Plotly javascript loaded.
\n", "To load again call
init_notebook(true)\n", " " ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stderr", "output_type": "stream", "text": [ "WARNING: Method definition describe(AbstractArray) in module StatsBase at /Users/mrestrep/.julia/v0.5/StatsBase/src/scalarstats.jl:573 overwritten in module DataFrames at /Users/mrestrep/.julia/v0.5/DataFrames/src/abstractdataframe/abstractdataframe.jl:407.\n" ] } ], "source": [ "using PlotlyJS\n", "using DataFrames, RDatasets" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "# Basics\n", "\n", "## Simple line scatter\n", "\n", "* First define your traces with x, y as keyword inputs\n", "* Pass the trace to the plot() function" ] }, { "cell_type": "code", "execution_count": 27, "metadata": { "slideshow": { "slide_type": "-" } }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "WARNING: Method definition linescatter() in module Main at In[8]:2 overwritten at In[27]:2.\n" ] }, { "data": { "application/vnd.plotly.v1+json": "{\"layout\":{\"margin\":{\"r\":50,\"l\":50,\"b\":50,\"t\":60}},\"data\":[{\"y\":[10,15,13,18],\"type\":\"scatter\",\"x\":[1,2,3,4]}]}", "text/html": [ "\n", "\n", "\n" ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ "function linescatter()\n", " trace1 = scatter(;x=1:4, y=[10, 15, 13, 18])\n", " plot(trace1)\n", "end\n", "linescatter()" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "### Customize and add multiple traces to one plot\n", "\n", "* Customize markers vs lines: Trace attributes are part of the trace definition\n", "* Multiple traces in one plot: Define multiple traces and pass them as an array to plot()\n", "* [JavaScript Docs](https://plot.ly/javascript/line-charts/)" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "slideshow": { "slide_type": "-" } }, "outputs": [ { "data": { "application/vnd.plotly.v1+json": "{\"layout\":{\"margin\":{\"r\":50,\"l\":50,\"b\":50,\"t\":60}},\"data\":[{\"y\":[10,15,13,17],\"name\":\"marker only\",\"type\":\"scatter\",\"x\":[1,2,3,4],\"mode\":\"markers\"},{\"y\":[16,5,11,9],\"name\":\"line\",\"type\":\"scatter\",\"x\":[1,2,3,4],\"mode\":\"lines\"},{\"y\":[12,9,15,12],\"name\":\"line+marker\",\"type\":\"scatter\",\"x\":[1,2,3,4],\"mode\":\"lines+markers\"},{\"y\":[5,10,8,12],\"name\":\"dash\",\"type\":\"scatter\",\"line\":{\"dash\":\"dash\"},\"x\":[1,2,3,4],\"mode\":\"lines\"}]}", "text/html": [ "\n", "\n", "\n" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "function multiple_scatter_traces()\n", " trace1 = scatter(;x=1:4, y=[10, 15, 13, 17], mode=\"markers\", name=\"marker only\")\n", " trace2 = scatter(;x=1:4, y=[16, 5, 11, 9], mode=\"lines\", name=\"line\")\n", " trace3 = scatter(;x=1:4, y=[12, 9, 15, 12], mode=\"lines+markers\", name=\"line+marker\")\n", " trace4 = scatter(;x=1:4, y=[5, 10, 8, 12], mode=\"lines\", line_dash=\"dash\", name=\"dash\")\n", " plot([trace1, trace2, trace3, trace4])\n", "end\n", "multiple_scatter_traces()" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "### Data labels and Figure Layout\n", "\n", "* Add the array of labels as an attribute to each trace\n", "* Layout modifies the \"Figure Pane Attributes\"" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "scrolled": true, "slideshow": { "slide_type": "-" } }, "outputs": [ { "data": { "application/vnd.plotly.v1+json": "{\"layout\":{\"yaxis\":{\"range\":[0,8]},\"legend\":{\"y\":0.5,\"size\":20,\"yref\":\"paper\",\"color\":\"grey\",\"family\":\"Arial, sans-serif\"},\"xaxis\":{\"range\":[0.75,5.25]},\"title\":\"Data Labels on the Plot\",\"margin\":{\"r\":50,\"l\":50,\"b\":50,\"t\":60}},\"data\":[{\"y\":[1,6,3,6,1],\"text\":[\"A-1\",\"A-2\",\"A-3\",\"A-4\",\"A-5\"],\"textfont\":{\"family\":\"Raleway, sans-serif\"},\"name\":\"Team A\",\"type\":\"scatter\",\"x\":[1,2,3,4,5],\"textposition\":\"top center\",\"mode\":\"markers+text\",\"marker\":{\"size\":12}},{\"y\":[4,1,7,1,4],\"text\":[\"B-a\",\"B-b\",\"B-c\",\"B-d\",\"B-e\"],\"textfont\":{\"family\":\"Times New Roman\"},\"name\":\"Team B\",\"type\":\"scatter\",\"x\":[1.0,2.0,3.0,4.0,5.0],\"textposition\":\"bottom center\",\"mode\":\"markers+text\",\"marker\":{\"size\":12}}]}", "text/html": [ "\n", "\n", "\n" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "function data_labels()\n", " trace1 = scatter(;x=1:5, y=[1, 6, 3, 6, 1],\n", " mode=\"markers+text\", name=\"Team A\",\n", " textposition=\"top center\",\n", " text=[\"A-1\", \"A-2\", \"A-3\", \"A-4\", \"A-5\"],\n", " marker_size=12, textfont_family=\"Raleway, sans-serif\")\n", "\n", " trace2 = scatter(;x=1:5+0.5, y=[4, 1, 7, 1, 4],\n", " mode=\"markers+text\", name= \"Team B\",\n", " textposition=\"bottom center\",\n", " text= [\"B-a\", \"B-b\", \"B-c\", \"B-d\", \"B-e\"],\n", " marker_size=12, textfont_family=\"Times New Roman\")\n", "\n", " data = [trace1, trace2]\n", "\n", " layout = Layout(;title=\"Data Labels on the Plot\", xaxis_range=[0.75, 5.25],\n", " yaxis_range=[0, 8], legend_y=0.5, legend_yref=\"paper\",\n", " legend=attr(family=\"Arial, sans-serif\", size=20,\n", " color=\"grey\"))\n", " plot(data, layout)\n", "end\n", "data_labels()" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "## Area" ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "slideshow": { "slide_type": "-" } }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "WARNING: Method definition area1() in module Main at In[17]:2 overwritten at In[18]:2.\n" ] }, { "data": { "application/vnd.plotly.v1+json": "{\"layout\":{\"margin\":{\"r\":50,\"l\":50,\"b\":50,\"t\":60}},\"data\":[{\"y\":[0,2,3,5],\"type\":\"scatter\",\"x\":[1,2,3,4],\"fill\":\"tozeroy\"},{\"y\":[3,5,1,7],\"type\":\"scatter\",\"x\":[1,2,3,4],\"fill\":\"tonexty\"}]}", "text/html": [ "\n", "\n", "\n" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "function area1()\n", " trace1 = scatter(;x=1:4, y=[0, 2, 3, 5], fill=\"tozeroy\")\n", " trace2 = scatter(;x=1:4, y=[3, 5, 1, 7], fill=\"tonexty\")\n", " plot([trace1, trace2])\n", "end\n", "area1()" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "## Other visual interpretations of Matrix Data and Subplots\n", "\n", "* Easy - just cancatenate plots, but...\n", "* 3d subplots are buggy" ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "slideshow": { "slide_type": "-" } }, "outputs": [ { "data": { "application/vnd.plotly.v1+json": 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"text/html": [ "\n", "\n", "\n" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "function matrix_subplots()\n", " z = rand(10,10)\n", " trace0 = scatter(; y=z)\n", "\n", " trace1 = heatmap(; z=z, showscale=false)\n", " trace2 = contour(; z=z)\n", " trace3 = surface(; z=z)\n", " p = [plot(trace1) plot(trace2)]\n", "end\n", "\n", "matrix_subplots()" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "## Advanced Layouts\n", "\n", "* Much more verbose\n", "* Fine-control of position of each element (powerful but time consuming)\n", "\n", "#### Challenge: Finish the layout" ] }, { "cell_type": "code", "execution_count": 20, "metadata": { "slideshow": { "slide_type": "-" } }, "outputs": [ { "data": { "application/vnd.plotly.v1+json": "{\"layout\":{\"xaxis3\":{\"domain\":[0.33,0.53],\"anchor\":\"y3\"},\"xaxis\":{\"domain\":[0.0,0.3]},\"yaxis2\":{\"domain\":[0.0,0.27],\"anchor\":\"x2\"},\"margin\":{\"r\":50,\"l\":50,\"b\":50,\"t\":60},\"xaxis2\":{\"domain\":[0.33,0.53],\"anchor\":\"y2\"},\"yaxis3\":{\"domain\":[0.33,0.63],\"anchor\":\"x3\"}},\"data\":[{\"y\":[0.9434053340973867,0.7751357194541428,0.7203334131419472,0.9553202782480761,0.03468305655839776,0.7194359950437361,0.9149380987374718,0.39976050044402234,0.14170019170778292,0.41279374442260575],\"type\":\"scatter\",\"mode\":\"markers\"},{\"yaxis\":\"y2\",\"y\":[0.7018803153466173,0.002205432245784067,0.42265252137482934,0.3721349122504365,0.8074509988012406,0.7381093605169611,0.9166931520308792,0.6588874196667196,0.9891215244039537,0.8937035805847835],\"type\":\"bar\",\"xaxis\":\"x2\"},{\"yaxis\":\"y3\",\"y\":[0.8438634675632299,0.30607184311841706,0.16238817283920381,0.9666039982700734,0.5383173383480508,0.2510677267911694,0.6130223652927922,0.05914057817374352,0.11428445318944513,0.05302031967124088],\"type\":\"scatter\",\"xaxis\":\"x3\"}]}", "text/html": [ "\n", "\n", "\n" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "function advanced_layouts()\n", " trace1 = scatter(;y=rand(10), mode=\"markers\")\n", " trace2 = bar(;y=rand(10), xaxis=\"x2\", yaxis=\"y2\")\n", " trace3 = scatter(;y=rand(10), xaxis=\"x3\", yaxis=\"y3\")\n", "\n", " data = [trace1, trace2, trace3]\n", " xdomains = [[0,0.3], [0.33, 0.53] , [0.56, 0.78], [0.8, 1] ]\n", " ydomains = [[0,1], [0, 0.27] , [0.33, 0.63], [0.66, 1] ]\n", " layout = Layout(; xaxis_domain=xdomains[1], \n", " xaxis2_domain=xdomains[2], yaxis2_domain=ydomains[2],yaxis2_anchor=\"x2\", xaxis2_anchor=\"y2\",\n", " xaxis3_domain=xdomains[2], yaxis3_domain=ydomains[3],yaxis3_anchor=\"x3\", xaxis3_anchor=\"y3\"\n", " )\n", " plot(data, layout)\n", "end\n", "p1 = advanced_layouts()" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "## Stats Plots" ] }, { "cell_type": "code", "execution_count": 21, "metadata": { "slideshow": { "slide_type": "-" } }, "outputs": [ { "data": { "application/vnd.plotly.v1+json": "{\"layout\":{\"barmode\":\"group\",\"margin\":{\"r\":50,\"l\":50,\"b\":50,\"t\":60}},\"data\":[{\"y\":[20,14,23],\"name\":\"SF Zoo\",\"type\":\"bar\",\"x\":[\"giraffes\",\"orangutans\",\"monkeys\"]},{\"y\":[12,18,29],\"name\":\"LA Zoo\",\"type\":\"bar\",\"x\":[\"giraffes\",\"orangutans\",\"monkeys\"]}]}", "text/html": [ "\n", "\n", "\n" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "function grouped_bar_example()\n", " trace1 = bar(;x=[\"giraffes\", \"orangutans\", \"monkeys\"],\n", " y=[20, 14, 23],\n", " name=\"SF Zoo\")\n", " trace2 = bar(;x=[\"giraffes\", \"orangutans\", \"monkeys\"],\n", " y=[12, 18, 29],\n", " name=\"LA Zoo\")\n", " data = [trace1, trace2]\n", " layout = Layout(;barmode=\"group\")\n", " plot(data, layout)\n", "end\n", "\n", "grouped_bar_example()" ] }, { "cell_type": "code", "execution_count": 22, "metadata": { "slideshow": { "slide_type": "slide" } }, "outputs": [ { "data": { "application/vnd.plotly.v1+json": "{\"layout\":{\"barmode\":\"stack\",\"margin\":{\"r\":50,\"l\":50,\"b\":50,\"t\":60}},\"data\":[{\"y\":[20,14,23],\"name\":\"SF Zoo\",\"type\":\"bar\",\"x\":[\"giraffes\",\"orangutans\",\"monkeys\"]},{\"y\":[12,18,29],\"name\":\"LA Zoo\",\"type\":\"bar\",\"x\":[\"giraffes\",\"orangutans\",\"monkeys\"]}]}", "text/html": [ "\n", "\n", "\n" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "function stacked_bar_example()\n", " trace1 = bar(;x=[\"giraffes\", \"orangutans\", \"monkeys\"],\n", " y=[20, 14, 23],\n", " name=\"SF Zoo\")\n", " trace2 = bar(x=[\"giraffes\", \"orangutans\", \"monkeys\"],\n", " y=[12, 18, 29],\n", " name=\"LA Zoo\")\n", " data = [trace1, trace2]\n", " layout = Layout(;barmode=\"stack\")\n", " plot(data, layout)\n", "end\n", "stacked_bar_example()" ] }, { "cell_type": "code", "execution_count": 23, "metadata": { "scrolled": true, "slideshow": { "slide_type": "slide" } }, "outputs": [ { "data": { "application/vnd.plotly.v1+json": 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"text/html": [ "\n", "\n", "\n" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" } ], "source": [ "function two_hists()\n", " x0 = randn(500)\n", " x1 = x0+1\n", "\n", " trace1 = histogram(x=x0, opacity=0.75)\n", " trace2 = histogram(x=x1, opacity=0.75)\n", " data = [trace1, trace2]\n", " layout = Layout(barmode=\"overlay\")\n", " plot(data, layout)\n", "end\n", "\n", "two_hists()" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "## Box (Whisker) Plots\n", "\n", "A box plot is a convenient way of graphically depicting numerical data through their quartiles. The first quartile (Q1) is the middle number between the smallest number and the median of the data set. The second quartile (Q2) is the median of the data. The third quartile (Q3) is the middle value between the median and the highest value of the data set.\n", "Box plots may also have lines extending vertically from the boxes (whiskers) indicating variability outside the upper and lower quartiles. Outliers may be plotted as individual points." ] }, { "cell_type": "code", "execution_count": 24, "metadata": { "slideshow": { "slide_type": "slide" } }, "outputs": [ { "data": { "application/vnd.plotly.v1+json": "{\"layout\":{\"yaxis\":{\"title\":\"normalized moisture\",\"zeroline\":false},\"margin\":{\"r\":50,\"l\":50,\"b\":50,\"t\":60},\"boxmode\":\"group\"},\"data\":[{\"y\":[0.2,0.2,0.6,1.0,0.5,0.4,0.2,0.7,0.9,0.1,0.5,0.3],\"name\":\"kale\",\"type\":\"box\",\"x\":[\"day 1\",\"day 1\",\"day 1\",\"day 1\",\"day 1\",\"day 1\",\"day 2\",\"day 2\",\"day 2\",\"day 2\",\"day 2\",\"day 2\"],\"marker\":{\"color\":\"#3D9970\"}},{\"y\":[0.6,0.7,0.3,0.6,0.0,0.5,0.7,0.9,0.5,0.8,0.7,0.2],\"name\":\"radishes\",\"type\":\"box\",\"x\":[\"day 1\",\"day 1\",\"day 1\",\"day 1\",\"day 1\",\"day 1\",\"day 2\",\"day 2\",\"day 2\",\"day 2\",\"day 2\",\"day 2\"],\"marker\":{\"color\":\"#FF4136\"}},{\"y\":[0.1,0.3,0.1,0.9,0.6,0.6,0.9,1.0,0.3,0.6,0.8,0.5],\"name\":\"carrots\",\"type\":\"box\",\"x\":[\"day 1\",\"day 1\",\"day 1\",\"day 1\",\"day 1\",\"day 1\",\"day 2\",\"day 2\",\"day 2\",\"day 2\",\"day 2\",\"day 2\"],\"marker\":{\"color\":\"#FF851B\"}}]}", "text/html": [ "\n", "\n", "\n" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "function box_plot()\n", " x0 = [\"day 1\", \"day 1\", \"day 1\", \"day 1\", \"day 1\", \"day 1\",\n", " \"day 2\", \"day 2\", \"day 2\", \"day 2\", \"day 2\", \"day 2\"]\n", " trace1 = box(;y=[0.2, 0.2, 0.6, 1.0, 0.5, 0.4, 0.2, 0.7, 0.9, 0.1, 0.5, 0.3],\n", " x=x0,\n", " name=\"kale\",\n", " marker_color=\"#3D9970\")\n", " trace2 = box(;y=[0.6, 0.7, 0.3, 0.6, 0.0, 0.5, 0.7, 0.9, 0.5, 0.8, 0.7, 0.2],\n", " x=x0,\n", " name=\"radishes\",\n", " marker_color=\"#FF4136\")\n", " trace3 = box(;y=[0.1, 0.3, 0.1, 0.9, 0.6, 0.6, 0.9, 1.0, 0.3, 0.6, 0.8, 0.5],\n", " x=x0,\n", " name=\"carrots\",\n", " marker_color=\"#FF851B\")\n", " data = [trace1, trace2, trace3]\n", " layout = Layout(;yaxis=attr(title=\"normalized moisture\", zeroline=false),\n", " boxmode=\"group\")\n", " plot(data, layout)\n", "end\n", "box_plot()" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "### Using DataFrames\n", "\n", "Some documentation lives [here](http://spencerlyon.com/PlotlyJS.jl/building_traces_layouts/#using-dataframes)\n", "and in the [convinience methods section](http://spencerlyon.com/PlotlyJS.jl/syncplots/#convenience-methods)\n", "\n", "#### Challenge: Is it possible to customize the markers of each grooup?" ] }, { "cell_type": "code", "execution_count": 26, "metadata": { "scrolled": true, "slideshow": { "slide_type": "-" } }, "outputs": [ { "data": { "application/vnd.plotly.v1+json": "{\"layout\":{\"margin\":{\"r\":50,\"l\":50,\"b\":50,\"t\":60}},\"data\":[{\"y\":[3.5,3.0,3.2,3.1,3.6,3.9,3.4,3.4,2.9,3.1,3.7,3.4,3.0,3.0,4.0,4.4,3.9,3.5,3.8,3.8,3.4,3.7,3.6,3.3,3.4,3.0,3.4,3.5,3.4,3.2,3.1,3.4,4.1,4.2,3.1,3.2,3.5,3.6,3.0,3.4,3.5,2.3,3.2,3.5,3.8,3.0,3.8,3.2,3.7,3.3],\"name\":\"setosa\",\"type\":\"scatter\",\"x\":[5.1,4.9,4.7,4.6,5.0,5.4,4.6,5.0,4.4,4.9,5.4,4.8,4.8,4.3,5.8,5.7,5.4,5.1,5.7,5.1,5.4,5.1,4.6,5.1,4.8,5.0,5.0,5.2,5.2,4.7,4.8,5.4,5.2,5.5,4.9,5.0,5.5,4.9,4.4,5.1,5.0,4.5,4.4,5.0,5.1,4.8,5.1,4.6,5.3,5.0],\"marker\":{\"size\":8},\"mode\":\"markers\"},{\"y\":[3.2,3.2,3.1,2.3,2.8,2.8,3.3,2.4,2.9,2.7,2.0,3.0,2.2,2.9,2.9,3.1,3.0,2.7,2.2,2.5,3.2,2.8,2.5,2.8,2.9,3.0,2.8,3.0,2.9,2.6,2.4,2.4,2.7,2.7,3.0,3.4,3.1,2.3,3.0,2.5,2.6,3.0,2.6,2.3,2.7,3.0,2.9,2.9,2.5,2.8],\"name\":\"versicolor\",\"type\":\"scatter\",\"x\":[7.0,6.4,6.9,5.5,6.5,5.7,6.3,4.9,6.6,5.2,5.0,5.9,6.0,6.1,5.6,6.7,5.6,5.8,6.2,5.6,5.9,6.1,6.3,6.1,6.4,6.6,6.8,6.7,6.0,5.7,5.5,5.5,5.8,6.0,5.4,6.0,6.7,6.3,5.6,5.5,5.5,6.1,5.8,5.0,5.6,5.7,5.7,6.2,5.1,5.7],\"marker\":{\"size\":8},\"mode\":\"markers\"},{\"y\":[3.3,2.7,3.0,2.9,3.0,3.0,2.5,2.9,2.5,3.6,3.2,2.7,3.0,2.5,2.8,3.2,3.0,3.8,2.6,2.2,3.2,2.8,2.8,2.7,3.3,3.2,2.8,3.0,2.8,3.0,2.8,3.8,2.8,2.8,2.6,3.0,3.4,3.1,3.0,3.1,3.1,3.1,2.7,3.2,3.3,3.0,2.5,3.0,3.4,3.0],\"name\":\"virginica\",\"type\":\"scatter\",\"x\":[6.3,5.8,7.1,6.3,6.5,7.6,4.9,7.3,6.7,7.2,6.5,6.4,6.8,5.7,5.8,6.4,6.5,7.7,7.7,6.0,6.9,5.6,7.7,6.3,6.7,7.2,6.2,6.1,6.4,7.2,7.4,7.9,6.4,6.3,6.1,7.7,6.3,6.4,6.0,6.9,6.7,6.9,5.8,6.8,6.7,6.7,6.3,6.5,6.2,5.9],\"marker\":{\"size\":8},\"mode\":\"markers\"}]}", "text/html": [ "\n", "\n", "\n" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stderr", "output_type": "stream", "text": [ "WARNING: Method definition data_frame_scatter() in module Main at In[25]:2 overwritten at In[26]:2.\n" ] } ], "source": [ "function data_frame_scatter()\n", " iris = dataset(\"datasets\", \"iris\");\n", "# display(head(iris))\n", " my_trace = scatter(iris, x=:SepalLength, y=:SepalWidth, mode=\"markers\", group=:Species)\n", " plot(my_trace)\n", " p = Plot(iris, x=:SepalLength, y=:SepalWidth, mode=\"markers\", marker_size=8, group=:Species)\n", " _p = JupyterPlot(p) #In Atom use _p = ElectronPlot(p)\n", " display(_p)\n", "end\n", "\n", "data_frame_scatter()" ] } ], "metadata": { "celltoolbar": "Slideshow", "kernelspec": { "display_name": "Julia 0.5.1", "language": "julia", "name": "julia-0.5" }, "language_info": { "file_extension": ".jl", "mimetype": "application/julia", "name": "julia", "version": "0.5.1" } }, "nbformat": 4, "nbformat_minor": 2 }