demo.ipynb

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   "source": [
    "<img src=\"./assets/notebook_header.svg\" width=\"384\" style=\"margin:auto\" />"
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  {
   "cell_type": "markdown",
   "id": "52e3a042-d172-4da0-9b2f-c65393dc1655",
   "metadata": {},
   "source": [
    "# `feedzai-altair-theme` demo"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ad200c67-f1f9-4984-9cdb-afa31c45f9cd",
   "metadata": {},
   "source": [
    "To use the `feedzai` theme in your Altair charts, you just need to import Altair (no need to import the `feedzai-altair-theme` package):"
   ]
  },
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   "execution_count": null,
   "id": "499c8566-683d-4fd8-a1a2-4c947b4ed4f5",
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   "source": [
    "import altair as alt\n",
    "\n",
    "# For the example charts in this notebook, NumPy and the vega_datasets package are also imported:\n",
    "import numpy as np\n",
    "from vega_datasets import data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d7bfd16b-93ea-4994-8510-d183636157f4",
   "metadata": {},
   "source": [
    "By default, the theme used by Altair is the `default` theme:"
   ]
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   "cell_type": "code",
   "execution_count": null,
   "id": "e9848138-e9b9-499b-981a-b5378242df4c",
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   "outputs": [],
   "source": [
    "alt.themes.active"
   ]
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   "id": "8d5e1ae3-a3ac-40a8-b5cd-174d60703aac",
   "metadata": {},
   "source": [
    "When checking all the available themes, the `feedzai` theme is one of them:"
   ]
  },
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   "cell_type": "code",
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   "id": "0135b57a-aae2-4fec-8d81-a8eaad94d001",
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   "source": [
    "alt.themes.names()"
   ]
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   "id": "4bae645f-756a-4a31-abb1-a60e3ef37a5c",
   "metadata": {},
   "source": [
    "To apply the `feedzai` theme to all charts on this notebook, enable it and confirm that it is the new active theme:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "be101ef3-6f1b-4cd7-b900-3408814f16fd",
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   "outputs": [],
   "source": [
    "alt.themes.enable(\"feedzai\")"
   ]
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   "cell_type": "code",
   "execution_count": null,
   "id": "94bac21a-3076-4c57-b7da-0e1f204c4d55",
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   "outputs": [],
   "source": [
    "alt.themes.active"
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   "cell_type": "markdown",
   "id": "6d19e02d-e086-4548-be43-3353e4a57e05",
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   "source": [
    "Now, let's see some examples! For other examples, go to the [Example Gallery in the Altair documentation](https://altair-viz.github.io/gallery/index.html) and copy and paste the code snippet into this notebook."
   ]
  },
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   "id": "ebd1d8e8-f1ae-46b6-aa10-387749943949",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Bar chart"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2061255e-0f90-46e7-af69-9314442f43d1",
   "metadata": {},
   "source": [
    "[Source](https://altair-viz.github.io/gallery/simple_bar_chart.html)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "41e17b91-8a09-4f71-8fc0-30391bc4ce59",
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   "outputs": [],
   "source": [
    "source = alt.pd.DataFrame(\n",
    "    {\n",
    "        \"a\": [\"A\", \"B\", \"C\", \"D\", \"E\", \"F\", \"G\", \"H\", \"I\"],\n",
    "        \"b\": [28, 55, 43, 91, 81, 53, 19, 87, 52],\n",
    "    }\n",
    ")\n",
    "\n",
    "alt.Chart(source).mark_bar(tooltip=True).encode(x=\"a:N\", y=\"b:Q\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "00842fcd-6625-4c42-946c-6e49caaf9fcd",
   "metadata": {},
   "source": [
    "## Line chart"
   ]
  },
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   "cell_type": "markdown",
   "id": "7d4bc44b-9e2b-40da-a4b3-f539e5fb2965",
   "metadata": {},
   "source": [
    "[Source](https://altair-viz.github.io/gallery/multi_series_line.html)"
   ]
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   "source": [
    "source = data.stocks()\n",
    "\n",
    "alt.Chart(source).mark_line().encode(\n",
    "    x=\"date:T\",\n",
    "    y=\"price:Q\",\n",
    "    color=\"symbol:N\",\n",
    "    strokeDash=\"symbol:N\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "60d23a22-b1bf-4a1e-86dd-529704289ac2",
   "metadata": {},
   "source": [
    "## Histogram"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "854b5c4d-4b52-4106-9804-20b775324d99",
   "metadata": {},
   "source": [
    "[Source](https://altair-viz.github.io/gallery/simple_histogram.html)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c3620958-883b-4429-ac76-5969fd4bf594",
   "metadata": {},
   "outputs": [],
   "source": [
    "source = data.movies()\n",
    "\n",
    "alt.Chart(source).mark_bar().encode(\n",
    "    x=alt.X(\"IMDB_Rating:Q\", bin=True),\n",
    "    y=\"count()\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cb69b118-b46b-47e2-ad3a-a84f7cb1a1c6",
   "metadata": {},
   "source": [
    "## Stacked area chart"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "061f3aee-d282-4a2f-8673-b96afd46b554",
   "metadata": {},
   "source": [
    "[Source](https://altair-viz.github.io/gallery/simple_stacked_area_chart.html)"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
   "id": "afecaf6d-7f37-44c1-b9f9-85a386db22b5",
   "metadata": {},
   "outputs": [],
   "source": [
    "source = data.iowa_electricity()\n",
    "\n",
    "alt.Chart(source).mark_area().encode(x=\"year:T\", y=\"net_generation:Q\", color=\"source:N\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "115df9d5-c8ec-41c2-b15d-f3cc9ee51fc6",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Heatmap"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f2e0f740-ef55-431d-9f66-ce7fd1d6ea9e",
   "metadata": {},
   "source": [
    "[Source](https://altair-viz.github.io/gallery/simple_heatmap.html)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b628d503-2a3f-45ab-80d2-8913576241be",
   "metadata": {},
   "outputs": [],
   "source": [
    "x, y = np.meshgrid(range(-5, 5), range(-5, 5))\n",
    "z = x**2 + y**2\n",
    "\n",
    "source = alt.pd.DataFrame({\"x\": x.ravel(), \"y\": y.ravel(), \"z\": z.ravel()})\n",
    "\n",
    "alt.Chart(source).mark_rect().encode(\n",
    "    x=\"x:O\", y=\"y:O\", color=alt.Color(\"z:Q\", scale=alt.Scale(reverse=True))\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "089e662d-d1b0-411d-a04d-858fd6288cb3",
   "metadata": {},
   "source": [
    "---"
   ]
  }
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