Статистика

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Статистика, Статистика сделок
 
Подскажите пожалуйста, необходимо написать модуль статистики на основании обезличенных сделок обсчитываемый в реальном времени и отображающий данные в виде таблицы такого характера

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[/img]
размер сделки - настраиваемый множественный фильтр, в котором указываются количество контрактов, прошедших в сделках за торговую сессию, для которых будет производится обсчет
купля и продажа сумма всех сделок указанной размерности
может быть такой код уже кто то делал
если нет, то чиркните краткий пример кода если возможно
спасибо
 
Размер сделкиКупляПродажаОбщий итог
1280903189659986
2107791127622055
37346744814794
4265427995453
55897647512372
6116913322501
85646631227
95585891147
10252625835109
Общий итог5958365061124644
хотел картинку вставить, вставился код картинки, сорри
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