{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "7eba22e3",
   "metadata": {},
   "source": [
    "# df000_simple\n",
    "Simple RDataFrame example in Python.\n",
    "\n",
    "This tutorial shows a minimal example of RDataFrame. It starts without input\n",
    "data, generates a new column `x` with random numbers, and finally draws\n",
    "a histogram for `x`.\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "**Author:** Enric Tejedor (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 08:09 PM.</small></i>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d7e756e9",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:09:17.794927Z",
     "iopub.status.busy": "2026-05-19T20:09:17.794804Z",
     "iopub.status.idle": "2026-05-19T20:09:18.781240Z",
     "shell.execute_reply": "2026-05-19T20:09:18.780543Z"
    }
   },
   "outputs": [],
   "source": [
    "import ROOT"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a5183799",
   "metadata": {},
   "source": [
    "Create a data frame with 100 rows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "d5c69fb3",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:09:18.790221Z",
     "iopub.status.busy": "2026-05-19T20:09:18.790086Z",
     "iopub.status.idle": "2026-05-19T20:09:19.270005Z",
     "shell.execute_reply": "2026-05-19T20:09:19.269481Z"
    }
   },
   "outputs": [],
   "source": [
    "rdf = ROOT.RDataFrame(100)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0202de44",
   "metadata": {},
   "source": [
    "Define a new column `x` that contains random numbers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "abaa723d",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:09:19.272102Z",
     "iopub.status.busy": "2026-05-19T20:09:19.271980Z",
     "iopub.status.idle": "2026-05-19T20:09:19.420236Z",
     "shell.execute_reply": "2026-05-19T20:09:19.415718Z"
    }
   },
   "outputs": [],
   "source": [
    "rdf_x = rdf.Define(\"x\", \"gRandom->Rndm()\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "123aecf7",
   "metadata": {},
   "source": [
    "Create a histogram from `x` and draw it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "dea1f5e7",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:09:19.426638Z",
     "iopub.status.busy": "2026-05-19T20:09:19.426492Z",
     "iopub.status.idle": "2026-05-19T20:09:20.743239Z",
     "shell.execute_reply": "2026-05-19T20:09:20.742704Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Info in <TCanvas::MakeDefCanvas>:  created default TCanvas with name c1\n"
     ]
    }
   ],
   "source": [
    "h = rdf_x.Histo1D(\"x\")\n",
    "h.Draw()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "80bc4ed3",
   "metadata": {},
   "source": [
    "Draw all canvases "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "591100f0",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:09:20.744484Z",
     "iopub.status.busy": "2026-05-19T20:09:20.744357Z",
     "iopub.status.idle": "2026-05-19T20:09:20.934349Z",
     "shell.execute_reply": "2026-05-19T20:09:20.933486Z"
    }
   },
   "outputs": [
    {
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').then(json => {\n",
       "   const obj = Core.parse(json);\n",
       "   Core.draw('root_plot_1779221360918', obj, '');\n",
       "});\n",
       "\n",
       "      }\n",
       "      const servers = ['/static/', 'https://root.cern/js/7.11.0/', 'https://jsroot.gsi.de/7.11.0/'],\n",
       "            path = 'build/jsroot';\n",
       "      if (typeof JSROOT !== 'undefined')\n",
       "         execCode(JSROOT);\n",
       "      else if (typeof requirejs !== 'undefined') {\n",
       "         servers.forEach((s,i) => { servers[i] = s + path; });\n",
       "         requirejs.config({ paths: { 'jsroot' : servers } })(['jsroot'],  execCode);\n",
       "      } else {\n",
       "         const config = document.getElementById('jupyter-config-data');\n",
       "         if (config)\n",
       "            servers[0] = (JSON.parse(config.innerHTML || '{}')?.baseUrl || '/') + 'static/';\n",
       "         else\n",
       "            servers.shift();\n",
       "         function loadJsroot() {\n",
       "            return !servers.length ? 0 : import(servers.shift() + path + '.js').catch(loadJsroot).then(() => execCode(JSROOT));\n",
       "         }\n",
       "         loadJsroot();\n",
       "      }\n",
       "   }\n",
       "   process_root_plot_1779221360918();\n",
       "</script>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from ROOT import gROOT \n",
    "gROOT.GetListOfCanvases().Draw()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
