IDEA Mini-demo data analysis

README.md

All IDEA Mini-demo data analysis notebooks to view on nbviewer.ipython.org

minidemo_between_day_variability.ipynb

{
 "metadata": {
  "name": "minidemo_between_day_variability"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# IDEA Mini-demo: variability between days\n",
      "\n",
      "<style>\n",
      "    .rendered_html h1 {\n",
      "        font-family: Arial;\n",
      "        color: #555;\n",
      "        padding: 10px;\n",
      "        padding-left: 20px;\n",
      "        border: 1px solid #AAA;\n",
      "        box-shadow: 0px 8px 10px -8px #999;\n",
      "        background: #EEE;\n",
      "        text-shadow: 0px 1px 1px white;\n",
      "    }\n",
      "    .rendered_html h2 {\n",
      "        border: 1px solid #BBB;\n",
      "        background: #F9F9F9;\n",
      "        padding:6px;\n",
      "        padding-left: 20px;\n",
      "        color: #4A4A4A;\n",
      "        box-shadow: 0px 8px 10px -10px #888;\n",
      "    }\n",
      "    .rendered_html h3 {\n",
      "        border-bottom: 1px solid #DDD;\n",
      "        border-top: 1px solid #DDD;\n",
      "        padding: 6px;\n",
      "        margin-top: 16px;\n",
      "        margin-bottom: 8px;\n",
      "        padding-left: 20px;\n",
      "        color: #4A4A4A;\n",
      "    }\n",
      "    .rendered_html h4 {\n",
      "        border-top: 1px solid #DDD;\n",
      "        color: #555;\n",
      "        text-align: center;\n",
      "        padding: 8px;\n",
      "    }\n",
      "    .rendered_html hr {\n",
      "        height: 0px;\n",
      "    }\n",
      "    .rendered_html p {\n",
      "        font-size: 16px;\n",
      "        color: #090909;\n",
      "        padding-left: 6px;\n",
      "        padding-right: 6px;\n",
      "    }\n",
      "    .rendered_html li {\n",
      "        font-size: 16px;\n",
      "        color: #090909;\n",
      "        padding-left: 6px;\n",
      "        padding-right: 6px;\n",
      "    }\n",
      "    .text_cell_render {\n",
      "        max-width:1000px;\n",
      "        margin-left:20px;\n",
      "    }\n",
      "</style>"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Mogelijkheden:\n",
      "\n",
      "- d"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<script type=\"text/javascript\">\n",
      "    on = \"View input\";\n",
      "    off = \"Hide input\"\n",
      "    function onoff(){\n",
      "      currentvalue = document.getElementById('onoff').value;\n",
      "      if(currentvalue == off){\n",
      "        document.getElementById(\"onoff\").value=on;\n",
      "          $('div.input').hide();\n",
      "      }else{\n",
      "        document.getElementById(\"onoff\").value=off;\n",
      "          $('div.input').show();\n",
      "      }\n",
      "}\n",
      "</script>\n",
      "<input type=\"button\" class=\"ui-button ui-widget ui-state-default ui-corner-all ui-button-text-only\" value=\"Hide input\" id=\"onoff\" onclick=\"onoff();\">"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Load all data and R functions from [minidemo_import.ipynb](http://nbviewer.ipython.org/5508591/minidemo_import.ipynb)"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import utils\n",
      "utils.execute_notebook(\"minidemo_import.ipynb\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%R\n",
      "data_mobile <- data[data$run_id != 0,]\n",
      "data1_mobile <- data1[data1$run_id != 0,]\n",
      "data2_mobile <- data2[data2$run_id != 0,]\n",
      "data2_mobile <- data2_mobile[data2_mobile$route==2,]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%R\n",
      "## Gemiddelden per run + per straat\n",
      "\n",
      "# aeroflex 1 metingen\n",
      "data1_streetrun <- aggregate(data1_mobile, list(street = data1_mobile$st_name, run_id = data1_mobile$run_id), mean, na.rm = TRUE)\n",
      "data1_streetrun2 <- aggregate(data1_mobile, list(street = data1_mobile$st_name, run_id = data1_mobile$run_id), median, na.rm = TRUE)\n",
      "\n",
      "# aeroflex 2 metingen\n",
      "data2_streetrun <- aggregate(data2_mobile, list(street = data2_mobile$st_name, run_id = data2_mobile$run_id), mean, na.rm = TRUE)\n",
      "data2_streetrun2 <- aggregate(data2_mobile, list(street = data2_mobile$st_name, run_id = data2_mobile$run_id), median, na.rm = TRUE)\n",
      "\n",
      "# all mobile measurements\n",
      "data_streetrun <- aggregate(data_mobile, list(street = data_mobile$st_name, run_id = data_mobile$run_id), mean, na.rm = TRUE)\n",
      "data_streetrun2 <- aggregate(data_mobile, list(street = data_mobile$st_name, run_id = data_mobile$run_id), median, na.rm = TRUE)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 4
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Diurnal variation"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%R --width 720 --height 480\n",
      "\n",
      "## All data\n",
      "boxplot(data1_streetrun$bc_ona_05~data1_streetrun$day, ylim=c(0,18000), ylab = \"Black Carbon (ng m-3)\", main=\"Route 1\")\n",
      "\n",
      "boxplot(data2_streetrun$bc_ona_05~data2_streetrun$day, ylim=c(0,18000), ylab = \"Black Carbon (ng m-3)\", main=\"Route 2\")\n",
      "\n",
      "boxplot(data_streetrun$bc_ona_05~data_streetrun$day, ylim=c(0,18000), ylab = \"Black Carbon (ng m-3)\", main=\"All mobile data\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": 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HR+FRSBCKGStFbTMzPgXGrFK+3SrS4MnA2F3QDEGXI8Daie9Dx/cfzyiXpJX9TanO1fAk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\nw35/3Z8pJghyLmj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GBY0IBQoaEQoUNCIUKGhEKFDQiFCgoBGhQEEjQmGwoJXFpJXFHR0O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\noUBBI0KBgkaEAgWNCAUKGhEKFDQiFP8Pds0vcapvUt4AAAAASUVORK5CYII=\n"
      },
      {
       "output_type": "display_data",
       "png": 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      },
      {
       "output_type": "display_data",
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yQcNdjoUXntq196gNQ7BwkMvBWFO9JjwVaNt550V9ayo4mXIux3cXTDi8s+WF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\n"
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%R --width 720 --height 480\n",
      "\n",
      "## All data\n",
      "boxplot(data1_streetrun$ufp~data1_streetrun$day, ylim=c(0,90000), ylab = \"Ultrafine Particles (#)\", main=\"Route 1\")\n",
      "\n",
      "boxplot(data2_streetrun$ufp~data2_streetrun$day, ylim=c(0,90000), ylab = \"Ultrafine Particles (#)\", main=\"Route 2\")\n",
      "\n",
      "boxplot(data_streetrun$ufp~data_streetrun$day, ylim=c(0,90000), ylab = \"Ultrafine Particles (#)\", main=\"All mobile data\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": 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      },
      {
       "output_type": "display_data",
       "png": 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      },
      {
       "output_type": "display_data",
       "png": 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I7HLsHT/6W90DzBJ0z9SBE5qnAhOdPq4+IDtmDixowvBWnrZDgY+5MHI5AIjb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\nBam0gwRN2EDCgnYXBn4Uus/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      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}

minidemo_calibration_aethalometers.ipynb

minidemo_calibration_ptraks.ipynb

minidemo_exploration.ipynb

minidemo_import.ipynb

minidemo_within_day_variability.ipynb

minidemo_within_street_between_runs_variability.ipynb