReportViewer
use a single Tablix to display the results (sort, grouping and other operations can be done in the Tablix)
Some passages can be combined in order to speed up the process.