Simple vega-based visualization of data.
Typical expected usage below. tech.ml.dataset is not necessary, it is just used
for processing data in this case.
user> (require '[tech.viz.vega :as vega])
nil
;;functions take a sequence of maps as the first argument
user> (vega/scatterplot [{:a 1 :b 2} {:a 2 :b 3}] :a :b)
{:$schema "https://vega.github.io/schema/vega/v5.json",
:autosize {:type "fit", :resize true, :contains "padding"},
:width 800,
:height 450,
:axes
[{:scale "x", :grid true, :orient "bottom", :title :a, :domain false}
{:scale "y", :grid true, :orient "left", :title :b, :domain false}],
:scales
({:zero false,
:name "x",
:type "linear",
:round true,
:nice true,
:domain {:data "source", :field :a},
:range "width"}
{:zero false,
:name "y",
:type "linear",
:round true,
:nice true,
:domain {:data "source", :field :b},
:range "height"}),
:marks
[{:encode
{:update
{:fill {:value "#222"},
:stroke {:value "#222"},
:opacity {:value 0.5},
:shape {:value "circle"},
:x {:field :a, :scale "x"},
:y {:field :b, :scale "y"}}},
:from {:data "source"},
:type "symbol"}],
:data [{:name "source", :values [{:a 1, :b 2} {:a 2, :b 3}]}]}
user> (require '[tech.ml.dataset :as ds])
nil
user> (require '[tech.v2.datatype.datetime.operations :as dtype-dt-ops])
;;Simple usage
user> (ds/select (ds/->dataset "test/data/spiral-ds.csv") :all (range 5))
test/data/spiral-ds.csv [5 3]:
| x | y | label |
|-------+--------+-------|
| 0.041 | 0.075 | green |
| 0.486 | 0.223 | green |
| 0.543 | -0.749 | green |
| 0.154 | -0.376 | green |
| 0.434 | -0.805 | green |
user> (-> (ds/->dataset "test/data/spiral-ds.csv")
(ds/mapseq-reader)
(vega/scatterplot "x" "y"
{:title "Spriral Dataset"
:label-key "label"
:background "white"})
(vega/vega->svg-file "scatterplot.svg"))
;; More involved data processing
user> (ds/select (ds/->dataset "https://vega.github.io/vega/data/stocks.csv")
:all (range 5))
https://vega.github.io/vega/data/stocks.csv [5 3]:
| symbol | date | price |
|--------+------------+--------|
| MSFT | 2000-01-01 | 39.810 |
| MSFT | 2000-02-01 | 36.350 |
| MSFT | 2000-03-01 | 43.220 |
| MSFT | 2000-04-01 | 28.370 |
| MSFT | 2000-05-01 | 25.450 |
user> (as-> (ds/->dataset "https://vega.github.io/vega/data/stocks.csv") ds
;;The time series chart expects time in epoch milliseconds
(ds/add-or-update-column ds "year" (dtype-dt-ops/get-years (ds "date")))
(ds/filter-column #{2007 2008 2009} "year" ds)
(ds/update-column ds "date" dtype-dt-ops/get-epoch-milliseconds)
(ds/mapseq-reader ds)
;;all graphing functions run from pure clojure data. No batteries required.
(vega/time-series ds "date" "price"
{:title "Stock Price (2007-2010)"
:label-key "symbol"
:background "white"})
(vega/vega->svg-file ds "timeseries.svg"))
nil
Raw data as a string:
(def iris-raw-str* (delay (slurp "https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data")))Converted to a sequence of maps:
(def iris-mapseq
(->> @iris-raw-str*
(clojure.string/split-lines)
(map #(clojure.string/split % #"\,"))
(map (fn [[sl sw pl pw class]]
{:sepal-length (Double. sl)
:sepal-width (Double. sw)
:petal-length (Double. pl)
:petal-width (Double. pw)
:class class}))))And saved as an svg:
(let [spec (pairs iris-mapseq
[:sepal-length :sepal-width :petal-length :petal-width]
{:label-key :class
:background :#f8f8f8})]
(clojure.pprint/pprint spec)
(vega->svg-file spec "iris-pairs.svg"))
CLOJARS_USERNAME=[your email] CLOJARS_PASSWORD=$(cat ~/.clojars-token) ./scripts/deploy
Copyright © 2022 TechAscent, LLC
This program and the accompanying materials are made available under the terms of the Eclipse Public License 2.0 which is available at http://www.eclipse.org/legal/epl-2.0.