bokeh_datacamp02.ipynb

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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Chapter 02"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import column and row from bokeh.layouts\n",
    "from bokeh.layouts import row, column\n",
    "\n",
    "# Make a column layout that will be used as the second row: row2\n",
    "row2 = column([mpg_hp, mpg_weight], sizing_mode='scale_width')\n",
    "\n",
    "# Make a row layout that includes the above column layout: layout\n",
    "layout = row([avg_mpg, row2], sizing_mode='scale_width')\n",
    "\n",
    "# Specify the name of the output_file and show the result\n",
    "output_file('layout_custom.html')\n",
    "show(layout)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Gridplot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import gridplot from bokeh.layouts\n",
    "from bokeh.layouts import gridplot\n",
    "\n",
    "# Create a list containing plots p1 and p2: row1\n",
    "row1=[p1,p2]\n",
    "\n",
    "# Create a list containing plots p3 and p4: row2\n",
    "row2 = [p3,p4]\n",
    "\n",
    "# Create a gridplot using row1 and row2: layout\n",
    "layout = gridplot([row1, row2])\n",
    "\n",
    "# Specify the name of the output_file and show the result\n",
    "output_file('grid.html')\n",
    "show(layout)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### tabbed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import Panel from bokeh.models.widgets\n",
    "from bokeh.models.widgets import Panel\n",
    "\n",
    "# Create tab1 from plot p1: tab1\n",
    "tab1 = Panel(child=p1, title='Latin America')\n",
    "\n",
    "# Create tab2 from plot p2: tab2\n",
    "tab2 = Panel(child=p2, title='Africa')\n",
    "\n",
    "# Create tab3 from plot p3: tab3\n",
    "tab3 = Panel(child=p3, title='Asia')\n",
    "\n",
    "# Create tab4 from plot p4: tab4\n",
    "tab4 = Panel(child=p4, title='Europe')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import Tabs from bokeh.models.widgets\n",
    "from bokeh.models.widgets import Tabs\n",
    "\n",
    "# Create a Tabs layout: layout\n",
    "layout = Tabs(tabs=[tab1, tab2, tab3, tab4])\n",
    "\n",
    "# Specify the name of the output_file and show the result\n",
    "output_file('tabs.html')\n",
    "show(layout)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Linking Ranges"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Link the x_range of p2 to p1: p2.x_range\n",
    "p2.x_range = p1.x_range\n",
    "\n",
    "# Link the y_range of p2 to p1: p2.y_range\n",
    "p2.y_range = p1.y_range\n",
    "\n",
    "# Link the x_range of p3 to p1: p3.x_range\n",
    "p3.x_range=p1.x_range\n",
    "\n",
    "# Link the y_range of p4 to p1: p4.y_range\n",
    "p4.y_range=p1.y_range\n",
    "\n",
    "# Specify the name of the output_file and show the result\n",
    "output_file('linked_range.html')\n",
    "show(layout)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Linked brushing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create ColumnDataSource: source\n",
    "source = ColumnDataSource(data)\n",
    "\n",
    "# Create the first figure: p1\n",
    "p1 = figure(x_axis_label='fertility (children per woman)', y_axis_label='female literacy (% population)',\n",
    "            tools='box_select,lasso_select')\n",
    "\n",
    "# Add a circle glyph to p1\n",
    "p1.circle('fertility',\"female literacy\", source=source)\n",
    "\n",
    "# Create the second figure: p2\n",
    "p2 = figure(x_axis_label='fertility (children per woman)', y_axis_label='population (millions)',\n",
    "            tools='box_select,lasso_select')\n",
    "\n",
    "# Add a circle glyph to p2\n",
    "p2.circle('fertility', 'population', source=source)\n",
    "\n",
    "# Create row layout of figures p1 and p2: layout\n",
    "layout = row(p1,p2)\n",
    "\n",
    "# Specify the name of the output_file and show the result\n",
    "output_file('linked_brush.html')\n",
    "show(layout)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#### Legends"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Add the first circle glyph to the figure p\n",
    "p.circle('fertility', 'female_literacy', source=latin_america, size=10, color='red', legend='Latin America')\n",
    "\n",
    "# Add the second circle glyph to the figure p\n",
    "p.circle('fertility', 'female_literacy', source=africa, size=10, color='blue', legend='Africa')\n",
    "\n",
    "# Specify the name of the output_file and show the result\n",
    "output_file('fert_lit_groups.html')\n",
    "show(p)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### legend Location"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Assign the legend to the bottom left: p.legend.location\n",
    "p.legend.location ='bottom_left'\n",
    "\n",
    "# Fill the legend background with the color 'lightgray': p.legend.background_fill_color\n",
    "p.legend.background_fill_color ='lightgray'\n",
    "\n",
    "# Specify the name of the output_file and show the result\n",
    "output_file('fert_lit_groups.html')\n",
    "show(p)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### HoverTools: ToolTips"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import HoverTool from bokeh.models\n",
    "from bokeh.models import HoverTool \n",
    "\n",
    "# Create a HoverTool object: hover\n",
    "hover = HoverTool(tooltips=[('Country', '@Country')])\n",
    "\n",
    "# Add the HoverTool object to figure p\n",
    "p.add_tools(hover)\n",
    "\n",
    "# Specify the name of the output_file and show the result\n",
    "output_file('hover.html')\n",
    "show(p)"
   ]
  }
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