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
Related
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.
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'm working in Pentaho 4.4.1-GA (Kettle / PDI). The database is Postgres.
I need to be able to insert multiple records into a fact table based on the fields that come from a single record. The single record contains fields:
productcode1, price1
productcode2, price2
productcode3, price3
...
productcode10,price10
So if there was a value for each of the 10 productcode / prices then I'd need to insert a total of 10 records into the fact table. If there were values for 4 of the combinations, then I'd need to insert 4 records into the fact table, etcetera. All field values for the fact records would be identical except for the PK (generated by sequence), product codes, and prices.
I figure that I need some type of looping construct which would let me check whether or not a value was present for each productx field, and if so, do an insert/update step on the fact table with the desired field values. I'm just not sure how to do this in Pentaho.
Any ideas? All suggestions are welcome :)
Thank You,
Rakesh
Could you give a sample input and output for your scenario??
From your example data I can infer that if there are 10 different product codes and only 4 product prices you want to have 4 records inserted into your table. Is that so?
Well for a start you can add a constant value of 1 to those records by filtering for NOT NULL and then use an Group BY Step to count the number of 1's. This would give you the count. BTW it would be helpful if you could provide more details on what columns you would be loading as there are ways to make a PDI transformation execute multiple times
I'm new to KDB ( sorry if this question is dumb). I'm creating the following table
q)dsPricing:([id:`int$(); date:`date$()] open:`float$();close:`float$();high:`float$();low:`float$();volume:`int$())
q)dsPricing:([id:`int$(); date:`date$()] open:`float$();close:`float$();high:`float$();low:`float$();volume:`int$())
q)`dsPricing insert(123;2003.03.23;1.0;3.0;4.0;2.0;1000)
q)`dsPricing insert(123;2003.03.24;1.0;3.0;4.0;2.0;2000)
q)save `:dsPricing
Let's say after saving I exit. After starting q, I like to add another pricing item in there without loading the entire file because the file could be large
q)`dsPricing insert(123;2003.03.25;1.0;3.0;4.0;2.0;1500)
I've been looking at .Q.dpft but I can't really figure it out. Also this table/file doesn't need to be partitioned.
Thanks
You can upsert with the file handle of a table to append on disk, your example would look like this:
`:dsPricing upsert(123;2003.03.25;1.0;3.0;4.0;2.0;1500)
You can load the table into your q session using get, load or \l
q)get `:dsPricing
id date | open close high low volume
--------------| --------------------------
123 2003.03.23| 1 3 4 2 1000
123 2003.03.24| 1 3 4 2 2000
123 2003.03.25| 1 3 4 2 1500
.Q.dpft will save a table splayed(one file for each column in the table and a .d file containing column names) with a parted attribute(p#) on one of the symbol columns. Any symbol columns will also be enumerated by .Q.en.
I have the following problem with MS Access:
Suppose I have a list of companies with monthly performance values. I can view the performance of a single company in a chart by hooking the chart into a query with a Month column and a Performance column.
Now suppose I want to display a chart for N companies. I could theoretically do this if I were to generate a query with a Month column and N Performance columns (one for each company). Is there any way to create a query with a variable column count like this? I have a SQL backend that I can use if necessary, and I'm fine with putting together any VBA code necessary to support it. The only impediment I'm seeing is that I'm stuck using MS Access, which I am not very familiar with.
So here are my main questions:
Is this even possible?
How would I go about tackling this issue? I'm trying to minimize research time, so it would be great if I could just get pointed in the right direction.
Thanks!
With this table:
company pmonth performance
1 1 10
2 1 8
3 1 15
1 2 15
2 2 5
3 2 25
1 3 5
2 3 4
3 3 20
I create this query:
SELECT p.company, p.pmonth, p.performance
FROM MonthlyPerformance AS p;
Then change the query to PivotChart View and drag company field to "Drop Series Fields Here", drag pmonth to "Drop Category Fields Here", and drag performance field to "Drop Data Fields Here".
If you prefer, you can create a form using the same query SQL as its data source, then set the form's Default View to PivotChart, and set up the chart the same way as I did for PivotChart view on the query.
If that's not what you want, give us some more information about the type of chart you want and the context in which you will display it.