I'm an IT-guy at a school and I try to make some apps for them.
I'm struggling with this problem:
I have two datasources:
one with all the students
one with a list of educational needs
There is a relation between these two.
I made a page where I can select the educational needs for every student.
So student1 has edu need 1 and edu need 3
Student2 has edu need 2 and edu need 3
The next step is to get a table like this:
educational need student1 student 2
need 1 x
need 2 x
need 3 x x
Someone? It would be a great help!
Related
Sorry I do not know how to properly title my question. It is easier to understand with an example.
Sample data
Consider the following example.
> l_ids=as.data.frame(cbind(a=c("strong","intense","intensity"),
id=c("1","2","3"),new_id=c("","1","2")),stringsAsFactors = FALSE)
a id new_id
1 strong 1
2 intense 2 1
3 intensity 3 2
I would like to update the id of each word in a with a new_id, if it applies. Consider this as a synonym dictionary. As I iterate over new_id;
> for (i in 1:nrow(l_ids)){
+ if (nchar(l_ids$new_id[i])>0){
+ l_ids$id[i]=l_ids$new_id[i]
+ }
+ }
> l_ids
a id new_id
1 strong 1
2 intense 1 1
3 intensity 2 2
The problem is that I would like for intensity to also be given a 1. Is there a way to do this without having to iterate multiple times?
Update on background
I have a document where I have a list of synonyms. These are synonyms only relevant to the field of application of the problem. Example:
> dictionary
good bad
1 strong intense
2 intense intensity
3 light soft
I am then given a list of words, each with a given id. My task is to check if any of those words is in the bad column of dictionary and, if so, update it with the id of the word to its left. As can be seen, intensity would need two steps to become strong (a good word in the dictionary). Is there a way to do so without having to do multiple iterations? (say, a for loop)
I have a data set that I would like to manipulate, but I am having difficulty getting it into a user friendly format. I have the following
Person 1
Class Grade
Math A
Science C
English A
Person 2
Class Grade
Math D
English A
Person 3
...
I would like to change it to the following format
Name Class Grade
Person 1 Math A
Person 1 Science C
Person 1 English A
Person 2 Math D
Person 2 English A
Person 3
The issues I am having is handling it for a different number of subsequent rows for each person and also just taking a single row and making it into a column for some of the subsequent rows.
Each row of data in my df is from a study (or "Article"). Each Article has a sponsor ("Sponsor") who may have sponsored a number of the articles in my dataset.
I want to produce a summary table to show how many articles each Sponsor has sponsored in my dataset.
I hope you can help!
many thanks!!!!
Annabel
What I presume your dataframe looks like:
df=data.frame(article=1:10,sponsor=letters[round(runif(10,1,5))])
head(df)
article sponsor
1 1 a
2 2 b
3 3 e
4 4 d
5 5 e
6 6 b
How you could quickly check the number of articles per sponsor:
table(df$sponsor)
I'm not sure what you want to do exactly, but
I guess what you are looking for is:
table(df$Sponsor)
If you want the value that occurs the most frequent, you can use:
names(sort(table(df$Sponsor), decreasing=TRUE))[1]
next time, please try to provide a MWE so it is easier for us to help.
Hi now i'm studying association rules with R.
i have a question.
in transcation data,
we consider just buy or non-buy (binary data)
i want to know how to perform association rules with count data
ex)
item1 item2 item3
1 2 0 1
2 0 1 0
3 1 0 0
first customer bought two item1s!!
but in ordinary association rules, that count information is ignored
how can we consider that information?
High, The quantitative association rules (QAR) mining may be helpful.
Firstly, you should divide the value field of every item to some sets and give every set an unique label. Then, the original dataset can be transformed to a binary dataset containing those labels.
for example, for item1, if the original data has the following information:
the first person have bought 5 item1s
the second one have bought 2 item1s
the third one have bought 7 item1s.
You can divide the value field of item1 to [0, 3), [3, 6) and [6, 9), and use a1, a2 and a3 to represent them, so the item 'item1' can be replaced by 3 other items, which are a1, a2 and a3, and the original data can be replaced by the follows.
the first person have bought one a2.
the second person have bought one a1.
the third person have bought one a3.
After doing this work on every item, the original dataset can be transformed to a binary dataset.
I need to show a report of same set of data with different condition.
I need to show count of users registered by grouping region, country and userType, I have used drill down feature for showing this and is working fine. Also the reported data is the count of users registered between two dates. Along with that I have to show the total users in the system using the same drill down that is total users by region, country and usertype in a separate column along with each count (count of users between two date)
so that my result will be as follwsinitialy it will be like
Region - Country - New Reg - Total Reg - User Type 1 - UserType2
+ Region1 2 10 1 5 1 5
+ Region2 3 7 2 4 1 3
and upon expanding the region it will be like
Region - Country - New Reg - Total Reg - User Type 1 - UserType2
+ Region1 2 10 1 5 1 5
country1 1 2 1 2 - -
country2 1 8 1 8 - -
+ Region2 3 7 2 4 1 3
Is there a way I can show my report like this, I have tried with two data sets one with conditional datas and other with non conditional but it didn't work, its always bing total number of regiostered users for all the total reg columns
Unless I'm mistaken, you're trying to create an expandable table, with different grouping levels? Fortunately, this can be easily done in SSRS if you know where to look. The totals on your example don't seem to match up in the user columns, so I may have misunderstood the problem.
For starters, set up your query to produce a single dataset like this:
Region Country New Reg - Total Reg - User Type 1 - User Type 2
Region1 country1 1 2 1
Region1 country2 1 8 1
Region2 country3 2 4 1 1
Region2 country4 1 3 1
Now that you've got that, you want to set up a new table with the fields "NewReg", "TotalReg", "UserType1" and "UserType2". Then right-click the table row, and go to "Add Group > Row Group > Parent Group". Select "Country" in the Group by and click okay. Then, repeat this process and select "Region". This time however, tick the "Add group header" box. This will insert another row above the original.
Now, for each of your fields ("NewReg", "TotalReg" etc), click in the new row above and select the field again. this will automaticaly add a Sum(FieldName) value into the cell. This will add together all the individual row totals and present a new, grouped by region row when you run the report.
That should give you the table you require with the data aggregated correctly, so all you need to do is manage the show/hide the detail rows on demand.
To do this, select your detail row (the original row) and right-click "> Row visibility". Set this to "Hide". Now, select the cell that contains the "Region" and take note of its ID using Properties (for now, let's assume it's called "Region"). Click back onto your detail row and look at the properties window. At the bottom you'll see a "Visibility" setting. In there, set "InitialToggleState" to False and "ToggleItem" to the name of your region group's cell (i.e. "Region").
Now all that should be left is to do the formatting etc and tidy up.
I have solved this problem by taking all the records from DB and filtering the records to collect new reg count by using an expression as following
=Sum(IIF(Fields!RegisteredOn.Value >Parameters!FromDate.Value and Fields!RegisteredOn.Value < Parameters!EndDate.Value , 1,0))