I have a tool that every x hours creates a y set of lines that I would simply like to add to a column into a specific smartsheet. And then every x hours I would simply like to overwrite these values with the new ones. That can have a different numbers of lines.
As I read the API in order to add or update anything I need to get all the row and columne IDs of the smart sheet in question.
Isn't there a easy way to formulate a JSON with a set of data and columne name and it just auto adds the rows as needed?
Data example is:
21
23
43
23
12
23
43
23
12
34
54
23
and then it could be:
23
23
55
4
322
12
3
455
3
AUTO
I really find it hard to believe that I need to read so much information into a script to be able to add just row of data. Nothing fancy.
Looking into sticking to just using cURL or Python
Thanks
If you want to add this data as new rows, this is fairly simple. It's only if you would like to replace existing data in existing rows where you would need to specify the row id.
The python SDK allows you to specify just a single column id, like so:
row_a = smartsheet.models.Row()
row_a.cells.append({
'column_id': 642523719853956
'value': 'New Status',
'strict': False
})
For more details, please see the API documentation regarding adding rows.
Related
I have a table which looks like this
id login_id trend_type sep oct nov
1 abc#abc.com Billing 10 34 43
1 abc#abc.com Visits 20 43 56
1 abc#abc.com Revenue 30 12 12
1 pqr#pqr.com Billing 40 23 54
1 pqr#pqr.com Visits 50 21 47
1 pqr#pqr.com Revenue 60 98 12
I want to create a dashboard where I can display graphs of all these Trend Types and add a filter for the user so they can select the month for which they want to view the graphs.
I have tried this solution -
https://community.tableau.com/thread/228965
but I wasn't successful.
Tableau really likes data that is taller rather than wider. In this case, you need to do a PIVOT on the month data. A pivot will create a column for the months and another column for the values. Your data will have more rows now but fewer columns.
When you bring the data into Tableau, on the Data Source screen, highlight the three month columns and select pivot.
You can also change the name of the Pivot Field Names (to Month) and Pivot Field Values (to Amount or another appropriate name).
Click on the orange Sheet 1 on the bottom left. Next, create a calculated field to create a full date. (Tableau doesn't know what 'sep' is.)
[Pivot Field Names] + "-01-2019"
This field just creates a string that Tableau can parse (eg 'sep-01-2019'). Now tell Tableau it is a Date field by changing the field type (click on the Abc next to the Dimension name).
At this point, you can create a viz and add filters. Here is an example.
My data is like below in one column coming from a file.
Source_data---(This is column name)
CUSTOMER 15
METER 8
METERStatement 1
READING 1
METER 56
Meterstatement 14
Reading 5
Reading 6
Reading 7
CUSTOMER 38
METER 24
METERStatement 1
READING 51
CUSTOMER 77
METER 38
READING 9
I want the output data to be like below in one column
CUSTOMER 15 METER 8 METERStatement 1 READING 1
CUSTOMER 15 METER 56 Meterstatement 14 Reading 5
CUSTOMER 15 METER 56 Meterstatement 14 Reading 6
CUSTOMER 15 METER 56 Meterstatement 14 Reading 7
CUSTOMER 38 METER 24 Meterstatement 1 Reading 51
CUSTOMER 77 METER 38 'pad 100 spaces' Reading 9
I am trying to solve by reading transformer looping documentation but could not figure out an actual solution. anything helps. thank you all.
Yes this could be solved within a transformer stage.
Concatenation is done with ":".
So use a stage variable to concat the input until a new "Meter" or "Customer" row comes up.
Save the "Customer" in a second stage variable in case it does not change.
Use a condition to only output thew rows where a "Reading" exists.
Reset the concatenated string when a "Reading" has been processed.
I guess you want the padding for missing fields in general - you could do these checks in separate stage variables. You have to store the previous item inorder to kow wat is missing - and maybe even more if two consecutive items could be missing.
I have three data sets:
First, called education.dta. It contains individuals(students) over many years with their achieved educations from yr 1990-2000. Originally it is in wide format, but I can easily reshape it to long. It is presented as wide under:
id educ_90 educ_91 ... educ_00 cohort
1 0 1 1 87
2 1 1 2 75
3 0 0 2 90
Second, called graduate.dta. It contains information of when individuals(students) have finished high school. However, this data set do not contain several years only a "snapshot" of the individ when they finish high school and characteristics of the individual students such as backgroung (for ex parents occupation).
id schoolid county cohort ...
1 11 123 87
2 11 123 75
3 22 243 90
The third data set is called teachers.dta. It contains informations about all teachers at high school such as their education, if they work full or part time, gender... This data set is long.
id schoolid county year education
22 11 123 2011 1
21 11 123 2001 1
23 22 243 2015 3
Now I want to merge these three data sets.
First, I want to merge education.dta and graduate.dta on id.
Problem when education.dta is wide: I manage to merge education and graduation.dta. Then I make a loop so that all the variables in graduation.dta takes the same over all years, for eksample:
forv j=1990/2000 {
gen county j´=.
replace countyj´=county
}
However, afterwards when reshaping to long stata reposts that variable id does not uniquely identify the observations.
further, I have tried to first reshape education.dta to long, and thereafter merge either 1:m or m:1 with education as master, using graduation.dta.
However stata again reposts that id is not unique. How do I deal with this?
In next step I want to merge the above with teachers.dta on schoolid.
I want my final dataset in long format.
Thanks for your help :)
I am not certain that I have exactly the format of your data, it would be helpful if you gave us a toy dataset to look at using dataex (and could even help you figure out the problem yourself!)
But to start, because you are seeing that id is not unique, you need to figure out why there might be multiple ids in any of the datasets. Can someone in graduate.dta or education.dta appear more than once? help duplicates will probably be useful to explore the data in this way.
Because you want your dataset in long format I suggest reshaping education.dta to long first, then doing something like merge m:1 id using "graduate.dta" (once you figure out why some observations are showing up more than once) and then, finally something like merge 1:1 schoolid year using "teacher.dta" and you will have your final dataset.
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 am pretty new to Birt reporting, i can make simple charts and tables, bet when it comes to some calculation of values from data sets - i have no clue in which direction should i watch.
For example i have this simple data set:
count1 count2 max type lenght
616 3858 21 STEEL 20
723 4432 14 STEEL 40
854 5869 21 ALL 20
838 5225 14 ALL 40
And i would like to have Birt to calculate approximately this:
SUM(count2)/SUM(count1) WHERE type=ALL
so this
((5869+5225)/(854+838))
My question would be how could i get there. At this point i think i would need just the right direction how these kind of operations could be made.
Thanks in advance.
I presume you want to display this value somewhere on the report, like at the bottom of a table where this data is presented. If this is the case then add an aggregation data element to the footer of the table where the data is displayed. In the aggregation data element you will have the opportunity to specify an expression SUM(count2) and a filter condition [type=ALL]. You can then do the division in another data element.
If you want to simply compute the value you described you you could do it with SQL, i.e. SELECT SUM(count2)/SUM(count1) FROM myTable WHERE type='ALL'. You would have to provide the data to the report as a data source which could be in the form of an excel spreadsheet, *.csv, database connection, etc.
So there are a few ways to do this depending on what your requirements are.