3  Hanami walkthrough 👣

Tableplot offers a Clojure API for creating Vega-Lite plots through layered pipelines.

The API not only uses Hanami templates but also partially composes with the classical Hanami templates and parameters.

Here, we provide a walkthrough of the API.

In this walkthrough, we will demonstrate the main functionality of Tableplot.

Soon, we will provide more in-depth explanations in additional chapters.

3.1 Setup

For this tutorial, we require:

• Tableplot’s Hanami API namepace

• Hanami

• Tablecloth

• the datetime namespace of dtype-next

• the print namespace of tech.ml.dataset for customized dataset printing

• Kindly (to specify how certain values should be visualized)

• the datasets defined in the Datasets chapter

(ns tableplot-book.hanami-walkthrough
  (:require [scicloj.tableplot.v1.hanami :as hanami]
            [aerial.hanami.templates :as ht]
            [tablecloth.api :as tc]
            [tech.v3.datatype.datetime :as datetime]
            [tech.v3.dataset.print :as print]
            [scicloj.kindly.v4.kind :as kind]
            [clojure.string :as str]
            [scicloj.kindly.v4.api :as kindly]
            [tableplot-book.datasets :as datasets]))

3.2 Basic usage

Let us create a scatter plot from the Iris dataset. We pass a Tablecloth dataset to a Tableplot function with a Tableplot template.

(-> datasets/iris
    (hanami/plot hanami/point-chart
                 {:=x :sepal-width
                  :=y :sepal-length
                  :=color :species
                  :=mark-size 200}))

Soon, the Tableplot docs will offer an introduction to the use of Hanami templates and substitution keys. For now, please see the Hanami documentation.

While Tableplot allows using the classic Hanami templates and substitution keys, it also offers its own sets of templates, that we just used here.

Unlike the classic Hanami keys of using capital letter substitution keys (e.g. :COLOR) Tableplot uses the convention of substitution keys beginning with = (e.g. :=color)

The templates of Tableplot also support a layered grammar which is demonstrated later in this document.

(Here is how we can express the same plot with the layered grammar:)

(-> datasets/iris
    (hanami/layer-point
     {:=x :sepal-width
      :=y :sepal-length
      :=color :species
      :=mark-size 200}))

The value returned by a hanami/plot function is a Vega-Lite spec:

(-> datasets/iris
    (hanami/plot hanami/point-chart
                 {:=x :sepal-width
                  :=y :sepal-length
                  :=color :species
                  :=mark-size 200})
    kind/pprint)

{:encoding
 {:color {:field :species, :type :nominal},
  :x {:field :sepal-width, :type :quantitative},
  :y {:field :sepal-length, :type :quantitative}},
 :usermeta {:embedOptions {:renderer :svg}},
 :mark {:type "circle", :size 200, :tooltip true},
 :width 400,
 :background "floralwhite",
 :height 300,
 :data
 {:values
  "rownames,sepal-length,sepal-width,petal-length,petal-width,species\n1,5.1,3.5,1.4,0.2,setosa\n2,4.9,3.0,1.4,0.2,setosa\n3,4.7,3.2,1.3,0.2,setosa\n4,4.6,3.1,1.5,0.2,setosa\n5,5.0,3.6,1.4,0.2,setosa\n6,5.4,3.9,1.7,0.4,setosa\n7,4.6,3.4,1.4,0.3,setosa\n8,5.0,3.4,1.5,0.2,setosa\n9,4.4,2.9,1.4,0.2,setosa\n10,4.9,3.1,1.5,0.1,setosa\n11,5.4,3.7,1.5,0.2,setosa\n12,4.8,3.4,1.6,0.2,setosa\n13,4.8,3.0,1.4,0.1,setosa\n14,4.3,3.0,1.1,0.1,setosa\n15,5.8,4.0,1.2,0.2,setosa\n16,5.7,4.4,1.5,0.4,setosa\n17,5.4,3.9,1.3,0.4,setosa\n18,5.1,3.5,1.4,0.3,setosa\n19,5.7,3.8,1.7,0.3,setosa\n20,5.1,3.8,1.5,0.3,setosa\n21,5.4,3.4,1.7,0.2,setosa\n22,5.1,3.7,1.5,0.4,setosa\n23,4.6,3.6,1.0,0.2,setosa\n24,5.1,3.3,1.7,0.5,setosa\n25,4.8,3.4,1.9,0.2,setosa\n26,5.0,3.0,1.6,0.2,setosa\n27,5.0,3.4,1.6,0.4,setosa\n28,5.2,3.5,1.5,0.2,setosa\n29,5.2,3.4,1.4,0.2,setosa\n30,4.7,3.2,1.6,0.2,setosa\n31,4.8,3.1,1.6,0.2,setosa\n32,5.4,3.4,1.5,0.4,setosa\n33,5.2,4.1,1.5,0.1,setosa\n34,5.5,4.2,1.4,0.2,setosa\n35,4.9,3.1,1.5,0.2,setosa\n36,5.0,3.2,1.2,0.2,setosa\n37,5.5,3.5,1.3,0.2,setosa\n38,4.9,3.6,1.4,0.1,setosa\n39,4.4,3.0,1.3,0.2,setosa\n40,5.1,3.4,1.5,0.2,setosa\n41,5.0,3.5,1.3,0.3,setosa\n42,4.5,2.3,1.3,0.3,setosa\n43,4.4,3.2,1.3,0.2,setosa\n44,5.0,3.5,1.6,0.6,setosa\n45,5.1,3.8,1.9,0.4,setosa\n46,4.8,3.0,1.4,0.3,setosa\n47,5.1,3.8,1.6,0.2,setosa\n48,4.6,3.2,1.4,0.2,setosa\n49,5.3,3.7,1.5,0.2,setosa\n50,5.0,3.3,1.4,0.2,setosa\n51,7.0,3.2,4.7,1.4,versicolor\n52,6.4,3.2,4.5,1.5,versicolor\n53,6.9,3.1,4.9,1.5,versicolor\n54,5.5,2.3,4.0,1.3,versicolor\n55,6.5,2.8,4.6,1.5,versicolor\n56,5.7,2.8,4.5,1.3,versicolor\n57,6.3,3.3,4.7,1.6,versicolor\n58,4.9,2.4,3.3,1.0,versicolor\n59,6.6,2.9,4.6,1.3,versicolor\n60,5.2,2.7,3.9,1.4,versicolor\n61,5.0,2.0,3.5,1.0,versicolor\n62,5.9,3.0,4.2,1.5,versicolor\n63,6.0,2.2,4.0,1.0,versicolor\n64,6.1,2.9,4.7,1.4,versicolor\n65,5.6,2.9,3.6,1.3,versicolor\n66,6.7,3.1,4.4,1.4,versicolor\n67,5.6,3.0,4.5,1.5,versicolor\n68,5.8,2.7,4.1,1.0,versicolor\n69,6.2,2.2,4.5,1.5,versicolor\n70,5.6,2.5,3.9,1.1,versicolor\n71,5.9,3.2,4.8,1.8,versicolor\n72,6.1,2.8,4.0,1.3,versicolor\n73,6.3,2.5,4.9,1.5,versicolor\n74,6.1,2.8,4.7,1.2,versicolor\n75,6.4,2.9,4.3,1.3,versicolor\n76,6.6,3.0,4.4,1.4,versicolor\n77,6.8,2.8,4.8,1.4,versicolor\n78,6.7,3.0,5.0,1.7,versicolor\n79,6.0,2.9,4.5,1.5,versicolor\n80,5.7,2.6,3.5,1.0,versicolor\n81,5.5,2.4,3.8,1.1,versicolor\n82,5.5,2.4,3.7,1.0,versicolor\n83,5.8,2.7,3.9,1.2,versicolor\n84,6.0,2.7,5.1,1.6,versicolor\n85,5.4,3.0,4.5,1.5,versicolor\n86,6.0,3.4,4.5,1.6,versicolor\n87,6.7,3.1,4.7,1.5,versicolor\n88,6.3,2.3,4.4,1.3,versicolor\n89,5.6,3.0,4.1,1.3,versicolor\n90,5.5,2.5,4.0,1.3,versicolor\n91,5.5,2.6,4.4,1.2,versicolor\n92,6.1,3.0,4.6,1.4,versicolor\n93,5.8,2.6,4.0,1.2,versicolor\n94,5.0,2.3,3.3,1.0,versicolor\n95,5.6,2.7,4.2,1.3,versicolor\n96,5.7,3.0,4.2,1.2,versicolor\n97,5.7,2.9,4.2,1.3,versicolor\n98,6.2,2.9,4.3,1.3,versicolor\n99,5.1,2.5,3.0,1.1,versicolor\n100,5.7,2.8,4.1,1.3,versicolor\n101,6.3,3.3,6.0,2.5,virginica\n102,5.8,2.7,5.1,1.9,virginica\n103,7.1,3.0,5.9,2.1,virginica\n104,6.3,2.9,5.6,1.8,virginica\n105,6.5,3.0,5.8,2.2,virginica\n106,7.6,3.0,6.6,2.1,virginica\n107,4.9,2.5,4.5,1.7,virginica\n108,7.3,2.9,6.3,1.8,virginica\n109,6.7,2.5,5.8,1.8,virginica\n110,7.2,3.6,6.1,2.5,virginica\n111,6.5,3.2,5.1,2.0,virginica\n112,6.4,2.7,5.3,1.9,virginica\n113,6.8,3.0,5.5,2.1,virginica\n114,5.7,2.5,5.0,2.0,virginica\n115,5.8,2.8,5.1,2.4,virginica\n116,6.4,3.2,5.3,2.3,virginica\n117,6.5,3.0,5.5,1.8,virginica\n118,7.7,3.8,6.7,2.2,virginica\n119,7.7,2.6,6.9,2.3,virginica\n120,6.0,2.2,5.0,1.5,virginica\n121,6.9,3.2,5.7,2.3,virginica\n122,5.6,2.8,4.9,2.0,virginica\n123,7.7,2.8,6.7,2.0,virginica\n124,6.3,2.7,4.9,1.8,virginica\n125,6.7,3.3,5.7,2.1,virginica\n126,7.2,3.2,6.0,1.8,virginica\n127,6.2,2.8,4.8,1.8,virginica\n128,6.1,3.0,4.9,1.8,virginica\n129,6.4,2.8,5.6,2.1,virginica\n130,7.2,3.0,5.8,1.6,virginica\n131,7.4,2.8,6.1,1.9,virginica\n132,7.9,3.8,6.4,2.0,virginica\n133,6.4,2.8,5.6,2.2,virginica\n134,6.3,2.8,5.1,1.5,virginica\n135,6.1,2.6,5.6,1.4,virginica\n136,7.7,3.0,6.1,2.3,virginica\n137,6.3,3.4,5.6,2.4,virginica\n138,6.4,3.1,5.5,1.8,virginica\n139,6.0,3.0,4.8,1.8,virginica\n140,6.9,3.1,5.4,2.1,virginica\n141,6.7,3.1,5.6,2.4,virginica\n142,6.9,3.1,5.1,2.3,virginica\n143,5.8,2.7,5.1,1.9,virginica\n144,6.8,3.2,5.9,2.3,virginica\n145,6.7,3.3,5.7,2.5,virginica\n146,6.7,3.0,5.2,2.3,virginica\n147,6.3,2.5,5.0,1.9,virginica\n148,6.5,3.0,5.2,2.0,virginica\n149,6.2,3.4,5.4,2.3,virginica\n150,5.9,3.0,5.1,1.8,virginica\n",
  :format {:type "csv"}}}

By looking at the :values key above, you can see that the dataset was implicitly represented as CSV, and that it was defined to be rendered as :svg by default.

The resulting plot is displayed correctly, as it is annotated by Kindly as a Vega-lite plot:

(-> datasets/iris
    (hanami/plot hanami/point-chart
                 {:=x :sepal-width
                  :=y :sepal-length
                  :=color :species
                  :=mark-size 200})
    meta)

#:kindly{:kind :kind/vega-lite, :options nil}

3.3 Using classic Hanami templates and defaults

We can also use Hanami’s original templates (ht/chart) and substitution keys (:X, :Y, :MSIZE).

(-> datasets/iris
    (hanami/plot ht/point-chart
                 {:X :sepal-width
                  :Y :sepal-length
                  :MSIZE 200
                  :COLOR "species"}))

(-> datasets/iris
    (hanami/plot ht/point-chart
                 {:X :sepal-width
                  :Y :sepal-length
                  :MSIZE 200
                  :COLOR "species"})
    kind/pprint)

{:encoding
 {:y {:field :sepal-length, :type "quantitative"},
  :color {:field "species", :type "nominal"},
  :x {:field :sepal-width, :type "quantitative"}},
 :mark {:type "circle", :size 200, :tooltip true},
 :width 400,
 :background "floralwhite",
 :height 300,
 :data
 {:values
  "rownames,sepal-length,sepal-width,petal-length,petal-width,species\n1,5.1,3.5,1.4,0.2,setosa\n2,4.9,3.0,1.4,0.2,setosa\n3,4.7,3.2,1.3,0.2,setosa\n4,4.6,3.1,1.5,0.2,setosa\n5,5.0,3.6,1.4,0.2,setosa\n6,5.4,3.9,1.7,0.4,setosa\n7,4.6,3.4,1.4,0.3,setosa\n8,5.0,3.4,1.5,0.2,setosa\n9,4.4,2.9,1.4,0.2,setosa\n10,4.9,3.1,1.5,0.1,setosa\n11,5.4,3.7,1.5,0.2,setosa\n12,4.8,3.4,1.6,0.2,setosa\n13,4.8,3.0,1.4,0.1,setosa\n14,4.3,3.0,1.1,0.1,setosa\n15,5.8,4.0,1.2,0.2,setosa\n16,5.7,4.4,1.5,0.4,setosa\n17,5.4,3.9,1.3,0.4,setosa\n18,5.1,3.5,1.4,0.3,setosa\n19,5.7,3.8,1.7,0.3,setosa\n20,5.1,3.8,1.5,0.3,setosa\n21,5.4,3.4,1.7,0.2,setosa\n22,5.1,3.7,1.5,0.4,setosa\n23,4.6,3.6,1.0,0.2,setosa\n24,5.1,3.3,1.7,0.5,setosa\n25,4.8,3.4,1.9,0.2,setosa\n26,5.0,3.0,1.6,0.2,setosa\n27,5.0,3.4,1.6,0.4,setosa\n28,5.2,3.5,1.5,0.2,setosa\n29,5.2,3.4,1.4,0.2,setosa\n30,4.7,3.2,1.6,0.2,setosa\n31,4.8,3.1,1.6,0.2,setosa\n32,5.4,3.4,1.5,0.4,setosa\n33,5.2,4.1,1.5,0.1,setosa\n34,5.5,4.2,1.4,0.2,setosa\n35,4.9,3.1,1.5,0.2,setosa\n36,5.0,3.2,1.2,0.2,setosa\n37,5.5,3.5,1.3,0.2,setosa\n38,4.9,3.6,1.4,0.1,setosa\n39,4.4,3.0,1.3,0.2,setosa\n40,5.1,3.4,1.5,0.2,setosa\n41,5.0,3.5,1.3,0.3,setosa\n42,4.5,2.3,1.3,0.3,setosa\n43,4.4,3.2,1.3,0.2,setosa\n44,5.0,3.5,1.6,0.6,setosa\n45,5.1,3.8,1.9,0.4,setosa\n46,4.8,3.0,1.4,0.3,setosa\n47,5.1,3.8,1.6,0.2,setosa\n48,4.6,3.2,1.4,0.2,setosa\n49,5.3,3.7,1.5,0.2,setosa\n50,5.0,3.3,1.4,0.2,setosa\n51,7.0,3.2,4.7,1.4,versicolor\n52,6.4,3.2,4.5,1.5,versicolor\n53,6.9,3.1,4.9,1.5,versicolor\n54,5.5,2.3,4.0,1.3,versicolor\n55,6.5,2.8,4.6,1.5,versicolor\n56,5.7,2.8,4.5,1.3,versicolor\n57,6.3,3.3,4.7,1.6,versicolor\n58,4.9,2.4,3.3,1.0,versicolor\n59,6.6,2.9,4.6,1.3,versicolor\n60,5.2,2.7,3.9,1.4,versicolor\n61,5.0,2.0,3.5,1.0,versicolor\n62,5.9,3.0,4.2,1.5,versicolor\n63,6.0,2.2,4.0,1.0,versicolor\n64,6.1,2.9,4.7,1.4,versicolor\n65,5.6,2.9,3.6,1.3,versicolor\n66,6.7,3.1,4.4,1.4,versicolor\n67,5.6,3.0,4.5,1.5,versicolor\n68,5.8,2.7,4.1,1.0,versicolor\n69,6.2,2.2,4.5,1.5,versicolor\n70,5.6,2.5,3.9,1.1,versicolor\n71,5.9,3.2,4.8,1.8,versicolor\n72,6.1,2.8,4.0,1.3,versicolor\n73,6.3,2.5,4.9,1.5,versicolor\n74,6.1,2.8,4.7,1.2,versicolor\n75,6.4,2.9,4.3,1.3,versicolor\n76,6.6,3.0,4.4,1.4,versicolor\n77,6.8,2.8,4.8,1.4,versicolor\n78,6.7,3.0,5.0,1.7,versicolor\n79,6.0,2.9,4.5,1.5,versicolor\n80,5.7,2.6,3.5,1.0,versicolor\n81,5.5,2.4,3.8,1.1,versicolor\n82,5.5,2.4,3.7,1.0,versicolor\n83,5.8,2.7,3.9,1.2,versicolor\n84,6.0,2.7,5.1,1.6,versicolor\n85,5.4,3.0,4.5,1.5,versicolor\n86,6.0,3.4,4.5,1.6,versicolor\n87,6.7,3.1,4.7,1.5,versicolor\n88,6.3,2.3,4.4,1.3,versicolor\n89,5.6,3.0,4.1,1.3,versicolor\n90,5.5,2.5,4.0,1.3,versicolor\n91,5.5,2.6,4.4,1.2,versicolor\n92,6.1,3.0,4.6,1.4,versicolor\n93,5.8,2.6,4.0,1.2,versicolor\n94,5.0,2.3,3.3,1.0,versicolor\n95,5.6,2.7,4.2,1.3,versicolor\n96,5.7,3.0,4.2,1.2,versicolor\n97,5.7,2.9,4.2,1.3,versicolor\n98,6.2,2.9,4.3,1.3,versicolor\n99,5.1,2.5,3.0,1.1,versicolor\n100,5.7,2.8,4.1,1.3,versicolor\n101,6.3,3.3,6.0,2.5,virginica\n102,5.8,2.7,5.1,1.9,virginica\n103,7.1,3.0,5.9,2.1,virginica\n104,6.3,2.9,5.6,1.8,virginica\n105,6.5,3.0,5.8,2.2,virginica\n106,7.6,3.0,6.6,2.1,virginica\n107,4.9,2.5,4.5,1.7,virginica\n108,7.3,2.9,6.3,1.8,virginica\n109,6.7,2.5,5.8,1.8,virginica\n110,7.2,3.6,6.1,2.5,virginica\n111,6.5,3.2,5.1,2.0,virginica\n112,6.4,2.7,5.3,1.9,virginica\n113,6.8,3.0,5.5,2.1,virginica\n114,5.7,2.5,5.0,2.0,virginica\n115,5.8,2.8,5.1,2.4,virginica\n116,6.4,3.2,5.3,2.3,virginica\n117,6.5,3.0,5.5,1.8,virginica\n118,7.7,3.8,6.7,2.2,virginica\n119,7.7,2.6,6.9,2.3,virginica\n120,6.0,2.2,5.0,1.5,virginica\n121,6.9,3.2,5.7,2.3,virginica\n122,5.6,2.8,4.9,2.0,virginica\n123,7.7,2.8,6.7,2.0,virginica\n124,6.3,2.7,4.9,1.8,virginica\n125,6.7,3.3,5.7,2.1,virginica\n126,7.2,3.2,6.0,1.8,virginica\n127,6.2,2.8,4.8,1.8,virginica\n128,6.1,3.0,4.9,1.8,virginica\n129,6.4,2.8,5.6,2.1,virginica\n130,7.2,3.0,5.8,1.6,virginica\n131,7.4,2.8,6.1,1.9,virginica\n132,7.9,3.8,6.4,2.0,virginica\n133,6.4,2.8,5.6,2.2,virginica\n134,6.3,2.8,5.1,1.5,virginica\n135,6.1,2.6,5.6,1.4,virginica\n136,7.7,3.0,6.1,2.3,virginica\n137,6.3,3.4,5.6,2.4,virginica\n138,6.4,3.1,5.5,1.8,virginica\n139,6.0,3.0,4.8,1.8,virginica\n140,6.9,3.1,5.4,2.1,virginica\n141,6.7,3.1,5.6,2.4,virginica\n142,6.9,3.1,5.1,2.3,virginica\n143,5.8,2.7,5.1,1.9,virginica\n144,6.8,3.2,5.9,2.3,virginica\n145,6.7,3.3,5.7,2.5,virginica\n146,6.7,3.0,5.2,2.3,virginica\n147,6.3,2.5,5.0,1.9,virginica\n148,6.5,3.0,5.2,2.0,virginica\n149,6.2,3.4,5.4,2.3,virginica\n150,5.9,3.0,5.1,1.8,virginica\n",
  :format {:type "csv"}}}

3.4 Inferring and overriding field types

Field types are inferred from the dataset’s column type. Here, for example, x and y are :quantitative, and color is :nominal (and is thus coloured with distinct colours rather than a gradient).

(-> datasets/iris
    (hanami/plot hanami/point-chart
                 {:=x :sepal-width
                  :=y :sepal-length
                  :=color :species
                  :=mark-size 200}))

(-> datasets/iris
    (hanami/plot hanami/point-chart
                {:=x :sepal-width
                 :=y :sepal-length
                 :=color :species
                 :=mark-size 200})
    kind/pprint)

{:encoding
 {:color {:field :species, :type :nominal},
  :x {:field :sepal-width, :type :quantitative},
  :y {:field :sepal-length, :type :quantitative}},
 :usermeta {:embedOptions {:renderer :svg}},
 :mark {:type "circle", :size 200, :tooltip true},
 :width 400,
 :background "floralwhite",
 :height 300,
 :data
 {:values
  "rownames,sepal-length,sepal-width,petal-length,petal-width,species\n1,5.1,3.5,1.4,0.2,setosa\n2,4.9,3.0,1.4,0.2,setosa\n3,4.7,3.2,1.3,0.2,setosa\n4,4.6,3.1,1.5,0.2,setosa\n5,5.0,3.6,1.4,0.2,setosa\n6,5.4,3.9,1.7,0.4,setosa\n7,4.6,3.4,1.4,0.3,setosa\n8,5.0,3.4,1.5,0.2,setosa\n9,4.4,2.9,1.4,0.2,setosa\n10,4.9,3.1,1.5,0.1,setosa\n11,5.4,3.7,1.5,0.2,setosa\n12,4.8,3.4,1.6,0.2,setosa\n13,4.8,3.0,1.4,0.1,setosa\n14,4.3,3.0,1.1,0.1,setosa\n15,5.8,4.0,1.2,0.2,setosa\n16,5.7,4.4,1.5,0.4,setosa\n17,5.4,3.9,1.3,0.4,setosa\n18,5.1,3.5,1.4,0.3,setosa\n19,5.7,3.8,1.7,0.3,setosa\n20,5.1,3.8,1.5,0.3,setosa\n21,5.4,3.4,1.7,0.2,setosa\n22,5.1,3.7,1.5,0.4,setosa\n23,4.6,3.6,1.0,0.2,setosa\n24,5.1,3.3,1.7,0.5,setosa\n25,4.8,3.4,1.9,0.2,setosa\n26,5.0,3.0,1.6,0.2,setosa\n27,5.0,3.4,1.6,0.4,setosa\n28,5.2,3.5,1.5,0.2,setosa\n29,5.2,3.4,1.4,0.2,setosa\n30,4.7,3.2,1.6,0.2,setosa\n31,4.8,3.1,1.6,0.2,setosa\n32,5.4,3.4,1.5,0.4,setosa\n33,5.2,4.1,1.5,0.1,setosa\n34,5.5,4.2,1.4,0.2,setosa\n35,4.9,3.1,1.5,0.2,setosa\n36,5.0,3.2,1.2,0.2,setosa\n37,5.5,3.5,1.3,0.2,setosa\n38,4.9,3.6,1.4,0.1,setosa\n39,4.4,3.0,1.3,0.2,setosa\n40,5.1,3.4,1.5,0.2,setosa\n41,5.0,3.5,1.3,0.3,setosa\n42,4.5,2.3,1.3,0.3,setosa\n43,4.4,3.2,1.3,0.2,setosa\n44,5.0,3.5,1.6,0.6,setosa\n45,5.1,3.8,1.9,0.4,setosa\n46,4.8,3.0,1.4,0.3,setosa\n47,5.1,3.8,1.6,0.2,setosa\n48,4.6,3.2,1.4,0.2,setosa\n49,5.3,3.7,1.5,0.2,setosa\n50,5.0,3.3,1.4,0.2,setosa\n51,7.0,3.2,4.7,1.4,versicolor\n52,6.4,3.2,4.5,1.5,versicolor\n53,6.9,3.1,4.9,1.5,versicolor\n54,5.5,2.3,4.0,1.3,versicolor\n55,6.5,2.8,4.6,1.5,versicolor\n56,5.7,2.8,4.5,1.3,versicolor\n57,6.3,3.3,4.7,1.6,versicolor\n58,4.9,2.4,3.3,1.0,versicolor\n59,6.6,2.9,4.6,1.3,versicolor\n60,5.2,2.7,3.9,1.4,versicolor\n61,5.0,2.0,3.5,1.0,versicolor\n62,5.9,3.0,4.2,1.5,versicolor\n63,6.0,2.2,4.0,1.0,versicolor\n64,6.1,2.9,4.7,1.4,versicolor\n65,5.6,2.9,3.6,1.3,versicolor\n66,6.7,3.1,4.4,1.4,versicolor\n67,5.6,3.0,4.5,1.5,versicolor\n68,5.8,2.7,4.1,1.0,versicolor\n69,6.2,2.2,4.5,1.5,versicolor\n70,5.6,2.5,3.9,1.1,versicolor\n71,5.9,3.2,4.8,1.8,versicolor\n72,6.1,2.8,4.0,1.3,versicolor\n73,6.3,2.5,4.9,1.5,versicolor\n74,6.1,2.8,4.7,1.2,versicolor\n75,6.4,2.9,4.3,1.3,versicolor\n76,6.6,3.0,4.4,1.4,versicolor\n77,6.8,2.8,4.8,1.4,versicolor\n78,6.7,3.0,5.0,1.7,versicolor\n79,6.0,2.9,4.5,1.5,versicolor\n80,5.7,2.6,3.5,1.0,versicolor\n81,5.5,2.4,3.8,1.1,versicolor\n82,5.5,2.4,3.7,1.0,versicolor\n83,5.8,2.7,3.9,1.2,versicolor\n84,6.0,2.7,5.1,1.6,versicolor\n85,5.4,3.0,4.5,1.5,versicolor\n86,6.0,3.4,4.5,1.6,versicolor\n87,6.7,3.1,4.7,1.5,versicolor\n88,6.3,2.3,4.4,1.3,versicolor\n89,5.6,3.0,4.1,1.3,versicolor\n90,5.5,2.5,4.0,1.3,versicolor\n91,5.5,2.6,4.4,1.2,versicolor\n92,6.1,3.0,4.6,1.4,versicolor\n93,5.8,2.6,4.0,1.2,versicolor\n94,5.0,2.3,3.3,1.0,versicolor\n95,5.6,2.7,4.2,1.3,versicolor\n96,5.7,3.0,4.2,1.2,versicolor\n97,5.7,2.9,4.2,1.3,versicolor\n98,6.2,2.9,4.3,1.3,versicolor\n99,5.1,2.5,3.0,1.1,versicolor\n100,5.7,2.8,4.1,1.3,versicolor\n101,6.3,3.3,6.0,2.5,virginica\n102,5.8,2.7,5.1,1.9,virginica\n103,7.1,3.0,5.9,2.1,virginica\n104,6.3,2.9,5.6,1.8,virginica\n105,6.5,3.0,5.8,2.2,virginica\n106,7.6,3.0,6.6,2.1,virginica\n107,4.9,2.5,4.5,1.7,virginica\n108,7.3,2.9,6.3,1.8,virginica\n109,6.7,2.5,5.8,1.8,virginica\n110,7.2,3.6,6.1,2.5,virginica\n111,6.5,3.2,5.1,2.0,virginica\n112,6.4,2.7,5.3,1.9,virginica\n113,6.8,3.0,5.5,2.1,virginica\n114,5.7,2.5,5.0,2.0,virginica\n115,5.8,2.8,5.1,2.4,virginica\n116,6.4,3.2,5.3,2.3,virginica\n117,6.5,3.0,5.5,1.8,virginica\n118,7.7,3.8,6.7,2.2,virginica\n119,7.7,2.6,6.9,2.3,virginica\n120,6.0,2.2,5.0,1.5,virginica\n121,6.9,3.2,5.7,2.3,virginica\n122,5.6,2.8,4.9,2.0,virginica\n123,7.7,2.8,6.7,2.0,virginica\n124,6.3,2.7,4.9,1.8,virginica\n125,6.7,3.3,5.7,2.1,virginica\n126,7.2,3.2,6.0,1.8,virginica\n127,6.2,2.8,4.8,1.8,virginica\n128,6.1,3.0,4.9,1.8,virginica\n129,6.4,2.8,5.6,2.1,virginica\n130,7.2,3.0,5.8,1.6,virginica\n131,7.4,2.8,6.1,1.9,virginica\n132,7.9,3.8,6.4,2.0,virginica\n133,6.4,2.8,5.6,2.2,virginica\n134,6.3,2.8,5.1,1.5,virginica\n135,6.1,2.6,5.6,1.4,virginica\n136,7.7,3.0,6.1,2.3,virginica\n137,6.3,3.4,5.6,2.4,virginica\n138,6.4,3.1,5.5,1.8,virginica\n139,6.0,3.0,4.8,1.8,virginica\n140,6.9,3.1,5.4,2.1,virginica\n141,6.7,3.1,5.6,2.4,virginica\n142,6.9,3.1,5.1,2.3,virginica\n143,5.8,2.7,5.1,1.9,virginica\n144,6.8,3.2,5.9,2.3,virginica\n145,6.7,3.3,5.7,2.5,virginica\n146,6.7,3.0,5.2,2.3,virginica\n147,6.3,2.5,5.0,1.9,virginica\n148,6.5,3.0,5.2,2.0,virginica\n149,6.2,3.4,5.4,2.3,virginica\n150,5.9,3.0,5.1,1.8,virginica\n",
  :format {:type "csv"}}}

On the other hand, in the following example, color is :quantitative:

(-> datasets/mtcars
    (hanami/plot hanami/point-chart
                {:=x :mpg
                 :=y :disp
                 :=color :cyl
                 :=mark-size 200}))

(-> datasets/mtcars
    (hanami/plot hanami/point-chart
                {:=x :mpg
                 :=y :disp
                 :=color :cyl
                 :=mark-size 200})
    kind/pprint)

{:encoding
 {:color {:field :cyl, :type :quantitative},
  :x {:field :mpg, :type :quantitative},
  :y {:field :disp, :type :quantitative}},
 :usermeta {:embedOptions {:renderer :svg}},
 :mark {:type "circle", :size 200, :tooltip true},
 :width 400,
 :background "floralwhite",
 :height 300,
 :data
 {:values
  "rownames,mpg,cyl,disp,hp,drat,wt,qsec,vs,am,gear,carb\nMazda RX4,21.0,6,160.0,110,3.9,2.62,16.46,0,1,4,4\nMazda RX4 Wag,21.0,6,160.0,110,3.9,2.875,17.02,0,1,4,4\nDatsun 710,22.8,4,108.0,93,3.85,2.32,18.61,1,1,4,1\nHornet 4 Drive,21.4,6,258.0,110,3.08,3.215,19.44,1,0,3,1\nHornet Sportabout,18.7,8,360.0,175,3.15,3.44,17.02,0,0,3,2\nValiant,18.1,6,225.0,105,2.76,3.46,20.22,1,0,3,1\nDuster 360,14.3,8,360.0,245,3.21,3.57,15.84,0,0,3,4\nMerc 240D,24.4,4,146.7,62,3.69,3.19,20.0,1,0,4,2\nMerc 230,22.8,4,140.8,95,3.92,3.15,22.9,1,0,4,2\nMerc 280,19.2,6,167.6,123,3.92,3.44,18.3,1,0,4,4\nMerc 280C,17.8,6,167.6,123,3.92,3.44,18.9,1,0,4,4\nMerc 450SE,16.4,8,275.8,180,3.07,4.07,17.4,0,0,3,3\nMerc 450SL,17.3,8,275.8,180,3.07,3.73,17.6,0,0,3,3\nMerc 450SLC,15.2,8,275.8,180,3.07,3.78,18.0,0,0,3,3\nCadillac Fleetwood,10.4,8,472.0,205,2.93,5.25,17.98,0,0,3,4\nLincoln Continental,10.4,8,460.0,215,3.0,5.424,17.82,0,0,3,4\nChrysler Imperial,14.7,8,440.0,230,3.23,5.345,17.42,0,0,3,4\nFiat 128,32.4,4,78.7,66,4.08,2.2,19.47,1,1,4,1\nHonda Civic,30.4,4,75.7,52,4.93,1.615,18.52,1,1,4,2\nToyota Corolla,33.9,4,71.1,65,4.22,1.835,19.9,1,1,4,1\nToyota Corona,21.5,4,120.1,97,3.7,2.465,20.01,1,0,3,1\nDodge Challenger,15.5,8,318.0,150,2.76,3.52,16.87,0,0,3,2\nAMC Javelin,15.2,8,304.0,150,3.15,3.435,17.3,0,0,3,2\nCamaro Z28,13.3,8,350.0,245,3.73,3.84,15.41,0,0,3,4\nPontiac Firebird,19.2,8,400.0,175,3.08,3.845,17.05,0,0,3,2\nFiat X1-9,27.3,4,79.0,66,4.08,1.935,18.9,1,1,4,1\nPorsche 914-2,26.0,4,120.3,91,4.43,2.14,16.7,0,1,5,2\nLotus Europa,30.4,4,95.1,113,3.77,1.513,16.9,1,1,5,2\nFord Pantera L,15.8,8,351.0,264,4.22,3.17,14.5,0,1,5,4\nFerrari Dino,19.7,6,145.0,175,3.62,2.77,15.5,0,1,5,6\nMaserati Bora,15.0,8,301.0,335,3.54,3.57,14.6,0,1,5,8\nVolvo 142E,21.4,4,121.0,109,4.11,2.78,18.6,1,1,4,2\n",
  :format {:type "csv"}}}

This can be overridden to define color as :noninal:

(-> datasets/mtcars
    (hanami/plot hanami/point-chart
                {:=x :mpg
                 :=y :disp
                 :=color :cyl
                 :=color-type :nominal
                 :=mark-size 200}))

(-> datasets/mtcars
    (hanami/plot hanami/point-chart
                 {:=x :mpg
                  :=y :disp
                  :=color :cyl
                  :=color-type :nominal
                  :=mark-size 200})
    kind/pprint)

{:encoding
 {:color {:field :cyl, :type :nominal},
  :x {:field :mpg, :type :quantitative},
  :y {:field :disp, :type :quantitative}},
 :usermeta {:embedOptions {:renderer :svg}},
 :mark {:type "circle", :size 200, :tooltip true},
 :width 400,
 :background "floralwhite",
 :height 300,
 :data
 {:values
  "rownames,mpg,cyl,disp,hp,drat,wt,qsec,vs,am,gear,carb\nMazda RX4,21.0,6,160.0,110,3.9,2.62,16.46,0,1,4,4\nMazda RX4 Wag,21.0,6,160.0,110,3.9,2.875,17.02,0,1,4,4\nDatsun 710,22.8,4,108.0,93,3.85,2.32,18.61,1,1,4,1\nHornet 4 Drive,21.4,6,258.0,110,3.08,3.215,19.44,1,0,3,1\nHornet Sportabout,18.7,8,360.0,175,3.15,3.44,17.02,0,0,3,2\nValiant,18.1,6,225.0,105,2.76,3.46,20.22,1,0,3,1\nDuster 360,14.3,8,360.0,245,3.21,3.57,15.84,0,0,3,4\nMerc 240D,24.4,4,146.7,62,3.69,3.19,20.0,1,0,4,2\nMerc 230,22.8,4,140.8,95,3.92,3.15,22.9,1,0,4,2\nMerc 280,19.2,6,167.6,123,3.92,3.44,18.3,1,0,4,4\nMerc 280C,17.8,6,167.6,123,3.92,3.44,18.9,1,0,4,4\nMerc 450SE,16.4,8,275.8,180,3.07,4.07,17.4,0,0,3,3\nMerc 450SL,17.3,8,275.8,180,3.07,3.73,17.6,0,0,3,3\nMerc 450SLC,15.2,8,275.8,180,3.07,3.78,18.0,0,0,3,3\nCadillac Fleetwood,10.4,8,472.0,205,2.93,5.25,17.98,0,0,3,4\nLincoln Continental,10.4,8,460.0,215,3.0,5.424,17.82,0,0,3,4\nChrysler Imperial,14.7,8,440.0,230,3.23,5.345,17.42,0,0,3,4\nFiat 128,32.4,4,78.7,66,4.08,2.2,19.47,1,1,4,1\nHonda Civic,30.4,4,75.7,52,4.93,1.615,18.52,1,1,4,2\nToyota Corolla,33.9,4,71.1,65,4.22,1.835,19.9,1,1,4,1\nToyota Corona,21.5,4,120.1,97,3.7,2.465,20.01,1,0,3,1\nDodge Challenger,15.5,8,318.0,150,2.76,3.52,16.87,0,0,3,2\nAMC Javelin,15.2,8,304.0,150,3.15,3.435,17.3,0,0,3,2\nCamaro Z28,13.3,8,350.0,245,3.73,3.84,15.41,0,0,3,4\nPontiac Firebird,19.2,8,400.0,175,3.08,3.845,17.05,0,0,3,2\nFiat X1-9,27.3,4,79.0,66,4.08,1.935,18.9,1,1,4,1\nPorsche 914-2,26.0,4,120.3,91,4.43,2.14,16.7,0,1,5,2\nLotus Europa,30.4,4,95.1,113,3.77,1.513,16.9,1,1,5,2\nFord Pantera L,15.8,8,351.0,264,4.22,3.17,14.5,0,1,5,4\nFerrari Dino,19.7,6,145.0,175,3.62,2.77,15.5,0,1,5,6\nMaserati Bora,15.0,8,301.0,335,3.54,3.57,14.6,0,1,5,8\nVolvo 142E,21.4,4,121.0,109,4.11,2.78,18.6,1,1,4,2\n",
  :format {:type "csv"}}}

3.5 More examples

A Tableplot boxplot:

(-> datasets/mtcars
    (hanami/plot hanami/boxplot-chart
                 {:=x :cyl
                  :=x-type :nominal
                  :=y :disp}))

An original Hanami boxplot:

(-> datasets/mtcars
    (hanami/plot ht/boxplot-chart
                 {:X :cyl
                  :XTYPE :nominal
                  :Y :disp}))

Plotting segments with Tableplot:

(-> datasets/iris
    (hanami/plot hanami/rule-chart
                 {:=x :sepal-width
                  :=y :sepal-length
                  :=x2 :petal-width
                  :=y2 :petal-length
                  :=mark-opacity 0.5
                  :=mark-size 3
                  :=color :species}))

Plotting segments with original Hanami:

(-> datasets/iris
    (hanami/plot ht/rule-chart
                {:X :sepal-width
                 :Y :sepal-length
                 :X2 :petal-width
                 :Y2 :petal-length
                 :OPACITY 0.5
                 :SIZE 3
                 :COLOR "species"}))

3.6 Time series

Let us plot a time series:

(-> datasets/economics-long
    (tc/select-rows #(-> % :variable (= "unemploy")))
    (hanami/plot hanami/line-chart
                {:=x :date
                 :=y :value
                 :=mark-color "purple"}))

You see, the :date field was correctly inferred to be of the :temporal kind.

(-> datasets/economics-long
    (tc/select-rows #(-> % :variable (= "unemploy")))
    (hanami/plot hanami/line-chart
                {:=x :date
                 :=y :value
                 :=mark-color "purple"})
    kind/pprint)

{:encoding
 {:x {:field :date, :type :temporal},
  :y {:field :value, :type :quantitative}},
 :usermeta {:embedOptions {:renderer :svg}},
 :mark {:type "line", :color "purple", :tooltip true},
 :width 400,
 :background "floralwhite",
 :height 300,
 :data
 {:values
  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03-01,unemploy,5783.0,0.24457251124970394\n2678,1999-04-01,unemploy,6004.0,0.2620194205415647\n2679,1999-05-01,unemploy,5796.0,0.2455988000315781\n2680,1999-06-01,unemploy,5951.0,0.25783532012315463\n2681,1999-07-01,unemploy,6025.0,0.26367727165074606\n2682,1999-08-01,unemploy,5838.0,0.2489145022499408\n2683,1999-09-01,unemploy,5915.0,0.25499328965027235\n2684,1999-10-01,unemploy,5778.0,0.24417778479513697\n2685,1999-11-01,unemploy,5716.0,0.23928317675850636\n2686,1999-12-01,unemploy,5653.0,0.23430962343096234\n2687,2000-01-01,unemploy,5708.0,0.23865161443119917\n2688,2000-02-01,unemploy,5858.0,0.25049340806820874\n2689,2000-03-01,unemploy,5733.0,0.2406252467040341\n2690,2000-04-01,unemploy,5481.0,0.22073103339385805\n2691,2000-05-01,unemploy,5758.0,0.24259887897686902\n2692,2000-06-01,unemploy,5651.0,0.23415173284913554\n2693,2000-07-01,unemploy,5747.0,0.24173048077682166\n2694,2000-08-01,unemploy,5853.0,0.25009868161364174\n2695,2000-09-01,unemploy,5625.0,0.23209915528538722\n2696,2000-10-01,unemploy,5534.0,0.2249151338122681\n2697,2000-11-01,unemploy,5639.0,0.23320438935817478\n2698,2000-12-01,unemploy,5634.0,0.2328096629036078\n2699,2001-01-01,unemploy,6023.0,0.26351938106891926\n2700,2001-02-01,unemploy,6089.0,0.2687297702692034\n2701,2001-03-01,unemploy,6141.0,0.27283492539670007\n2702,2001-04-01,unemploy,6271.0,0.2830978132154417\n2703,2001-05-01,unemploy,6226.0,0.27954527512433885\n2704,2001-06-01,unemploy,6484.0,0.29991316017999525\n2705,2001-07-01,unemploy,6583.0,0.30772874398042155\n2706,2001-08-01,unemploy,7042.0,0.3439646325096708\n2707,2001-09-01,unemploy,7142.0,0.3518591616010105\n2708,2001-10-01,unemploy,7694.0,0.39543696218520563\n2709,2001-11-01,unemploy,8003.0,0.41983105707744534\n2710,2001-12-01,unemploy,8258.0,0.4399621062603616\n2711,2002-01-01,unemploy,8182.0,0.4339622641509434\n2712,2002-02-01,unemploy,8215.0,0.4365674587510855\n2713,2002-03-01,unemploy,8304.0,0.44359358964237783\n2714,2002-04-01,unemploy,8599.0,0.46688245046182997\n2715,2002-05-01,unemploy,8399.0,0.4510933922791506\n2716,2002-06-01,unemploy,8393.0,0.45061972053367016\n2717,2002-07-01,unemploy,8390.0,0.45038288466092996\n2718,2002-08-01,unemploy,8304.0,0.44359358964237783\n2719,2002-09-01,unemploy,8251.0,0.4394094892239678\n2720,2002-10-01,unemploy,8307.0,0.44383042551511803\n2721,2002-11-01,unemploy,8520.0,0.4606457724796716\n2722,2002-12-01,unemploy,8640.0,0.4701192073892792\n2723,2003-01-01,unemploy,8520.0,0.4606457724796716\n2724,2003-02-01,unemploy,8618.0,0.4683824109891845\n2725,2003-03-01,unemploy,8588.0,0.4660140522617826\n2726,2003-04-01,unemploy,8842.0,0.4860661561537854\n2727,2003-05-01,unemploy,8957.0,0.49514486460882606\n2728,2003-06-01,unemploy,9266.0,0.5195389595010658\n2729,2003-07-01,unemploy,9011.0,0.4994079103181495\n2730,2003-08-01,unemploy,8896.0,0.49032920186310885\n2731,2003-09-01,unemploy,8921.0,0.4923028341359438\n2732,2003-10-01,unemploy,8732.0,0.47738217415331174\n2733,2003-11-01,unemploy,8576.0,0.46506670877082185\n2734,2003-12-01,unemploy,8317.0,0.444619878424252\n2735,2004-01-01,unemploy,8370.0,0.44880397884266204\n2736,2004-02-01,unemploy,8167.0,0.43277808478724245\n2737,2004-03-01,unemploy,8491.0,0.45835635904318306\n2738,2004-04-01,unemploy,8170.0,0.43301492065998265\n2739,2004-05-01,unemploy,8212.0,0.4363306228783453\n2740,2004-06-01,unemploy,8286.0,0.4421725744059367\n2741,2004-07-01,unemploy,8136.0,0.4303307807689271\n2742,2004-08-01,unemploy,7990.0,0.4188047682955712\n2743,2004-09-01,unemploy,7927.0,0.41383121496802716\n2744,2004-10-01,unemploy,8061.0,0.42440988395042234\n2745,2004-11-01,unemploy,7932.0,0.41422594142259417\n2746,2004-12-01,unemploy,7934.0,0.4143838320044209\n2747,2005-01-01,unemploy,7784.0,0.40254203836741137\n2748,2005-02-01,unemploy,7980.0,0.4180153153864372\n2749,2005-03-01,unemploy,7737.0,0.3988316096944817\n2750,2005-04-01,unemploy,7672.0,0.3937001657851109\n2751,2005-05-01,unemploy,7651.0,0.3920423146759296\n2752,2005-06-01,unemploy,7524.0,0.38201626272992817\n2753,2005-07-01,unemploy,7406.0,0.3727007184021473\n2754,2005-08-01,unemploy,7345.0,0.3678850556564301\n2755,2005-09-01,unemploy,7553.0,0.3843056761664167\n2756,2005-10-01,unemploy,7453.0,0.37641114707507695\n2757,2005-11-01,unemploy,7566.0,0.38533196494829086\n2758,2005-12-01,unemploy,7279.0,0.3626746664561459\n2759,2006-01-01,unemploy,7064.0,0.3457014289097655\n2760,2006-02-01,unemploy,7184.0,0.3551748638193732\n2761,2006-03-01,unemploy,7072.0,0.34633299123707273\n2762,2006-04-01,unemploy,7120.0,0.3501223652009158\n2763,2006-05-01,unemploy,6980.0,0.3390700244730402\n2764,2006-06-01,unemploy,7001.0,0.3407278755822215\n2765,2006-07-01,unemploy,7175.0,0.3544643562011526\n2766,2006-08-01,unemploy,7091.0,0.34783295176442725\n2767,2006-09-01,unemploy,6847.0,0.32857030078155836\n2768,2006-10-01,unemploy,6727.0,0.31909686587195074\n2769,2006-11-01,unemploy,6872.0,0.3305439330543933\n2770,2006-12-01,unemploy,6762.0,0.3218599510539196\n2771,2007-01-01,unemploy,7116.0,0.34980658403726217\n2772,2007-02-01,unemploy,6927.0,0.33488592405463014\n2773,2007-03-01,unemploy,6731.0,0.31941264703560435\n2774,2007-04-01,unemploy,6850.0,0.32880713665429856\n2775,2007-05-01,unemploy,6766.0,0.32217573221757323\n2776,2007-06-01,unemploy,6979.0,0.3389910791821268\n2777,2007-07-01,unemploy,7149.0,0.3524117786374043\n2778,2007-08-01,unemploy,7067.0,0.3459382647825057\n2779,2007-09-01,unemploy,7170.0,0.3540696297465856\n2780,2007-10-01,unemploy,7237.0,0.35935896423778324\n2781,2007-11-01,unemploy,7240.0,0.3595958001105234\n2782,2007-12-01,unemploy,7645.0,0.3915686429304492\n2783,2008-01-01,unemploy,7685.0,0.3947264545669851\n2784,2008-02-01,unemploy,7497.0,0.37988473987526644\n2785,2008-03-01,unemploy,7822.0,0.40554195942212046\n2786,2008-04-01,unemploy,7637.0,0.39093708060314203\n2787,2008-05-01,unemploy,8395.0,0.45077761111549697\n2788,2008-06-01,unemploy,8575.0,0.46498776347990844\n2789,2008-07-01,unemploy,8937.0,0.49356595879055815\n2790,2008-08-01,unemploy,9438.0,0.53311754953817\n2791,2008-09-01,unemploy,9494.0,0.5375384858293203\n2792,2008-10-01,unemploy,10074.0,0.5833267545590906\n2793,2008-11-01,unemploy,10538.0,0.6199573695429068\n2794,2008-12-01,unemploy,11286.0,0.6790084471461277\n2795,2009-01-01,unemploy,12058.0,0.7399542117312702\n2796,2009-02-01,unemploy,12898.0,0.8062682560985237\n2797,2009-03-01,unemploy,13426.0,0.8479513697007973\n2798,2009-04-01,unemploy,13853.0,0.8816610089208179\n2799,2009-05-01,unemploy,14499.0,0.9326596668508723\n2800,2009-06-01,unemploy,14707.0,0.9490802873608589\n2801,2009-07-01,unemploy,14601.0,0.9407120865240388\n2802,2009-08-01,unemploy,14814.0,0.9575274334885924\n2803,2009-09-01,unemploy,15009.0,0.9729217652167048\n2804,2009-10-01,unemploy,15352.0,1.0\n2805,2009-11-01,unemploy,15219.0,0.9895002763085182\n2806,2009-12-01,unemploy,15098.0,0.9799478961079972\n2807,2010-01-01,unemploy,15046.0,0.9758427409805005\n2808,2010-02-01,unemploy,15113.0,0.9811320754716981\n2809,2010-03-01,unemploy,15202.0,0.9881582063629905\n2810,2010-04-01,unemploy,15325.0,0.9978684771453383\n2811,2010-05-01,unemploy,14849.0,0.9602905186705613\n2812,2010-06-01,unemploy,14474.0,0.9306860345780374\n2813,2010-07-01,unemploy,14512.0,0.9336859556327465\n2814,2010-08-01,unemploy,14648.0,0.9444225151969685\n2815,2010-09-01,unemploy,14579.0,0.9389752901239441\n2816,2010-10-01,unemploy,14516.0,0.9340017367964001\n2817,2010-11-01,unemploy,15081.0,0.9786058261624694\n2818,2010-12-01,unemploy,14348.0,0.9207389279229494\n2819,2011-01-01,unemploy,14013.0,0.8942922554669614\n2820,2011-02-01,unemploy,13820.0,0.8790558143206758\n2821,2011-03-01,unemploy,13737.0,0.8725033551748638\n2822,2011-04-01,unemploy,13957.0,0.8898713191758112\n2823,2011-05-01,unemploy,13855.0,0.8818188995026447\n2824,2011-06-01,unemploy,13962.0,0.8902660456303781\n2825,2011-07-01,unemploy,13763.0,0.8745559327386121\n2826,2011-08-01,unemploy,13818.0,0.878897923738849\n2827,2011-09-01,unemploy,13948.0,0.8891608115575906\n2828,2011-10-01,unemploy,13594.0,0.8612141785742481\n2829,2011-11-01,unemploy,13302.0,0.8381621536275361\n2830,2011-12-01,unemploy,13093.0,0.8216625878266361\n2831,2012-01-01,unemploy,12797.0,0.7982947817162707\n2832,2012-02-01,unemploy,12813.0,0.799557906370885\n2833,2012-03-01,unemploy,12713.0,0.7916633772795453\n2834,2012-04-01,unemploy,12646.0,0.7863740427883477\n2835,2012-05-01,unemploy,12660.0,0.7874792768611353\n2836,2012-06-01,unemploy,12692.0,0.7900055261703639\n2837,2012-07-01,unemploy,12656.0,0.7871634956974817\n2838,2012-08-01,unemploy,12471.0,0.7725586168785032\n2839,2012-09-01,unemploy,12115.0,0.7444540933133339\n2840,2012-10-01,unemploy,12124.0,0.7451646009315545\n2841,2012-11-01,unemploy,12005.0,0.7357701113128602\n2842,2012-12-01,unemploy,12298.0,0.7589010815504855\n2843,2013-01-01,unemploy,12471.0,0.7725586168785032\n2844,2013-02-01,unemploy,11950.0,0.7314281203126234\n2845,2013-03-01,unemploy,11689.0,0.7108233993842268\n2846,2013-04-01,unemploy,11760.0,0.7164285150390779\n2847,2013-05-01,unemploy,11654.0,0.7080603142022578\n2848,2013-06-01,unemploy,11751.0,0.7157180074208573\n2849,2013-07-01,unemploy,11335.0,0.6828767664008842\n2850,2013-08-01,unemploy,11279.0,0.678455830109734\n2851,2013-09-01,unemploy,11270.0,0.6777453224915134\n2852,2013-10-01,unemploy,11136.0,0.6671666535091182\n2853,2013-11-01,unemploy,10787.0,0.6396147469803426\n2854,2013-12-01,unemploy,10404.0,0.6093787005605116\n2855,2014-01-01,unemploy,10202.0,0.5934317517960054\n2856,2014-02-01,unemploy,10349.0,0.6050367095602748\n2857,2014-03-01,unemploy,10380.0,0.60748401357859\n2858,2014-04-01,unemploy,9702.0,0.5539591063393069\n2859,2014-05-01,unemploy,9859.0,0.5663535170127102\n2860,2014-06-01,unemploy,9460.0,0.5348543459382648\n2861,2014-07-01,unemploy,9608.0,0.5465382489934475\n2862,2014-08-01,unemploy,9599.0,0.5458277413752269\n2863,2014-09-01,unemploy,9262.0,0.5192231783374122\n2864,2014-10-01,unemploy,8990.0,0.4977500592089682\n2865,2014-11-01,unemploy,9090.0,0.5056445883003079\n2866,2014-12-01,unemploy,8717.0,0.4761979947896108\n2867,2015-01-01,unemploy,8903.0,0.49088181889950266\n2868,2015-02-01,unemploy,8610.0,0.4677508486618773\n2869,2015-03-01,unemploy,8504.0,0.4593826478250572\n2870,2015-04-01,unemploy,8526.0,0.46111944422515194\n",
  :format {:type "csv"}}}

3.7 Delayed transformation

Instead of the hanami/plot function, it is possible to used hanami/base:

(-> datasets/economics-long
    (tc/select-rows #(-> % :variable (= "unemploy")))
    (hanami/base hanami/line-chart
                {:=x :date
                 :=y :value
                 :=mark-color "purple"}))

The result is displayed the same way, but the internal representation delays the Hanami transformation of templates.

Let us compare the two:

(-> datasets/economics-long
    (tc/select-rows #(-> % :variable (= "unemploy")))
    (hanami/plot hanami/line-chart
                {:=x :date
                 :=y :value
                 :=mark-color "purple"})
    kind/pprint)

{:encoding
 {:x {:field :date, :type :temporal},
  :y {:field :value, :type :quantitative}},
 :usermeta {:embedOptions {:renderer :svg}},
 :mark {:type "line", :color "purple", :tooltip true},
 :width 400,
 :background "floralwhite",
 :height 300,
 :data
 {:values
  "rownames,date,variable,value,value01\n2297,1967-07-01,unemploy,2944.0,0.020446830346569828\n2298,1967-08-01,unemploy,2945.0,0.020525775637483226\n2299,1967-09-01,unemploy,2958.0,0.021552064419357385\n2300,1967-10-01,unemploy,3143.0,0.036156943238335834\n2301,1967-11-01,unemploy,3066.0,0.030078155838004262\n2302,1967-12-01,unemploy,3018.0,0.026288781874161206\n2303,1968-01-01,unemploy,2878.0,0.015236441146285624\n2304,1968-02-01,unemploy,3001.0,0.024946711928633458\n2305,1968-03-01,unemploy,2877.0,0.015157495855372228\n2306,1968-04-01,unemploy,2709.0,0.0018946869819215285\n2307,1968-05-01,unemploy,2740.0,0.004341991000236836\n2308,1968-06-01,unemploy,2938.0,0.019973158601089443\n2309,1968-07-01,unemploy,2883.0,0.01563116760085261\n2310,1968-08-01,unemploy,2768.0,0.006552459145811952\n2311,1968-09-01,unemploy,2686.0,7.894529091339702E-5\n2312,1968-10-01,unemploy,2689.0,3.157811636535881E-4\n2313,1968-11-01,unemploy,2715.0,0.0023683587274019105\n2314,1968-12-01,unemploy,2685.0,0.0\n2315,1969-01-01,unemploy,2718.0,0.0026051946001421017\n2316,1969-02-01,unemploy,2692.0,5.526170363937791E-4\n2317,1969-03-01,unemploy,2712.0,0.0021315228546617193\n2318,1969-04-01,unemploy,2758.0,0.005763006236677982\n2319,1969-05-01,unemploy,2713.0,0.0022104681455751164\n2320,1969-06-01,unemploy,2816.0,0.010341833109655009\n2321,1969-07-01,unemploy,2868.0,0.014446988237151653\n2322,1969-08-01,unemploy,2856.0,0.01349964474619089\n2323,1969-09-01,unemploy,3040.0,0.02802557827425594\n2324,1969-10-01,unemploy,3049.0,0.028736085892476514\n2325,1969-11-01,unemploy,2856.0,0.01349964474619089\n2326,1969-12-01,unemploy,2884.0,0.015710112891766007\n2327,1970-01-01,unemploy,3201.0,0.04073577011131286\n2328,1970-02-01,unemploy,3453.0,0.06062998342148891\n2329,1970-03-01,unemploy,3635.0,0.07499802636772716\n2330,1970-04-01,unemploy,3797.0,0.08778716349569748\n2331,1970-05-01,unemploy,3919.0,0.09741848898713192\n2332,1970-06-01,unemploy,4071.0,0.10941817320596826\n2333,1970-07-01,unemploy,4175.0,0.11762848346096155\n2334,1970-08-01,unemploy,4256.0,0.1240230520249467\n2335,1970-09-01,unemploy,4456.0,0.13981211020762613\n2336,1970-10-01,unemploy,4591.0,0.1504697244809347\n2337,1970-11-01,unemploy,4898.0,0.1747059287913476\n2338,1970-12-01,unemploy,5076.0,0.18875819057393226\n2339,1971-01-01,unemploy,4986.0,0.18165311439172654\n2340,1971-02-01,unemploy,4903.0,0.1751006552459146\n2341,1971-03-01,unemploy,4987.0,0.18173205968263992\n2342,1971-04-01,unemploy,4959.0,0.17952159153706482\n2343,1971-05-01,unemploy,4996.0,0.1824425673008605\n2344,1971-06-01,unemploy,4949.0,0.17873213862793083\n2345,1971-07-01,unemploy,5035.0,0.185521433646483\n2346,1971-08-01,unemploy,5134.0,0.1933370174469093\n2347,1971-09-01,unemploy,5042.0,0.18607405068287677\n2348,1971-10-01,unemploy,4954.0,0.17912686508249784\n2349,1971-11-01,unemploy,5161.0,0.19546854030157101\n2350,1971-12-01,unemploy,5154.0,0.19491592326517723\n2351,1972-01-01,unemploy,5019.0,0.18425830899186862\n2352,1972-02-01,unemploy,4928.0,0.1770742875187495\n2353,1972-03-01,unemploy,5038.0,0.18575826951922317\n2354,1972-04-01,unemploy,4959.0,0.17952159153706482\n2355,1972-05-01,unemploy,4922.0,0.17660061577326913\n2356,1972-06-01,unemploy,4923.0,0.17667956106418253\n2357,1972-07-01,unemploy,4913.0,0.17589010815504855\n2358,1972-08-01,unemploy,4939.0,0.17794268571879687\n2359,1972-09-01,unemploy,4849.0,0.17083760953659113\n2360,1972-10-01,unemploy,4875.0,0.17289018710033946\n2361,1972-11-01,unemploy,4602.0,0.15133812268098207\n2362,1972-12-01,unemploy,4543.0,0.14668035051709166\n2363,1973-01-01,unemploy,4326.0,0.1295492223888845\n2364,1973-02-01,unemploy,4452.0,0.13949632904397252\n2365,1973-03-01,unemploy,4394.0,0.1349175021709955\n2366,1973-04-01,unemploy,4459.0,0.1400489460803663\n2367,1973-05-01,unemploy,4329.0,0.1297860582616247\n2368,1973-06-01,unemploy,4363.0,0.13247019815268019\n2369,1973-07-01,unemploy,4305.0,0.12789137127970315\n2370,1973-08-01,unemploy,4305.0,0.12789137127970315\n2371,1973-09-01,unemploy,4350.0,0.13144390937080602\n2372,1973-10-01,unemploy,4144.0,0.11518117944264625\n2373,1973-11-01,unemploy,4396.0,0.1350753927528223\n2374,1973-12-01,unemploy,4489.0,0.1424173048077682\n2375,1974-01-01,unemploy,4644.0,0.15465382489934476\n2376,1974-02-01,unemploy,4731.0,0.1615220652088103\n2377,1974-03-01,unemploy,4634.0,0.15386437199021077\n2378,1974-04-01,unemploy,4618.0,0.15260124733559643\n2379,1974-05-01,unemploy,4705.0,0.15946948764506197\n2380,1974-06-01,unemploy,4927.0,0.1769953422278361\n2381,1974-07-01,unemploy,5063.0,0.1877319017920581\n2382,1974-08-01,unemploy,5022.0,0.18449514486460883\n2383,1974-09-01,unemploy,5437.0,0.21725744059366858\n2384,1974-10-01,unemploy,5523.0,0.22404673561222074\n2385,1974-11-01,unemploy,6140.0,0.27275598010578667\n2386,1974-12-01,unemploy,6636.0,0.3119128443988316\n2387,1975-01-01,unemploy,7501.0,0.38020052103892005\n2388,1975-02-01,unemploy,7520.0,0.38170048156627456\n2389,1975-03-01,unemploy,7978.0,0.4178574248046104\n2390,1975-04-01,unemploy,8210.0,0.4361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oy,6927.0,0.33488592405463014\n2773,2007-03-01,unemploy,6731.0,0.31941264703560435\n2774,2007-04-01,unemploy,6850.0,0.32880713665429856\n2775,2007-05-01,unemploy,6766.0,0.32217573221757323\n2776,2007-06-01,unemploy,6979.0,0.3389910791821268\n2777,2007-07-01,unemploy,7149.0,0.3524117786374043\n2778,2007-08-01,unemploy,7067.0,0.3459382647825057\n2779,2007-09-01,unemploy,7170.0,0.3540696297465856\n2780,2007-10-01,unemploy,7237.0,0.35935896423778324\n2781,2007-11-01,unemploy,7240.0,0.3595958001105234\n2782,2007-12-01,unemploy,7645.0,0.3915686429304492\n2783,2008-01-01,unemploy,7685.0,0.3947264545669851\n2784,2008-02-01,unemploy,7497.0,0.37988473987526644\n2785,2008-03-01,unemploy,7822.0,0.40554195942212046\n2786,2008-04-01,unemploy,7637.0,0.39093708060314203\n2787,2008-05-01,unemploy,8395.0,0.45077761111549697\n2788,2008-06-01,unemploy,8575.0,0.46498776347990844\n2789,2008-07-01,unemploy,8937.0,0.49356595879055815\n2790,2008-08-01,unemploy,9438.0,0.53311754953817\n2791,2008-09-01,unemploy,9494.0,0.5375384858293203\n2792,2008-10-01,unemploy,10074.0,0.5833267545590906\n2793,2008-11-01,unemploy,10538.0,0.6199573695429068\n2794,2008-12-01,unemploy,11286.0,0.6790084471461277\n2795,2009-01-01,unemploy,12058.0,0.7399542117312702\n2796,2009-02-01,unemploy,12898.0,0.8062682560985237\n2797,2009-03-01,unemploy,13426.0,0.8479513697007973\n2798,2009-04-01,unemploy,13853.0,0.8816610089208179\n2799,2009-05-01,unemploy,14499.0,0.9326596668508723\n2800,2009-06-01,unemploy,14707.0,0.9490802873608589\n2801,2009-07-01,unemploy,14601.0,0.9407120865240388\n2802,2009-08-01,unemploy,14814.0,0.9575274334885924\n2803,2009-09-01,unemploy,15009.0,0.9729217652167048\n2804,2009-10-01,unemploy,15352.0,1.0\n2805,2009-11-01,unemploy,15219.0,0.9895002763085182\n2806,2009-12-01,unemploy,15098.0,0.9799478961079972\n2807,2010-01-01,unemploy,15046.0,0.9758427409805005\n2808,2010-02-01,unemploy,15113.0,0.9811320754716981\n2809,2010-03-01,unemploy,15202.0,0.9881582063629905\n2810,2010-04-01,unemploy,15325.0,0.9978684771453383\n2811,2010-05-01,unemploy,14849.0,0.9602905186705613\n2812,2010-06-01,unemploy,14474.0,0.9306860345780374\n2813,2010-07-01,unemploy,14512.0,0.9336859556327465\n2814,2010-08-01,unemploy,14648.0,0.9444225151969685\n2815,2010-09-01,unemploy,14579.0,0.9389752901239441\n2816,2010-10-01,unemploy,14516.0,0.9340017367964001\n2817,2010-11-01,unemploy,15081.0,0.9786058261624694\n2818,2010-12-01,unemploy,14348.0,0.9207389279229494\n2819,2011-01-01,unemploy,14013.0,0.8942922554669614\n2820,2011-02-01,unemploy,13820.0,0.8790558143206758\n2821,2011-03-01,unemploy,13737.0,0.8725033551748638\n2822,2011-04-01,unemploy,13957.0,0.8898713191758112\n2823,2011-05-01,unemploy,13855.0,0.8818188995026447\n2824,2011-06-01,unemploy,13962.0,0.8902660456303781\n2825,2011-07-01,unemploy,13763.0,0.8745559327386121\n2826,2011-08-01,unemploy,13818.0,0.878897923738849\n2827,2011-09-01,unemploy,13948.0,0.8891608115575906\n2828,2011-10-01,unemploy,13594.0,0.8612141785742481\n2829,2011-11-01,unemploy,13302.0,0.8381621536275361\n2830,2011-12-01,unemploy,13093.0,0.8216625878266361\n2831,2012-01-01,unemploy,12797.0,0.7982947817162707\n2832,2012-02-01,unemploy,12813.0,0.799557906370885\n2833,2012-03-01,unemploy,12713.0,0.7916633772795453\n2834,2012-04-01,unemploy,12646.0,0.7863740427883477\n2835,2012-05-01,unemploy,12660.0,0.7874792768611353\n2836,2012-06-01,unemploy,12692.0,0.7900055261703639\n2837,2012-07-01,unemploy,12656.0,0.7871634956974817\n2838,2012-08-01,unemploy,12471.0,0.7725586168785032\n2839,2012-09-01,unemploy,12115.0,0.7444540933133339\n2840,2012-10-01,unemploy,12124.0,0.7451646009315545\n2841,2012-11-01,unemploy,12005.0,0.7357701113128602\n2842,2012-12-01,unemploy,12298.0,0.7589010815504855\n2843,2013-01-01,unemploy,12471.0,0.7725586168785032\n2844,2013-02-01,unemploy,11950.0,0.7314281203126234\n2845,2013-03-01,unemploy,11689.0,0.7108233993842268\n2846,2013-04-01,unemploy,11760.0,0.7164285150390779\n2847,2013-05-01,unemploy,11654.0,0.7080603142022578\n2848,2013-06-01,unemploy,11751.0,0.7157180074208573\n2849,2013-07-01,unemploy,11335.0,0.6828767664008842\n2850,2013-08-01,unemploy,11279.0,0.678455830109734\n2851,2013-09-01,unemploy,11270.0,0.6777453224915134\n2852,2013-10-01,unemploy,11136.0,0.6671666535091182\n2853,2013-11-01,unemploy,10787.0,0.6396147469803426\n2854,2013-12-01,unemploy,10404.0,0.6093787005605116\n2855,2014-01-01,unemploy,10202.0,0.5934317517960054\n2856,2014-02-01,unemploy,10349.0,0.6050367095602748\n2857,2014-03-01,unemploy,10380.0,0.60748401357859\n2858,2014-04-01,unemploy,9702.0,0.5539591063393069\n2859,2014-05-01,unemploy,9859.0,0.5663535170127102\n2860,2014-06-01,unemploy,9460.0,0.5348543459382648\n2861,2014-07-01,unemploy,9608.0,0.5465382489934475\n2862,2014-08-01,unemploy,9599.0,0.5458277413752269\n2863,2014-09-01,unemploy,9262.0,0.5192231783374122\n2864,2014-10-01,unemploy,8990.0,0.4977500592089682\n2865,2014-11-01,unemploy,9090.0,0.5056445883003079\n2866,2014-12-01,unemploy,8717.0,0.4761979947896108\n2867,2015-01-01,unemploy,8903.0,0.49088181889950266\n2868,2015-02-01,unemploy,8610.0,0.4677508486618773\n2869,2015-03-01,unemploy,8504.0,0.4593826478250572\n2870,2015-04-01,unemploy,8526.0,0.46111944422515194\n",
  :format {:type "csv"}}}

(-> datasets/economics-long
    (tc/select-rows #(-> % :variable (= "unemploy")))
    (hanami/base hanami/line-chart
                {:=x :date
                 :=y :value
                 :=mark-color "purple"})
    kind/pprint)

{:encoding :=encoding,
 :usermeta :=usermeta,
 :mark
 {:type "line",
  :color :=mark-color,
  :size :=mark-size,
  :opacity :=mark-opacity,
  :tooltip :=mark-tooltip},
 :width :=width,
 :background :=background,
 :title :=title,
 :layer :=layer,
 :kindly/f #'scicloj.tableplot.v1.hanami/vega-lite-xform,
 :aerial.hanami.templates/defaults
 {:=x2 :com.rpl.specter.impl/NONE,
  :=base-dataset ggplot2/economics_long [574 5]:

| :rownames |      :date | :variable | :value |   :value01 |
|----------:|------------|-----------|-------:|-----------:|
|      2297 | 1967-07-01 |  unemploy | 2944.0 | 0.02044683 |
|      2298 | 1967-08-01 |  unemploy | 2945.0 | 0.02052578 |
|      2299 | 1967-09-01 |  unemploy | 2958.0 | 0.02155206 |
|      2300 | 1967-10-01 |  unemploy | 3143.0 | 0.03615694 |
|      2301 | 1967-11-01 |  unemploy | 3066.0 | 0.03007816 |
|      2302 | 1967-12-01 |  unemploy | 3018.0 | 0.02628878 |
|      2303 | 1968-01-01 |  unemploy | 2878.0 | 0.01523644 |
|      2304 | 1968-02-01 |  unemploy | 3001.0 | 0.02494671 |
|      2305 | 1968-03-01 |  unemploy | 2877.0 | 0.01515750 |
|      2306 | 1968-04-01 |  unemploy | 2709.0 | 0.00189469 |
|       ... |        ... |       ... |    ... |        ... |
|      2860 | 2014-06-01 |  unemploy | 9460.0 | 0.53485435 |
|      2861 | 2014-07-01 |  unemploy | 9608.0 | 0.54653825 |
|      2862 | 2014-08-01 |  unemploy | 9599.0 | 0.54582774 |
|      2863 | 2014-09-01 |  unemploy | 9262.0 | 0.51922318 |
|      2864 | 2014-10-01 |  unemploy | 8990.0 | 0.49775006 |
|      2865 | 2014-11-01 |  unemploy | 9090.0 | 0.50564459 |
|      2866 | 2014-12-01 |  unemploy | 8717.0 | 0.47619799 |
|      2867 | 2015-01-01 |  unemploy | 8903.0 | 0.49088182 |
|      2868 | 2015-02-01 |  unemploy | 8610.0 | 0.46775085 |
|      2869 | 2015-03-01 |  unemploy | 8504.0 | 0.45938265 |
|      2870 | 2015-04-01 |  unemploy | 8526.0 | 0.46111944 |
,
  :=layer [],
  :=y-type #function[clojure.lang.AFunction/1],
  :=x2-encoding #function[clojure.lang.AFunction/1],
  :=opacity :com.rpl.specter.impl/NONE,
  :=y2-after-stat :=y2,
  :=x2-after-stat :=x2,
  :=usermeta {:embedOptions {:renderer :=renderer}},
  :=title :com.rpl.specter.impl/NONE,
  :=y-type-after-stat #function[clojure.lang.AFunction/1],
  :=height 300,
  :=renderer :svg,
  :=mark-opacity :com.rpl.specter.impl/NONE,
  :=y-title :com.rpl.specter.impl/NONE,
  :=size :com.rpl.specter.impl/NONE,
  :=group #function[clojure.lang.AFunction/1],
  :=mark-size :com.rpl.specter.impl/NONE,
  :=layer? :com.rpl.specter.impl/NONE,
  :=size-type #function[clojure.lang.AFunction/1],
  :=layer-dataset ggplot2/economics_long [574 5]:

| :rownames |      :date | :variable | :value |   :value01 |
|----------:|------------|-----------|-------:|-----------:|
|      2297 | 1967-07-01 |  unemploy | 2944.0 | 0.02044683 |
|      2298 | 1967-08-01 |  unemploy | 2945.0 | 0.02052578 |
|      2299 | 1967-09-01 |  unemploy | 2958.0 | 0.02155206 |
|      2300 | 1967-10-01 |  unemploy | 3143.0 | 0.03615694 |
|      2301 | 1967-11-01 |  unemploy | 3066.0 | 0.03007816 |
|      2302 | 1967-12-01 |  unemploy | 3018.0 | 0.02628878 |
|      2303 | 1968-01-01 |  unemploy | 2878.0 | 0.01523644 |
|      2304 | 1968-02-01 |  unemploy | 3001.0 | 0.02494671 |
|      2305 | 1968-03-01 |  unemploy | 2877.0 | 0.01515750 |
|      2306 | 1968-04-01 |  unemploy | 2709.0 | 0.00189469 |
|       ... |        ... |       ... |    ... |        ... |
|      2860 | 2014-06-01 |  unemploy | 9460.0 | 0.53485435 |
|      2861 | 2014-07-01 |  unemploy | 9608.0 | 0.54653825 |
|      2862 | 2014-08-01 |  unemploy | 9599.0 | 0.54582774 |
|      2863 | 2014-09-01 |  unemploy | 9262.0 | 0.51922318 |
|      2864 | 2014-10-01 |  unemploy | 8990.0 | 0.49775006 |
|      2865 | 2014-11-01 |  unemploy | 9090.0 | 0.50564459 |
|      2866 | 2014-12-01 |  unemploy | 8717.0 | 0.47619799 |
|      2867 | 2015-01-01 |  unemploy | 8903.0 | 0.49088182 |
|      2868 | 2015-02-01 |  unemploy | 8610.0 | 0.46775085 |
|      2869 | 2015-03-01 |  unemploy | 8504.0 | 0.45938265 |
|      2870 | 2015-04-01 |  unemploy | 8526.0 | 0.46111944 |
,
  :=color :com.rpl.specter.impl/NONE,
  :=mark-color "purple",
  :=x :date,
  :=y2 :com.rpl.specter.impl/NONE,
  :=x-after-stat :=x,
  :DFMT {:type "csv"},
  :=encoding
  {:color {:field :=color, :type :=color-type},
   :size {:field :=size, :type :=size-type},
   :x
   {:field :=x-after-stat,
    :type :=x-type-after-stat,
    :title :=x-title,
    :bin :=x-bin},
   :y
   {:field :=y-after-stat,
    :type :=y-type-after-stat,
    :title :=y-title,
    :bin :=y-bin},
   :x2 :=x2-encoding,
   :y2 :=y2-encoding},
  :=x-type-after-stat #function[clojure.lang.AFunction/1],
  :=x-bin :com.rpl.specter.impl/NONE,
  :=x-type #function[clojure.lang.AFunction/1],
  :=histogram-nbins 10,
  :=stat :com.rpl.specter.impl/NONE,
  :=width 400,
  :=color-type #function[clojure.lang.AFunction/1],
  :=mark "circle",
  :=dataset-after-stat #function[clojure.lang.AFunction/1],
  :=y-bin :com.rpl.specter.impl/NONE,
  :=x-title :com.rpl.specter.impl/NONE,
  :=csv-data #function[clojure.lang.AFunction/1],
  :=y :value,
  :=data {:values :=csv-data, :format {:type "csv"}},
  :=dataset #function[clojure.lang.AFunction/1],
  :VALDATA :=csv-data,
  :=mark-tooltip true,
  :=background "floralwhite",
  :=y-after-stat :=y,
  :=predictors [:=x],
  :=y2-encoding #function[clojure.lang.AFunction/1]},
 :height :=height,
 :data :=data}

The structure returned by hanami/base is a Hanami template (with local defaults). When it is displayed, it goes through the Hanami transform to recieve the Vega-Lite spec.

When we use base, we can keep processing the template in a pipeline of transformations. We will use it soon with layers.

3.8 Adding layers

A base plot does not need to have a specified chart. Instead, we may add layers:

(-> datasets/economics-long
    (tc/select-rows #(-> % :variable (= "unemploy")))
    (hanami/base {:=x :date
                 :=y :value
                 :=mark-color "purple"})
    hanami/layer-line)

The substitution keys can also be specified on the layer level:

(-> datasets/economics-long
    (tc/select-rows #(-> % :variable (= "unemploy")))
    (hanami/base {:=x :date
                 :=y :value})
    (hanami/layer-line {:=mark-color "purple"}))

This allows us to create, e.g., aesthetic differences between layers:

(-> datasets/economics-long
    (tc/select-rows #(-> % :variable (= "unemploy")))
    (hanami/base {:=x :date
                 :=y :value})
    (hanami/layer-point {:=mark-color "green"
                        :=mark-size 200
                        :=mark-opacity 0.1})
    (hanami/layer-line {:=mark-color "purple"}))

We can also skip the base and have everything in the layer:

(-> datasets/economics-long
    (tc/select-rows #(-> % :variable (= "unemploy")))
    (hanami/layer-line {:=x :date
                       :=y :value
                       :=mark-color "purple"}))

3.9 Updating data

Using hanami/update-data, we may process the dataset during the pipeline, affecting only the layers added further down the pipeline.

This functionality is inspired by ggbuilder and metamorph.

(-> datasets/economics-long
    (tc/select-rows #(-> % :variable (= "unemploy")))
    (hanami/base {:=x :date
                 :=y :value})
    (hanami/layer-line {:=mark-color "purple"})
    (hanami/update-data tc/random 5)
    (hanami/layer-point {:=mark-color "green"
                        :=mark-size 200}))

You see, we have lots of data for the lines, but only five random points.

3.10 Processing raw vega-lite

During a pipeline, we may call hanami/plot to apply the Hanami transform and realize the Vega-Lite spec.

(-> datasets/economics-long
    (tc/select-rows #(-> % :variable (= "unemploy")))
    (hanami/base {:=x :date
                 :=y :value})
    (hanami/layer-line {:=mark-color "purple"})
    (hanami/update-data tc/random 5)
    (hanami/layer-point {:=mark-color "green"
                        :=mark-size 200})
    hanami/plot
    kind/pprint)

{:encoding
 {:x {:field :date, :type :temporal},
  :y {:field :value, :type :quantitative}},
 :usermeta {:embedOptions {:renderer :svg}},
 :width 400,
 :background "floralwhite",
 :layer
 [{:mark {:type "line", :color "purple", :tooltip true},
   :encoding
   {:x {:field :date, :type :temporal},
    :y {:field :value, :type :quantitative}},
   :data
   {:values
    "rownames,date,variable,value,value01\n2297,1967-07-01,unemploy,2944.0,0.020446830346569828\n2298,1967-08-01,unemploy,2945.0,0.020525775637483226\n2299,1967-09-01,unemploy,2958.0,0.021552064419357385\n2300,1967-10-01,unemploy,3143.0,0.036156943238335834\n2301,1967-11-01,unemploy,3066.0,0.030078155838004262\n2302,1967-12-01,unemploy,3018.0,0.026288781874161206\n2303,1968-01-01,unemploy,2878.0,0.015236441146285624\n2304,1968-02-01,unemploy,3001.0,0.024946711928633458\n2305,1968-03-01,unemploy,2877.0,0.015157495855372228\n2306,1968-04-01,unemploy,2709.0,0.0018946869819215285\n2307,1968-05-01,unemploy,2740.0,0.004341991000236836\n2308,1968-06-01,unemploy,2938.0,0.019973158601089443\n2309,1968-07-01,unemploy,2883.0,0.01563116760085261\n2310,1968-08-01,unemploy,2768.0,0.006552459145811952\n2311,1968-09-01,unemploy,2686.0,7.894529091339702E-5\n2312,1968-10-01,unemploy,2689.0,3.157811636535881E-4\n2313,1968-11-01,unemploy,2715.0,0.0023683587274019105\n2314,1968-12-01,unemploy,2685.0,0.0\n2315,1969-01-01,unemploy,2718.0,0.0026051946001421017\n2316,1969-02-01,unemploy,2692.0,5.526170363937791E-4\n2317,1969-03-01,unemploy,2712.0,0.0021315228546617193\n2318,1969-04-01,unemploy,2758.0,0.005763006236677982\n2319,1969-05-01,unemploy,2713.0,0.0022104681455751164\n2320,1969-06-01,unemploy,2816.0,0.010341833109655009\n2321,1969-07-01,unemploy,2868.0,0.014446988237151653\n2322,1969-08-01,unemploy,2856.0,0.01349964474619089\n2323,1969-09-01,unemploy,3040.0,0.02802557827425594\n2324,1969-10-01,unemploy,3049.0,0.028736085892476514\n2325,1969-11-01,unemploy,2856.0,0.01349964474619089\n2326,1969-12-01,unemploy,2884.0,0.015710112891766007\n2327,1970-01-01,unemploy,3201.0,0.04073577011131286\n2328,1970-02-01,unemploy,3453.0,0.06062998342148891\n2329,1970-03-01,unemploy,3635.0,0.07499802636772716\n2330,1970-04-01,unemploy,3797.0,0.08778716349569748\n2331,1970-05-01,unemploy,3919.0,0.09741848898713192\n2332,1970-06-01,unemploy,4071.0,0.10941817320596826\n2333,1970-07-01,unemploy,4175.0,0.11762848346096155\n2334,1970-08-01,unemploy,4256.0,0.1240230520249467\n2335,1970-09-01,unemploy,4456.0,0.13981211020762613\n2336,1970-10-01,unemploy,4591.0,0.1504697244809347\n2337,1970-11-01,unemploy,4898.0,0.1747059287913476\n2338,1970-12-01,unemploy,5076.0,0.18875819057393226\n2339,1971-01-01,unemploy,4986.0,0.18165311439172654\n2340,1971-02-01,unemploy,4903.0,0.1751006552459146\n2341,1971-03-01,unemploy,4987.0,0.18173205968263992\n2342,1971-04-01,unemploy,4959.0,0.17952159153706482\n2343,1971-05-01,unemploy,4996.0,0.1824425673008605\n2344,1971-06-01,unemploy,4949.0,0.17873213862793083\n2345,1971-07-01,unemploy,5035.0,0.185521433646483\n2346,1971-08-01,unemploy,5134.0,0.1933370174469093\n2347,1971-09-01,unemploy,5042.0,0.18607405068287677\n2348,1971-10-01,unemploy,4954.0,0.17912686508249784\n2349,1971-11-01,unemploy,5161.0,0.19546854030157101\n2350,1971-12-01,unemploy,5154.0,0.19491592326517723\n2351,1972-01-01,unemploy,5019.0,0.18425830899186862\n2352,1972-02-01,unemploy,4928.0,0.1770742875187495\n2353,1972-03-01,unemploy,5038.0,0.18575826951922317\n2354,1972-04-01,unemploy,4959.0,0.17952159153706482\n2355,1972-05-01,unemploy,4922.0,0.17660061577326913\n2356,1972-06-01,unemploy,4923.0,0.17667956106418253\n2357,1972-07-01,unemploy,4913.0,0.17589010815504855\n2358,1972-08-01,unemploy,4939.0,0.17794268571879687\n2359,1972-09-01,unemploy,4849.0,0.17083760953659113\n2360,1972-10-01,unemploy,4875.0,0.17289018710033946\n2361,1972-11-01,unemploy,4602.0,0.15133812268098207\n2362,1972-12-01,unemploy,4543.0,0.14668035051709166\n2363,1973-01-01,unemploy,4326.0,0.1295492223888845\n2364,1973-02-01,unemploy,4452.0,0.13949632904397252\n2365,1973-03-01,unemploy,4394.0,0.1349175021709955\n2366,1973-04-01,unemploy,4459.0,0.1400489460803663\n2367,1973-05-01,unemploy,4329.0,0.1297860582616247\n2368,1973-06-01,unemploy,4363.0,0.13247019815268019\n2369,1973-07-01,unemploy,4305.0,0.12789137127970315\n2370,1973-08-01,unemploy,4305.0,0.12789137127970315\n2371,1973-09-01,unemploy,4350.0,0.13144390937080602\n2372,1973-10-01,unemploy,4144.0,0.11518117944264625\n2373,1973-11-01,unemploy,4396.0,0.1350753927528223\n2374,1973-12-01,unemploy,4489.0,0.1424173048077682\n2375,1974-01-01,unemploy,4644.0,0.15465382489934476\n2376,1974-02-01,unemploy,4731.0,0.1615220652088103\n2377,1974-03-01,unemploy,4634.0,0.15386437199021077\n2378,1974-04-01,unemploy,4618.0,0.15260124733559643\n2379,1974-05-01,unemploy,4705.0,0.15946948764506197\n2380,1974-06-01,unemploy,4927.0,0.1769953422278361\n2381,1974-07-01,unemploy,5063.0,0.1877319017920581\n2382,1974-08-01,unemploy,5022.0,0.18449514486460883\n2383,1974-09-01,unemploy,5437.0,0.21725744059366858\n2384,1974-10-01,unemploy,5523.0,0.22404673561222074\n2385,1974-11-01,unemploy,6140.0,0.27275598010578667\n2386,1974-12-01,unemploy,6636.0,0.3119128443988316\n2387,1975-01-01,unemploy,7501.0,0.38020052103892005\n2388,1975-02-01,unemploy,7520.0,0.38170048156627456\n2389,1975-03-01,unemploy,7978.0,0.4178574248046104\n2390,1975-04-01,unemploy,8210.0,0.4361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oy,6927.0,0.33488592405463014\n2773,2007-03-01,unemploy,6731.0,0.31941264703560435\n2774,2007-04-01,unemploy,6850.0,0.32880713665429856\n2775,2007-05-01,unemploy,6766.0,0.32217573221757323\n2776,2007-06-01,unemploy,6979.0,0.3389910791821268\n2777,2007-07-01,unemploy,7149.0,0.3524117786374043\n2778,2007-08-01,unemploy,7067.0,0.3459382647825057\n2779,2007-09-01,unemploy,7170.0,0.3540696297465856\n2780,2007-10-01,unemploy,7237.0,0.35935896423778324\n2781,2007-11-01,unemploy,7240.0,0.3595958001105234\n2782,2007-12-01,unemploy,7645.0,0.3915686429304492\n2783,2008-01-01,unemploy,7685.0,0.3947264545669851\n2784,2008-02-01,unemploy,7497.0,0.37988473987526644\n2785,2008-03-01,unemploy,7822.0,0.40554195942212046\n2786,2008-04-01,unemploy,7637.0,0.39093708060314203\n2787,2008-05-01,unemploy,8395.0,0.45077761111549697\n2788,2008-06-01,unemploy,8575.0,0.46498776347990844\n2789,2008-07-01,unemploy,8937.0,0.49356595879055815\n2790,2008-08-01,unemploy,9438.0,0.53311754953817\n2791,2008-09-01,unemploy,9494.0,0.5375384858293203\n2792,2008-10-01,unemploy,10074.0,0.5833267545590906\n2793,2008-11-01,unemploy,10538.0,0.6199573695429068\n2794,2008-12-01,unemploy,11286.0,0.6790084471461277\n2795,2009-01-01,unemploy,12058.0,0.7399542117312702\n2796,2009-02-01,unemploy,12898.0,0.8062682560985237\n2797,2009-03-01,unemploy,13426.0,0.8479513697007973\n2798,2009-04-01,unemploy,13853.0,0.8816610089208179\n2799,2009-05-01,unemploy,14499.0,0.9326596668508723\n2800,2009-06-01,unemploy,14707.0,0.9490802873608589\n2801,2009-07-01,unemploy,14601.0,0.9407120865240388\n2802,2009-08-01,unemploy,14814.0,0.9575274334885924\n2803,2009-09-01,unemploy,15009.0,0.9729217652167048\n2804,2009-10-01,unemploy,15352.0,1.0\n2805,2009-11-01,unemploy,15219.0,0.9895002763085182\n2806,2009-12-01,unemploy,15098.0,0.9799478961079972\n2807,2010-01-01,unemploy,15046.0,0.9758427409805005\n2808,2010-02-01,unemploy,15113.0,0.9811320754716981\n2809,2010-03-01,unemploy,15202.0,0.9881582063629905\n2810,2010-04-01,unemploy,15325.0,0.9978684771453383\n2811,2010-05-01,unemploy,14849.0,0.9602905186705613\n2812,2010-06-01,unemploy,14474.0,0.9306860345780374\n2813,2010-07-01,unemploy,14512.0,0.9336859556327465\n2814,2010-08-01,unemploy,14648.0,0.9444225151969685\n2815,2010-09-01,unemploy,14579.0,0.9389752901239441\n2816,2010-10-01,unemploy,14516.0,0.9340017367964001\n2817,2010-11-01,unemploy,15081.0,0.9786058261624694\n2818,2010-12-01,unemploy,14348.0,0.9207389279229494\n2819,2011-01-01,unemploy,14013.0,0.8942922554669614\n2820,2011-02-01,unemploy,13820.0,0.8790558143206758\n2821,2011-03-01,unemploy,13737.0,0.8725033551748638\n2822,2011-04-01,unemploy,13957.0,0.8898713191758112\n2823,2011-05-01,unemploy,13855.0,0.8818188995026447\n2824,2011-06-01,unemploy,13962.0,0.8902660456303781\n2825,2011-07-01,unemploy,13763.0,0.8745559327386121\n2826,2011-08-01,unemploy,13818.0,0.878897923738849\n2827,2011-09-01,unemploy,13948.0,0.8891608115575906\n2828,2011-10-01,unemploy,13594.0,0.8612141785742481\n2829,2011-11-01,unemploy,13302.0,0.8381621536275361\n2830,2011-12-01,unemploy,13093.0,0.8216625878266361\n2831,2012-01-01,unemploy,12797.0,0.7982947817162707\n2832,2012-02-01,unemploy,12813.0,0.799557906370885\n2833,2012-03-01,unemploy,12713.0,0.7916633772795453\n2834,2012-04-01,unemploy,12646.0,0.7863740427883477\n2835,2012-05-01,unemploy,12660.0,0.7874792768611353\n2836,2012-06-01,unemploy,12692.0,0.7900055261703639\n2837,2012-07-01,unemploy,12656.0,0.7871634956974817\n2838,2012-08-01,unemploy,12471.0,0.7725586168785032\n2839,2012-09-01,unemploy,12115.0,0.7444540933133339\n2840,2012-10-01,unemploy,12124.0,0.7451646009315545\n2841,2012-11-01,unemploy,12005.0,0.7357701113128602\n2842,2012-12-01,unemploy,12298.0,0.7589010815504855\n2843,2013-01-01,unemploy,12471.0,0.7725586168785032\n2844,2013-02-01,unemploy,11950.0,0.7314281203126234\n2845,2013-03-01,unemploy,11689.0,0.7108233993842268\n2846,2013-04-01,unemploy,11760.0,0.7164285150390779\n2847,2013-05-01,unemploy,11654.0,0.7080603142022578\n2848,2013-06-01,unemploy,11751.0,0.7157180074208573\n2849,2013-07-01,unemploy,11335.0,0.6828767664008842\n2850,2013-08-01,unemploy,11279.0,0.678455830109734\n2851,2013-09-01,unemploy,11270.0,0.6777453224915134\n2852,2013-10-01,unemploy,11136.0,0.6671666535091182\n2853,2013-11-01,unemploy,10787.0,0.6396147469803426\n2854,2013-12-01,unemploy,10404.0,0.6093787005605116\n2855,2014-01-01,unemploy,10202.0,0.5934317517960054\n2856,2014-02-01,unemploy,10349.0,0.6050367095602748\n2857,2014-03-01,unemploy,10380.0,0.60748401357859\n2858,2014-04-01,unemploy,9702.0,0.5539591063393069\n2859,2014-05-01,unemploy,9859.0,0.5663535170127102\n2860,2014-06-01,unemploy,9460.0,0.5348543459382648\n2861,2014-07-01,unemploy,9608.0,0.5465382489934475\n2862,2014-08-01,unemploy,9599.0,0.5458277413752269\n2863,2014-09-01,unemploy,9262.0,0.5192231783374122\n2864,2014-10-01,unemploy,8990.0,0.4977500592089682\n2865,2014-11-01,unemploy,9090.0,0.5056445883003079\n2866,2014-12-01,unemploy,8717.0,0.4761979947896108\n2867,2015-01-01,unemploy,8903.0,0.49088181889950266\n2868,2015-02-01,unemploy,8610.0,0.4677508486618773\n2869,2015-03-01,unemploy,8504.0,0.4593826478250572\n2870,2015-04-01,unemploy,8526.0,0.46111944422515194\n",
  :format {:type "csv"}}}

While this in itself does not affect the display of the plot, it allows us to keep editing it as a Vega-Lite spec. For example, let us change the backgound colour this way:

(-> datasets/economics-long
    (tc/select-rows #(-> % :variable (= "unemploy")))
    (hanami/base {:=x :date
                 :=y :value})
    (hanami/layer-line {:=mark-color "purple"})
    (hanami/update-data tc/random 5)
    (hanami/layer-point {:=mark-color "green"
                        :=mark-size 200})
    hanami/plot
    (assoc :background "lightgrey"))

For another example, let us change the y scale to logarithmic. See Scale in the Vega-Lite documentation.

(-> datasets/economics-long
    (tc/select-rows #(-> % :variable (= "unemploy")))
    (hanami/base {:=x :date
                 :=y :value})
    (hanami/layer-line {:=mark-color "purple"})
    (hanami/update-data tc/random 5)
    (hanami/layer-point {:=mark-color "green"
                        :=mark-size 200})
    hanami/plot
    (assoc-in [:encoding :y :scale :type] "log"))

3.11 Smoothing

hanami/layer-smooth is a layer that applies some statistical processing to the dataset to model it as a smooth shape. It is inspired by ggplot’s geom_smooth.

At the moment, it can only be used to model :=y by linear regression. Soon we will add more ways of modelling the data.

(-> datasets/iris
    (hanami/base {:=title "dummy"
                 :=mark-color "green"
                 :=x :sepal-width
                 :=y :sepal-length})
    hanami/layer-point
    (hanami/layer-smooth {:=mark-color "orange"}))

By default, the regression is computed with only one predictor variable, which is :=x. But this can be overriden using the :predictors key. We may compute a regression with more than one predictor.

(-> datasets/iris
    (hanami/base {:=x :sepal-width
                 :=y :sepal-length})
    hanami/layer-point
    (hanami/layer-smooth {:=predictors [:petal-width
                                       :petal-length]}))

3.12 Grouping

The regression computed by hanami/layer-smooth is affected by the inferred grouping of the data.

For example, here we recieve three regression lines, each for every species.

(-> datasets/iris
    (hanami/base {:=title "dummy"
                 :=color :species
                 :=x :sepal-width
                 :=y :sepal-length})
    hanami/layer-point
    hanami/layer-smooth)

This happened because the :color field was :species, which is of :nominal type.

But we may override this using the :group key. For example, let us avoid grouping:

(-> datasets/iris
    (hanami/base {:=title "dummy"
                 :=mark-color "green"
                 :=color :species
                 :=group []
                 :=x :sepal-width
                 :=y :sepal-length})
    hanami/layer-point
    hanami/layer-smooth)

3.13 Example: out-of-sample predictions

Here is a slighly more elaborate example inpired by the London Clojurians talk mentioned in the preface.

Assume we wish to predict the unemployment rate for 96 months. Let us add those months to our dataset, and mark them as Future (considering the original data as Past):

(-> datasets/economics-long
    (tc/select-rows #(-> % :variable (= "unemploy")))
    (tc/add-column :relative-time "Past")
    (tc/concat (tc/dataset {:date (-> datasets/economics-long
                                      :date
                                      last
                                      (datetime/plus-temporal-amount (range 96) :days))
                            :relative-time "Future"}))
    (print/print-range 6))

ggplot2/economics_long [670 6]:

:rownames	:date	:variable	:value	:value01	:relative-time
2297	1967-07-01	unemploy	2944.0	0.02044683	Past
2298	1967-08-01	unemploy	2945.0	0.02052578	Past
2299	1967-09-01	unemploy	2958.0	0.02155206	Past
…	…	…	…	…	…
	2015-07-02				Future
	2015-07-03				Future
	2015-07-04				Future
	2015-07-05				Future

Let us represent our dates as numbers, so that we can use them in linear regression:

(-> datasets/economics-long
    (tc/select-rows #(-> % :variable (= "unemploy")))
    (tc/add-column :relative-time "Past")
    (tc/concat (tc/dataset {:date (-> datasets/economics-long
                                      :date
                                      last
                                      (datetime/plus-temporal-amount (range 96) :months))
                            :relative-time "Future"}))
    (tc/add-column :year #(datetime/long-temporal-field :years (:date %)))
    (tc/add-column :month #(datetime/long-temporal-field :months (:date %)))
    (tc/map-columns :yearmonth [:year :month] (fn [y m] (+ m (* 12 y))))
    (print/print-range 6))

ggplot2/economics_long [670 9]:

:rownames	:date	:variable	:value	:value01	:relative-time	:year	:month	:yearmonth
2297	1967-07-01	unemploy	2944.0	0.02044683	Past	1967	7	23611
2298	1967-08-01	unemploy	2945.0	0.02052578	Past	1967	8	23612
2299	1967-09-01	unemploy	2958.0	0.02155206	Past	1967	9	23613
…	…	…	…	…	…	…	…	…
	2022-12-01				Future	2022	12	24276
	2023-01-01				Future	2023	1	24277
	2023-02-01				Future	2023	2	24278
	2023-03-01				Future	2023	3	24279

Let us use the same regression line for the Past and Future groups. To do this, we avoid grouping by assigning [] to :=group. The line is affected only by the past, since in the Future, :=y is missing. We use the numerical field :yearmonth as the regression predictor, but for plotting, we still use the :temporal field :date.

(-> datasets/economics-long
    (tc/select-rows #(-> % :variable (= "unemploy")))
    (tc/add-column :relative-time "Past")
    (tc/concat (tc/dataset {:date (-> datasets/economics-long
                                      :date
                                      last
                                      (datetime/plus-temporal-amount (range 96) :months))
                            :relative-time "Future"}))
    (tc/add-column :year #(datetime/long-temporal-field :years (:date %)))
    (tc/add-column :month #(datetime/long-temporal-field :months (:date %)))
    (tc/map-columns :yearmonth [:year :month] (fn [y m] (+ m (* 12 y))))
    (hanami/base {:=x :date
                 :=y :value})
    (hanami/layer-smooth {:=color :relative-time
                         :=mark-size 10
                         :=group []
                         :=predictors [:yearmonth]})
    ;; Keep only the past for the following layer:
    (hanami/update-data (fn [dataset]
                         (-> dataset
                             (tc/select-rows (fn [row]
                                               (-> row :relative-time (= "Past")))))))
    (hanami/layer-line {:=mark-color "purple"
                       :=mark-size 3}))

3.14 Histograms

Histograms can also be represented as layers with statistical processing:

(-> datasets/iris
    (hanami/layer-histogram {:=x :sepal-width}))

(-> datasets/iris
    (hanami/layer-histogram {:=x :sepal-width
                            :=histogram-nbins 30}))

source: notebooks/tableplot_book/hanami_walkthrough.clj