Getting_Started/Charting_and_Visualization/Charting_and_Visualization_SQL.ipynb

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    "<header>\n",
    "   <p  style='font-size:36px;font-family:Arial; color:#F0F0F0; background-color: #00233c; padding-left: 20pt; padding-top: 20pt;padding-bottom: 10pt; padding-right: 20pt;'>\n",
    "       Charting and Data Visualization Demo\n",
    "  <br>\n",
    "       <img id=\"teradata-logo\" src=\"https://storage.googleapis.com/clearscape_analytics_demo_data/DEMO_Logo/teradata.svg\" alt=\"Teradata\" style=\"width: 125px; height: auto; margin-top: 20pt;\">\n",
    "    </p>\n",
    "</header>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p style = 'font-size:20px;font-family:Arial;color:#00233C'><b>Introduction:</b></p>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    This notebook demonstrates the ability to Visualize result sets and other data sets using Teradata SQL Notebook %chart magic command.\n",
    "</p>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    <b>***NOTE: To execute the SQL or magic command in the cell, press SHIFT+ENTER or the run button in the toolbar.</b>\n",
    "</p>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    The %chart magic supports:\n",
    "</p>\n",
    "\n",
    "<ul style='font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    <li>The creation of simple Vega-Lite charts based on Vantage database query result sets</li>\n",
    "    <li>Rendering of more advanced Vega and Vega-Lite charts in a Teradata SQL Notebook</li>\n",
    "    <li>The use of other CSV and JSON data sources for charting and visualization</li>\n",
    "</ul>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    This notebook provides SQL statements to create sample tables and uses the %dataload magic to load sample data. You will be able to execute magic commands to query the tables and visualize %chart options. Several examples of more advanced Vega and Vega-Lite charts are also provided.\n",
    "</p>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    For more details on Vega and Vega-Lite charts see <a href=\"https://vega.github.io/vega/\" style='font-size:16px;font-family:Arial;'>Vega</a> and <a href=\"https://vega.github.io/vega-lite/\" style='font-size:16px;font-family:Arial;'>Vega-Lite</a>.\n",
    "</p>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr style='height:2px;border:none;background-color:#00233C;'>\n",
    "<p style='font-size:18px;font-family:Arial;color:#00233c;'><b>Chart Generation</b></p>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    When a chart is generated from a Teradata SQL result set using the %chart magic, the chart spec file is written to the Teradata/Charts directory with the name &lt;ResultSetID&gt;.json, where &lt;ResultSetID&gt; is the time-stamp ID of the result set found in the Teradata/ResultSets directory.\n",
    "</p>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    For example, if the result set is in\n",
    "</p>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    <code style='font-family: monospace;'>Teradata/ResultSets/2019.09.06_16.37.27.534_PDT</code>\n",
    "</p>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    the chart file would be\n",
    "</p>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    <code style='font-family: monospace;'>Teradata/Charts/2019.09.06_16.37.27.534_PDT.json</code>\n",
    "</p>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr style='height:2px;border:none;background-color:#00233C;'>\n",
    "<p style='font-size:18px;font-family:Arial;color:#00233c;'><b>Chart Data</b></p>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    Chart specifications, whether generated, created manually or acquired from an external source, can be applied to data from a Teradata SQL result set or another external source. Both JSON and CSV formatted data are supported.\n",
    "</p>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    This allows you to:\n",
    "</p>\n",
    "\n",
    "<ul style='font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    <li>Apply different result sets to the same chart spec\n",
    "        <ul>\n",
    "            <li>%chart spec=2019.09.06_16.37.27.534_PDT.json, id=2019.09.06_16.37.27.534_PDT</li>\n",
    "            <li>%chart spec=2019.09.06_16.37.27.534_PDT.json, id=2019.09.09_13.42.23.830_PDT</li>\n",
    "        </ul>\n",
    "    </li>\n",
    "    <li>Apply different data sets to the same chart spec\n",
    "        <ul>\n",
    "            <li>%chart spec=mycharts/myspec.json, data=data/dataset1.json</li>\n",
    "            <li>%chart spec=mycharts/myspec.json, data=data/dataset2.json</li>\n",
    "        </ul>\n",
    "    </li>\n",
    "    <li>Apply different chart specs to the same result set or data set\n",
    "        <ul>\n",
    "            <li>%chart spec=myspec1.json, id=145</li>\n",
    "            <li>%chart spec=myspec2.json, id=145</li>\n",
    "        </ul>\n",
    "    </li>\n",
    "</ul>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    Data can be embedded in a chart (\"values\" element) or can be referenced from the chart in a separate data file (\"url\" element).\n",
    "</p>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    If chart data is not specified with the <b>spec</b> (with embedded data), <b>data</b> or <b>id</b> parameters, the most recent result set is used.\n",
    "</p>"
   ]
  },
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr style='height:2px;border:none;background-color:#00233C;'>\n",
    "\n",
    "<p style='font-size:18px;font-family:Arial;color:#00233c;'><b>Chart Editing</b></p>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    Chart specification files are JSON formatted and can be edited using any text editor or specialized JSON editor.\n",
    "</p>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    In the upper right corner of each chart is a menu (a circle containing ...) which supports several options:\n",
    "</p>\n",
    "\n",
    "<ul style='font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    <li>Save as SVG</li>\n",
    "    <li>Save as PNG</li>\n",
    "    <li>View Source</li>\n",
    "    <li>View Compiled Vega</li>\n",
    "    <li>Open in Vega Editor</li>\n",
    "</ul>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    The 'View Source' and 'Open in Vega Editor' options are useful for editing a chart spec:\n",
    "</p>\n",
    "\n",
    "<ul style='font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    <li>\n",
    "        'View Source' will open a new browser tab with the chart spec. While this can't be edited directly, it can be copied to an editor and saved to a new chart spec file which can be rendered using the %chart command.\n",
    "    </li>\n",
    "    <li>\n",
    "        'Open in Vega Editor' will open the chart spec in an external Vega/Vega-Lite editor. This option requires the data to be embedded in the chart and allows the chart to be edited next to a live rendering of the chart. This is very useful because you can see the results of any changes immediately. To save any changes, you will need to export the chart back to your local system. The newly edited chart can then be rendered into your notebook with the %chart magic.\n",
    "    </li>\n",
    "</ul>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    It is also possible to edit a chart locally with a live view of the changes:\n",
    "</p>\n",
    "\n",
    "<ul style='font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    <li>\n",
    "        right-click the chart file and selecting Open With -> Vega-Lite3 or Vega5\n",
    "        <ul>\n",
    "            <li>opens the chart in a separate tab</li>\n",
    "        </ul>\n",
    "    </li>\n",
    "    <li>\n",
    "        right-click the chart file again and select Open With -> Editor\n",
    "        <ul>\n",
    "            <li>opens the chart spec in a separate editor tab</li>\n",
    "        </ul>\n",
    "    </li>\n",
    "    <li>\n",
    "        drag one of the tabs to be next to or above or below the other\n",
    "    </li>\n",
    "    <li>\n",
    "        any edits made in the chart spec in the editor tab will be rendered immediately in the chart tab\n",
    "        <ul>\n",
    "            <li>note using this method, it is possible that the rendered chart may crash if any syntax errors are introduced</li>\n",
    "        </ul>\n",
    "    </li>\n",
    "</ul>\n",
    "\n",
    "![Screen Shot 2021-12-16 at 11.10.25 AM.png](attachment:8024918b-6d3a-4447-a9f6-dad8e8c0056f.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr style='height:2px;border:none;background-color:#00233C;'>\n",
    "\n",
    "<p style='font-size:18px;font-family:Arial;color:#00233c;'><b>Advanced Charting</b></p>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    Charts generated using the %chart magic support a limited set of capabilities. Vega and Vega-Lite support a large variety of complex charting capabilities. More advanced charts can be created by:\n",
    "</p>\n",
    "\n",
    "<ul style='font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    <li>Editing a chart generated by the %chart magic</li>\n",
    "    <li>Pulling in a chart from an external source (web, other user, etc.)</li>\n",
    "    <li>Manually editing a chart spec</li>\n",
    "</ul>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    Any Vega or Vega-Lite spec can be rendered in a Teradata SQL notebook using the %chart magic with the <b>spec</b> parameter (see examples below).\n",
    "</p>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr style='height:2px;border:none;background-color:#00233C;'>\n",
    "\n",
    "<p style='font-size:18px;font-family:Arial;color:#00233c;'><b>Help for the %chart magic</b></p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "vscode": {
     "languageId": "teradata sql"
    }
   },
   "outputs": [],
   "source": [
    "%help chart"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    \n",
    "</p>\n",
    "\n",
    "<ul style='font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    <li><b>x</b> and <b>y</b> - represent the x and y axes of the graph. These values must be specified.</li>\n",
    "    <li><b>title</b> - the title displayed above the chart (optional)</li>\n",
    "    <li><b>id</b> - the history id or result set id to use as input (most recently accessed if not specified)</li>\n",
    "    <li><b>labelx</b> - the label of the x axis (default is the x column name)</li>\n",
    "    <li><b>labely</b> - the label of the y axis (default is the y column name)</li>\n",
    "    <li><b>gridx</b> - whether to show grid lines for the x axis (default is true)</li>\n",
    "    <li><b>gridy</b> - whether to show grid lines for the y axis (default is true)</li>\n",
    "    <li><b>mark</b> - the type of chart to show (bar, line, area, point, rect, square, text, tick) (default is bar)</li>\n",
    "    <li>\n",
    "        <b>typex</b> and <b>typey</b> - the data type of the x and y axes \n",
    "        <a href='https://vega.github.io/vega-lite/docs/type.html' style='font-weight:bold;'>[(see the vega-lite specification)]</a>\n",
    "        <ul>\n",
    "            <li>q=quantitative - represents quantity values - generally numeric values</li>\n",
    "            <li>n=nominal - categorical data values based only on their names or categories. E.g., gender, nationality, music genre.</li>\n",
    "            <li>o=ordinal - represents ranked order (1st, 2nd, …) by which the data can be sorted. There is no notion of relative degree of difference between values</li>\n",
    "            <li>t=temporal - time and date/time values</li>\n",
    "            <li>default types are assigned based on the column data types\n",
    "                <ul>\n",
    "                    <li>numeric types -> quantitative</li>\n",
    "                    <li>time types -> temporal</li>\n",
    "                    <li>other types -> nominal</li>\n",
    "                </ul>\n",
    "            </li>\n",
    "        </ul>\n",
    "    </li>\n",
    "</ul>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr style='height:2px;border:none;background-color:#00233C;'>\n",
    "<p style='font-size:18px;font-family:Arial;color:#00233c;'><b>Connect to Vantage</b></p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "vscode": {
     "languageId": "teradata sql"
    }
   },
   "outputs": [],
   "source": [
    "%connect local, hidewarnings=true"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr style='height:1px;border:none;background-color:#00233C;'>\n",
    "<p style='font-size:18px;font-family:Arial;color:#00233c;'><b>Create a table to store sales center data.</b></p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": [],
    "vscode": {
     "languageId": "teradata sql"
    }
   },
   "outputs": [],
   "source": [
    "CREATE MULTISET TABLE SalesCenter ,\n",
    "     NO BEFORE JOURNAL,\n",
    "     NO AFTER JOURNAL,\n",
    "     CHECKSUM = DEFAULT,\n",
    "     DEFAULT MERGEBLOCKRATIO\n",
    "     (\n",
    "      Sales_Center_id INTEGER NOT NULL,\n",
    "      Sales_Center_Name VARCHAR(255) CHARACTER SET LATIN NOT CASESPECIFIC)\n",
    "NO PRIMARY INDEX ;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "vscode": {
     "languageId": "teradata sql"
    }
   },
   "outputs": [],
   "source": [
    "help database demo_user;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr style='height:1px;border:none;background-color:#00233C;'>\n",
    "<p style='font-size:18px;font-family:Arial;color:#00233c;'><b>Load data into the SalesCenter table using the %dataload magic</b></p>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    Run <b>%help dataload</b> for more information on using the <b>%dataload</b> magic.\n",
    "</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": [],
    "vscode": {
     "languageId": "teradata sql"
    }
   },
   "outputs": [],
   "source": [
    "%dataload DATABASE = demo_user, TABLE = SalesCenter, FILEPATH = Getting_Started/Charting_and_Visualization/data/salescenter.csv"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr style='height:1px;border:none;background-color:#00233C;'>\n",
    "\n",
    "<p style='font-size:18px;font-family:Arial;color:#00233c;'><b>Verify data was inserted</b></p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "vscode": {
     "languageId": "teradata sql"
    }
   },
   "outputs": [],
   "source": [
    "SELECT TOP 5 * FROM SalesCenter ORDER BY 1;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr style='height:1px;border:none;background-color:#00233C;'>\n",
    "\n",
    "<p style='font-size:18px;font-family:Arial;color:#00233c;'><b>Create a table with sales demo data</b></p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "vscode": {
     "languageId": "teradata sql"
    }
   },
   "outputs": [],
   "source": [
    "CREATE MULTISET TABLE SalesDemo ,\n",
    "     NO BEFORE JOURNAL,\n",
    "     NO AFTER JOURNAL,\n",
    "     CHECKSUM = DEFAULT,\n",
    "     DEFAULT MERGEBLOCKRATIO\n",
    "     (\n",
    "      Sales_Center_ID INTEGER NOT NULL,\n",
    "      UNITS DECIMAL(15,4),\n",
    "      SALES DECIMAL(15,2),\n",
    "      COST DECIMAL(15,2))\n",
    "NO PRIMARY INDEX ;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr style='height:1px;border:none;background-color:#00233C;'>\n",
    "<p style='font-size:18px;font-family:Arial;color:#00233c;'><b>Load data into the SalesDemo table using the %dataload magic</b></p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "vscode": {
     "languageId": "teradata sql"
    }
   },
   "outputs": [],
   "source": [
    "%dataload DATABASE = demo_user, TABLE = SalesDemo, FILEPATH = Getting_Started/Charting_and_Visualization/data/salesdemo.csv"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr style='height:1px;border:none;background-color:#00233C;'>\n",
    "<p style='font-size:18px;font-family:Arial;color:#00233c;'><b>Verify that the sales demo data inserted successfully</b></p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "vscode": {
     "languageId": "teradata sql"
    }
   },
   "outputs": [],
   "source": [
    "SELECT TOP 5 * FROM SalesDemo ORDER BY sales;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr style='height:1px;border:none;background-color:#00233C;'>\n",
    "<p style='font-size:18px;font-family:Arial;color:#00233c;'><b>Create a result set from the sales data</b></p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "vscode": {
     "languageId": "teradata sql"
    }
   },
   "outputs": [],
   "source": [
    "SELECT\n",
    "    f.sales,\n",
    "    f.sales_center_id,\n",
    "    s.sales_center_name\n",
    "FROM\n",
    "    SalesDemo f\n",
    "INNER JOIN\n",
    "    SalesCenter s ON s.Sales_Center_id = f.Sales_Center_id;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr style='height:1px;border:none;background-color:#00233C;'>\n",
    "<p style='font-size:18px;font-family:Arial;color:#00233c;'><b>Create a table with stock price data</b></p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "vscode": {
     "languageId": "teradata sql"
    }
   },
   "outputs": [],
   "source": [
    "CREATE MULTISET TABLE stocks ,\n",
    "     NO BEFORE JOURNAL,\n",
    "     NO AFTER JOURNAL,\n",
    "     CHECKSUM = DEFAULT,\n",
    "     DEFAULT MERGEBLOCKRATIO,\n",
    "     MAP = TD_MAP1\n",
    "     (\n",
    "      symbol VARCHAR(20) CHARACTER SET LATIN CASESPECIFIC,\n",
    "      pricedate VARCHAR(20) CHARACTER SET LATIN CASESPECIFIC,\n",
    "      price FLOAT)\n",
    "NO PRIMARY INDEX ;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "vscode": {
     "languageId": "teradata sql"
    }
   },
   "outputs": [],
   "source": [
    "%dataload DATABASE = demo_user, TABLE = stocks, FILEPATH = Getting_Started/Charting_and_Visualization/data/stocks.csv, skiprows = 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr style='height:2px;border:none;background-color:#00233C;'>\n",
    "<p style='font-size:18px;font-family:Arial;color:#00233c;'><b>The %chart magic allows you to quickly visualize the result</b></p>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    By default, the most recent result set is used as the chart data. Another result set can be specified using the <b>id</b> parameter as follows:\n",
    "</p>\n",
    "\n",
    "<ul style='font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    <li><b>HistoryID</b> - the ID of a previous query as shown by the %history magic command (<b>id=0</b> uses the most recent result set)</li>\n",
    "    <li><b>ResultSetId</b> - the timestamp ID of a previous result set as shown in the Teradata/ResultSets directory</li>\n",
    "</ul>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    If a multipart result set is used, the <b>part</b> parameter can be used to specify which part to render (default is part 1).\n",
    "</p>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    The types of the axes are inferred from the column types as follows:\n",
    "</p>\n",
    "\n",
    "<ul style='font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    <li>numeric types -&gt; quantitative</li>\n",
    "    <li>time types -&gt; temporal</li>\n",
    "    <li>other types -&gt; nominal</li>\n",
    "</ul>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    If the column type does not match the desired axis type, the <b>typex</b> and <b>typey</b> parameters can be used.\n",
    "</p>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    The values for <b>typex</b> and <b>typey</b> are the first letter of the types defined by the Vega-Lite spec \n",
    "    (<a href='https://vega.github.io/vega-lite/docs/type.html' style='font-weight:bold;'>see the Vega-Lite spec</a>):\n",
    "</p>\n",
    "\n",
    "<ul style='font-size:16px;font-family:Arial;'>\n",
    "    <li><b>q</b> = quantitative</li>\n",
    "    <li><b>n</b> = nominal</li>\n",
    "    <li><b>o</b> = ordinal</li>\n",
    "    <li><b>t</b> = temporal</li>\n",
    "</ul>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    Labels for the x and y axes can be specified (the default is the column name) with <b>labelx</b> and <b>labely</b> parameters.\n",
    "</p>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    Grid lines for the x and y axes can be enabled (default) or disabled with <b>gridx</b>=true|false and <b>gridy</b>=true|false.\n",
    "</p>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr style='height:1px;border:none;background-color:#00233C;'>\n",
    "\n",
    "<p style='font-size:18px;font-family:Arial;color:#00233c;'><b>A simple bar chart can be generated by specifying the columns to use for the x and y axes</b></p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "vscode": {
     "languageId": "teradata sql"
    }
   },
   "outputs": [],
   "source": [
    "%chart sales_center_name, sales"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr style='height:1px;border:none;background-color:#00233C;'>\n",
    "<p style='font-size:18px;font-family:Arial;color:#00233c;'><b>The same chart with some non-default parameter values specified</b></p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "vscode": {
     "languageId": "teradata sql"
    }
   },
   "outputs": [],
   "source": [
    "%chart x = sales_center_name, y = sales, gridx = false, gridy = false, \n",
    "title = Sales Data, labelx = Sales, labely = Sales Center Name, typex = n, typey = q, id = 0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr style='height:1px;border:none;background-color:#00233C;'>\n",
    "<p style='font-size:18px;font-family:Arial;color:#00233c;'><b>The color of the chart can be changed</b></p>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    The <b>color</b> parameter supports CSS color names \n",
    "    (<a href='https://developer.mozilla.org/en-US/docs/Web/CSS/color_value' style='font-weight:bold;'>see CSS color names</a>).\n",
    "</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "vscode": {
     "languageId": "teradata sql"
    }
   },
   "outputs": [],
   "source": [
    "%chart sales_center_name, sales, title=Sales Data, color=darkgreen"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr style='height:1px;border:none;background-color:#00233C;'>\n",
    "<p style='font-size:18px;font-family:Arial;color:#00233c;'><b>A CSS RGB hex color specification can also be used</b></p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "vscode": {
     "languageId": "teradata sql"
    }
   },
   "outputs": [],
   "source": [
    "%chart sales_center_name, sales, title = Sales Data, color = #428495"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr style='height:1px;border:none;background-color:#00233C;'>\n",
    "\n",
    "<p style='font-size:18px;font-family:Arial;color:#00233c;'><b>The height and width of the chart can be adjusted</b></p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "vscode": {
     "languageId": "teradata sql"
    }
   },
   "outputs": [],
   "source": [
    "%chart sales_center_name, sales, title = Sales Data, color = #428495, width = 500, height = 500"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr style='height:1px;border:none;background-color:#00233C;'>\n",
    "<p style='font-size:18px;font-family:Arial;color:#00233c;'><b>Different styles of chart can be generated using the mark parameter</b></p>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    Supported mark types include <b>area, bar, circle, line, point, rect, rule, square, text, tick, rect</b>.\n",
    "</p>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    See the Vega-Lite specification for the complete list of mark types \n",
    "    (<a href='https://vega.github.io/vega-lite/' style='font-weight:bold;'>Vega-Lite specification</a>).\n",
    "</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "vscode": {
     "languageId": "teradata sql"
    }
   },
   "outputs": [],
   "source": [
    "%chart sales_center_name, sales, title = Sales Data, color = #428495, mark = point"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr style='height:1px;border:none;background-color:#00233C;'>\n",
    "\n",
    "<p style='font-size:18px;font-family:Arial;color:#00233c;'><b>Multi series chart</b></p>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    Use <b>groupingcol</b> to produce a multi-series chart. \n",
    "    It can also be used to produce a stacked chart.\n",
    "</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": [],
    "vscode": {
     "languageId": "teradata sql"
    }
   },
   "outputs": [],
   "source": [
    "SELECT * FROM stocks;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "vscode": {
     "languageId": "teradata sql"
    }
   },
   "outputs": [],
   "source": [
    "%chart title = stock price change over time, x = pricedate, labelx = year, y = price,\n",
    "typex = t, typey = q, groupingcol = symbol, typegroupingcol = n, mark = line, height = 500, width = 500"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr style='height:2px;border:none;background-color:#00233C;'>\n",
    "\n",
    "<p style='font-size:18px;font-family:Arial;color:#00233c;'><b>Aggregating data</b></p>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    Use <b>aggregatex</b> or <b>aggregatey</b> to aggregate the x or y column.\n",
    "</p>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    Supported aggregate functions include \n",
    "    <b>sum, count, mean, median, min, max, variance, stdev</b>.\n",
    "</p>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    See the Vega-Lite specification for the complete list of aggregate functions \n",
    "    (<a href='https://vega.github.io/vega-lite/docs/aggregate.html#ops' style='font-weight:bold;'>Vega-Lite aggregate functions</a>).\n",
    "</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "vscode": {
     "languageId": "teradata sql"
    }
   },
   "outputs": [],
   "source": [
    "%chart title=average stock price, x=symbol, y=price, typey=q, aggregatey=mean, mark=bar,  height=500, width=500"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr style='height:2px;border:none;background-color:#00233C;'>\n",
    "\n",
    "<p style='font-size:18px;font-family:Arial;color:#00233c;'><b>Sorting data</b></p>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    Use <b>sortx</b> or <b>sorty</b> to sort data in the x or y column.\n",
    "</p>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    Supported values are '<b>ascending</b>' and '<b>descending</b>'.\n",
    "</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "vscode": {
     "languageId": "teradata sql"
    }
   },
   "outputs": [],
   "source": [
    "%chart x = symbol, y = price, typey = q, aggregatey = mean, sortx = descending, mark = bar, height = 500, width = 500"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr style='height:2px;border:none;background-color:#00233C;'>\n",
    "<p style='font-size:18px;font-family:Arial;color:#00233c;'><b>Binning</b></p>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    Use binning to group continuous numeric values into a set of bins.\n",
    "</p>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    Set <b>binx</b> or <b>biny</b> to '<b>true</b>' to turn on binning.\n",
    "</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "vscode": {
     "languageId": "teradata sql"
    }
   },
   "outputs": [],
   "source": [
    "%chart x = price, y = symbol, binx = true, typex = n, aggregatey = count, height = 500, width = 500"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr style='height:2px;border:none;background-color:#00233C;'>\n",
    "\n",
    "<p style='font-size:18px;font-family:Arial;color:#00233c;'><b>Timeunit</b></p>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    Use <b>timeunitx</b> or <b>timeunity</b> to extract year, month, day, week from a date field.\n",
    "</p>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    See the Vega-Lite specification for the complete list of timeunits \n",
    "    (<a href='https://vega.github.io/vega-lite/docs/timeunit.html' style='font-weight:bold;'>Vega-Lite timeunits</a>).\n",
    "</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "vscode": {
     "languageId": "teradata sql"
    }
   },
   "outputs": [],
   "source": [
    "%chart x = pricedate, typex = t, timeunitx = month, y = price, typey = q,\n",
    "aggregatey = mean, mark = bar, groupingcol = symbol, height = 500, width = 500"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr style='height:2px;border:none;background-color:#00233C;'>\n",
    "\n",
    "<p style='font-size:18px;font-family:Arial;color:#00233c;'><b>Random sampling</b></p>\n",
    "\n",
    "<p style = 'font-size:16px;font-family:Arial;color:#00233C'>\n",
    "    Use <b>sample</b> to get a random sample of specified size and use it for graphing.\n",
    "</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "vscode": {
     "languageId": "teradata sql"
    }
   },
   "outputs": [],
   "source": [
    "%chart title = stock price change over time, sample = 100, x = pricedate, labelx = year, y = price,\n",
    "typex = t, typey = q, groupingcol = symbol, typegroupingcol = n, mark = line, height = 500, width = 500"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr style='height:2px;border:none;background-color:#00233C;'>\n",
    "<p style='font-size:18px;font-family:Arial;color:#00233c;'><b>Drop tables to clean up data</b></p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "vscode": {
     "languageId": "teradata sql"
    }
   },
   "outputs": [],
   "source": [
    "DROP TABLE SalesCenter;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "vscode": {
     "languageId": "teradata sql"
    }
   },
   "outputs": [],
   "source": [
    "DROP TABLE SalesDemo;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "vscode": {
     "languageId": "teradata sql"
    }
   },
   "outputs": [],
   "source": [
    "DROP TABLE stocks;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<footer style=\"padding-bottom:35px; background:#f9f9f9; border-bottom:3px solid #00233C\">\n",
    "    <div style=\"float:left;margin-top:14px\">ClearScape Analytics™</div>\n",
    "    <div style=\"float:right;\">\n",
    "        <div style=\"float:left; margin-top:14px\">\n",
    "            Copyright © Teradata Corporation - 2023. All Rights Reserved\n",
    "        </div>\n",
    "    </div>\n",
    "</footer>"
   ]
  }
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