aggregation

Suppose I've got this employee list: Dept Date Name ----- --------- --------------- 30 07-DEC-02 Raphaely 30 18-MAY-03 Khoo 40 07-JUN-02 Mavris 50 01-MAY-03 Kaufling 50 14-JUL-03 Ladwig 70 07-JUN-02 Baer 90 13-JAN-01 De Haan 90 17-JUN-03 King 100 16-AUG-02 Faviet 100 17-AUG-02 Greenberg 110 07-JUN-02 Gietz 110 07-JUN-02 Higgins I want a list aggregation by department in R (similar to Oracle PL/SQL's LISTAGG function ) that would product this last column: Dept Date Name Emp_list ----- --------- --------------- --------------------------------------------- 30 07-DEC-02 Raphaely Raphaely; Khoo 30

From Design Pattern by GoF: An object reference representing a part-of or aggregation relationship is indicated by an arrowheaded line with a diamond at the base. The arrow points to the class that is aggregated (e.g., Shape). An arrowheaded line without the diamond denotes acquaintance (e.g., a LineShape keeps a reference to a Color object, which other shapes may share). A name for the reference may appear near the base to distinguish it from other references Another useful thing to show is which classes instantiate which others. We use a dashed arrowheaded line to indicate this, since OMT

How can I get SQL Server to return the first value (any one, I don't care, it just needs to be fast) it comes across when aggregating? For example, let's say I have: ID Group 1 A 2 A 3 A 4 B 5 B and I need to get any one of the ID's for each group. I can do this as follows: Select max(id) ,group from Table group by group which returns ID Group 3 A 5 B That does the job, but it seems stupid to me to ask SQL Server to calculate the highest ID when all it really needs to do is to pick the first ID it comes across. Thanks PS - the fields are indexed, so maybe it doesn't really make a difference?

I have a very a very large 2D numpy array that contains 2x2 subsets that I need to take the average of. I am looking for a way to vectorize this operation. For example, given x: # |- col 0 -| |- col 1 -| |- col 2 -| x = np.array( [[ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0], # row 0 [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0], # row 0 [12.0, 13.0, 14.0, 15.0, 16.0, 17.0], # row 1 [18.0, 19.0, 20.0, 21.0, 22.0, 23.0]]) # row 1 I need to end up with a 2x3 array which are the averages of each 2x2 sub array, i.e.: result = np.array( [[ 3.5, 5.5, 7.5], [15.5, 17.5, 19.5]]) so element [0,0] is calculated as the average

Hello I have this question: I would like to have a vector as class member. This is perhaps my question easier for you and I apologize for that. how should I declare the vector? And is this correct? std::vector<int> *myVector; or std::vector<int> myVector ? how should I handle this vector in dealloc? How can I initialize the array into a if? Is this correct? if(myCondition) { if(!myVector) //is this correct? myVector = new std::vector<int>(); //is this correct? on this i have a error } You most certainly want to use std::vector<int> myVector . No need to initialize it, as it gets automatically

I've recently spent a good deal of time performing detailed UML designs of various SW components that I have since written. Looking back on what I have recently finished and comparing that to when I first learned UML, I see that I now almost strictly use Aggregation and Composition relationships, and have virtually abandoned "vanilla" non-directed/directed relationships. I still of course use Generalizations and Realizations, but these are distinctly different than those above and are not considered part of this question. It seems to me that Aggregation/Composition implies the same meaning of