{
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  {
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   "source": [
    "# df031_Stats\n",
    "Use the Stats action to extract the statistics of a column.\n",
    "\n",
    "Extract the statistics relative to RDataFrame columns and store them\n",
    "in TStatistic instances.\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "**Author:** Danilo Piparo (CERN)  \n",
    "<i><small>This notebook tutorial was automatically generated with <a href= \"https://github.com/root-project/root/blob/master/documentation/doxygen/converttonotebook.py\">ROOTBOOK-izer</a> from the macro found in the ROOT repository  on Tuesday, May 19, 2026 at 08:10 PM.</small></i>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d3933bd1",
   "metadata": {},
   "source": [
    "Create a data frame and add two columns: one for the values and one for the weight."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "10330357",
   "metadata": {
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    "execution": {
     "iopub.execute_input": "2026-05-19T20:10:07.056562Z",
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     "shell.execute_reply": "2026-05-19T20:10:07.839316Z"
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   "source": [
    "ROOT::RDataFrame r(256);\n",
    "auto rr = r.Define(\"v\", [](ULong64_t e){return e;}, {\"rdfentry_\"})\n",
    "           .Define(\"w\", [](ULong64_t e){return 1./(e+1);}, {\"v\"});"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c9fadc4f",
   "metadata": {},
   "source": [
    "Now extract the statistics, weighted, unweighted - with and without explicit types."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "4980899f",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:10:07.845332Z",
     "iopub.status.busy": "2026-05-19T20:10:07.845203Z",
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     "shell.execute_reply": "2026-05-19T20:10:09.121338Z"
    }
   },
   "outputs": [],
   "source": [
    "auto stats_eu = rr.Stats<ULong64_t>(\"v\");\n",
    "auto stats_ew = rr.Stats<ULong64_t, double>(\"v\", \"w\");\n",
    "auto stats_iu = rr.Stats(\"v\");\n",
    "auto stats_iw = rr.Stats(\"v\", \"w\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "26acd488",
   "metadata": {},
   "source": [
    "Now print them: they are all identical of course!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "8d74f09c",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:10:09.123758Z",
     "iopub.status.busy": "2026-05-19T20:10:09.123632Z",
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     "shell.execute_reply": "2026-05-19T20:10:09.725290Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " OBJ: TStatistic\t  \t Mean = 127.5 +- 4.628 \t RMS = 74.045 \t Count = 256 \t Min = 0 \t Max = 255\n",
      " OBJ: TStatistic\t  \t Mean = 40.8 +- 12.86 \t RMS = 60.318 \t Count = 256 \t Min = 0 \t Max = 255\n",
      " OBJ: TStatistic\t  \t Mean = 127.5 +- 4.628 \t RMS = 74.045 \t Count = 256 \t Min = 0 \t Max = 255\n",
      " OBJ: TStatistic\t  \t Mean = 40.8 +- 12.86 \t RMS = 60.318 \t Count = 256 \t Min = 0 \t Max = 255\n"
     ]
    }
   ],
   "source": [
    "stats_eu->Print();\n",
    "stats_ew->Print();\n",
    "stats_iu->Print();\n",
    "stats_iw->Print();"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "770b625f",
   "metadata": {},
   "source": [
    "Draw all canvases "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "86bc4262",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:10:09.732484Z",
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     "shell.execute_reply": "2026-05-19T20:10:09.934733Z"
    }
   },
   "outputs": [],
   "source": [
    "gROOT->GetListOfCanvases()->Draw()"
   ]
  }
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