数据透视表 PHP/MySQL

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时间:2020-08-24 22:43:19  来源:igfitidea点击:

Pivot Tables PHP/MySQL

phpmysqlpivot-table

提问by franglais

What's the best way of handling pivot tables in php/MySQL (or something to that effect)

在 php/MySQL 中处理数据透视表的最佳方法是什么(或类似的东西)

I have a query that returns information as below

我有一个查询返回如下信息

id      eng     week        type                sourceid    userid

95304   AD      2012-01-02  Technical           744180      271332
95308   AD      2012-01-02  Non-Technical       744180      280198
96492   AD      2012-01-23  Non-Technical       1056672     283843
97998   AD      2012-01-09  Technical           1056672     284264
99608   AD      2012-01-16  Technical           1056672     283842
99680   AD      2012-01-02  Technical           1056672     284264
100781  AD      2012-01-23  Non-Technical       744180      280671

And I am wanting to build a report in PHP that counts by groups with column headers of week commencing. E.g.

我想在 PHP 中构建一个报告,该报告按组开始计数,列标题从一周开始。例如

week commencing: 2012-01-02    2012-01-09    2012-01-16    2012-01-23    2012-01-30
Total:           3             1             1             1             0
Technical:       2             1             1             0             0
Non-Technical:   1             0             0             1             0

But am not really sure where to start as the headers are dynamic depending on which month the report will be run for.

但我不确定从哪里开始,因为标题是动态的,具体取决于报告运行的月份。

I know how to pass the details of the month and retrieve all the data in PHP, but it's currently outputting in one column rather than being able to group and put it in an array.

我知道如何传递月份的详细信息并在 PHP 中检索所有数据,但它目前输出在一列中,而不是能够将其分组并将其放入数组中。

Any help appreciated!

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回答by Paul Bain

You can likely do this with a sub-query and then produce and aggregation of this data. Try something along the lines of this:

您可以使用子查询执行此操作,然后生成和聚合此数据。尝试一些类似的东西:

select week, 
    count(*) as total, 
    sum(technical) as technical, 
    sum(non_technical) as non_technical) 
from(
    select week, 
    case(type) when 'Technical' then 1 else 0 END as technical, 
    case(type) when 'Non-Technical' then 1 else 0 END as non_technical
) as data
GROUP BY week