rank

I have the following mysql table called "pics", with the following fields and sample data: id vehicle_id filename priority 1 45 a.jpg 4 2 45 b.jpg 1 3 56 f.jpg 4 4 67 cc.jpg 4 5 45 kt.jpg 3 6 67 gg.jpg 1 Is it possible, in a single query, to get one row for each vehicle_id, and the row be the highest priority? The result I'm looking for: array ( [0] => array( [id] => '2', [vehicle_id] => '45', [filename] => 'b.jpg', [priority] => '1' ), [1] => array( [id] => '3', [vehicle_id] => '56', [filename] => 'f.jpg', [priority] => '4' ), [2] => array( [id] => '6', [vehicle_id] => '67', [filename] => 'gg

I have a query which is something like this SELECT t.category, tc.product, tc.sub-product, count(*) as sales FROM tg t, ttc tc WHERE t.value = tc.value GROUP BY t.category, tc.product, tc.sub-product; Now in my query I want to get top 10 products for every category (top by sales ) and for every category I need top 5 sub category (top by sales) You can assume the problem statement as something like this : Get top 10 products for each category by sales and for each product get top 5 sub-products by sales . Here category can be Books Product can be Harry Porter book sub productcan be HarryPorter

I have a table that has some columns: User, Category, Value And I want to make a query that will give me a ranking, of all the users by the value, but reset for the category. Example: user1 CategoryA 10 user2 CategoryA 11 user3 CategoryA 9 user4 CategoryB 3 user1 CategoryB 11 the query would return: Rank User Category 1 user2 CategoryA 2 user1 CategoryA 3 user3 CategoryA 1 user1 CategoryB 2 user4 CategoryB Any ideas? I write the query and specify the Category, It works but then I have to write loops and its very slow. Use "Partition by" in the ranking function OVER clause SELECT Rank() over

This question already has an answer here: pandas group by year, rank by sales column, in a dataframe with duplicate data 1 answer I have a dataframe that has auction IDs and bid prices. The dataframe is sorted by auction id (ascending) and bid price (descending): Auction_ID Bid_Price 123 9 123 7 123 6 123 2 124 3 124 2 124 1 125 1 I'd like to add a column called 'Auction_Rank' that ranks auction id's by bid prices: Auction_ID Bid_Price Auction_Rank 123 9 1 123 7 2 123 6 3 123 2 4 124 3 1 124 2 2 124 1 3 125 1 1 Zero Here's one way to do it in Pandas-way You could groupby on Auction_ID and take

I have an Oracle table which has a name,value,time columns.Basically the table is for logging purposes to store what are the changes made to a particular name,what was the previous value and what time the change was made. I need to formulate a query to fetch the top n changes for a particular name,and the output should have all the names in the table. Any help/suggesstions? Edit: Name Value Time Harish Pass 1-Nov-2011 Ravi Fail 2-Nov-2011 Harish Absent 31-Oct-2011 Harish Attended 31-Aug-2011 Harish Present 31-Jul-2011 I need to select details of Harish on 1st Nov,Oct 31st,31st Aug and Ravi.

I have written a program which reads a file containing multidimensional data (most commonly 3D, but 2D could occur as well). To heighten simplicity I would like to store the data in an array of the same rank (or something pretending to be one), i.e. using a three-dimensional array for 3D data, etc.; the trouble is that the program only learns about the dimensionality on reading the data file. Currently I store all data in an array of rank one and calculate each element's index in that array from the element's coordinates (this was also suggested here ). However, I have also read about pointer