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35061585 · Carla Elena Gomez Alvarado · 33300325 · 35061585
Commit 35061585 authored 4 years ago by Carla Elena Gomez Alvarado
--- a/codigo/Data_analisis_data_cega.ipynb
+++ b/codigo/Data_analisis_data_cega.ipynb
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#This code meants to be generic to analyze data from a .root file using ROOT. \n",
+    "\n",
+    "At this time the data is a file from  (insert path to gitmilab) .csv file\n",
+    "\n",
+    "wich relates etnies with height. \n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Welcome to JupyROOT 6.18/04\n"
+     ]
+    }
+   ],
+   "source": [
+    "import ROOT\n",
+    "import uproot\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# activates javascripts for interactive graphs.\n",
+    "\n",
+    "%jsroot on"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#data anlysis using root\n",
+    "\n",
+    "#open .root file and named it \"data\"\n",
+    "\n",
+    "data = ROOT.TFile.Open(\"/home/student/ejercicios-clase-08-datos/codigo/data_analisis.root\") "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#define canvas , named \"canva\", and Title \"Height vs Race\" \n",
+    "\n",
+    "canva = ROOT.TCanvas(\"Canvas\",\"Height vs Race\",800,600)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#define a tree to store .root file form the spreadsheet \"data_analisis\"\n",
+    "tree = data.Get(\"data_analisis\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "32"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# To know how many entries has the file\n",
+    "tree.GetEntries()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#Build the histogram using ROOT. \n",
+    "\n",
+    "# Data_ analysis has 4 countries each of them represents a colum on the X axis.\n",
+    "\n",
+    "hist = ROOT.TH1F(\"hist_data\",\" Height vs Origen; Origen ; Height \" ,4,-0.5,4.5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Done!\n"
+     ]
+    }
+   ],
+   "source": [
+    "for origen in tree:\n",
+    "    hist.Fill(tree.tamano)\n",
+    "    \n",
+    "print(\"Done!\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "hist.SetFillColor(40)\n",
+    "hist.Draw()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "<div id=\"root_plot_3\"\n",
+       "     style=\"width: 796px; height: 572px\">\n",
+       "</div>\n",
+       "\n",
+       "<script>\n",
+       " requirejs.config({\n",
+       "     paths: {\n",
+       "       'JSRootCore' : 'https://root.cern.ch/js/notebook//scripts/JSRootCore',\n",
+       "     }\n",
+       "   });\n",
+       " require(['JSRootCore'],\n",
+       "     function(Core) {\n",
+       "       var obj = Core.JSONR_unref({\"_typename\":\"TCanvas\",\"fUniqueID\":0,\"fBits\":53673992,\"fLineColor\":1,\"fLineStyle\":1,\"fLineWidth\":1,\"fFillColor\":0,\"fFillStyle\":1001,\"fLeftMargin\":0.1,\"fRightMargin\":0.1,\"fBottomMargin\":0.1,\"fTopMargin\":0.1,\"fXfile\":2,\"fYfile\":2,\"fAfile\":1,\"fXstat\":0.99,\"fYstat\":0.99,\"fAstat\":2,\"fFrameFillColor\":0,\"fFrameLineColor\":1,\"fFrameFillStyle\":1001,\"fFrameLineStyle\":1,\"fFrameLineWidth\":1,\"fFrameBorderSize\":1,\"fFrameBorderMode\":0,\"fX1\":-1.12500004656613,\"fY1\":-0.131250009778888,\"fX2\":5.12500004656613,\"fY2\":1.18125000977889,\"fXtoAbsPixelk\":143.280053795624,\"fXtoPixelk\":143.280053795624,\"fXtoPixel\":127.359998102188,\"fYtoAbsPixelk\":514.800046590614,\"fYtoPixelk\":514.800046590614,\"fYtoPixel\":-435.809517315456,\"fUtoAbsPixelk\":5e-5,\"fUtoPixelk\":5e-5,\"fUtoPixel\":796,\"fVtoAbsPixelk\":572.00005,\"fVtoPixelk\":572,\"fVtoPixel\":-572,\"fAbsPixeltoXk\":-1.12500004656613,\"fPixeltoXk\":-1.12500004656613,\"fPixeltoX\":0.00785175891097018,\"fAbsPixeltoYk\":1.18125000977889,\"fPixeltoYk\":-0.131250009778888,\"fPixeltoY\":-0.00229458045377233,\"fXlowNDC\":0,\"fYlowNDC\":0,\"fXUpNDC\":0,\"fYUpNDC\":0,\"fWNDC\":1,\"fHNDC\":1,\"fAbsXlowNDC\":0,\"fAbsYlowNDC\":0,\"fAbsWNDC\":1,\"fAbsHNDC\":1,\"fUxmin\":-0.5,\"fUymin\":0,\"fUxmax\":4.5,\"fUymax\":1.05,\"fTheta\":30,\"fPhi\":30,\"fAspectRatio\":0,\"fNumber\":0,\"fTickx\":0,\"fTicky\":0,\"fLogx\":0,\"fLogy\":0,\"fLogz\":0,\"fPadPaint\":0,\"fCrosshair\":0,\"fCrosshairPos\":0,\"fBorderSize\":2,\"fBorderMode\":0,\"fModified\":false,\"fGridx\":false,\"fGridy\":false,\"fAbsCoord\":false,\"fEditable\":true,\"fFixedAspectRatio\":false,\"fPrimitives\":{\"_typename\":\"TList\",\"name\":\"TList\",\"arr\":[{\"_typename\":\"TFrame\",\"fUniqueID\":0,\"fBits\":50331656,\"fLineColor\":1,\"fLineStyle\":1,\"fLineWidth\":1,\"fFillColor\":0,\"fFillStyle\":1001,\"fX1\":-0.5,\"fY1\":0,\"fX2\":4.5,\"fY2\":1.05,\"fBorderSize\":1,\"fBorderMode\":0},{\"_typename\":\"TH1F\",\"fUniqueID\":0,\"fBits\":50331656,\"fName\":\"hist_data\",\"fTitle\":\" Height vs Origen\",\"fLineColor\":602,\"fLineStyle\":1,\"fLineWidth\":1,\"fFillColor\":40,\"fFillStyle\":1001,\"fMarkerColor\":1,\"fMarkerStyle\":1,\"fMarkerSize\":1,\"fNcells\":6,\"fXaxis\":{\"_typename\":\"TAxis\",\"fUniqueID\":0,\"fBits\":50331648,\"fName\":\"xaxis\",\"fTitle\":\" Origen \",\"fNdivisions\":510,\"fAxisColor\":1,\"fLabelColor\":1,\"fLabelFont\":42,\"fLabelOffset\":0.005,\"fLabelSize\":0.035,\"fTickLength\":0.03,\"fTitleOffset\":1,\"fTitleSize\":0.035,\"fTitleColor\":1,\"fTitleFont\":42,\"fNbins\":4,\"fXmin\":-0.5,\"fXmax\":4.5,\"fXbins\":[],\"fFirst\":0,\"fLast\":0,\"fBits2\":0,\"fTimeDisplay\":false,\"fTimeFormat\":\"\",\"fLabels\":null,\"fModLabs\":null},\"fYaxis\":{\"_typename\":\"TAxis\",\"fUniqueID\":0,\"fBits\":50331648,\"fName\":\"yaxis\",\"fTitle\":\" Height \",\"fNdivisions\":510,\"fAxisColor\":1,\"fLabelColor\":1,\"fLabelFont\":42,\"fLabelOffset\":0.005,\"fLabelSize\":0.035,\"fTickLength\":0.03,\"fTitleOffset\":0,\"fTitleSize\":0.035,\"fTitleColor\":1,\"fTitleFont\":42,\"fNbins\":1,\"fXmin\":0,\"fXmax\":1,\"fXbins\":[],\"fFirst\":0,\"fLast\":0,\"fBits2\":0,\"fTimeDisplay\":false,\"fTimeFormat\":\"\",\"fLabels\":null,\"fModLabs\":null},\"fZaxis\":{\"_typename\":\"TAxis\",\"fUniqueID\":0,\"fBits\":50331648,\"fName\":\"zaxis\",\"fTitle\":\"\",\"fNdivisions\":510,\"fAxisColor\":1,\"fLabelColor\":1,\"fLabelFont\":42,\"fLabelOffset\":0.005,\"fLabelSize\":0.035,\"fTickLength\":0.03,\"fTitleOffset\":1,\"fTitleSize\":0.035,\"fTitleColor\":1,\"fTitleFont\":42,\"fNbins\":1,\"fXmin\":0,\"fXmax\":1,\"fXbins\":[],\"fFirst\":0,\"fLast\":0,\"fBits2\":0,\"fTimeDisplay\":false,\"fTimeFormat\":\"\",\"fLabels\":null,\"fModLabs\":null},\"fBarOffset\":0,\"fBarWidth\":1000,\"fEntries\":64,\"fTsumw\":0,\"fTsumw2\":0,\"fTsumwx\":0,\"fTsumwx2\":0,\"fMaximum\":-1111,\"fMinimum\":-1111,\"fNormFactor\":0,\"fContour\":[],\"fSumw2\":[],\"fOption\":\"\",\"fFunctions\":{\"_typename\":\"TList\",\"name\":\"TList\",\"arr\":[{\"_typename\":\"TPaveStats\",\"fUniqueID\":0,\"fBits\":50331657,\"fLineColor\":1,\"fLineStyle\":1,\"fLineWidth\":1,\"fFillColor\":0,\"fFillStyle\":1001,\"fX1\":3.75000012665987,\"fY1\":0.885937513201498,\"fX2\":5.00000016391278,\"fY2\":1.09593751163688,\"fX1NDC\":0.780000016093254,\"fY1NDC\":0.775000005960464,\"fX2NDC\":0.980000019073486,\"fY2NDC\":0.935000002384186,\"fBorderSize\":1,\"fInit\":1,\"fShadowColor\":1,\"fCornerRadius\":0,\"fOption\":\"brNDC\",\"fName\":\"stats\",\"fTextAngle\":0,\"fTextSize\":0,\"fTextAlign\":12,\"fTextColor\":1,\"fTextFont\":42,\"fLabel\":\"\",\"fLongest\":18,\"fMargin\":0.05,\"fLines\":{\"_typename\":\"TList\",\"name\":\"TList\",\"arr\":[{\"_typename\":\"TLatex\",\"fUniqueID\":0,\"fBits\":50331648,\"fName\":\"\",\"fTitle\":\"hist_data\",\"fTextAngle\":0,\"fTextSize\":0.0368,\"fTextAlign\":0,\"fTextColor\":0,\"fTextFont\":0,\"fX\":0,\"fY\":0,\"fLineColor\":1,\"fLineStyle\":1,\"fLineWidth\":2,\"fLimitFactorSize\":3,\"fOriginSize\":0.0368000008165836},{\"_typename\":\"TLatex\",\"fUniqueID\":0,\"fBits\":50331648,\"fName\":\"\",\"fTitle\":\"Entries = 64     \",\"fTextAngle\":0,\"fTextSize\":0,\"fTextAlign\":0,\"fTextColor\":0,\"fTextFont\":0,\"fX\":0,\"fY\":0,\"fLineColor\":1,\"fLineStyle\":1,\"fLineWidth\":2,\"fLimitFactorSize\":3,\"fOriginSize\":0.04},{\"_typename\":\"TLatex\",\"fUniqueID\":0,\"fBits\":50331648,\"fName\":\"\",\"fTitle\":\"Mean  =      0\",\"fTextAngle\":0,\"fTextSize\":0,\"fTextAlign\":0,\"fTextColor\":0,\"fTextFont\":0,\"fX\":0,\"fY\":0,\"fLineColor\":1,\"fLineStyle\":1,\"fLineWidth\":2,\"fLimitFactorSize\":3,\"fOriginSize\":0.04},{\"_typename\":\"TLatex\",\"fUniqueID\":0,\"fBits\":50331648,\"fName\":\"\",\"fTitle\":\"Std Dev   =      0\",\"fTextAngle\":0,\"fTextSize\":0,\"fTextAlign\":0,\"fTextColor\":0,\"fTextFont\":0,\"fX\":0,\"fY\":0,\"fLineColor\":1,\"fLineStyle\":1,\"fLineWidth\":2,\"fLimitFactorSize\":3,\"fOriginSize\":0.04}],\"opt\":[\"\",\"\",\"\",\"\"]},\"fOptFit\":0,\"fOptStat\":1111,\"fFitFormat\":\"5.4g\",\"fStatFormat\":\"6.4g\",\"fParent\":{\"$ref\":3}}],\"opt\":[\"brNDC\"]},\"fBufferSize\":0,\"fBuffer\":[],\"fBinStatErrOpt\":0,\"fStatOverflows\":2,\"fArray\":[0,0,0,0,0,64]},{\"_typename\":\"TPaveText\",\"fUniqueID\":0,\"fBits\":50331657,\"fLineColor\":1,\"fLineStyle\":1,\"fLineWidth\":1,\"fFillColor\":0,\"fFillStyle\":0,\"fX1\":0.999214809207741,\"fY1\":1.09483611614831,\"fX2\":3.00078519079226,\"fY2\":1.17468751593959,\"fX1NDC\":0.339874371859296,\"fY1NDC\":0.934160843929211,\"fX2NDC\":0.660125628140704,\"fY2NDC\":0.995000004768372,\"fBorderSize\":0,\"fInit\":1,\"fShadowColor\":1,\"fCornerRadius\":0,\"fOption\":\"blNDC\",\"fName\":\"title\",\"fTextAngle\":0,\"fTextSize\":0,\"fTextAlign\":22,\"fTextColor\":1,\"fTextFont\":42,\"fLabel\":\"\",\"fLongest\":17,\"fMargin\":0.05,\"fLines\":{\"_typename\":\"TList\",\"name\":\"TList\",\"arr\":[{\"_typename\":\"TLatex\",\"fUniqueID\":0,\"fBits\":50331648,\"fName\":\"\",\"fTitle\":\" Height vs Origen\",\"fTextAngle\":0,\"fTextSize\":0,\"fTextAlign\":0,\"fTextColor\":0,\"fTextFont\":0,\"fX\":0,\"fY\":0,\"fLineColor\":1,\"fLineStyle\":1,\"fLineWidth\":2,\"fLimitFactorSize\":3,\"fOriginSize\":0.0517132878303528}],\"opt\":[\"\"]}}],\"opt\":[\"\",\"\",\"blNDC\"]},\"fExecs\":null,\"fName\":\"Canvas\",\"fTitle\":\"Height vs Race\",\"fNumPaletteColor\":0,\"fNextPaletteColor\":0,\"fDISPLAY\":\"$DISPLAY\",\"fDoubleBuffer\":0,\"fRetained\":true,\"fXsizeUser\":0,\"fYsizeUser\":0,\"fXsizeReal\":20,\"fYsizeReal\":15,\"fWindowTopX\":0,\"fWindowTopY\":0,\"fWindowWidth\":0,\"fWindowHeight\":0,\"fCw\":796,\"fCh\":572,\"fCatt\":{\"_typename\":\"TAttCanvas\",\"fXBetween\":2,\"fYBetween\":2,\"fTitleFromTop\":1.2,\"fXdate\":0.2,\"fYdate\":0.3,\"fAdate\":1},\"kMoveOpaque\":true,\"kResizeOpaque\":true,\"fHighLightColor\":2,\"fBatch\":true,\"kShowEventStatus\":false,\"kAutoExec\":true,\"kMenuBar\":true});\n",
+       "       Core.draw(\"root_plot_3\", obj, \"\");\n",
+       "     }\n",
+       " );\n",
+       "</script>\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "canva.Draw()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "file = uproot.open(\"/home/student/ejercicios-clase-08-datos/codigo/data_analisis.root\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[b'data_analisis;1']"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "file.keys()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "NameError",
+     "evalue": "name 'analisis' is not defined",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-33-dcded93941c6>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mylabel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Tamaño'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mxlabel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Origen'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 5\u001b[0;31m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbar\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0manalisis\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'tree.origen'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mheight\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0manalisis\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'tree.tamano'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+      "\u001b[0;31mNameError\u001b[0m: name 'analisis' is not defined"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 720x720 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "#plt.title('Titulo')\n",
+    "plt.figure(figsize=(10,10))\n",
+    "plt.ylabel('Tamaño')\n",
+    "plt.xlabel('Origen')\n",
+    "plt.bar(x=analisis['tree.origen'], height=analisis['tree.tamano'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "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": "3.6.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
+%% Cell type:markdown id: tags:
+
+#This code meants to be generic to analyze data from a .root file using ROOT.
+
+At this time the data is a file from  (insert path to gitmilab) .csv file
+
+wich relates etnies with height.
+
+
+%% Cell type:code id: tags:
+
+``` python
+import ROOT
+import uproot
+import matplotlib.pyplot as plt
+```
+
+%% Output
+
+    Welcome to JupyROOT 6.18/04
+
+%% Cell type:code id: tags:
+
+``` python
+# activates javascripts for interactive graphs.
+
+%jsroot on
+```
+
+%% Cell type:code id: tags:
+
+``` python
+#data anlysis using root
+
+#open .root file and named it "data"
+
+data = ROOT.TFile.Open("/home/student/ejercicios-clase-08-datos/codigo/data_analisis.root")
+```
+
+%% Cell type:code id: tags:
+
+``` python
+#define canvas , named "canva", and Title "Height vs Race"
+
+canva = ROOT.TCanvas("Canvas","Height vs Race",800,600)
+```
+
+%% Cell type:code id: tags:
+
+``` python
+#define a tree to store .root file form the spreadsheet "data_analisis"
+tree = data.Get("data_analisis")
+```
+
+%% Cell type:code id: tags:
+
+``` python
+# To know how many entries has the file
+tree.GetEntries()
+```
+
+%% Output
+
+    32
+
+%% Cell type:code id: tags:
+
+``` python
+#Build the histogram using ROOT.
+
+# Data_ analysis has 4 countries each of them represents a colum on the X axis.
+
+hist = ROOT.TH1F("hist_data"," Height vs Origen; Origen ; Height " ,4,-0.5,4.5)
+```
+
+%% Cell type:code id: tags:
+
+``` python
+for origen in tree:
+    hist.Fill(tree.tamano)
+
+print("Done!")
+```
+
+%% Output
+
+    Done!
+
+%% Cell type:code id: tags:
+
+``` python
+hist.SetFillColor(40)
+hist.Draw()
+```
+
+%% Cell type:code id: tags:
+
+``` python
+canva.Draw()
+```
+
+%% Output
+
+
+%% Cell type:code id: tags:
+
+``` python
+```
+
+%% Cell type:code id: tags:
+
+``` python
+file = uproot.open("/home/student/ejercicios-clase-08-datos/codigo/data_analisis.root")
+```
+
+%% Cell type:code id: tags:
+
+``` python
+file.keys()
+```
+
+%% Output
+
+    [b'data_analisis;1']
+
+%% Cell type:code id: tags:
+
+``` python
+#plt.title('Titulo')
+plt.figure(figsize=(10,10))
+plt.ylabel('Tamaño')
+plt.xlabel('Origen')
+plt.bar(x=analisis['tree.origen'], height=analisis['tree.tamano'])
+```
+
+%% Output
+
+    ---------------------------------------------------------------------------
+    NameError                                 Traceback (most recent call last)
+    <ipython-input-33-dcded93941c6> in <module>
+          3 plt.ylabel('Tamaño')
+          4 plt.xlabel('Origen')
+    ----> 5 plt.bar(x=analisis['tree.origen'], height=analisis['tree.tamano'])
+
+    NameError: name 'analisis' is not defined
+
+
+
+%% Cell type:code id: tags:
+
+``` python
+```