Just iterate over the array and use another array for the groups. It should be fast enough and is probably faster than the overhead involved when using sqlite or similar. $groups = array(); foreach ($data as $item) { $key = $item[‘key_to_group’]; if (!isset($groups[$key])) { $groups[$key] = array( ‘items’ => array($item), ‘count’ => 1, ); } … Read more
Use array_chunk() to break the array up in to $cols: $chunks = array_chunk($array, ceil(count($array) / $cols)); Which would give you: array(array(‘A’, ‘B’, ‘C’, ‘D’), array(‘E’, ‘F’, ‘G’)); Then combine the values from each array where the keys match. array_unshift($chunks, null); $chunks = call_user_func_array(‘array_map’, $chunks); // array(array(‘A’, ‘E’), array(‘B’, ‘F’), array(‘C’, ‘G’), array(‘D’, NULL)) Here’s an … Read more
Let’s pretend that $array contains our data. We will go through the array and continually add the time_spent to another array keyed by url_id. $ts_by_url = array(); foreach($array as $data) { if(!array_key_exists($data[‘url_id’], $ts_by_url)) $ts_by_url[ $data[‘url_id’] ] = 0; $ts_by_url[ $data[‘url_id’] ] += $data[‘time_spent’]; } $ts_by_url should now contain: 2191238 => 41 2191606 => 240 // … Read more
We can use cut to do the grouping. We create the ‘gr’ column within the group_by, use summarise to create the number of elements in each group (n()), and order the output (arrange) based on ‘gr’. library(dplyr) DT %>% group_by(gr=cut(B, breaks= seq(0, 1, by = 0.05)) ) %>% summarise(n= n()) %>% arrange(as.numeric(gr)) As the initial … Read more
Well, the brute force answer is: subList = [theList[n:n+N] for n in range(0, len(theList), N)] where N is the group size (3 in your case): >>> theList = list(range(10)) >>> N = 3 >>> subList = [theList[n:n+N] for n in range(0, len(theList), N)] >>> subList [[0, 1, 2], [3, 4, 5], [6, 7, 8], [9]] … Read more
I based my answer on the title of your post only, as I don’t know C# and didn’t understand the given query. But in MySQL I suggest you try subselects. First get a set of primary keys of interesting columns then select data from those rows: SELECT somecolumn, anothercolumn FROM sometable WHERE id IN ( … Read more
Everything in the g element is positioned relative to the current transform matrix. To move the content, just put the transformation in the g element: <g transform=”translate(20,2.5) rotate(10)”> <rect x=”0″ y=”0″ width=”60″ height=”10″/> </g> Links: Example from the SVG 1.1 spec
You basically need a Stream that is made out of a Pair (I choose AbstractMap.SimpleEntry here) that has the left part as a Hobby and right as the Student (could be the other way around, does not matter). Later just group those based on Hobby (that is a String in your case). data.stream() .flatMap(student -> … Read more
Here’s a solution using reduce. Split the time into a date string, and then set a key for each date. If the key exists push it onto the array: Update added the array format version const data = [ {notes: ‘Game was played’, time: ‘2017-10-04T20:24:30+00:00’, sport: ‘hockey’, owner: ‘steve’, players: ’10’, game_id: 1}, { notes: … Read more
Here’s one approach. First group into lists and then process the lists into the values you actually want: import static java.util.Comparator.comparingLong; import static java.util.stream.Collectors.groupingBy; import static java.util.stream.Collectors.toMap; Map<Route,Integer> routeCounts = routes.stream() .collect(groupingBy(x -> x)) .values().stream() .collect(toMap( lst -> lst.stream().max(comparingLong(Route::getLastUpdated)).get(), List::size ));