我在数据库中有一些记录,我正在将它们作为。
def get_all_records_for_sim(sim_number) do
SimLogs
|> where(number: ^sim_number)
|> order_by(asc: :datetime)
|> Repo.all
|> IO.inspect
end
因此,我得到了这种数据,
%EdgeCommander.ThreeScraper.SimLogs{__meta__: #Ecto.Schema.Metadata<:loaded, "sim_logs">,
addon: "60GB Broadband", allowance: "61,440.00Â MB",
datetime: ~N[2017-10-12 10:39:00.839670], id: 795, name: "User 6Â Sim",
number: "0860100421", volume_used: "0.00Â MB"},
%EdgeCommander.ThreeScraper.SimLogs{__meta__: #Ecto.Schema.Metadata<:loaded, "sim_logs">,
addon: "60GB Broadband", allowance: "61,440.00Â MB",
datetime: ~N[2017-10-12 11:02:20.296758], id: 815, name: "User 6Â Sim",
number: "0860100421", volume_used: "0.00Â MB"},
%EdgeCommander.ThreeScraper.SimLogs{__meta__: #Ecto.Schema.Metadata<:loaded, "sim_logs">,
addon: "60GB Broadband", allowance: "61,440.00Â MB",
datetime: ~N[2017-10-13 05:30:25.800565], id: 837, name: "User 6Â Sim",
number: "0860100421", volume_used: "0.00Â MB"},
%EdgeCommander.ThreeScraper.SimLogs{__meta__: #Ecto.Schema.Metadata<:loaded, "sim_logs">,
addon: "60GB Broadband", allowance: "61,440.00Â MB",
datetime: ~N[2017-10-16 05:24:04.536224], id: 859, name: "User 6Â Sim",
number: "0860100421", volume_used: "0.00Â MB"},
%EdgeCommander.ThreeScraper.SimLogs{__meta__: #Ecto.Schema.Metadata<:loaded, "sim_logs">,
addon: "60GB Broadband", allowance: "61,440.00Â MB",
datetime: ~N[2017-10-16 12:28:21.565377], id: 881, name: "User 6Â Sim",
number: "0860100421", volume_used: "43.09Â MB"},
%EdgeCommander.ThreeScraper.SimLogs{__meta__: #Ecto.Schema.Metadata<:loaded, "sim_logs">,
addon: "60GB Broadband", allowance: "61,440.00Â MB",
datetime: ~N[2017-10-17 05:03:49.866221], id: 903, name: "User 6Â Sim",
number: "0860100421", volume_used: "43.09Â MB"}]
它有许多重复,这并不完全相同,但如果你看
DateTime
2017-10-12
和
2017-10-16
,在上面的示例中,我正在处理该数据,以进一步创建一条图表线,如下所示:
chartjs_data =
sim_number
|> get_all_records_for_sim()
|> Enum.map(fn(one_record) ->
{current_in_number, _} = one_record |> get_volume_used() |> String.replace(",", "") |> Float.parse()
{allowance_in_number, _} = one_record |> get_allowance() |> String.replace(",", "") |> Float.parse()
%{
datetime: "#{shift_datetime(one_record.datetime)}",
percentage_used: (current_in_number / allowance_in_number * 100) |> Float.round(3)
}
end)
这就产生了一系列这样的对象
{percentage_used: 0, datetime: "2017-10-10 05:03:49"}
,我的问题是,我想合并相同的日期,例如,如果有7条
2017-10-12
,然后使它们成为一个,因为对象的另一半是基于
volume_used
(ecto结果查询),因此得到所有这7个记录的平均值
使用的volume_
{percentage_used: MEAN_OF_ALL_7_RECORDS, datetime: "2017-10-12"}
..
[{percentage_used: 0, datetime: "2017-10-10 05:03:49"}
{percentage_used: 0, datetime: "2017-10-10 17:13:38"}
{percentage_used: 0, datetime: "2017-10-11 04:39:32"}
{percentage_used: 0, datetime: "2017-10-11 12:50:42"}
{percentage_used: 0, datetime: "2017-10-12 06:31:22"}
{percentage_used: 0, datetime: "2017-10-12 09:21:08"}
{percentage_used: 0, datetime: "2017-10-12 09:34:33"}
{percentage_used: 0, datetime: "2017-10-12 10:17:00"}
{percentage_used: 0, datetime: "2017-10-12 10:39:00"}
{percentage_used: 0, datetime: "2017-10-12 11:02:20"}]
做一些类似的事情
[{percentage_used: 0, datetime: "2017-10-10"}
{percentage_used: 0, datetime: "2017-10-11"}
{percentage_used: 0, datetime: "2017-10-11"}]
任何解决方案都是值得赞赏的。谢谢