4
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I want to create a Query to a Dataset that will select a subset of three columns, modify the date column in this subset (to month), group by month and a second column (location), take the group means of the third column (temperature) and create a single DateListPlot displaying the multiple lines for the date/location temperature vectors.

I am able to do this in multiple steps; but creating one query which combines a "descending" subquery and an "ascending" summary query eludes me. A very reduced Dataset is included below along with my current code attempt. The first query returns a Dataset without named columns and so the next Query uses position "values".

ds1 = Query[
    All, {Replace[#date, #date -> DateObject[#date, "Month"]] &, 
     "temperature", "temp_value"}][energyDS];
ds2b = Query[GroupBy[#[[2]] &], GroupBy[#[[1]] &], Mean][ds1];
DateListPlot[ds2b[#, All, 3] & /@ Keys[ds2b], 
 PlotLegends -> Normal[Keys[ds2b]]]

I would appreciate assistance with the code and, if possible some insight into combining subqueries into queries -- beyond that provided by the sparse examples in Help documentation. I should also add that this code runs slow as molasses on the actual dataset of 1.6 million records.

energyDS = 
  Dataset[{<|"date" -> "2016-01-11 17:00:00", "Appliances" -> 60, 
     "lights" -> 30, "T_out" -> 6.6`, "Press_mm_hg" -> 733.5`, 
     "RH_out" -> 92, "Windspeed" -> 7, "Visibility" -> 63, 
     "Tdewpoint" -> 5.3`, "rv1" -> 13.275433157104999`, 
     "rv2" -> 13.275433157104999`, "temperature" -> "kitchen", 
     "temp_value" -> 19.89`, "humidity" -> "kitchen", 
     "hum_value" -> 47.5966666666667`|>, <|"date" -> 
      "2016-01-15 13:30:00", "Appliances" -> 190, "lights" -> 0, 
     "T_out" -> 4.05`, "Press_mm_hg" -> 755, "RH_out" -> 86.5`, 
     "Windspeed" -> 8, "Visibility" -> 45, "Tdewpoint" -> 2, 
     "rv1" -> 19.12523116916418`, "rv2" -> 19.12523116916418`, 
     "temperature" -> "laundry", "temp_value" -> 20.5`, 
     "humidity" -> "living", 
     "hum_value" -> 38.015`|>, <|"date" -> "2016-01-19 10:10:00", 
     "Appliances" -> 50, "lights" -> 0, "T_out" -> -3.48333333333333`,
      "Press_mm_hg" -> 757.316666666667`, 
     "RH_out" -> 89.3333333333333`, "Windspeed" -> 1, 
     "Visibility" -> 62.3333333333333`, "Tdewpoint" -> -5.05`, 
     "rv1" -> 34.51393429422751`, "rv2" -> 34.51393429422751`, 
     "temperature" -> "kitchen", "temp_value" -> 18.6`, 
     "humidity" -> "laundry", 
     "hum_value" -> 39.79`|>, <|"date" -> "2016-01-23 06:40:00", 
     "Appliances" -> 40, "lights" -> 0, "T_out" -> 5.9`, 
     "Press_mm_hg" -> 767.133333333333`, 
     "RH_out" -> 99.3333333333333`, "Windspeed" -> 4, 
     "Visibility" -> 29, "Tdewpoint" -> 5.76666666666667`, 
     "rv1" -> 14.32367623783648`, "rv2" -> 14.32367623783648`, 
     "temperature" -> "laundry", "temp_value" -> 17.6`, 
     "humidity" -> "office", 
     "hum_value" -> 42.59`|>, <|"date" -> "2016-01-27 03:20:00", 
     "Appliances" -> 20, "lights" -> 0, "T_out" -> 10.1`, 
     "Press_mm_hg" -> 758.4`, "RH_out" -> 80.3333333333333`, 
     "Windspeed" -> 10, "Visibility" -> 40, "Tdewpoint" -> 6.8`, 
     "rv1" -> 37.99445059848949`, "rv2" -> 37.99445059848949`, 
     "temperature" -> "kitchen", "temp_value" -> 20.6`, 
     "humidity" -> "bathroom", 
     "hum_value" -> 58.5733333333333`|>, <|"date" -> 
      "2016-01-30 23:50:00", "Appliances" -> 40, "lights" -> 0, 
     "T_out" -> 4.41666666666667`, "Press_mm_hg" -> 754.7`, 
     "RH_out" -> 87.1666666666667`, "Windspeed" -> 5, 
     "Visibility" -> 28.8333333333333`, 
     "Tdewpoint" -> 2.43333333333333`, "rv1" -> 6.051994732115418`, 
     "rv2" -> 6.051994732115418`, "temperature" -> "laundry", 
     "temp_value" -> 20.79`, "humidity" -> "north", 
     "hum_value" -> 99.3`|>, <|"date" -> "2016-02-03 20:30:00", 
     "Appliances" -> 130, "lights" -> 20, "T_out" -> 5, 
     "Press_mm_hg" -> 764.15`, "RH_out" -> 82, "Windspeed" -> 3, 
     "Visibility" -> 40, "Tdewpoint" -> 2.1`, 
     "rv1" -> 16.25068896682933`, "rv2" -> 16.25068896682933`, 
     "temperature" -> "kitchen", "temp_value" -> 22.6`, 
     "humidity" -> "ironing", 
     "hum_value" -> 35.3327777777778`|>, <|"date" -> 
      "2016-02-07 17:00:00", "Appliances" -> 100, "lights" -> 20, 
     "T_out" -> 8.2`, "Press_mm_hg" -> 747.3`, "RH_out" -> 66, 
     "Windspeed" -> 8, "Visibility" -> 40, "Tdewpoint" -> 2.2`, 
     "rv1" -> 5.914690508507192`, "rv2" -> 5.914690508507192`, 
     "temperature" -> "laundry", "temp_value" -> 21.5`, 
     "humidity" -> "teenager", 
     "hum_value" -> 46.7355555555556`|>, <|"date" -> 
      "2016-02-11 13:40:00", "Appliances" -> 80, "lights" -> 20, 
     "T_out" -> 5.06666666666667`, "Press_mm_hg" -> 749, 
     "RH_out" -> 85.6666666666667`, "Windspeed" -> 5, 
     "Visibility" -> 35, "Tdewpoint" -> 2.83333333333333`, 
     "rv1" -> 10.903250332921743`, "rv2" -> 10.903250332921743`, 
     "temperature" -> "kitchen", "temp_value" -> 20.5`, 
     "humidity" -> "parents", 
     "hum_value" -> 41.6633333333333`|>, <|"date" -> 
      "2016-02-15 10:20:00", "Appliances" -> 740, "lights" -> 20, 
     "T_out" -> 3.06666666666667`, "Press_mm_hg" -> 757.666666666667`,
      "RH_out" -> 74.6666666666667`, "Windspeed" -> 6, 
     "Visibility" -> 40, "Tdewpoint" -> -1.06666666666667`, 
     "rv1" -> 1.7749762744642794`, "rv2" -> 1.7749762744642794`, 
     "temperature" -> "kitchen", "temp_value" -> 19.5`, 
     "humidity" -> "kitchen", 
     "hum_value" -> 42.1333333333333`|>, <|"date" -> 
      "2016-02-19 06:50:00", "Appliances" -> 50, "lights" -> 0, 
     "T_out" -> -0.9`, "Press_mm_hg" -> 759.633333333333`, 
     "RH_out" -> 99, "Windspeed" -> 2, 
     "Visibility" -> 45.6666666666667`, 
     "Tdewpoint" -> -1.08333333333333`, "rv1" -> 17.355701071210206`, 
     "rv2" -> 17.355701071210206`, "temperature" -> "laundry", 
     "temp_value" -> 20.1`, "humidity" -> "living", 
     "hum_value" -> 37.5675`|>, <|"date" -> "2016-02-23 03:30:00", 
     "Appliances" -> 60, "lights" -> 0, "T_out" -> 3.75`, 
     "Press_mm_hg" -> 753.8`, "RH_out" -> 95.5`, "Windspeed" -> 1.5`, 
     "Visibility" -> 26.5`, "Tdewpoint" -> 3.05`, 
     "rv1" -> 40.263680985663086`, "rv2" -> 40.263680985663086`, 
     "temperature" -> "kitchen", "temp_value" -> 21, 
     "humidity" -> "laundry", 
     "hum_value" -> 42.59`|>, <|"date" -> "2016-02-27 00:00:00", 
     "Appliances" -> 50, "lights" -> 0, "T_out" -> 1.7`, 
     "Press_mm_hg" -> 751, "RH_out" -> 85, "Windspeed" -> 2, 
     "Visibility" -> 20, "Tdewpoint" -> -0.6`, 
     "rv1" -> 22.86010766401887`, "rv2" -> 22.86010766401887`, 
     "temperature" -> "laundry", "temp_value" -> 20.5`, 
     "humidity" -> "office", 
     "hum_value" -> 35.2`|>, <|"date" -> "2016-03-01 20:40:00", 
     "Appliances" -> 80, "lights" -> 20, "T_out" -> 7, 
     "Press_mm_hg" -> 751.766666666667`, "RH_out" -> 96, 
     "Windspeed" -> 8, "Visibility" -> 55.6666666666667`, 
     "Tdewpoint" -> 6.4`, "rv1" -> 27.875589963514358`, 
     "rv2" -> 27.875589963514358`, "temperature" -> "kitchen", 
     "temp_value" -> 21.5`, "humidity" -> "bathroom", 
     "hum_value" -> 44.6633333333333`|>, <|"date" -> 
      "2016-03-05 17:10:00", "Appliances" -> 70, "lights" -> 0, 
     "T_out" -> 5.76666666666667`, "Press_mm_hg" -> 743.05`, 
     "RH_out" -> 67.3333333333333`, "Windspeed" -> 2.16666666666667`, 
     "Visibility" -> 40, "Tdewpoint" -> 0.0666666666666667`, 
     "rv1" -> 20.385111880023032`, "rv2" -> 20.385111880023032`, 
     "temperature" -> "laundry", "temp_value" -> 21.86`, 
     "humidity" -> "north", 
     "hum_value" -> 51.5666666666667`|>, <|"date" -> 
      "2016-03-09 13:50:00", "Appliances" -> 80, "lights" -> 10, 
     "T_out" -> 7.16666666666667`, "Press_mm_hg" -> 744.133333333333`,
      "RH_out" -> 64.3333333333333`, "Windspeed" -> 9.83333333333333`,
      "Visibility" -> 40, "Tdewpoint" -> 0.75`, 
     "rv1" -> 37.6603338168934`, "rv2" -> 37.6603338168934`, 
     "temperature" -> "kitchen", "temp_value" -> 19.4633333333333`, 
     "humidity" -> "ironing", 
     "hum_value" -> 31.2`|>, <|"date" -> "2016-03-13 10:20:00", 
     "Appliances" -> 100, "lights" -> 0, "T_out" -> 3.13333333333333`,
      "Press_mm_hg" -> 769.7`, "RH_out" -> 76.6666666666667`, 
     "Windspeed" -> 6.33333333333333`, 
     "Visibility" -> 49.6666666666667`, 
     "Tdewpoint" -> -0.666666666666667`, "rv1" -> 41.63221240742132`, 
     "rv2" -> 41.63221240742132`, "temperature" -> "laundry", 
     "temp_value" -> 20, "humidity" -> "teenager", 
     "hum_value" -> 38.13`|>, <|"date" -> "2016-03-17 07:00:00", 
     "Appliances" -> 50, "lights" -> 0, "T_out" -> -0.4`, 
     "Press_mm_hg" -> 766.3`, "RH_out" -> 87, "Windspeed" -> 1, 
     "Visibility" -> 63, "Tdewpoint" -> -2.4`, 
     "rv1" -> 3.332387760747224`, "rv2" -> 3.332387760747224`, 
     "temperature" -> "kitchen", "temp_value" -> 20.6666666666667`, 
     "humidity" -> "parents", 
     "hum_value" -> 39.3266666666667`|>, <|"date" -> 
      "2016-03-21 03:40:00", "Appliances" -> 50, "lights" -> 0, 
     "T_out" -> 4.7`, "Press_mm_hg" -> 761.1`, 
     "RH_out" -> 95.3333333333333`, "Windspeed" -> 1, 
     "Visibility" -> 49.3333333333333`, 
     "Tdewpoint" -> 4.03333333333333`, "rv1" -> 3.2356246723793447`, 
     "rv2" -> 3.2356246723793447`, "temperature" -> "kitchen", 
     "temp_value" -> 21.7`, "humidity" -> "kitchen", 
     "hum_value" -> 37.4`|>, <|"date" -> "2016-03-25 00:10:00", 
     "Appliances" -> 60, "lights" -> 0, "T_out" -> 6.3`, 
     "Press_mm_hg" -> 755.666666666667`, "RH_out" -> 96, 
     "Windspeed" -> 3, "Visibility" -> 43.6666666666667`, 
     "Tdewpoint" -> 5.7`, "rv1" -> 28.789900441188365`, 
     "rv2" -> 28.789900441188365`, "temperature" -> "laundry", 
     "temp_value" -> 22, "humidity" -> "living", 
     "hum_value" -> 41.9333333333333`|>, <|"date" -> 
      "2016-03-28 20:50:00", "Appliances" -> 90, "lights" -> 0, 
     "T_out" -> 8.16666666666667`, "Press_mm_hg" -> 744.333333333333`,
      "RH_out" -> 77.8333333333333`, "Windspeed" -> 3.33333333333333`,
      "Visibility" -> 40, "Tdewpoint" -> 4.51666666666667`, 
     "rv1" -> 5.767669249325991`, "rv2" -> 5.767669249325991`, 
     "temperature" -> "kitchen", "temp_value" -> 23.39`, 
     "humidity" -> "laundry", 
     "hum_value" -> 38.5`|>, <|"date" -> "2016-04-01 17:20:00", 
     "Appliances" -> 50, "lights" -> 0, "T_out" -> 10.4333333333333`, 
     "Press_mm_hg" -> 759.933333333333`, 
     "RH_out" -> 59.6666666666667`, "Windspeed" -> 2.66666666666667`, 
     "Visibility" -> 40, "Tdewpoint" -> 2.86666666666667`, 
     "rv1" -> 32.87173660937697`, "rv2" -> 32.87173660937697`, 
     "temperature" -> "laundry", "temp_value" -> 22.39`, 
     "humidity" -> "office", 
     "hum_value" -> 36.79`|>, <|"date" -> "2016-04-05 14:00:00", 
     "Appliances" -> 270, "lights" -> 10, "T_out" -> 11.6`, 
     "Press_mm_hg" -> 751, "RH_out" -> 73, "Windspeed" -> 3, 
     "Visibility" -> 29, "Tdewpoint" -> 6.9`, 
     "rv1" -> 13.358150830026716`, "rv2" -> 13.358150830026716`, 
     "temperature" -> "kitchen", "temp_value" -> 22.1333333333333`, 
     "humidity" -> "bathroom", 
     "hum_value" -> 45.3`|>, <|"date" -> "2016-04-09 10:30:00", 
     "Appliances" -> 390, "lights" -> 0, "T_out" -> 9.8`, 
     "Press_mm_hg" -> 750.35`, "RH_out" -> 69, "Windspeed" -> 4.5`, 
     "Visibility" -> 32.5`, "Tdewpoint" -> 4.35`, 
     "rv1" -> 42.310866445768625`, "rv2" -> 42.310866445768625`, 
     "temperature" -> "laundry", "temp_value" -> 22.1`, 
     "humidity" -> "north", 
     "hum_value" -> 18.1666666666667`|>, <|"date" -> 
      "2016-04-13 07:10:00", "Appliances" -> 60, "lights" -> 0, 
     "T_out" -> 5.08333333333333`, "Press_mm_hg" -> 750.266666666667`,
      "RH_out" -> 93.5`, "Windspeed" -> 1.33333333333333`, 
     "Visibility" -> 40, "Tdewpoint" -> 4.15`, 
     "rv1" -> 4.957313183695078`, "rv2" -> 4.957313183695078`, 
     "temperature" -> "kitchen", "temp_value" -> 22, 
     "humidity" -> "ironing", 
     "hum_value" -> 33.9`|>, <|"date" -> "2016-04-17 03:40:00", 
     "Appliances" -> 60, "lights" -> 0, "T_out" -> 1.46666666666667`, 
     "Press_mm_hg" -> 751.566666666667`, "RH_out" -> 97, 
     "Windspeed" -> 1, "Visibility" -> 63, 
     "Tdewpoint" -> 1.03333333333333`, "rv1" -> 39.543289749417454`, 
     "rv2" -> 39.543289749417454`, "temperature" -> "laundry", 
     "temp_value" -> 23.7`, "humidity" -> "teenager", 
     "hum_value" -> 40.53`|>, <|"date" -> "2016-04-21 00:20:00", 
     "Appliances" -> 60, "lights" -> 0, "T_out" -> 7.96666666666667`, 
     "Press_mm_hg" -> 764.5`, "RH_out" -> 65, "Windspeed" -> 4, 
     "Visibility" -> 40, "Tdewpoint" -> 1.7`, 
     "rv1" -> 36.77555826725438`, "rv2" -> 36.77555826725438`, 
     "temperature" -> "kitchen", "temp_value" -> 22.1`, 
     "humidity" -> "parents", 
     "hum_value" -> 37.73`|>, <|"date" -> "2016-04-24 21:00:00", 
     "Appliances" -> 90, "lights" -> 0, "T_out" -> 4.1`, 
     "Press_mm_hg" -> 758, "RH_out" -> 82, "Windspeed" -> 3, 
     "Visibility" -> 40, "Tdewpoint" -> 1.2`, 
     "rv1" -> 10.66819637781009`, "rv2" -> 10.66819637781009`, 
     "temperature" -> "kitchen", "temp_value" -> 21.9266666666667`, 
     "humidity" -> "kitchen", 
     "hum_value" -> 35.5`|>, <|"date" -> "2016-04-28 17:30:00", 
     "Appliances" -> 230, "lights" -> 0, "T_out" -> 9.85`, 
     "Press_mm_hg" -> 756.1`, "RH_out" -> 50.5`, "Windspeed" -> 3.5`, 
     "Visibility" -> 40, "Tdewpoint" -> 0, "rv1" -> 29.4617329724133`,
      "rv2" -> 29.4617329724133`, "temperature" -> "laundry", 
     "temp_value" -> 21.5`, "humidity" -> "living", 
     "hum_value" -> 31.39`|>, <|"date" -> "2016-05-02 14:10:00", 
     "Appliances" -> 80, "lights" -> 0, "T_out" -> 16.1833333333333`, 
     "Press_mm_hg" -> 762.516666666667`, "RH_out" -> 34.5`, 
     "Windspeed" -> 3, "Visibility" -> 29.1666666666667`, 
     "Tdewpoint" -> 0.483333333333333`, "rv1" -> 40.099792391993105`, 
     "rv2" -> 40.099792391993105`, "temperature" -> "kitchen", 
     "temp_value" -> 22.4633333333333`, "humidity" -> "laundry", 
     "hum_value" -> 35.4`|>, <|"date" -> "2016-05-06 10:40:00", 
     "Appliances" -> 70, "lights" -> 0, "T_out" -> 17.4666666666667`, 
     "Press_mm_hg" -> 754.4`, "RH_out" -> 51.6666666666667`, 
     "Windspeed" -> 3, "Visibility" -> 40, 
     "Tdewpoint" -> 7.33333333333333`, "rv1" -> 2.572263346519321`, 
     "rv2" -> 2.572263346519321`, "temperature" -> "laundry", 
     "temp_value" -> 23.7`, "humidity" -> "office", 
     "hum_value" -> 35.79`|>, <|"date" -> "2016-05-10 07:20:00", 
     "Appliances" -> 50, "lights" -> 0, "T_out" -> 15.2666666666667`, 
     "Press_mm_hg" -> 751, "RH_out" -> 92.3333333333333`, 
     "Windspeed" -> 3, "Visibility" -> 40, 
     "Tdewpoint" -> 13.9666666666667`, "rv1" -> 5.569597787689418`, 
     "rv2" -> 5.569597787689418`, "temperature" -> "kitchen", 
     "temp_value" -> 24.89`, "humidity" -> "bathroom", 
     "hum_value" -> 57.2633333333333`|>, <|"date" -> 
      "2016-05-14 03:50:00", "Appliances" -> 60, "lights" -> 0, 
     "T_out" -> 8.85`, "Press_mm_hg" -> 754.25`, 
     "RH_out" -> 78.1666666666667`, "Windspeed" -> 3.66666666666667`, 
     "Visibility" -> 24.6666666666667`, 
     "Tdewpoint" -> 5.16666666666667`, "rv1" -> 37.84072716953233`, 
     "rv2" -> 37.84072716953233`, "temperature" -> "laundry", 
     "temp_value" -> 24.79`, "humidity" -> "north", 
     "hum_value" -> 21.3633333333333`|>, <|"date" -> 
      "2016-05-18 00:30:00", "Appliances" -> 50, "lights" -> 0, 
     "T_out" -> 12.4`, "Press_mm_hg" -> 756.05`, "RH_out" -> 76, 
     "Windspeed" -> 2, "Visibility" -> 33, "Tdewpoint" -> 8.2`, 
     "rv1" -> 3.8205624907277524`, "rv2" -> 3.8205624907277524`, 
     "temperature" -> "kitchen", "temp_value" -> 23.5`, 
     "humidity" -> "ironing", 
     "hum_value" -> 40.7`|>, <|"date" -> "2016-05-21 21:00:00", 
     "Appliances" -> 100, "lights" -> 10, "T_out" -> 18.8`, 
     "Press_mm_hg" -> 753.1`, "RH_out" -> 76, "Windspeed" -> 2, 
     "Visibility" -> 40, "Tdewpoint" -> 14.4`, 
     "rv1" -> 35.10843818075955`, "rv2" -> 35.10843818075955`, 
     "temperature" -> "laundry", "temp_value" -> 26.612`, 
     "humidity" -> "teenager", 
     "hum_value" -> 49.96`|>, <|"date" -> "2016-05-25 17:40:00", 
     "Appliances" -> 160, "lights" -> 0, "T_out" -> 16.3333333333333`,
      "Press_mm_hg" -> 756.133333333333`, 
     "RH_out" -> 54.3333333333333`, "Windspeed" -> 1.66666666666667`, 
     "Visibility" -> 35.6666666666667`, 
     "Tdewpoint" -> 7.06666666666667`, "rv1" -> 16.66860954137519`, 
     "rv2" -> 16.66860954137519`, "temperature" -> "kitchen", 
     "temp_value" -> 24.5`, "humidity" -> "parents", 
     "hum_value" -> 37.3333333333333`|>}];
$\endgroup$

2 Answers 2

2
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I try to give more detailed answer. From the comments I understood what the main problem is and will try to give the optimal code for handling string dates here.

Special function for getting month as DateObject with memoization

toMonthMem[s_] := toMonthMem[s] = 
    DateObject[Map[ToExpression] @ StringSplit[s, "-"]]; 

toMonth[s_] := 
    toMonthMem[StringTake[s, 7]]; 

And try to apply this function to the dataset

AbsoluteTiming[Query[All, {"date" -> toMonth}] @ energyDS;]

(*Out[..] := {0.0026185, Null}*)

For the perfomance testing we can create dataset with a large number of random dates

randDateString := 
    DateString[
        RandomInteger[Round[AbsoluteTime[]]], 
        {"Year", "-", "Month", "-", "Day", " ", "Hour", ":", "Minute", ":", "Second"} 
    ]

datasetDatesTest = 
    Table[Prepend[Rest @ First @ Normal @ energyDS, "date" -> randDateString], {16000}]; 

AbsoluteTiming[Query[All, {"date" -> toMonth}] @ datasetDatesTest;]

(* Out[..] := {0.0838846, Null}*)
```
$\endgroup$
1
  • 1
    $\begingroup$ This works well. Took 6.335 seconds to "mutate" the date column in a Dataset of 1.6 million records. I have used memorization in recursive functions but not as you have employed it here. This and your StringCase replacement syntax (along with StringRiffle) are new examples for me. Please keep contributing to Mathematica StackExchange! $\endgroup$ Sep 10, 2020 at 14:28
1
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This does what I want (using Composition).

dsQuery = 
  Query[Query[GroupBy[#[[2]] &], GroupBy[#[[1]] &], Mean] @* 
     Query[All, {Replace[#date, #date -> 
          DateObject[#date, "Month"]] &, "temperature", 
       "temp_value"}]][energyDS];

Or using Right Composition

Query[Query[
    All, {Replace[#date, #date -> DateObject[#date, "Month"]] &, 
     "temperature", "temp_value"}] /* 
   Query[GroupBy[#[[2]] &], GroupBy[#[[1]] &], Mean]][energyDS]

DateListPlot[dsQuery[#, All, 3] & /@ Keys[dsQuery], 
 PlotLegends -> Normal[Keys[dsQuery]]]

So is this how subqueries are embedded in Query?

And, it still is horribly slow. Is there a better way to handle the Replace function?

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4
  • 2
    $\begingroup$ Try to make your Query chain like this: Query[All, GroupBy[#["T_out"] &]] @ GroupBy[#date &] @ Query[All, {"date" -> toMonth}] @ energyDS Query[All, {#columnName -> function}] applying functioon only to one column. toMonth = Function[s, DateObject[DateList[DateObject[s]][[1 ;; 2]]]] $\endgroup$ Sep 7, 2020 at 8:10
  • $\begingroup$ Thank you @Belov. My problematic code is definitely the transforming of the datetime string to a "month" string to enable grouping by month. (It takes 620 sec. on my computer to "mutate" 1.6 million datetime strings. Therefore, I tried your toMonth function suggestion. Unfortunately, it is no faster. Thanks nonetheless, because you made me consider alternate simplifications, e.g., "DateString[#date, "MonthName"]&" instead of the "Replace[#date, #date -> DateObject[#date, "Month"]] &". But this is no better. An R code-equivalent runs in 22.2 sec. So I must be on the wrong track. $\endgroup$ Sep 7, 2020 at 20:50
  • 1
    $\begingroup$ try to evaluate this on your dataset toMonth2[s_] := StringRiffle[StringCases[s, Shortest[StartOfLine ~~ year__ ~~ "-" ~~ month__ ~~ "-" ~~ __ ~~ EndOfLine] :> year <> " " <> month], "\n"]; toMonthAll = (Map[DateObject] @ ImportString[toMonth2 @ StringRiffle[#, "\n"], "Table"])&; Transpose @ Query[{"date" -> toMonthAll}] @ Transpose @ energyDS in my computer this code takes about 1.6 seconds for 160k lines with DateObject (I think it will take about 16 seconds for 1.6 million lines) in your foemat. But I tested it only on pure string array with dates $\endgroup$ Sep 8, 2020 at 11:22
  • $\begingroup$ This is impressive. Thank you so much for taking the time to work through this. I have not implemented it fully; but my quick test on 1.6 M records comes in at 23.9 sec; so it rivals my R code. And, of course, I prefer to work in Mathematica. Again, I really appreciate your assistance. $\endgroup$ Sep 9, 2020 at 19:49

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