{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Recognized Formats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from beakerx import *\n",
    "\n",
    "TableDisplay({\"a\":100, \"b\":200, \"c\":300})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "TableDisplay([{\"a\":1}, {\"a\":10, \"b\":20}])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "TableDisplay({\"a\":1/10, \"b\":1/20, \"c\":0.33})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "TableDisplay([{\"a\":1/10}, {\"a\":1/100, \"b\":3.12345}])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "TableDisplay({\"a\":'a a a', \"b\":'b b b', \"c\":'c c c'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "TableDisplay([{\"a\":'a'}, {\"a\":'1a', \"b\":'2b'}])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "TableDisplay({\"a\":[1, 2, 3], \"b\":[10, 20, 30], \"c\":[100, 200, 300]})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "TableDisplay([\n",
    "    {\"a\":[1, 2, 3]}, \n",
    "    {\"a\":[10, 20, 30], \"b\":[100, 200, 300]}])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "row1 = {\"a\":100, \"b\":200, \"c\":300}\n",
    "row2 = {\"a\":1/10, \"b\":1/20, \"c\":0.33}\n",
    "row3 = {\"a\":'a a a', \"b\":'b b b', \"c\":'c c c'}\n",
    "row4 = {\"a\":[1, 2, 3], \"b\":[10, 20, 30], \"c\":[100, 200, 300]}\n",
    "TableDisplay([row1, row2, row3, row4])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "TableDisplay({\"a\":100, \"b\":1/20, \"c\":'c c c', \"d\":[100, 200, 300]})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "row1 = {\"a\":10, \"b\":1/10, \"c\":'c', \"d\":[100, 200]}\n",
    "row2 = {\"a\":100, \"b\":1/20, \"c\":'c c c', \"d\":[100, 200, 300]}\n",
    "TableDisplay([row1, row2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "TableDisplay({10:20, 1/10:1/20, 'c':'c c c', '[100, 200]':[100, 200, 300]})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "row1 = {10:10, 1/10:1/10, 'c':'c'}\n",
    "row2 = {10:20, 1/10:1/20, 'c':'c c c', '[100, 200]':[100, 200, 300]}\n",
    "TableDisplay([row1, row2])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Python API for Table Display\n",
    "\n",
    "In addition to APIs for creating and formatting BeakerX's interactive table widget, the Python runtime configures pandas to display tables with the interactive widget instead of static HTML."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from beakerx import *\n",
    "\n",
    "df = pd.DataFrame({\"runway\": [\"24\", \"36L\"]})\n",
    "\n",
    "TableDisplay(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.read_csv('../../../doc/resources/data/interest-rates.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "table2 = TableDisplay(pd.read_csv('../../../doc/resources/data/interest-rates-small.csv'))\n",
    "table2.setAlignmentProviderForColumn('m3', TableDisplayAlignmentProvider.CENTER_ALIGNMENT)\n",
    "table2.setRendererForColumn(\"y10\", TableDisplayCellRenderer.getDataBarsRenderer(False))\n",
    "table2.setRendererForType(ColumnType.Double, TableDisplayCellRenderer.getDataBarsRenderer(True))\n",
    "table2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df3 = pd.read_csv('../../../doc/resources/data/interest-rates-small.csv')\n",
    "df3['time'] = df3['time'].str.slice(0,19).astype('datetime64[ns]')\n",
    "table3 = TableDisplay(df3)\n",
    "table3.setStringFormatForTimes(TimeUnit.DAYS)\n",
    "table3.setStringFormatForType(ColumnType.Double, TableDisplayStringFormat.getDecimalFormat(2,3))\n",
    "table3.setStringFormatForColumn(\"m3\", TableDisplayStringFormat.getDecimalFormat(0, 0))\n",
    "table3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "table4 = TableDisplay(pd.read_csv('../../../doc/resources/data/interest-rates-small.csv'))\n",
    "#freeze a column\n",
    "table4.setColumnFrozen(\"y1\", True)\n",
    "#freeze a column to the right\n",
    "table4.setColumnFrozenRight(\"y10\", True)\n",
    "#hide a column\n",
    "table4.setColumnVisible(\"y30\", False)\n",
    "table4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "table5 = TableDisplay(pd.read_csv('../../../doc/resources/data/interest-rates-small.csv'))\n",
    "#Columns in the list will be shown in the provided order. Columns not in the list will be hidden.\n",
    "table5.setColumnOrder([\"m3\", \"y1\", \"y10\", \"time\", \"y2\"])\n",
    "table5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "colNames = [\"m3\",\"y30\",\"time\",\"y5\",\"y7\",\"spread\"]\n",
    "row1 = [7.8981, 8.2586, \"1990-01-30 19:00:00.000 -0500\", 8.1195, 8.1962, 0.3086]\n",
    "row2 = [2.0021, 8.5037, \"1990-02-27 19:00:00.000 -0500\", 8.4247, 8.4758, 0.4711]\n",
    "row3 = [2.0021, 3.5037, \"1990-05-27 19:00:00.000 -0500\", 1.4247, 4.4758, 5.4711]\n",
    "table6 = TableDisplay(pd.DataFrame([row1, row2, row3], columns=colNames))\n",
    "table6.addCellHighlighter(TableDisplayCellHighlighter.getHeatmapHighlighter(\"m3\", TableDisplayCellHighlighter.FULL_ROW))\n",
    "table6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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