I have a Day Strucuture Table, which has following Columns I want to display:
DoW HoD Value
1 1 1
1 2 2
1 3 2
1 4 2
1 5 2
1 6 2
1 7 2
1 8 2
1 9 2
1 10 2
1 11 4
1 12 4
1 13 4
1 14 4
1 15 4
1 16 4
1 17 4
1 18 4
1 19 4
1 20 4
1 21 1
1 22 1
1 23 1
1 24 1
Dow is The Day of Week (Monday etc.), HoD is the Hour of Day and Value is the actual value.
Now I want to Bind this Day Structure Entity Collection directly to a Control so any Changes can be bound TwoWay
Like this Format:
I think the best way to achieve this is to use a Template and/or a converter, but I just dont know how ;)
I already read this article, but Lack of a TwoWay Binding functionality makes it not useful for me :(
I Hope you can help me
Jonny
Again i solved it on my own ;)
For this problem i created a Grid with a fixed amout of rows and columns. Inside this Grid I put a Itemscontrol bound to my List of data. Inside the DataTemplate I placed a Textbox bound to the current value and bound the Grid Row and Columnproperties to the Day of the Week/Hour of Day.
Pro:
The Textbox is TwoWay Databound to a certain Object or Element.
Very Easy to implement if Row and Colum Property is numeric.
Con:
Limited to a fixed amout of Rows/Columns.
Very much Code to write in XAML (Copy and Paste)
Kinda "dirty" Code. Feels not like the best way to do it.
Im still open for other suggestions.
Related
I have a dataset on multiple outcome for individuals in two groups that were treated (or not treated) by an intervention at two time points. However, not every individual has complete data for each measure at each time point.
id
outcome
outcome_value
group
time
1
depression
10
1
1
1
depression
8
1
2
2
depression
10
2
1
2
depression
.
2
2
1
anxiety
12
1
1
1
anxiety
8
1
2
2
anxiety
12
2
1
2
anxiety
6
2
2
How do I exclude IDs that do not have an outcome in both periods? I only want to see how outcomes changed between groups over time for observations have data in all periods. I am using the mixed command in Stata to conduct this analysis.
First drop the missing rows
keep if !missing(outcome_value)
Then, keep the ID/outcome combinations that have _N==2
bysort id outcome: keep if _N==2
Output:
id outcome outco~ue group time ct
1 anxiety 8 1 2 2
1 anxiety 12 1 1 2
1 depression 10 1 1 2
1 depression 8 1 2 2
2 anxiety 6 2 2 2
2 anxiety 12 2 1 2
As #NickCox has pointed out in the comments, while we cannot directly combine these two, there is still a one-line approach:
bysort id outcome (time) : keep if !missing(outcome_value[1], outcome_value[2])
Of note, we cannot do this:
bysort id outcome : keep if !missing(outcome_value) & _N==2
because _N is not reduced by group until after the rows with missing outcome have been removed.
I have the following scenario. My datasource looks like this:
Order Item Type Value
1 1 A 14
1 1 B 10
1 1 C 12
1 2 A 12
2 1 C 19
2 1 D 15
2 2 B 11
Now I apply a few steps in the query editor, inter alia, a Group By (by Order and Item), so that my finished table looks like this:
Order Item Value
1 1 36
1 2 12
2 1 34
2 2 11
I am looking now for a possiblity to filter my datasource table before the steps are getting applied (Filter datasource > query steps getting applied > chart changes).
In my example here I would filter the datasource by Type <> B:
Order Item Type Value
1 1 A 14
1 1 C 12
1 2 A 12
2 1 C 19
2 1 D 15
And the final table (chart datasource) would be looking like this:
Order Item Value
1 1 26
1 2 12
2 1 34
I tried it with parameters. But the problem is I need the filter in power bi online, so that the enduser can apply this filter.
Thanks in advance for any ideas !!
Don't apply the grouping in your query. Leave the source table as it is, create a measure which sums Value, and filter Type.
using order and item in a table visual(don't summarise) and for value using SUM of values, which can later be filtered by type should give the desired result.
I've spent quite a lot of time on Stack Overflow looking for answers to other questions, but I'm really stuck on this one, so I'm finally asking a question!
I have a dataset of fish in SAS, with:
a unique ID for each angler
three different variables with number of fish released in each category by that angler: over legal size, under legal size, and released dead
a sequential number (fishno) based on the number of rows for each ID; 1 to the last row of that ID.
Variable to be created: Disposition--could be either character variable with "legal" "under" "dead" options or even numeric values of 1-3.
It was originally set up with one row per unique ID, but I set it so that now there is one row per fish discarded (i.e. if there were 3 legal size and 2 undersize fish, I now have 5 rows).
I need to assign, by unique ID, whether each row/fish was released legal, undersize or dead. In the previous example, for a unique ID, I'd need 3 rows assigned to a Disposition of "legal" and 2 rows assigned to a Disposition of "under".
I've tried first.var statements along with if-then-do statements; played around with macros; nothing worked quite right and I'm pretty stuck here. Is there some sort of random assignment I should try? Is there a much easier way that I'm missing?
Example of the data below...
THANK YOU!!
Data in Excel format
Assuming you already have the FISHNO variable, there needs to be some method for assigning each fish as legal, dead, or undersize. The following code will assign the disposition in the that order:
data have;
input ID LEGAL DEAD UNDERSIZE FISHNO;
datalines;
15 1 0 1 1
15 1 0 1 2
29 2 0 2 1
29 2 0 2 2
29 2 0 2 3
29 2 0 2 4
38 1 0 1 1
38 1 0 1 2
53 1 0 1 1
53 1 0 1 2
55 1 0 1 1
55 1 0 1 2
;
run;
data want;
set have;
if legal>0 and legal>=fishno then disposition = 'legal';
else if dead>0 and legal+dead>=fishno then disposition = 'dead';
else if undersize>0 and legal+dead+undersize>=fishno then disposition = 'under';
run;
I have a set of individuals with characteristics. Each individual belongs to one or more group. I need to merge individuals to group characteristics, by firstly duplicating each row of individual data set as many times as is given by n_groups.
The data looks like
id age n_groups
1 50 2
2 46 1
3 51 3
4 44 2
I need to have
id age n_groups group_index
1 50 2 1
1 50 2 2
2 46 1 1
3 51 3 1
3 51 3 2
3 51 3 3
4 44 2 1
4 44 2 1
It seems like a very easy task, and I need some variation of expand with variable number of duplicates. Any ideas if there is a simple command for this?
Thanks!
Appears the solution is very standard. The expand command indeed allows for expanding based on variable: expand n_groups solved the question.
I have a trouble using L1 command in Stata 14 to create lag variables.
The resulted Lag variable is 100% missing values!
gen d = L1.equity
tnanks in advance
There is hardly enough information given in the question to know for certain, but as #Dimitriy V. Masterov suggested by questioning how your data is tsset, you likely have an issue there.
As a quick example, imagine a panel with two countries, country 1 and country 3, with gdp by country measured over five years:
clear
input float(id year gdp)
1 1 5
1 2 2
1 3 7
1 4 9
1 5 6
3 1 3
3 2 4
3 3 5
3 4 3
3 5 4
end
Now, if you improperly tsset this data, you can easily generate the missing values you describe:
tsset year id
gen lag_gdp = L1.gdp
And notice now how you have 10 missing values generated. In this example, it happens because the panel and time variables are out of order and the (incorrectly specified) time variable has gaps (period 1 and period 3, but no period 2).
Something else I have witnessed is someone trying to tsset by their time variable and their analysis variable, which is also incorrect:
clear
input float(year gdp)
1 5
2 3
3 2
4 4
5 7
end
tsset year gdp
gen d = L1.gdp
I suspect you are having a similar issue.
Without knowing what your data looks like or how it is tsset there is no possible way to diagnose this, but it is very likely an issue with how the data is tsset.