Skip to main content

dataset - Learning Resources for Data Science in the Wolfram Language


I'm delivering an upcoming course on Data Science with the programming/analysis done predominantly in the Wolfram Language. I created the following table to leverage students' familiarity with Lists by way of introducing Associations by way of introducing Datasets. Juxtaposing the various invocations one can't help but be struck with the foresight or "naturalness" of the original language design and subsequent integrations - (IMO an extraterrestrial would be hard-pressed to predict the chronology of sequentially added features, and in particular, to note that all three didn't emerge simultaneously).


My sense is that programming expertise in the Wolfram Language starts with an awareness of its existing (or "likely") functionality followed by inculcating and memorising its basic functional forms. While the documentation is essential for understanding all the details and an overall coherency, for quick reference/comparison/contrast, I think cheatsheets could be more commonly deployed (with no doubt improved visual design - the code follows which could potentially be improved/combined with other users' cheatsheets into a larger, more powerful "Demonstration"?)


At any rate, while an introduction involves becoming familiar with the basic syntax and manipulating structured datasets, the next stage involves applying these to some real-life examples. While there are good texts/datasets available (e.g. Luís Torgo's Data Mining with R: Learning with Case Studies) I'm wondering if anyone has found useful, available datasets from a variety of contexts (health, business, economics, ecology, physics, learning analytics) that might be particularly suitable for showcasing some of the benefits of data science in the Wolfram Language (this might be due to their size, unusual analysis, parallelizability, integration with curated data etc).



SetAttributes[{IOCells, DefCells, InsertIOCells, InsertDefCells}, 
HoldAll];



DefCells[Set[lhs_, rhs_]] := Row[{
ExpressionCell[Defer@lhs, "Input", ShowStringCharacters -> True,
FontSize -> 16],
ExpressionCell[" = ", ShowStringCharacters -> False,
FontSize -> 16],
ExpressionCell[lhs = rhs, "Input", ShowStringCharacters -> True,
FontSize -> 16]}];

(* Need to split in this way since a Defer wrapper seems to produce \

unexpected formatting - compare:
ExpressionCell[Defer[lhs=<|"a"\[Rule]8,"b"\[Rule]9,"c"\[Rule]10|>],\
"Input"]
ExpressionCell[Defer[lhs=\[LeftAngleBracket]"a"\[Rule]8,"b"\[Rule]9,\
"c"\[Rule]10\[RightAngleBracket]],"Input"]
*)

DefCells[R : Set[dataset, Dataset[{_}]]] := (R; Row[{
ExpressionCell[Defer@dataset, "Input",
ShowStringCharacters -> True, FontSize -> 16],

ExpressionCell[" = ", ShowStringCharacters -> False,
FontSize -> 16],
ExpressionCell["Dataset"[HoldForm[{assoc}]], "Input",
ShowStringCharacters -> False, FontSize -> 16]}]);

IOCells[expr_] /; !
FreeQ[Hold@expr,
Histogram | ListPlot | ListLinePlot | BarChart3D | BarChart |
PieChart | SmoothHistogram] := Grid[{
{ExpressionCell[Defer@expr, "Input",

ShowStringCharacters -> True]},
{ExpressionCell[expr, "Output", Magnification -> 0.41]}
}, Frame -> True, Alignment -> Left,
Background -> {None, {1 -> GrayLevel[.9], 2 -> White}}];


IOCells[expr_] := Grid[{
{ExpressionCell[Defer@expr, "Input",
ShowStringCharacters -> True]},
{ExpressionCell[expr, "Output"]}

}, Frame -> True, Alignment -> Left,
Background -> {None, {1 -> GrayLevel[.9], 2 -> White}}];

(* For the same reason above need a specific definition when <| |> \
notation is in input *)

IOCells[R : KeySelect[assoc_, assoc2_]] := With[
{t = ToExpression@ToBoxes[assoc2]}, Grid[{
{ExpressionCell[HoldForm@KeySelect[assoc, t], "Input",
ShowStringCharacters -> True]},

{ExpressionCell[ReleaseHold@R, "Output"]}
}, Frame -> True, Alignment -> Left,
Background -> {None, {1 -> GrayLevel[.9], 2 -> White}}]];

IOCells[R : Dataset[expr_][op_]] := Grid[{
{ExpressionCell["Dataset"[HoldForm@assoc][op], "Input",
ShowStringCharacters -> False]},
{ExpressionCell[ReleaseHold@R, "Output"]}
}, Frame -> True, Alignment -> Left,
Background -> {None, {1 -> GrayLevel[.9], 2 -> White}}];


(* Since Dataset outputs as grid in the input - means copying \
expression from the grid and evaluating won't work *)


InsertDefCells[defs_List] :=
ReleaseHold@With[{t = Hold@defs}, Map[DefCells, t, {2}]];
InsertIOCells[exprLs_] :=
Sequence @@
Map[Row,

ReleaseHold@With[{t = Hold@exprLs}, Map[IOCells, t, {4}]], {2}];

ColumnHeadStyle[cheads_List] :=
ExpressionCell[#, Style[#, {Bold, 18}],
ShowStringCharacters -> False] & /@ cheads;


Block[{$PlotTheme = "Minimal"}, Grid[{
{"List", "Association", "Dataset"} // ColumnHeadStyle,
{ls = {7, 8, 9}, assoc = <| "a" -> 7, b -> 8, "c" -> 9 |>,

dataset = Dataset[{assoc}]} // InsertDefCells,
{
{{ls[[All]]}, {Values[assoc], Keys[assoc], Normal[assoc],
Lookup[assoc, "b", "No-b"]}, {dataset[1, Values],
dataset[1, Keys]}},
{{(Query@1)[ls], ls[[1]], ls[[2]]}, {assoc[["a"]], assoc["a"],
assoc[[Key@b]], assoc@Key@b,
Query["a"][assoc]}, {Query[1, Key["a"]][dataset],
dataset[1, Key["a"]]}},
{{ls[[3]], ls[[-1]]}, {assoc[[3]], assoc[[-1]], assoc[a],

assoc["b"]}, {dataset[1, 3], dataset[1, -1],
dataset[1, Key["d"]]}},
{{ls[[1 ;; 3]], ls[[1 ;; 3 ;; 2]], Take[ls, {1, 3}],
Query[Take[{1, 3}]][ls]}, {assoc[[1 ;; 3]],
assoc[[1 ;; 3 ;; 2]], Take[assoc, {1, 3}],
Take[assoc, {1, 3, 2}],
Query[1 ;; 3][assoc]}, {dataset[1, 1 ;; 3],
Query[1, 1 ;; 3][dataset]}},
{{Query[{1, 3}][ls], ls[[{1, 3}]]}, {Query[{1, 3}][assoc],
assoc[[{1, 3}]], assoc[[{"a", "c"}]],

KeyTake[assoc, {"a", "c"}]}, {dataset[1, {1, 3}],
dataset[1, {"a", "c"}]}},
{{Cases[ls, _?OddQ], Cases[_?OddQ][ls]}, {Cases[assoc, _?OddQ],
Cases[_?OddQ][assoc]}, {dataset[1, Cases[_?OddQ]]}},
{{Query[Select[OddQ]][assoc], Select[ls, OddQ],
SelectFirst[ls, OddQ]}, {Select[assoc, OddQ],
Select[OddQ][assoc],
SelectFirst[assoc, OddQ]}, {dataset[1, Select[OddQ]],
dataset[1, SelectFirst[OddQ]]}},
{{Position[ls, _?OddQ],

FirstPosition[ls, _?OddQ]}, {Position[assoc, _?OddQ],
Position[_?OddQ][assoc],
FirstPosition[assoc, _?OddQ]}, {dataset[1, Position[_?OddQ]],
dataset[1, FirstPosition[_?OddQ]]}},
{{PositionIndex[ls],
Query[PositionIndex][ls]}, {PositionIndex[assoc],
Query[PositionIndex][assoc]}, {dataset[1, PositionIndex]}},
{{Select[Keys@assoc, MemberQ[{"a", "c"}, #] &]}, {KeySelect[
assoc, MemberQ[{"a", "c"}, #] &],
KeySelect[assoc, <| "a" -> True, "c" -> True |>]}, {dataset[1,

KeySelect[(# == "a" \[Or] # == "c") &]]}},
{{f[ls[[3]]], Query[3, f][ls]}, {f[assoc[["c"]]],
Query["c", f][assoc]}, {dataset[1, "c", f],
dataset[1, 3, f]}},
{{f /@ ls, Map[f][ls], Query[Map[f]][ls]}, {f /@ assoc,
Map[f][assoc]}, {dataset[1, Map@f], dataset[1, All, f]}},
{{MapIndexed[f, ls], MapIndexed[f][ls]}, {MapIndexed[f, assoc],
MapIndexed[f][assoc]}, {dataset[1, MapIndexed[f]]}},
{{MapAt[f, ls, 2], MapAt[f, 2][ls]}, {MapAt[f, assoc, 2],
MapAt[f, 2][assoc],

MapAt[f, Key[b]][assoc]}, {dataset[1, MapAt[f, Key@b]]}},
{{MapAt[f, Normal@assoc, {All, 1}]}, {KeyMap[f, assoc],
KeyMap[f][assoc]}, {dataset[1, KeyMap[f]]}},
{{Reverse /@ Normal@assoc,
Association[f /@ Normal@assoc]}, {AssociationMap[Reverse,
assoc], AssociationMap[f, assoc]}, {dataset[1,
AssociationMap@Reverse], dataset[1, AssociationMap[f]]}},
{{Sort@ls, Sort[ls, Greater],
Query[Sort[#1, Greater] &][ls]}, {Sort@assoc,
Sort[assoc, Greater],

Query[Sort[#1, Greater] &][assoc]}, {dataset[1, Sort],
dataset[1, Sort[#, Greater] &]}},
{{Total[ls]}, {Total[assoc], Query[Total][assoc],
Query[Values /* Total][assoc]}, {dataset[1, Total],
dataset[1, All /* Total], dataset[1, Total@*Values]}},
{{Through[{Min, Max, Total, Variance, Median}@
ls]}, {Query[{Min, Max, Total, Variance, Median}][
assoc]}, {dataset[1, {Min, Max, Total, Variance, Median}]}},
{{Through[{Histogram, BarChart, SmoothHistogram, PieChart,
ListLinePlot[#, Filling -> Axis] &}@ls]},

{Query[{Histogram, BarChart, SmoothHistogram, PieChart,
ListLinePlot[#1, Filling -> Axis] &}][
assoc]}, {dataset[
1, {Histogram, BarChart, SmoothHistogram, PieChart,
ListLinePlot[#1, Filling -> Axis] &}] // Normal}},
{{Thread[Keys[assoc] -> ls]}, {AssociationThread[
Keys[assoc] -> ls],
AssociationThread[Keys[assoc],
ls]}, {dataset[
1, {AssociationThread[Keys@#,

Values@#] &, (Keys@# -> Values@#) & /*
AssociationThread}] // Normal}},
{{Thread[Keys[assoc] -> f /@ Keys[assoc]]}, {AssociationMap[f,
Keys[assoc]],
Query[AssociationMap[f]@*Keys][assoc]}, {dataset[1,
Keys /* AssociationMap[f]]}},
{{(f[#1, #2, #3] &)[Sequence @@ ls]}, {(f[#a, #1[Key[b]], #c] &)[
assoc], (f[#1["a"], #1[Key[b]], #1["c"]] &)[assoc]}, {dataset[
1, All /* (f[#a, #1[Key[b]], #c] &)],
dataset[1, (Apply@f)@*Catenate]}},

{{(f[##1] &)[Sequence @@ ls], (f[##2] &)[
Sequence @@ ls]}, {((f[##] &)[Sequence @@ Values@#] &)[
assoc]}, {dataset[1,
Values /* (Sequence @@ # &) /* (f[##] &)],
dataset[1, (f[##] &)@*(Sequence @@ # &)@*Values]}}
} // InsertIOCells
}, Frame -> True,
Dividers -> {Thick, {Thick, {None}, Thick}, {3 -> Thick, 8 -> Thick,
13 -> Thick, 19 -> Thick, 23 -> Thick, 25 -> Thick}},
Alignment -> {Center, Center},

Background -> {Automatic, {ColorData[17, 4],
LightBrown, {LightBlue, LightGreen}}},
ItemStyle -> {Automatic, {19}}, Spacings -> {1, {1, 1, 1, {0.5}}}]]


Comments

Popular posts from this blog

plotting - Filling between two spheres in SphericalPlot3D

Manipulate[ SphericalPlot3D[{1, 2 - n}, {θ, 0, Pi}, {ϕ, 0, 1.5 Pi}, Mesh -> None, PlotPoints -> 15, PlotRange -> {-2.2, 2.2}], {n, 0, 1}] I cant' seem to be able to make a filling between two spheres. I've already tried the obvious Filling -> {1 -> {2}} but Mathematica doesn't seem to like that option. Is there any easy way around this or ... Answer There is no built-in filling in SphericalPlot3D . One option is to use ParametricPlot3D to draw the surfaces between the two shells: Manipulate[ Show[SphericalPlot3D[{1, 2 - n}, {θ, 0, Pi}, {ϕ, 0, 1.5 Pi}, PlotPoints -> 15, PlotRange -> {-2.2, 2.2}], ParametricPlot3D[{ r {Sin[t] Cos[1.5 Pi], Sin[t] Sin[1.5 Pi], Cos[t]}, r {Sin[t] Cos[0 Pi], Sin[t] Sin[0 Pi], Cos[t]}}, {r, 1, 2 - n}, {t, 0, Pi}, PlotStyle -> Yellow, Mesh -> {2, 15}]], {n, 0, 1}]

plotting - Plot 4D data with color as 4th dimension

I have a list of 4D data (x position, y position, amplitude, wavelength). I want to plot x, y, and amplitude on a 3D plot and have the color of the points correspond to the wavelength. I have seen many examples using functions to define color but my wavelength cannot be expressed by an analytic function. Is there a simple way to do this? Answer Here a another possible way to visualize 4D data: data = Flatten[Table[{x, y, x^2 + y^2, Sin[x - y]}, {x, -Pi, Pi,Pi/10}, {y,-Pi,Pi, Pi/10}], 1]; You can use the function Point along with VertexColors . Now the points are places using the first three elements and the color is determined by the fourth. In this case I used Hue, but you can use whatever you prefer. Graphics3D[ Point[data[[All, 1 ;; 3]], VertexColors -> Hue /@ data[[All, 4]]], Axes -> True, BoxRatios -> {1, 1, 1/GoldenRatio}]

plotting - Mathematica: 3D plot based on combined 2D graphs

I have several sigmoidal fits to 3 different datasets, with mean fit predictions plus the 95% confidence limits (not symmetrical around the mean) and the actual data. I would now like to show these different 2D plots projected in 3D as in but then using proper perspective. In the link here they give some solutions to combine the plots using isometric perspective, but I would like to use proper 3 point perspective. Any thoughts? Also any way to show the mean points per time point for each series plus or minus the standard error on the mean would be cool too, either using points+vertical bars, or using spheres plus tubes. Below are some test data and the fit function I am using. Note that I am working on a logit(proportion) scale and that the final vertical scale is Log10(percentage). (* some test data *) data = Table[Null, {i, 4}]; data[[1]] = {{1, -5.8}, {2, -5.4}, {3, -0.8}, {4, -0.2}, {5, 4.6}, {1, -6.4}, {2, -5.6}, {3, -0.7}, {4, 0.04}, {5, 1.0}, {1, -6.8}, {2, -4.7}, {3, -1.