continent=Asia
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
year=%{customdata[1]}
continent=Europe
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
year=%{customdata[1]}
continent=Africa
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
year=%{customdata[1]}
continent=Americas
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
year=%{customdata[1]}
continent=Oceania
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
year=%{customdata[1]}
\n",
" \n",
" \n",
" \n",
" \n",
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"px.scatter(\n",
" gapminder, x=\"gdpPercap\", y=\"lifeExp\", log_x=True,\n",
" color=\"continent\", size=\"pop\", size_max=40,\n",
" hover_name=\"country\", # これだけ！\n",
" hover_data=[\"pop\", \"year\"], # これだけ！\n",
").show()"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"### ホバーツールで得られた情報\n",
"\n",
"- 国名(ホバーツールのタイトル)\n",
"- 座標の具体的な数値\n",
" - 寿命\n",
" - 人口当りGDP\n",
"- 人口\n",
"- 年度"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"### アニメーション\n",
"\n",
"- 静的な画像では表現できないデータを可視化\n",
"- フレームにデータを分割して描画\n",
"- フレームは自動再生したり、特定の位置を指定できる\n",
"- Plotly Expressを使うと超簡単に実装できる\n",
"\n",
""
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"### 散布図をアニメーション化"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"slideshow": {
"slide_type": "fragment"
}
},
"outputs": [
{
"data": {
"application/vnd.plotly.v1+json": {
"config": {
"plotlyServerURL": "https://plot.ly"
},
"data": [
{
"customdata": [
[
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"hovertemplate": "%{hovertext}continent=Asia
year=1952
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Europe
year=1952
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Africa
year=1952
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Americas
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gdpPercap=%{x}
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continent=Oceania
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gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Asia
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gdpPercap=%{x}
lifeExp=%{y}
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continent=Europe
year=1952
gdpPercap=%{x}
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gdpPercap=%{x}
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gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Asia
year=1957
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Europe
year=1957
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Africa
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gdpPercap=%{x}
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continent=Americas
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gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Oceania
year=1957
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Asia
year=1962
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Europe
year=1962
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Africa
year=1962
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Americas
year=1962
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Oceania
year=1962
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Asia
year=1967
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Europe
year=1967
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Africa
year=1967
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Americas
year=1967
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Oceania
year=1967
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Asia
year=1972
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Europe
year=1972
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Africa
year=1972
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Americas
year=1972
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Oceania
year=1972
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Asia
year=1977
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Europe
year=1977
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Africa
year=1977
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Americas
year=1977
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Oceania
year=1977
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Asia
year=1982
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Europe
year=1982
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Africa
year=1982
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Americas
year=1982
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Oceania
year=1982
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Asia
year=1987
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Europe
year=1987
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Africa
year=1987
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Americas
year=1987
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Oceania
year=1987
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Asia
year=1992
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Europe
year=1992
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Africa
year=1992
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Americas
year=1992
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Oceania
year=1992
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Asia
year=1997
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Europe
year=1997
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Africa
year=1997
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Americas
year=1997
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Oceania
year=1997
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Asia
year=2002
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Europe
year=2002
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Africa
year=2002
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Americas
year=2002
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Oceania
year=2002
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Asia
year=2007
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Europe
year=2007
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Africa
year=2007
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Americas
year=2007
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
continent=Oceania
year=2007
gdpPercap=%{x}
lifeExp=%{y}
pop=%{customdata[0]}
\n",
" \n",
" \n",
" \n",
" \n",
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"px.scatter(\n",
" gapminder,\n",
" x=\"gdpPercap\", y=\"lifeExp\", log_x=True,\n",
" size=\"pop\", size_max=40, color=\"continent\",\n",
" hover_name=\"country\", hover_data=[\"pop\"],\n",
" animation_frame=\"year\", # これだけ！\n",
").show()"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"### 階層をもったデータをインタラクティブに\n",
"\n",
"- 親子関係があるデータを可視化\n",
"- 階層が増えると下の階層のデータが多くなり、可視化するとわかりにくくなる\n",
"- ドリルダウンして階層を深堀りできる"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"### サンバーストグラフ"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"slideshow": {
"slide_type": "fragment"
}
},
"outputs": [
{
"data": {
"application/vnd.plotly.v1+json": {
"config": {
"plotlyServerURL": "https://plot.ly"
},
"data": [
{
"branchvalues": "total",
"domain": {
"x": [
0,
1
],
"y": [
0,
1
]
},
"hovertemplate": "labels=%{label}pop=%{value}
parent=%{parent}
id=%{id}
\n",
" \n",
" \n",
" \n",
" \n",
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"gapminder_2007 = gapminder[gapminder[\"year\"] == 2007]\n",
"px.sunburst(\n",
" gapminder_2007, path=[\"continent\", \"country\"], values=\"pop\", title=\"各国の人口\"\n",
").show()"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"### ツリーマップ"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"scrolled": false,
"slideshow": {
"slide_type": "fragment"
}
},
"outputs": [
{
"data": {
"application/vnd.plotly.v1+json": {
"config": {
"plotlyServerURL": "https://plot.ly"
},
"data": [
{
"branchvalues": "total",
"domain": {
"x": [
0,
1
],
"y": [
0,
1
]
},
"hovertemplate": "labels=%{label}pop=%{value}
parent=%{parent}
id=%{id}
\n",
" \n",
" \n",
" \n",
" \n",
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"px.treemap(gapminder_2007, path=[\"continent\", \"country\"], values=\"pop\", title=\"各国の人口\").show()"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"### 要素を移動\n",
"\n",
"- 要素の位置を移動して関係をみやすくできる\n",
" - 平行グラフ\n",
" - ネットワーク図(あとで紹介)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"slideshow": {
"slide_type": "fragment"
}
},
"outputs": [
{
"data": {
"application/vnd.plotly.v1+json": {
"config": {
"plotlyServerURL": "https://plot.ly"
},
"data": [
{
"dimensions": [
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"label": "sex",
"values": [
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},
{
"label": "smoker",
"values": [
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"Yes",
"No",
"Yes",
"No",
"Yes",
"Yes",
"Yes",
"Yes",
"No",
"No",
"No",
"Yes",
"No",
"Yes",
"No",
"No",
"Yes",
"Yes",
"No",
"No",
"Yes",
"No",
"No",
"No",
"Yes",
"No",
"No",
"Yes",
"No",
"No",
"No",
"No",
"No",
"No",
"Yes",
"No",
"Yes",
"Yes",
"No",
"Yes",
"Yes",
"Yes",
"Yes",
"No",
"Yes",
"Yes",
"Yes",
"Yes",
"No",
"Yes",
"Yes",
"Yes",
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"Yes",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"Yes",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"No",
"Yes",
"No",
"No",
"No",
"Yes",
"Yes",
"Yes",
"Yes",
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"Yes",
"Yes",
"Yes",
"Yes",
"Yes",
"Yes",
"Yes",
"Yes",
"Yes",
"Yes",
"Yes",
"Yes",
"No",
"Yes",
"Yes",
"Yes",
"Yes",
"Yes",
"Yes",
"Yes",
"Yes",
"Yes",
"No",
"Yes",
"Yes",
"Yes",
"Yes",
"Yes",
"Yes",
"Yes",
"Yes",
"Yes",
"Yes",
"Yes",
"Yes",
"Yes",
"Yes",
"Yes",
"Yes",
"No",
"Yes",
"Yes",
"Yes",
"Yes",
"Yes",
"Yes",
"Yes",
"Yes",
"Yes",
"Yes",
"No",
"Yes",
"Yes",
"Yes",
"No",
"No",
"Yes",
"Yes",
"Yes",
"No",
"No",
"Yes",
"No",
"Yes",
"Yes",
"No",
"No",
"Yes",
"Yes",
"No",
"No"
]
},
{
"label": "time",
"values": [
"Dinner",
"Dinner",
"Dinner",
"Dinner",
"Dinner",
"Dinner",
"Dinner",
"Dinner",
"Dinner",
"Dinner",
"Dinner",
"Dinner",
"Dinner",
"Dinner",
"Dinner",
"Dinner",
"Dinner",
"Dinner",
"Dinner",
"Dinner",
"Dinner",
"Dinner",
"Dinner",
"Dinner",
"Dinner",
"Dinner",
"Dinner",
"Dinner",
"Dinner",
"Dinner",
"Dinner",
"Dinner",
"Dinner",
"Dinner",
"Dinner",
"Dinner",
"Dinner",
"Dinner",
"Dinner",
"Dinner",
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"polar": {
"angularaxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
},
"bgcolor": "#E5ECF6",
"radialaxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
}
},
"scene": {
"xaxis": {
"backgroundcolor": "#E5ECF6",
"gridcolor": "white",
"gridwidth": 2,
"linecolor": "white",
"showbackground": true,
"ticks": "",
"zerolinecolor": "white"
},
"yaxis": {
"backgroundcolor": "#E5ECF6",
"gridcolor": "white",
"gridwidth": 2,
"linecolor": "white",
"showbackground": true,
"ticks": "",
"zerolinecolor": "white"
},
"zaxis": {
"backgroundcolor": "#E5ECF6",
"gridcolor": "white",
"gridwidth": 2,
"linecolor": "white",
"showbackground": true,
"ticks": "",
"zerolinecolor": "white"
}
},
"shapedefaults": {
"line": {
"color": "#2a3f5f"
}
},
"ternary": {
"aaxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
},
"baxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
},
"bgcolor": "#E5ECF6",
"caxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
}
},
"title": {
"x": 0.05
},
"xaxis": {
"automargin": true,
"gridcolor": "white",
"linecolor": "white",
"ticks": "",
"title": {
"standoff": 15
},
"zerolinecolor": "white",
"zerolinewidth": 2
},
"yaxis": {
"automargin": true,
"gridcolor": "white",
"linecolor": "white",
"ticks": "",
"title": {
"standoff": 15
},
"zerolinecolor": "white",
"zerolinewidth": 2
}
}
}
}
},
"text/html": [
"\n",
" \n",
" \n",
" \n",
" \n",
"
"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"tips = px.data.tips()\n",
"px.parallel_categories(\n",
" tips, dimensions=[\"sex\", \"smoker\", \"time\", \"day\"], color=\"size\"\n",
").show()"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"### インタラクティブな可視化は超簡単\n",
"\n",
"- 引数にデータ(列名)を渡すだけ\n",
"- ホバーツールで探索\n",
"- アニメーションで多次元のデータをわかりやすく\n",
"- ドリルダウンで詳細に\n",
"- 移動してみやすく\n",
"\n",
""
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"### コールバック\n",
"\n",
"- コールバック関数\n",
" - なにかをきっかけに呼び出される関数\n",
" - 必ず実行されるわけではない\n",
"- ハンドラ\n",
" - 特定の条件でコールバック関数を呼び出す\n",
"\n",
""
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"### コールバックの例\n",
"\n",
"時刻が5時のときだけコールバック関数が実行される(※ import文は省略)\n",
"\n",
"```python\n",
"def handler(callback):\n",
" while True:\n",
" if datetime.datetime.now().hour == 5:\n",
" callback()\n",
" time.sleep(360)\n",
"\n",
"def callback():\n",
" print(\"5時です\")\n",
"```"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"### コールバックによるインタラクティブな可視化\n",
"\n",
"- イベント(発生条件)\n",
" - UIを操作\n",
" - グラフの要素を選択\n",
"- 処理(コールバック関数)\n",
" - グラフを描画する\n",
" - 種類を変更する\n",
" - データを変更する\n",
" - スタイルを変更する\n",
" - テーブルを表示する(Dash DataTable)\n",
" - 計器を表示する(Dash Daq)"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"### plotly/Dashのコールバック\n",
"\n",
"- コールバック関数だけを書けばよい\n",
" - デコレータをつけるだけでコールバック関数となる\n",
"- ハンドラ(イベント)はライブラリのものを使う\n",
" - クリックされた\n",
" - 値が変わった\n",
" - UIを操作した"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"### コールバックを利用したグラフ"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"slideshow": {
"slide_type": "fragment"
}
},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "7726fca5f9384f2fa2f89d4b5d870a23",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"FigureWidget({\n",
" 'data': [{'mode': 'markers',\n",
" 'name': '散布図',\n",
" 'text': array(['Afg…"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import plotly.graph_objects as go\n",
"from plotly.subplots import make_subplots\n",
"\n",
"# ❶ 引数にfigureを渡す\n",
"subplots_fig = go.FigureWidget(make_subplots(rows=1, cols=2))\n",
"subplots_fig.add_trace(\n",
" go.Scatter(\n",
" x=gapminder[\"gdpPercap\"],\n",
" y=gapminder[\"lifeExp\"],\n",
" text=gapminder[\"country\"],\n",
" mode=\"markers\",\n",
" name=\"散布図\",\n",
" ),\n",
" row=1,\n",
" col=1,\n",
")\n",
"subplots_fig.add_trace(go.Scatter(name=\"時系列データ\"), row=1, col=2)\n",
"trace0, trace1 = subplots_fig.data\n",
"title_text = \"1人当りGDPと平均余命の散布図（左図）\" \"と平均余命の時系列データ（右図）\"\n",
"subplots_fig.update_layout(title={\"text\": title_text})\n",
"# 軸ラベル\n",
"subplots_fig.update_xaxes(title=\"1人当りGDP\", type=\"log\", row=1, col=1)\n",
"subplots_fig.update_xaxes(title=\"年\", row=1, col=2)\n",
"subplots_fig.update_yaxes(title=\"平均余命\")\n",
"\n",
"\n",
"def update_line(trace, points, selector): # ❷\n",
" n = points.point_inds[0]\n",
" country = gapminder.iloc[n, 0] # ❸ インデックスから国名を取得\n",
" # ❸ countryから選択された国名のデータを抽出\n",
" country_df = gapminder.loc[gapminder[\"country\"] == country].sort_values(\"year\")\n",
" trace1.x = country_df[\"year\"] # ❹\n",
" trace1.y = country_df[\"lifeExp\"] # ❹\n",
" subplots_fig.update_layout( # ❺\n",
" annotations=[\n",
" {\n",
" \"x\": 1,\n",
" \"y\": 1.1,\n",
" \"showarrow\": False,\n",
" \"text\": country,\n",
" \"xref\": \"paper\",\n",
" \"yref\": \"paper\",\n",
" }\n",
" ]\n",
" )\n",
"\n",
"\n",
"trace0.on_click(update_line)\n",
"subplots_fig"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "slide"
}
},
"source": [
"## Dashによるインタラクティブな可視化\n",
"\n",
"![](\"https://regeld.xsrv.jp/desi/wp-content/uploads/2019/04/Information1904_4_Illustration.png\")
"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"### Dash\n",
"\n",
"- データ可視化のWebフレームワーク\n",
" - ダッシュボードが簡単に作れる\n",
"- フロントエンドの知識なしでUIを実装できる\n",
"- plotlyのグラフが利用できる\n",
"- HTMLコンポーネントを利用して柔軟なレイアウトを実装\n",
" - HTMLの知識があるとレイアウトが自由に組める\n",
" - CSSの知識があると見た目を綺麗にできる"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"### DashによるUIを実装したグラフ\n",
"\n",
"- demo: https://stapy61-dash-sample.herokuapp.com\n",
"- source: [dash_sample.py](https://github.com/drillan/stapy61/blob/master/dash_sample.py)"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"### Jupyter Dash\n",
"\n",
"- Jupyter上からDashを実行\n",
"- Colabにも対応\n",
"- Jupyterでデータを処理しながらDashで可視化できる"
]
},
{
"cell_type": "markdown",
"metadata": {
"slideshow": {
"slide_type": "subslide"
}
},
"source": [
"### Jupyter Dashのデモ"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"slideshow": {
"slide_type": "fragment"
}
},
"outputs": [],
"source": [
"import dash\n",
"from jupyter_dash import JupyterDash\n",
"import dash_core_components as dcc\n",
"import dash_html_components as html\n",
"from dash.dependencies import Input, Output\n",
"\n",
"JupyterDash.infer_jupyter_proxy_config()"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"scrolled": false,
"slideshow": {
"slide_type": "fragment"
}
},
"outputs": [],
"source": [
"external_stylesheets = [\"https://codepen.io/chriddyp/pen/bWLwgP.css\"]\n",
"app = JupyterDash(__name__, external_stylesheets=external_stylesheets)\n",
"\n",
"continents = gapminder[\"continent\"].unique().tolist()\n",
"years = gapminder[\"year\"].unique().tolist()\n",
"contries = gapminder.country.unique().tolist()\n",
"\n",
"app.layout = html.Div(\n",
" [\n",
" html.Div(\n",
" [\n",
" dcc.Dropdown(\n",
" id=\"continent-dropdown\",\n",
" options=[{\"label\": c, \"value\": c} for c in continents],\n",
" value=continents,\n",
" multi=True,\n",
" style={\"textAlign\": \"center\"},\n",
" ),\n",
" dcc.Graph(id=\"scatter\"),\n",
" dcc.Slider(\n",
" id=\"year-slider\",\n",
" min=gapminder[\"year\"].min(),\n",
" max=gapminder[\"year\"].max(),\n",
" value=gapminder[\"year\"].min(),\n",
" marks={str(year): str(year)[2:] for year in years},\n",
" step=None,\n",
" ),\n",
" ],\n",
" style={\"width\": \"50%\", \"display\": \"inline-block\", \"verticalAlign\": \"top\"},\n",
" ),\n",
" html.Div(\n",
" [\n",
" dcc.Dropdown(\n",
" id=\"country-dropdown\",\n",
" options=[{\"value\": contry, \"label\": contry} for contry in contries],\n",
" value=[\"Japan\", \"United States\"],\n",
" multi=True,\n",
" ),\n",
" dcc.Graph(id=\"line\"),\n",
" ],\n",
" style={\"width\": \"50%\", \"display\": \"inline-block\", \"verticalAlign\": \"top\"},\n",
" ),\n",
" ]\n",
")\n",
"\n",
"\n",
"@app.callback(\n",
" Output(\"scatter\", \"figure\"),\n",
" [Input(\"year-slider\", \"value\"), Input(\"continent-dropdown\", \"value\")],\n",
")\n",
"def update_figure(selected_year, selected_continent):\n",
" filtered_df = gapminder[\n",
" (gapminder[\"year\"] == selected_year)\n",
" & gapminder[\"continent\"].isin(selected_continent)\n",
" ]\n",
"\n",
" if len(filtered_df) == 0:\n",
" fig = px.scatter()\n",
" else:\n",
" fig = px.scatter(\n",
" filtered_df,\n",
" x=\"gdpPercap\",\n",
" y=\"lifeExp\",\n",
" size=\"pop\",\n",
" color=\"continent\",\n",
" hover_name=\"country\",\n",
" log_x=True,\n",
" size_max=55,\n",
" )\n",
"\n",
" fig.update_layout(transition_duration=500)\n",
"\n",
" return fig\n",
"\n",
"\n",
"@app.callback(Output(\"line\", \"figure\"), [Input(\"country-dropdown\", \"value\")])\n",
"def update_graph(selected_country):\n",
" selected_gapminder = gapminder[gapminder[\"country\"].isin(selected_country)]\n",
" return px.line(selected_gapminder, x=\"year\", y=\"lifeExp\", color=\"country\")"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Dash app running on http://localhost:8888/proxy/8050/\n"
]
}
],
"source": [
"app.run_server()"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"