evanbiederstedt/discordant_methylation_project_April27_2016_moresamples.ipynb

## discordant_methylation_project_April27_2016_moresamples.ipynb
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# similar to discordant_methylation_project_April25_2016.ipynb, but more samples\n",
    "%matplotlib inline  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import os\n",
    "os.chdir('/Users/evanbiederstedt/downloads/cellsamples')   \n",
    "# files at http://www.broadinstitute.org/~kendell/seq/scRRBS/anno/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib\n",
    "pd.set_option('display.max_columns', 50) # print all rows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#\n",
    "# first 11 mammary cell samples, CD27\n",
    "#\n",
    "# NOTE: the first file, 'RRBS_NormalBCD19_CD27_cell1_22_CGAGGCTG.ACAACC.reads.anno' 111 KB is empty\n",
    "# We begin with the second file\n",
    "# Also, the 4th file 'RRBS_NormalBCD19_CD27_cell1_22_CGAGGCTG.AGGATG.reads.anno' only has 3 rows\n",
    "# The 10th file 'RRBS_NormalBCD19_CD27_cell1_22_CGAGGCTG.CGGTAG.reads.anno' only has 71 rows\n",
    "#\n",
    "# Therefore, we include 22 files\n",
    "#\n",
    "df_mam1 = pd.read_table('RRBS_NormalBCD19_CD27_cell1_22_CGAGGCTG.ACCGCG.reads.anno')\n",
    "df_mam2 = pd.read_table('RRBS_NormalBCD19_CD27_cell1_22_CGAGGCTG.ACGTGG.reads.anno')\n",
    "df_mam3 = pd.read_table('RRBS_NormalBCD19_CD27_cell1_22_CGAGGCTG.ACTCAC.reads.anno')\n",
    "df_mam4 = pd.read_table('RRBS_NormalBCD19_CD27_cell1_22_CGAGGCTG.AGGATG.reads.anno') # shaped (3, 30), \n",
    "df_mam5 = pd.read_table('RRBS_NormalBCD19_CD27_cell1_22_CGAGGCTG.ATAGCG.reads.anno')\n",
    "df_mam6 = pd.read_table('RRBS_NormalBCD19_CD27_cell1_22_CGAGGCTG.ATCGAC.reads.anno')\n",
    "df_mam7 = pd.read_table('RRBS_NormalBCD19_CD27_cell1_22_CGAGGCTG.CAAGAG.reads.anno')\n",
    "df_mam8 = pd.read_table('RRBS_NormalBCD19_CD27_cell1_22_CGAGGCTG.CATGAC.reads.anno')\n",
    "df_mam9 = pd.read_table('RRBS_NormalBCD19_CD27_cell1_22_CGAGGCTG.CCTTCG.reads.anno')\n",
    "df_mam10 = pd.read_table('RRBS_NormalBCD19_CD27_cell1_22_CGAGGCTG.CGGTAG.reads.anno') # shaped (71, 30)\n",
    "df_mam11 = pd.read_table('RRBS_NormalBCD19_CD27_cell1_22_CGAGGCTG.CTATTG.reads.anno')\n",
    "df_mam12 = pd.read_table('RRBS_NormalBCD19_CD27_cell1_22_CGAGGCTG.CTCAGC.reads.anno')\n",
    "df_mam13 = pd.read_table('RRBS_NormalBCD19_CD27_cell1_22_CGAGGCTG.GACACG.reads.anno')\n",
    "df_mam14 = pd.read_table('RRBS_NormalBCD19_CD27_cell1_22_CGAGGCTG.GCATTC.reads.anno')\n",
    "df_mam15 = pd.read_table('RRBS_NormalBCD19_CD27_cell1_22_CGAGGCTG.GCTGCC.reads.anno')\n",
    "df_mam16 = pd.read_table('RRBS_NormalBCD19_CD27_cell1_22_CGAGGCTG.GGCATC.reads.anno')\n",
    "df_mam17 = pd.read_table('RRBS_NormalBCD19_CD27_cell1_22_CGAGGCTG.GTGAGG.reads.anno')\n",
    "df_mam18 = pd.read_table('RRBS_NormalBCD19_CD27_cell1_22_CGAGGCTG.GTTGAG.reads.anno')\n",
    "df_mam19 = pd.read_table('RRBS_NormalBCD19_CD27_cell1_22_CGAGGCTG.TAGCGG.reads.anno')\n",
    "df_mam20 = pd.read_table('RRBS_NormalBCD19_CD27_cell1_22_CGAGGCTG.TATCTC.reads.anno')\n",
    "df_mam21 = pd.read_table('RRBS_NormalBCD19_CD27_cell1_22_CGAGGCTG.TCTCTG.reads.anno')\n",
    "# df_mam22 = pd.read_table('RRBS_NormalBCD19_CD27_cell1_22_CGAGGCTG.TGCTGC.reads.anno') # (0, 12)  there is no data here\n",
    "df_mam23 = pd.read_table('RRBS_NormalBCD19_CD27_cell1_22_TAGGCATG.ACAACC.reads.anno')\n",
    "df_mam24 = pd.read_table('RRBS_NormalBCD19_CD27_cell1_22_TAGGCATG.ACCGCG.reads.anno')\n",
    "df_mam25 = pd.read_table('RRBS_NormalBCD19_CD27_cell1_22_TAGGCATG.ACGTGG.reads.anno')\n",
    "df_mam26 = pd.read_table('RRBS_NormalBCD19_CD27_cell1_22_TAGGCATG.ACTCAC.reads.anno')\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#\n",
    "# first 20 naïve cell samples, IGD\n",
    "#\n",
    "# NOTE: these files are labeled incorrectly, e.g. \n",
    "# The format should be 'RRBS_NormalBCD19_cell1_IDG_22_TAAGGCGA.ACAACC.reads.anno'\n",
    "# \n",
    "df_igd1 = pd.read_table('RRBS_NormalBCD19_cell1_22_TAAGGCGA.ACAACC.reads.anno')\n",
    "df_igd2 = pd.read_table('RRBS_NormalBCD19_cell1_22_TAAGGCGA.ACCGCG.reads.anno')\n",
    "df_igd3 = pd.read_table('RRBS_NormalBCD19_cell1_22_TAAGGCGA.ACGTGG.reads.anno')\n",
    "df_igd4 = pd.read_table('RRBS_NormalBCD19_cell1_22_TAAGGCGA.ACTCAC.reads.anno')\n",
    "df_igd5 = pd.read_table('RRBS_NormalBCD19_cell1_22_TAAGGCGA.AGGATG.reads.anno')\n",
    "df_igd6 = pd.read_table('RRBS_NormalBCD19_cell1_22_TAAGGCGA.ATAGCG.reads.anno')\n",
    "df_igd7 = pd.read_table('RRBS_NormalBCD19_cell1_22_TAAGGCGA.ATCGAC.reads.anno')\n",
    "df_igd8 = pd.read_table('RRBS_NormalBCD19_cell1_22_TAAGGCGA.CAAGAG.reads.anno')\n",
    "df_igd9 = pd.read_table('RRBS_NormalBCD19_cell1_22_TAAGGCGA.CATGAC.reads.anno')\n",
    "df_igd10 = pd.read_table('RRBS_NormalBCD19_cell1_22_TAAGGCGA.CCTTCG.reads.anno')\n",
    "df_igd11 = pd.read_table('RRBS_NormalBCD19_cell1_22_TAAGGCGA.CGGTAG.reads.anno')\n",
    "df_igd12 = pd.read_table('RRBS_NormalBCD19_cell1_22_TAAGGCGA.CTATTG.reads.anno')\n",
    "df_igd13 = pd.read_table('RRBS_NormalBCD19_cell1_22_TAAGGCGA.CTCAGC.reads.anno')\n",
    "df_igd14 = pd.read_table('RRBS_NormalBCD19_cell1_22_TAAGGCGA.GACACG.reads.anno')\n",
    "df_igd15 = pd.read_table('RRBS_NormalBCD19_cell1_22_TAAGGCGA.GCATTC.reads.anno')\n",
    "df_igd16 = pd.read_table('RRBS_NormalBCD19_cell1_22_TAAGGCGA.GCTGCC.reads.anno')\n",
    "df_igd17 = pd.read_table('RRBS_NormalBCD19_cell1_22_TAAGGCGA.GGCATC.reads.anno')\n",
    "df_igd18 = pd.read_table('RRBS_NormalBCD19_cell1_22_TAAGGCGA.GTGAGG.reads.anno')\n",
    "df_igd19 = pd.read_table('RRBS_NormalBCD19_cell1_22_TAAGGCGA.GTTGAG.reads.anno')\n",
    "df_igd20 = pd.read_table('RRBS_NormalBCD19_cell1_22_TAAGGCGA.TAGCGG.reads.anno')\n",
    "df_igd21 = pd.read_table('RRBS_NormalBCD19_cell1_22_TAAGGCGA.TATCTC.reads.anno')\n",
    "df_igd22 = pd.read_table('RRBS_NormalBCD19_cell1_22_TAAGGCGA.TCTCTG.reads.anno')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(5114, 30)\n",
      "(7570, 30)\n",
      "(18944, 30)\n",
      "(3, 30)\n",
      "(6458, 30)\n",
      "(17978, 30)\n",
      "(12115, 30)\n",
      "(19065, 30)\n",
      "(10828, 30)\n",
      "(71, 30)\n",
      "(16147, 30)\n",
      "(9887, 30)\n",
      "(8876, 30)\n",
      "(8434, 30)\n",
      "(8095, 30)\n",
      "(9628, 30)\n",
      "(12718, 30)\n",
      "(14306, 30)\n",
      "(10644, 30)\n",
      "(3072, 30)\n",
      "(2, 30)\n",
      "(30586, 30)\n",
      "(5545, 30)\n",
      "(1, 30)\n",
      "(23170, 30)\n",
      "************\n",
      "(46743, 30)\n",
      "(8014, 30)\n",
      "(14718, 30)\n",
      "(40029, 30)\n",
      "(11751, 30)\n",
      "(50812, 30)\n",
      "(35110, 30)\n",
      "(11386, 30)\n",
      "(17053, 30)\n",
      "(8043, 30)\n",
      "(16967, 30)\n",
      "(15398, 30)\n",
      "(10949, 30)\n",
      "(22450, 30)\n",
      "(4515, 30)\n",
      "(17790, 30)\n",
      "(10087, 30)\n",
      "(379, 30)\n",
      "(11962, 30)\n",
      "(16955, 30)\n",
      "(9498, 30)\n",
      "(17055, 30)\n"
     ]
    }
   ],
   "source": [
    "print(df_mam1.shape)\n",
    "print(df_mam2.shape)\n",
    "print(df_mam3.shape)\n",
    "print(df_mam4.shape)\n",
    "print(df_mam5.shape)\n",
    "print(df_mam6.shape)\n",
    "print(df_mam7.shape)\n",
    "print(df_mam8.shape)\n",
    "print(df_mam9.shape)\n",
    "print(df_mam10.shape)\n",
    "print(df_mam11.shape)\n",
    "print(df_mam12.shape)\n",
    "print(df_mam13.shape)\n",
    "print(df_mam14.shape)\n",
    "print(df_mam15.shape)\n",
    "print(df_mam16.shape)\n",
    "print(df_mam17.shape)\n",
    "print(df_mam18.shape)\n",
    "print(df_mam19.shape)\n",
    "print(df_mam20.shape)\n",
    "print(df_mam21.shape)\n",
    "# print(df_mam22.shape) # (0, 12)  there is no data here\n",
    "print(df_mam23.shape)\n",
    "print(df_mam24.shape)\n",
    "print(df_mam25.shape)\n",
    "print(df_mam26.shape)\n",
    "print('************')\n",
    "print(df_igd1.shape)\n",
    "print(df_igd2.shape)\n",
    "print(df_igd3.shape)\n",
    "print(df_igd4.shape)\n",
    "print(df_igd5.shape)\n",
    "print(df_igd6.shape)\n",
    "print(df_igd7.shape)\n",
    "print(df_igd8.shape)\n",
    "print(df_igd9.shape)\n",
    "print(df_igd10.shape)\n",
    "print(df_igd11.shape)\n",
    "print(df_igd12.shape)\n",
    "print(df_igd13.shape)\n",
    "print(df_igd14.shape)\n",
    "print(df_igd15.shape)\n",
    "print(df_igd16.shape)\n",
    "print(df_igd17.shape)\n",
    "print(df_igd18.shape)\n",
    "print(df_igd19.shape)\n",
    "print(df_igd20.shape)\n",
    "print(df_igd21.shape)\n",
    "print(df_igd22.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "cols = list(range(8,30)) # define list of columns to drop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "df_mam1 = df_mam1.drop(df_mam1.columns[cols], axis=1) # drop columns\n",
    "df_mam2 = df_mam2.drop(df_mam2.columns[cols], axis=1)\n",
    "df_mam3 = df_mam3.drop(df_mam3.columns[cols], axis=1)\n",
    "df_mam4 = df_mam4.drop(df_mam4.columns[cols], axis=1)\n",
    "df_mam5 = df_mam5.drop(df_mam5.columns[cols], axis=1)\n",
    "df_mam6 = df_mam6.drop(df_mam6.columns[cols], axis=1)\n",
    "df_mam7 = df_mam7.drop(df_mam7.columns[cols], axis=1)\n",
    "df_mam8 = df_mam8.drop(df_mam8.columns[cols], axis=1)\n",
    "df_mam9 = df_mam9.drop(df_mam9.columns[cols], axis=1)\n",
    "df_mam10 = df_mam10.drop(df_mam10.columns[cols], axis=1)\n",
    "df_mam11 = df_mam11.drop(df_mam11.columns[cols], axis=1)\n",
    "df_mam12 = df_mam12.drop(df_mam12.columns[cols], axis=1)\n",
    "df_mam13 = df_mam13.drop(df_mam13.columns[cols], axis=1) \n",
    "df_mam14 = df_mam14.drop(df_mam14.columns[cols], axis=1) \n",
    "df_mam15 = df_mam15.drop(df_mam15.columns[cols], axis=1) \n",
    "df_mam16 = df_mam16.drop(df_mam16.columns[cols], axis=1) \n",
    "df_mam17 = df_mam17.drop(df_mam17.columns[cols], axis=1) \n",
    "df_mam18 = df_mam18.drop(df_mam18.columns[cols], axis=1) \n",
    "df_mam19 = df_mam19.drop(df_mam19.columns[cols], axis=1)\n",
    "df_mam20 = df_mam20.drop(df_mam20.columns[cols], axis=1) \n",
    "df_mam21 = df_mam21.drop(df_mam21.columns[cols], axis=1) \n",
    "# df_mam22 = df_mam22.drop(df_mam22.columns[cols], axis=1) \n",
    "df_mam23 = df_mam23.drop(df_mam23.columns[cols], axis=1) \n",
    "df_mam24 = df_mam24.drop(df_mam24.columns[cols], axis=1) \n",
    "df_mam25 = df_mam25.drop(df_mam25.columns[cols], axis=1) \n",
    "df_mam26 = df_mam26.drop(df_mam26.columns[cols], axis=1) \n",
    "\n",
    "df_igd1 = df_igd1.drop(df_igd1.columns[cols], axis=1)\n",
    "df_igd2 = df_igd2.drop(df_igd2.columns[cols], axis=1)\n",
    "df_igd3 = df_igd3.drop(df_igd3.columns[cols], axis=1)\n",
    "df_igd4 = df_igd4.drop(df_igd4.columns[cols], axis=1)\n",
    "df_igd5 = df_igd5.drop(df_igd5.columns[cols], axis=1)\n",
    "df_igd6 = df_igd6.drop(df_igd6.columns[cols], axis=1)\n",
    "df_igd7 = df_igd7.drop(df_igd7.columns[cols], axis=1)\n",
    "df_igd8 = df_igd8.drop(df_igd8.columns[cols], axis=1)\n",
    "df_igd9 = df_igd9.drop(df_igd9.columns[cols], axis=1)\n",
    "df_igd10 = df_igd10.drop(df_igd10.columns[cols], axis=1)\n",
    "df_igd11 = df_igd11.drop(df_igd11.columns[cols], axis=1)\n",
    "df_igd12 = df_igd12.drop(df_igd12.columns[cols], axis=1)\n",
    "df_igd13 = df_igd13.drop(df_igd13.columns[cols], axis=1)\n",
    "df_igd14 = df_igd14.drop(df_igd14.columns[cols], axis=1)\n",
    "df_igd15 = df_igd15.drop(df_igd15.columns[cols], axis=1)\n",
    "df_igd16 = df_igd16.drop(df_igd16.columns[cols], axis=1)\n",
    "df_igd17 = df_igd17.drop(df_igd17.columns[cols], axis=1)\n",
    "df_igd18 = df_igd18.drop(df_igd18.columns[cols], axis=1)\n",
    "df_igd19 = df_igd19.drop(df_igd19.columns[cols], axis=1)\n",
    "df_igd20 = df_igd20.drop(df_igd20.columns[cols], axis=1)\n",
    "df_igd21 = df_igd21.drop(df_igd21.columns[cols], axis=1)\n",
    "df_igd22 = df_igd22.drop(df_igd22.columns[cols], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "df_mam1['total_reads'] = df_mam1[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1)  # sum total reads\n",
    "df_mam2['total_reads'] = df_mam2[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_mam3['total_reads'] = df_mam3[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_mam4['total_reads'] = df_mam4[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_mam5['total_reads'] = df_mam5[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_mam6['total_reads'] = df_mam6[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_mam7['total_reads'] = df_mam7[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_mam8['total_reads'] = df_mam8[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_mam9['total_reads'] = df_mam9[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_mam10['total_reads'] = df_mam10[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_mam11['total_reads'] = df_mam11[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_mam12['total_reads'] = df_mam12[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_mam13['total_reads'] = df_mam13[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_mam14['total_reads'] = df_mam14[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_mam15['total_reads'] = df_mam15[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_mam16['total_reads'] = df_mam16[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_mam17['total_reads'] = df_mam17[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_mam18['total_reads'] = df_mam18[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_mam19['total_reads'] = df_mam19[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1)\n",
    "df_mam20['total_reads'] = df_mam20[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_mam21['total_reads'] = df_mam21[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "# df_mam22['total_reads'] = df_mam12[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_mam23['total_reads'] = df_mam23[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_mam24['total_reads'] = df_mam24[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_mam25['total_reads'] = df_mam25[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_mam26['total_reads'] = df_mam26[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_igd1['total_reads'] = df_igd1[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1)  # sum total reads\n",
    "df_igd2['total_reads'] = df_igd2[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_igd3['total_reads'] = df_igd3[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_igd4['total_reads'] = df_igd4[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_igd5['total_reads'] = df_igd5[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_igd6['total_reads'] = df_igd6[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_igd7['total_reads'] = df_igd7[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_igd8['total_reads'] = df_igd8[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_igd9['total_reads'] = df_igd9[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_igd10['total_reads'] = df_igd10[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_igd11['total_reads'] = df_igd11[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1)  \n",
    "df_igd12['total_reads'] = df_igd12[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_igd13['total_reads'] = df_igd13[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_igd14['total_reads'] = df_igd14[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_igd15['total_reads'] = df_igd15[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_igd16['total_reads'] = df_igd16[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_igd17['total_reads'] = df_igd17[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_igd18['total_reads'] = df_igd18[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_igd19['total_reads'] = df_igd19[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_igd20['total_reads'] = df_igd20[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_igd21['total_reads'] = df_igd21[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) \n",
    "df_igd22['total_reads'] = df_igd22[[\"readMeth\", \"readUnmeth\", \"readMixed\"]].sum(axis=1) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "df_mam1['PDR'] =  df_mam1.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_mam2['PDR'] =  df_mam2.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_mam3['PDR'] =  df_mam3.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_mam4['PDR'] =  df_mam4.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_mam5['PDR'] =  df_mam5.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_mam6['PDR'] =  df_mam6.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_mam7['PDR'] =  df_mam7.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_mam8['PDR'] =  df_mam8.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_mam9['PDR'] =  df_mam9.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_mam10['PDR'] =  df_mam10.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_mam11['PDR'] =  df_mam11.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_mam12['PDR'] =  df_mam12.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_mam13['PDR'] =  df_mam13.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_mam14['PDR'] =  df_mam14.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_mam15['PDR'] =  df_mam15.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_mam16['PDR'] =  df_mam16.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_mam17['PDR'] =  df_mam17.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_mam18['PDR'] =  df_mam18.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_mam19['PDR'] =  df_mam19.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_mam20['PDR'] =  df_mam20.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_mam21['PDR'] =  df_mam21.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "# df_mam22['PDR'] =  df_mam22.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_mam23['PDR'] =  df_mam23.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_mam24['PDR'] =  df_mam24.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_mam25['PDR'] =  df_mam25.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_mam26['PDR'] =  df_mam26.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_igd1['PDR'] =  df_igd1.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_igd2['PDR'] =  df_igd2.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_igd3['PDR'] =  df_igd3.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_igd4['PDR'] =  df_igd4.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_igd5['PDR'] =  df_igd5.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_igd6['PDR'] =  df_igd6.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_igd7['PDR'] =  df_igd7.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_igd8['PDR'] =  df_igd8.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_igd9['PDR'] =  df_igd9.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_igd10['PDR'] =  df_igd10.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_igd11['PDR'] =  df_igd11.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_igd12['PDR'] =  df_igd12.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_igd13['PDR'] =  df_igd13.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_igd14['PDR'] =  df_igd14.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_igd15['PDR'] =  df_igd15.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_igd16['PDR'] =  df_igd16.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_igd17['PDR'] =  df_igd17.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_igd18['PDR'] =  df_igd18.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_igd19['PDR'] =  df_igd19.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_igd20['PDR'] =  df_igd20.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_igd21['PDR'] =  df_igd21.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)\n",
    "df_igd22['PDR'] =  df_igd22.apply(lambda row: row['readMixed']/row['total_reads'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 4719 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZAAAAEZCAYAAAC5AHPcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nHm7cbgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11ca4de10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 5114 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_mam1['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_mam1[df_mam1['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 6837 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZAAAAEZCAYAAAC5AHPcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAMUBAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11ca4df98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 7570 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_mam2['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_mam2[df_mam2['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 16172 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZUAAAEZCAYAAABfKbiYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1155b7c18>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 18944 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_mam3['PDR'].plot(kind='hist', color = 'darkred')\n",
    "print('There are ' + str(len(df_mam3[df_mam3['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 3 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYgAAAEZCAYAAACNebLAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\ncZsp4AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x117809438>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 3 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_mam4['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_mam4[df_mam4['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 5824 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZAAAAEZCAYAAAC5AHPcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzt3XmYHFW5x/HvJARkGaLAgLIICPJDQSHBsBMQAsgmKHoR\n5coiILIKglxQQHFBFlEQBAkIoqIoq4BhUZZEDMgSlmB4iYQggkLIRsIiWeb+cU4znaZnplOhl8n8\nPs+TJ91Vp6vePlNdb51TVafaOjs7MTMzW1gDmh2AmZn1TU4gZmZWiBOImZkV4gRiZmaFOIGYmVkh\nTiBmZlbIEs0OoK+RNB9YKSKmlU3bH/hMROwh6dvAxIj4VQ/LOAV4JCJuqn/Ei07S3cD7gRl5UhvQ\nGRFDmxZUk0i6CNgJuCoiTimbvj9wHjAJ6CQdnM0GToiI+ySdBhwB/ItUf0vkssdHxMS8jLtZsJ6X\nAJYEvhcRv6whtuHAmcDSeRkHRsQzFWWuA/4VEUfn9xsCY4GJZcX2iYiJkrYGfpTjeB04KiIeqqWe\n6kHSbsDwiDixDsveBLgmItZeiM9cAlwUEeMKrG9NYHxEtC/sZ1uJE8jC6+7GmU6AiDithmVsDzzx\njkVUf53A1yLi+mYH0gIOBdaIiBeqzBsdEZ8svZG0O3CdpNXzpN+Wdtx5/n7AnyV9OCJmU6We847t\nXknXRcSr3QUlaTXgOmCHiHhU0lHAhcCuZWW+DmwFXF320S2BX0fEYVUW+0vggIi4R9JewC+ADbuL\noQH2Ai6v4/IX9qa4HYGLG7i+luMEsvDaepop6XLg8Yg4N7dG9gTeBKYCBwKfBj4GnC1pHnAX6Ye+\nMTAfuBU4KSLmS9oV+AEwF3gUGEHaAXwc+BKwLOlIcw/gImBdYEVgFvD5fBR5F/AQKWl1AOcDqwDb\nAssA/xMRT0jaA/hyROy+MN87L38aoBzDL0lH4hsCg4A/k47C50vaGzgdeA34I3ByRAwqb8HlZZa3\n6AaRjqqHAwOBccDRETFb0jPAFcAOwBrA70pHp5IOAo7LdfcycABwKvBSRHwzl/kC8OmI2LviO20A\n/CTX5XzghxHxK0mjc5FRkg6PiHu7qauSP5Pq+t3VZuZl/i/weeCSPLmyntchtWT+28u6PgP8MSIe\nze8vAW4r+07bkVpOFwPvKfvclsDaku4n7dDOLEtgA4AV8uvlSa2QBeQj6THABGBN0na1Bamu20jb\n4nGk1tazwMoR8bqknwGKiO3ycp4ibcfbA1/O3/cN0jb5pKQ2YNOIOCS35rYAViW15L8o6WTSb2sA\nMBk4PCL+I2lz0vazJPA+4E8RcXBe51eAr5J+Q+OrVaqkgaRtYUtgTv4eBwEn5fX/WtIX83rPKlvP\nHRFxSF7G7sB3cn28CnwFmFm2jvVJv4djgZuBC/L3K63vwIh4rVp8zeZzIMXcJenh/G8caae4gHzU\neQwwLCI2BW4n/QB+CjxI6rq4kbRDfzkiPkJKLBsBx0taAbiSlAiGkhLNqmWr+DCpOb8DsAswPSK2\nioj18/KPLCu7Zl7G3qQf050RMYy0gzkKICJu6iF5QEp4D0sal///RNm8aRGxYURcSOryeDAvfygp\naR0n6b3AZaQd9jDSDqJ8+6s8Giu9/z9gTkR8LCKGAP8mJdWSZSNiOCmxHiVpTUkb5TI7RcTGwB+A\nk0k/zAMlldZ7KCnpvSXvMG4EzouIjUhH8GdI2iyvpw3YrobkAWlHOL68u7OKR4GPlL0v1fMzkv5D\nOgDZISLm9rKu9YDXJP1G0sPAb0k7ICStSvq7fIGUEMvNJnXHbUZKshdLKnVNfgn4paTnSHV3JNWt\nDnw7b3vvJtXpp/Lf6zRS/c8B7icd/EBKNOtJWkbSh0kHWRNznDvneC4Bts7ltwD+VrbO9wMb5eTx\nv6Q63DRv56NI2xqk7fuUiNgC2AD4pKQheRs5Ddg6r+vNbr7bFqS/98Z5u50EfCQfhLxA+n0+ABxd\nsZ4983pWJh1U7Z+3xXOAM0oLzwcrNwEH5f3BFsC2Fev7aDexNZ1bIMVsFxHTS2/yEfPeFWWeBx4B\nxkkaBYyKiDvL5peONHchHd0QEXMkXUw6KnoKeCIixud5V0o6r+zzj5W6NCLiWkmTJB1JaoVsB/y1\nrOx1+f+nSTvm28reb1vjdz4hIq7rZt6Yste7A8MkHZzfvyuvcyvg0YiIPP0C0lFZb3YHBkvaKb8f\nBLxYNv9GgIh4QdKLpCPm7YBbS91MEXF+qbCkScBukiYC74uIP1Wsbz1gqfxjJiL+Lela4BOkHSB0\n3wodnnfekI5En+Tt20WlTlKLrOSEiLhO0oqko9IpZa2Kngwi1dXWETEpd2FdJ2kYcBVwbES8KGmB\nD0XEkWWvn5R0NbCHpH8BI4FtImKcpD2BayV9MCIqWyJzgPvy6+1JR/nP5mXelf8uQ4EbgF3z3+B5\n4HHS3+qjwLW5lfo7YKykW0jb6VV5uXvmz5fcFxGlg4zdgWHAQ/n7DSCdB4KUFHeVdBKwPml7XC6X\nvy0ipuRylwA7V6nXx4G5uYV2G3BdThglpW2hu/VsReqReCzXx/XA9bnl9i7gTuCeiLi7xvW1FLdA\niumxGwsgIjpz83x/UhfKjyT9qErRASx49D2AlNjn8Pa/T3m52aUXuSl+Gal5/GvgNxUxLtD9ERHz\neot/Ic0uez0A+GxEDMlHoJuRjgJfr4ip/Ii6s2LekmWvBwLHlC1vU+CzZfMrd2Ztedlv1ZWkd6lr\nz/lT0pH1QXR1G5UbyNtbQwNIO+jejI6IofnfhhHxmYj4Ry+fGQY8VjkxIqYCnwMOyV1/vXkBuDci\nJuX3l5F2zJsAawPn5tbyYcA+ki6RNEDSyZKWLVtOG2nb2waYHPkEcU6oc4APVVn3fyOi1LKpVn8D\nSfV3PemAaSdSi/yO/HoP4Jq8ni+SEsJEUuuzdNAyAihP9uXb3EBS11tpG/kYXS2XMXmdE0g9BS/Q\nta11tz2+JSJmkrqXv5bLXC3pmCpFu1vP25YrqdTi7CSd1xkq6dMLub6W4ARSJ5I+Kmk8MCEiziQ1\nzTfKs+fStUO6ldw1IGkpUrfK7aQWxAeVrpIh70QGU/3E207A5RFxOemHtwfpR1VNr8lvEd1G6vMu\nfZ+bSFcfjSV9n41zuQPKPjMF2FDSkpKWIMVfvrwjJQ3KXU+XUdYF0I27gBGSVsnvDyN13UHaUQ0h\ntQx+XuWzTwJz8knjUvfP3qS/yTtK0pdIO/ffV5sf6Qqq75EOPpauVqbM9cBW+cgWUsxPRMT9EbFm\nTmpDSOdAro6IQ/NO/5Okba50PuPTpDp6jPQ3+WCetxnpqP6pKusu36b+DOwsaa38ue1JXVz3R8Tz\npIOpL5Pq8/Yc54oR8bikFSX9E5iaW43fBDbK5wieiYjuzgPdBhwsqXRF03dJXW+DSQn0xIi4Icex\nLum3cTuwU/77Qjo/+TZKV379GRgbEaeTupUX+B33sp77gfUlfSgvby9SlxbAmxExlnRAc5GkVXpZ\nX8txAll4NV05kZusV5Oa1Q+QNtCv5tk3AefkvtujgVUkPU7qD58AfD93kX2e9EN4kJQk5rJgd0fJ\nOcBhufvkDtJJ83W7ibdq/JL2kHRzN1+np+9cOe8YYJn8fR7J3+ms/H0+C4zM32dY2WduB+4BIv9f\nfkT+HdJJ0XGkE52dpKOzausuXQk3HjgBuC0fde9ESiJExBzSDvKv1c5N5HMNewFflfRoju1bEVE6\ngb4oV87sU3HubEdSd2ip/73ass8h/c1LJ/5vUTopWxn3o8DhwA257g9hwZZadz5P6np5DLiF1Np7\nKtKlxYeRuq0eIR0AfSrS1WKV3oo7IibkOK7Py/w+sHtEzMpFrgc6ImJcREzO3+26/NmppL/3nXkb\nOQM4mNR9dWMP3+FS0snn+/J335B0zmFmXsY4SX8DTgT+Aqybt5Gv53X9jQVbveVGkba78fl3vAXw\nrTzvBtJvfFgP63mJdO7pyvz7/CqwT3m9RcQ9pF6Dy0jdlk90s76W0+bh3FtTPpr6JnBaRLwhaQhw\nc0Ss1uTQ3hG5j39KRDT0ICZ319xDukrnb72VbzX53NKU0jkas2aq+0l0Sf9HaiYPIvU/jyZdejmf\ndIXKEbncqcBupH7WYyPiAUnrVCvbH0TELElvAg9KmkO6SqSWI8q+pKFHL/lE/G+AS/ti8sjmkI62\nzZquri0QSdsCx0XEnvnI73jS1RjnRMQYpbt6bwX+CZwdESMkrUG6ImNTSTdWlvWRl5lZa6h398HO\npL68G0jXgt8MDI2I0mWfo0j9wFuTT1JGxHPAQEkrAZtUlB1R53jNzKxG9e7CWol0w8/uwAdISaQ8\nac0iXVnUTrpTu3I6vUwzM7MmqXcCmUq6jHUu8JSkN0iXuJW0A9OBV0hDJZRPn8GCd82WpnWrs7Oz\ns62t3lepmpktdgrtOOudQP5Cukz1R/l662VJg8dtmy9d24V0J+bTwJmSziGNaTQgIqYqDZsxPF9C\nWSrbrba2NqZMmdVTkX6jo6PddZG5Lrq4Lrq4Lrp0dBQbFLiuCSQibpG0Tb42uo00iNhk4FKlQfIm\nkIZQ7pQ0hnSzWRvpOnJIJ91HlpetZ7xmZla7xe0+kE4fUSQ+uuriuujiuujSCnUxb948Jk+e1HvB\nOtt886Et2YVlZmbdmDx5Esec/QeWGbxy02J4beZL3H9tsWfDOYGYmTXRMoNXZrn39M0BJjwWlpmZ\nFeIEYmZmhTiBmJlZIU4gZmZWiBOImZkV4gRiZmaFOIGYmVkhTiBmZlaIE4iZmRXiBGJmZoU4gZiZ\nWSFOIGZmVogTiJmZFeIEYmZmhTiBmJlZIU4gZmZWiBOImZkV4gRiZmaFOIGYmVkhTiBmZlaIE4iZ\nmRXiBGJmZoU4gZiZWSFOIGZmVogTiJmZFeIEYmZmhTiBmJlZIUvUewWSHgZm5LfPAJcA5wFzgDsi\n4nRJbcBPgY2AN4CDI2KSpM2BH5eXrXe8ZmZWm7q2QCQtBXRGxPb535eAi4HPRcQ2wGaSNgb2ApaK\niC2Bk4Bz8yIuqlLWzMxaQL1bIBsBy0q6DRgIfBtYMiIm5/m3ASOA9wG3AkTE/ZI2kdRepewOwCN1\njtnMzGpQ73MgrwFnR8TOwFeAy/O0klnAYKAdmFk2fV6e9kqVsmZm1gLq3QJ5CvgHQERMlDQTWKFs\nfjswHVg6vy4ZQEoey1eUnUEvOjraeyvSb7guurguurguujS7LqZPX66p619U9U4gBwEfAY6QtCqw\nDPCqpLWBycDOwLeANYDdgWvyifPHI2K2pP9WKdujKVNmvfPfog/q6Gh3XWSuiy6uiy6tUBfTps1u\n6voXVb0TyGXA5ZLGAPOBA/P/V5FaGbdHxAOSHgR2lHRv/tyB+f+vVJatc7xmZlajuiaQiJgD7Fdl\n1hYV5TpJyaLy8/dXljUzs9bgGwnNzKwQJxAzMyvECcTMzApxAjEzs0KcQMzMrBAnEDMzK8QJxMzM\nCnECMTOzQpxAzMysECcQMzMrxAnEzMwKcQIxM7NCnEDMzKwQJxAzMyvECcTMzApxAjEzs0KcQMzM\nrBAnEDMzK8QJxMzMCnECMTOzQpxAzMysECcQMzMrxAnEzMwKcQIxM7NCnEDMzKwQJxAzMyvECcTM\nzApxAjEzs0KcQMzMrJAl6r0CSSsDDwIjgHnAFcB8YHxEHJHLnArsBswBjo2IByStU62smZm1hrq2\nQCQtAVwMvJYnnQucHBHbAgMk7SlpCDA8IjYD9gUu7K5sPWM1M7OFU+8urHOAi4AXgDZgaESMyfNG\nATsCWwO3A0TEc8BASSsBm1SUHVHnWM3MbCHULYFIOgB4KSLuICWPyvXNAgYD7cDMKtPpZZqZmTVR\nPc+BHAjMl7QjsBFwJdBRNr8dmA68AixfMX0G6dxH5bRedXS0L0LIixfXRRfXRRfXRZdm18X06cs1\ndf2Lqm4JJJ+7AEDSncBhwNmShkfEaGAX4E7gaeBMSecAawADImKqpHFVyvZqypRZ7/RX6ZM6Otpd\nF5nroovroksr1MW0abObuv5FVfersCocD4yUNAiYAFwTEZ2SxgBjSV1dh3dXtsGxmplZDxqSQCJi\n+7K321WZfzpwesW0idXKmplZa/CNhGZmVogTiJmZFeIEYmZmhTiBmJlZIU4gZmZWiBOImZkV4gRi\nZmaFOIGYmVkhTiBmZlaIE4iZmRVS01Amkv4IXA7cGBFv1jckMzPrC2ptgZwJfAJ4StKFkobVMSYz\nM+sDamqBRMQ9wD2SlgY+A1wr6RXgUuCiiPhvHWM0M7MWVPM5EEnbARcA3wduBY4GVgH+UJfIzMys\npdV6DuRZYBLpPMiREfF6nn438GDdojMzs5ZVawtke2CfiLgSQNK6ABExPyKG1is4MzNrXbUmkN1I\n3VYAKwM3STq0PiGZmVlfUGsCORTYBiAingU2AY6qV1BmZtb6ak0gg4DyK63eBDrf+XDMzKyvqPWZ\n6DcAd0r6HSlx7I2vvjIz69dqaoFExInA+YCAdYDzI+Kb9QzMzMxa28KMhTUB+B2pNTJN0vD6hGRm\nZn1BrfeBXAjsATxdNrmTdHmvmZn1Q7WeA9kJUOkGQjMzs1q7sCYBbfUMxMzM+pZaWyDTgL9L+ivw\nRmliRBxUl6jMzKzl1ZpAbqXrTnQzM7Oah3P/haS1gA2A24A1IuKZegZmZmatraZzIJL2AW4CzgNW\nAMZK2q+egZmZWWurtQvrRGBLYHREvCRpCPAn4Fc9fUjSAGAk6QbE+cBhpCFRrsjvx0fEEbnsqaRB\nG+cAx0bEA5LWqVbWzMyar9arsOZFxKzSm4j4N2mn3ps9gM6I2Bo4hfQwqnOBkyNiW2CApD1zQhoe\nEZsB+wIX5s+/rWyN8ZqZWZ3VmkCekHQkMEjSxpIuAR7p7UMRcSNpJF+ANYHpwNCIGJOnjQJ2BLYG\nbs+feQ4YKGklYJOKsiNqjNfMzOqs1gRyBLAa8Drwc+AV4PBaPhgR8yVdQRpL6yoWvJ9kFjAYaAdm\nVplOL9PMzKxJar0K61XgpPxvoUXEAZJWBh4Ali6b1U5qlbwCLF8xfQYLdpOVpvWoo6O9SIiLJddF\nF9dFF9dFl2bXxfTpyzV1/Yuq1rGw5vP253/8OyJW7+Vz+wGrR8QPSDcgzgMelLRtRNwD7ALcSRpj\n60xJ5wBrAAMiYqqkcZKGR8TosrI9mjJlVm9F+oWOjnbXRea66OK66NIKdTFt2uymrn9R1doCeaur\nS9IgYC9gixo+eh1wuaR78rqOBp4ELs3LmQBcExGdksYAY0ldXKXuseOBkeVla/pWZmZWd7VexvuW\niJgD/F7SN2oo+xqwT5VZ21UpezpwesW0idXKmplZ89XahfXFsrdtpDvS59QlIjMz6xNqbYF8vOx1\nJ/Ay1VsWZmbWT9R6DuTAegdiZmZ9S61dWM/w9quwIHVndUbEB97RqMzMrOXV2oV1FWkMq5Gkcx9f\nAIYBvZ5INzOzxVOtCWTniPhY2fvzJD0UEc/WIygzM2t9tQ5l0ibprXGoJO1OunvczMz6qVpbIIcC\nV0p6L+lcyJPA/nWLyszMWl6tV2E9BGyQR8h9PY+NZWZm/VitTyRcU9IdpKFG2iXdmR9xa2Zm/VSt\n50B+BpwNzAZeBH4DXFmvoMzMrPXVmkBWiojSA586I2IkCw6/bmZm/UytCeR1SauTbyaUtDXpvhAz\nM+unar0K61jgZmAdSY8AKwCfrVtUZmbW8mpNIKuQ7jxfDxgIPBkRb9YtKjMza3m1JpCzIuIW4Il6\nBmNmZn1HrQnkaUk/B+4HXi9NjAhfiWVm1k/1eBJd0mr55VTSyLubk54N8nH8pEAzs36ttxbITcDQ\niDhQ0tci4oeNCMrMzFpfb5fxtpW9/kI9AzEzs76ltwRS/hCptm5LmZlZv1PrjYRQ/YmEZmbWT/V2\nDmQDSZPy69XKXvtRtmZm/VxvCWS9hkRhZmZ9To8JxI+sNTOz7izMORAzM7O3OIGYmVkhTiBmZlaI\nE4iZmRXiBGJmZoXUOhrvQpO0BPBzYC1gSeB7wN+BK4D5wPiIOCKXPRXYDZgDHBsRD0hap1pZMzNr\nDfVsgewHvBwRw4FdgAuAc4GTI2JbYICkPSUNAYZHxGbAvsCF+fNvK1vHWM3MbCHVM4H8DjilbD1z\nSSP7jsnTRgE7AlsDtwNExHPAQEkrAZtUlB1Rx1jNzGwh1a0LKyJeA5DUDvwe+AZwTlmRWcBgoJ30\nvJHK6fQyraqOjvaCES9+XBddXBddXBddml0X06cv19T1L6q6JRAASWsA1wEXRMRvJZ1VNrsdmA68\nAixfMX0G6dxH5bReTZkya5FiXlx0dLS7LjLXRRfXRZdWqItp02Y3df2Lqm5dWJJWAW4Dvh4Rv8iT\nx0kanl/vAowB/grsJKlN0vuBARExtZuyZmbWIurZAjkJeDdwSr7KqhM4BviJpEHABOCaiOiUNAYY\nSxrl9/D8+eOBkeVl6xirmZktpHqeA/kq8NUqs7arUvZ04PSKaROrlTUzs9bgGwnNzKwQJxAzMyvE\nCcTMzApxAjEzs0KcQMzMrBAnEDMzK8QJxMzMCnECMTOzQpxAzMysECcQMzMrxAnEzMwKcQIxM7NC\nnEDMzKwQJxAzMyvECcTMzApxAjEzs0KcQMzMrBAnEDMzK8QJxMzMCnECMTOzQpxAzMysECcQMzMr\nxAnEzMwKcQIxM7NCnEDMzKwQJxAzMyvECcTMzApxAjEzs0KcQMzMrJAl6r0CSZsBP4iIj0taB7gC\nmA+Mj4gjcplTgd2AOcCxEfFAd2XNzKw11LUFIukEYCSwVJ50LnByRGwLDJC0p6QhwPCI2AzYF7iw\nu7L1jNXMzBZOvbuw/gF8quz9JhExJr8eBewIbA3cDhARzwEDJa1UpeyIOsdqZmYLoa4JJCKuB+aW\nTWorez0LGAy0AzOrTKeXaWZm1kR1PwdSYX7Z63ZgOvAKsHzF9BlVys6oZQUdHe2LGOLiw3XRxXXR\nxXXRpdl1MX36ck1d/6JqdAJ5WNLwiBgN7ALcCTwNnCnpHGANYEBETJU0rkrZXk2ZMqtesfcpHR3t\nrovMddHFddGlFepi2rTZTV3/omp0AjkeGClpEDABuCYiOiWNAcaSurgO765sg2M1M7Me1D2BRMSz\nwJb59URguyplTgdOr5hWtayZmbUG30hoZmaFOIGYmVkhTiBmZlaIE4iZmRXiBGJmZoU4gZiZWSFO\nIGZmVogTiJmZFeIEYmZmhTiBmJlZIU4gZmZWiBOImZkV4gRiZmaFOIGYmVkhTiBmZlaIE4iZmRXi\nBGJmZoU4gZiZWSFOIGZmVogTiJmZFeIEYmZmhTiBmJlZIU4gZmZWiBOImZkV4gRiZmaFOIGYmVkh\nTiBmZlaIE4iZmRWyRLMDMKunefPm8dRTTzFt2uymxwFtDBzY3GO2FVbYqKnrt8VLSycQSW3AT4GN\ngDeAgyNiUnOjan3eaXb55z+f5YdXP8oyg1duWgwAU/81gaXbV2xqHK/O+A/f+fIUBg/uaFoMJWut\n9QEGDhzY7DBsEbV0AgH2ApaKiC0lbQacm6dV9fzzz/P88y83LLhq2tramDdvblNj8E5zwRhWXP1D\nLPee1ZoWA8BrM19kmcErNzWO12a+yKmXjG36dvHqjP9w/OeG8P73r9m0GObNm8fLLy/HzJmvNy0G\nSL/VvqzVE8jWwK0AEXG/pI/1VPjoUy9i+vz3NiSw7rz6/IPQvpZ3mrTOTtO6NPvvAelvkg5w/t20\nGFrh4KYUx4qrf6ipMSyKVk8gywMzy97PlTQgIuZXK7zUgLksPW9GYyLrxn/b3qS57Y/ktZkvNTsE\nXp81DWjr9zG0ShytEEMpjqXbV2x2GC2j2b/VRVl/qyeQV4D2svfdJg+Aq0b+oPm/DjOzfqLVL+O9\nF9gVQNLmwOPNDcfMzEpavQVyPbCjpHvz+wObGYyZmXVp6+zsbHYMZmbWB7V6F5aZmbUoJxAzMyvE\nCcTMzApp9ZPoVfU2xImkQ4BDgTnA9yLilqYE2gA11MWxwD5AJ/DHiPhOUwJtgFqGvsllbgFuiIhL\nGh9lY9SwXewCnEraLh6OiCObEmgD1FAXxwOfA+YBZ0TEDU0JtEHyqB4/iIiPV0zfAziFtN+8PCIu\n7W1ZfbUF8tYQJ8BJpCFOAJC0CnAUsAXwCeAMSYOaEmVj9FQXawP7RsTmwJbAzpI2bE6YDdFtXZT5\nLvCehkbVHD1tF8sBZwG75fmTJS3Od/b1VBeDSfuLzYCdgR83JcIGkXQCMBJYqmL6EqR6GQFsBxwq\nqdfb9PtqAllgiBOgfIiTTYG/RMTciHgFmAh8tPEhNkxPdfFPUhIlIjqBQaQjsMVVT3WBpL1JR5mj\nGh9aw/VUF1uS7qk6V9Jo4MWImNr4EBump7p4FZhMumF5OdL2sTj7B/CpKtM/BEyMiFciYg7wF2Cb\n3hbWVxNI1SFOupk3GxjcqMCaoNu6iIh5ETENQNLZpK6KfzQhxkbpti4kbQB8HjiNVhjPo/56+o2s\nRDrKPAHYBThW0rqNDa+heqoLgH8BfwceBM5vZGCNFhHXQ9XRlirraBY17Df7agLpaYiTV0iVUdIO\nNHeArPrqcbgXSUtJ+jWwLHB4o4NrsJ7q4ovAqsCdwAHAcZJ2amx4DdVTXUwFHoiIKRHxKjAa2LjR\nATZQT3WxC/BeYE3g/cCnehu0dTFVaL/ZJ0+ik4Y42R24psoQJ38DvitpSWBpYH1gfONDbJie6gLg\nD8CfIuLshkfWeN3WRUScWHot6TTg3xFxe+NDbJietouHgA0lrUDacWwOLLYXFNBzXUwHXs/dNkia\nAby78SE2XGUrfAKwrqR3A68Bw4Fe9xl9NYG8bYiTfLXRxIi4WdL5pD68NuDkiHizWYE2QLd1Qfr7\nbgMMkrQr6Yqbk3I/8OKox+2iiXE1Q2+/kZOA20nbxNUR8fdmBdoAvdXFg5LuI53/+EtE/KlpkTZO\nJ4CkfYFlI+JSSceRtok24NKI6HW8fQ9lYmZmhfTVcyBmZtZkTiBmZlaIE4iZmRXiBGJmZoU4gZiZ\nWSFOIGY+74BqAAAC2ElEQVRmVkhfvQ/EbJFIWhN4CngiT1oSeB44MCJekHQ3sBppSIfSGGKnRsSo\n/Pm7gNXz/DbSXbxPA1+IiCmLENe2wLcqR0o1a0VugVh/9nxEDM3/NiTdof2TPK8TOCjP+whwGPBL\nSeuXfb40f0hErENKJse9A3H55izrE9wCMesyGtij7P1bwz1ExEOSrgYOBo7Pk986AJPUThqk8L7y\nBeZnLBwSEZ/M748E1iE9i+MyUitnVWB0ROxf8dm7gNMiYnRuMd0dEWvnYbZ/RmoBzSeNLnCnpB2A\nM/O06aSh/KctSoWY9cQtEDMgPzNmH9IQON0ZTxpbrWSkpHGSXgDGkoaB+FHFZ0YBQ/NzJyA9uOhX\nwG7AuIjYClgP2FLSkF7CLLVMzgMui4hhwJ7AJfkZH98AvhwRmwI3AUN7WZ7ZInELxPqz1SQ9TGpp\nLEkaiPOkHsp3Aq+Xvf9SRIyRtAVwDemJjwsMlR0RcyVdD+wt6Q5ghYh4CHhI0jBJx5CexbAC6XkU\ntRgBSFLp6ZIDgQ8ANwI3SLoBuLGfjOlkTeQEYv3Z8xGxMEfpHyU9N6KkDSAixkr6CekcyUfLh9PP\nfgV8h5Qkfg0g6Sjg06SuqDuADXn7CKmdZdPKn6o5ENg+ImbkZb2X9FCoxyTdRBp59ixJv4+IMxbi\n+5ktFHdhWX9W84OlJG0K7A1095zoc4FlSCfbF5BHP14V2I+cQEitiJ9FxG9zHBuTEkO5l4EN8uvy\np8j9GTgix/Vh0vDky+QRZZePiPNJXWnuwrK6cgKx/qy3q50ulfRw7ub6IfA/EfFctc/mRwZ8Ezgt\nn1CvdDUwKyIm5/c/Br4l6UHgAtIzK9au+MxZwBG5TPkzrI8GNpf0KPAb0qXDr5K6367I5Q8hPX3R\nrG48nLuZmRXiFoiZmRXiBGJmZoU4gZiZWSFOIGZmVogTiJmZFeIEYmZmhTiBmJlZIU4gZmZWyP8D\nX/ZlOMb8WvsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1161c3358>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 6458 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_mam5['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_mam5[df_mam5['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 15338 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZUAAAEZCAYAAABfKbiYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x111f9bd30>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 17978 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_mam6['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_mam6[df_mam6['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 10696 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZUAAAEZCAYAAABfKbiYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x118bd7a20>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 12115 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_mam7['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_mam7[df_mam7['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 16245 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZUAAAEZCAYAAABfKbiYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x116f50c88>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 19065 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_mam8['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_mam8[df_mam8['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 9685 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZUAAAEZCAYAAABfKbiYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nWlUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11ca50208>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 10828 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_mam9['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_mam9[df_mam9['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 68 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYUAAAEZCAYAAAB4hzlwAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nYGZmhf8PbKZCSvdyLLUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1159783c8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 71 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_mam10['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_mam10[df_mam10['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 13957 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZUAAAEZCAYAAABfKbiYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nrDBOKmZmVhgnFTMzK4yTipmZFeb/AfXiyUqiQVXNAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x116171828>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 16147 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_mam11['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_mam11[df_mam11['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 8833 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZAAAAEZCAYAAAC5AHPcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nQpxAzMyskP8PigroWCdjgsAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11940deb8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 9887 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_mam12['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_mam12[df_mam12['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 8004 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZAAAAEZCAYAAAC5AHPcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nzKyQ/w8ZpfV9g/8/eAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x116f4afd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 8876 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_mam13['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_mam13[df_mam13['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 7541 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZAAAAEZCAYAAAC5AHPcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nVogTiJmZFeIEYmZmhTiBmJlZIf8fgDh5F3nmi2UAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x118d40898>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 8434 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_mam14['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_mam14[df_mam14['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 7379 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZAAAAEZCAYAAAC5AHPcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\naAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1122cbfd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 8095 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_mam15['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_mam15[df_mam15['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 8616 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZAAAAEZCAYAAAC5AHPcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nM7NCnEDMzKwQJxAzMyvk/wGtgBItmqLA4wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1198a9940>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 9628 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_mam16['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_mam16[df_mam16['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 11251 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZUAAAEZCAYAAABfKbiYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nVN4xH2EAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x114427780>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 12718 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_mam17['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_mam17[df_mam17['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 12456 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZUAAAEZCAYAAABfKbiYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x116dd8860>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 14306 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_mam18['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_mam18[df_mam18['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 9773 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZUAAAEZCAYAAABfKbiYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nZlYYh4qZmRXGoWJmZoVxqJiZWWH+PwOk0PZwQj/6AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x111f85400>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 10644 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_mam19['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_mam19[df_mam19['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 2825 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZAAAAEZCAYAAAC5AHPcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nWD/4Z35yUgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x115684710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 3072 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_mam20['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_mam20[df_mam20['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 2 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYgAAAEZCAYAAACNebLAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nkwrBn+TpyrkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11b9a2048>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 2 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_mam21['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_mam21[df_mam21['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# df_mam22 has no data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 27423 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZUAAAEZCAYAAABfKbiYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nScXMzArjpGJmZoVxUjEzs8L8P7OFXY2S7BTwAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x118d40f28>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 30586 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_mam23['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_mam23[df_mam23['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 5288 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZAAAAEZCAYAAAC5AHPcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n/wdcCi7zEpKevQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x112ac48d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 5545 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_mam24['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_mam24[df_mam24['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 1 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYgAAAEZCAYAAACNebLAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nwDcXJCDafKMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11ca7ab38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 1 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_mam25['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_mam25[df_mam25['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 20158 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZUAAAEZCAYAAABfKbiYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nWWH+HyGCrkrfbBZDAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11ca52f98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 23170 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_mam26['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_mam26[df_mam26['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 35054 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZUAAAEZCAYAAABfKbiYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n5mZGxOIJAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1133d11d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 46743 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_igd1['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_igd1[df_igd1['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 7276 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZAAAAEZCAYAAAC5AHPcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nhfx/oG5DKzdHB2MAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x118b6d4a8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 8014 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_igd2['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_igd2[df_igd2['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 12597 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZUAAAEZCAYAAABfKbiYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n7wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x115eb46d8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 14718 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_igd3['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_igd3[df_igd3['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 32169 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZUAAAEZCAYAAABfKbiYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1178a24e0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 40029 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_igd4['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_igd4[df_igd4['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 10276 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZUAAAEZCAYAAABfKbiYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nYZxUzMysMP8P7d9zfGJqDiYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x116187f28>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 11751 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_igd5['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_igd5[df_igd5['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 34157 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZUAAAEZCAYAAABfKbiYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nwjiomJlZYRxUzMysMP8f1eQ27xXgZ6EAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1126d5c18>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 50812 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_igd6['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_igd6[df_igd6['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 26121 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZUAAAEZCAYAAABfKbiYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzt3XmYXFWZx/FvZ4EB0kSWBmURMY6vCwIJsogQUBZlE5Rx\nQXAUF2ZMEAYNjxMUcBlHIYCyiSYIiIqybzJsApLIJmFTEH+EhAiiYvYFAoSk5o9zKl3p9FKd3Krb\n3fl9nidPqm6de+97T9+q955z7tJSqVQwMzMrwqCyAzAzs4HDScXMzArjpGJmZoVxUjEzs8I4qZiZ\nWWGcVMzMrDBDyg6gv4qI5cCmkubWTPs08G+SDomIbwLTJP28m2WcDDwq6cbGR7zmIuK3wBuB+XlS\nC1CRNKq0oEoSERcA+wOXSTq5ZvqngbOBGUCFdOC2GDhR0v0RcSowFvgrqf6G5LLjJE3Ly/gtK9fz\nEGAd4DuSflZHbN8GPpLX/yDwRUkvR8SGwAvAkzXFT5B0d828nwUOk/ShDstcF7gR+JGka/K09YAL\ngZF5W/5b0vU9xdcoEdECPCZp+wYt/4/AWEmT6yx/ILCrpFNXc313AedW67u/cFJZfV1d4FMBqHNH\nej/wRGERNV4F+Iqka8sOpA84Btha0t86+Wxy7Y9yRBwMXBMRW+VJv5J0XM3nRwF3RMQ7JC2mk3qO\niJ2AeyLiGkkvdhVURHwY2A/YXtKyiLgCOB44DdgNuFvSBzuZbyPgf4FPAXd2+Gw34IdAAD+q+egb\nwCJJ74iIrYH7IuLBLuqkGXYH7i9p3Z3ZGdio7CCazUll9bV092FEXAz8UdJZudVyKPAqMAc4mnQk\n+W5gQkQsA+4Czgd2BJYDtwDjJS3PRzzfA14DHgP2Bd4LvA/4HLAB6aj2EOAC4C3AJsAi4JOSpuWj\nnodIiawNOAfYHNgLWB/4mKQnIuIQ4D8kHdyb7c7Ln0v64bkA+BnpiH07YChwB+lofXlEHA58C3gJ\n+D/gJElDa1t6eZm1Lb+hpB/G0cBg4BHgOEmLI+IZ4BJgH2Br4ApJX83L+Czw5Vx3s4HPAKcA/5T0\n9VzmSOAjkg7vsE3vBM7NdbkcOFPSzyOieqR6c0SMkXRPF3VVdQeprl/X2Yd5mZ8CPglMzJM71vMI\nUovnle5WJOnaiLghJ5QNgc3ydkP60d0kIqaQ9pmJkqpJ4mPA34CvAAd1WOyXgK8BJ3aY/mHgiLze\n5yLi9rycH9QW6mTfuC7//6Zc5KeSzoyIa4EbJF0cEe8B7gHeLGlmRHwNGEb6O/8EWDfX0U8kXZCX\ncyhwXURsA0whtci2Ie3jI0jfofWBZcC3JN0UEevT9Xfm7cBFwHqA8ryriIiP5PpZlv+dSPqu/ycw\nKCIWAN/tZj2bk5L12/L8P5J0Xs3yBwOX5WV+Gjis4/ok/a6z2MrgMZU1c1dEPJz/PUL6oVxJPjo9\nHthZ0i7AbcAukn4ITCV1e1xP+pGfLeldpGSzAzAuIjYGLiXtgKNIyWeLmlW8AxgtaR/gAGCepPdK\nelte/rE1ZbfJyzic9AN9p6SdgVtJPxxIurGbhAIpCT4cEY/k/2uPeudK2k7S+cD3gal5+aNIiezL\nEfF60o/CR/Jnr7DyftixBVh9/9/AUknvljQS+DvpR6JqA0mjScn2SxGxTUTskMvsL2lH4AbgJOA8\n4OiIqK73GNIXfoX8Rb4eOFvSDsCBwHcjYte8nhZg7zoSCsB/AI/XdpV24jHgXTXvq/X8TET8g/SD\nuY+k13paWU4oY4G/kH7ArssfLSXVwWjgYOCEiPhQnufHkr4NvNzJ8o6UdDOrJrqtgedq3v8V2IrO\n1e4bvwDuyN1UewCfioiPAVeT9mGAD5L+xvvm9x/Kn59ISjw7k5LfnjXr2Bf4TX69FfDN/D14hZQc\njpL0btKP8gX5u9ndd+YXwI/zvnM2KUF15nRSF+MuwMmk/eL3pERxee4e7W49FwCS9HZS4j8mIt6c\nP1sXuBJ4QdKnJC3vbH1dxFUKt1TWzN6S5lXf5CPrwzuUeR54FHgkIm4GbpZU271Q/aIeQNqhkLQ0\nIn4E/BfwFPCEpMfzZ5dGxNk18/+h2h0i6eqImBERx5KOiPYG7q0pW+2bnU76sb615v1edW7zid30\n8U6peX0wsHNEfD6//5e8zveS+r2Vp58HfLuO9R4MDI+I/fP7oaTxgarrAST9LSJeADYmbf8t1e4Y\nSedUC0fEDOCgiJgGvEHSb1jZW4F1q2MEkv4eEVeTfuweyGW6aq2OjoiH8+t1gD+z6n7RUYXUcqs6\nUdI1EbEJqTU3S9JjPSxjhfzjfX4eX7matK9+p6bI3yLix6TWxg31LreDFlY+CGghHTl3ZgpAbhm8\nl9RFh6SFEXEJaf8/ATgrJ/T9gf8B9ouIm4A2SVNza+anEbErKYEcl5f7dmC6pFcjAlICrXaFvQd4\nA6kVU/2bLSN1EXb6nckHc9uTWtxIujciuuqq/mVe9k3A7aQf/ZX08N3cBxhXrY+8XvJ2nElqoY3o\nzfrK5JbKmum2CwxAUkXS3qRm62zg+xHx/U6KDmLlL+ggUtJfyqp/p9pyi6svIuKLpFbAi6SjrF92\niHGlrhNJXf0ArK7FNa8HAR+VNDK3LHYltYaWdIip9si70uGzdWpeDwaOr1neLsBHaz5f0iGWlrzs\nFXUVEf8S+ZtKGiP4HPBZ2rucag1m1VbTIFIy68lkSaPyv+0k/Zukp3uYZ2fgDx0nSpoDfAL4Qu42\n7FZEbB8RO9ZMqg6kExHH5rGPqhbS/rW6nmXlVvMWpNZKZ6r7Rme/OYOAoZLmkw7ADgFaSS300aSW\nxbUAkm4C/hW4nLRdj0fEtrlM7UkCr+Sjekh/yz/lv0d1/9kduK2H70zH/bHTVmJuibyXdFLEZ+hk\nXKeH9XTcT7eNiNb89lJSS+bC3qyvTE4qDZa/5I8DT0o6jdQttEP++DXaf6RuITeHI51pcwypq+xe\n4F8jYrv82eHAcDo/UWB/4GJJFwPTSF/OwV2E1mNCXEO3ksYyas8cGgvcR9qe6g/fZ2rmmQVsFxHr\nRMQQUvy1yzs2IobmbqufkPqpu3MXsG/us4bUx31afn0V6UfpcFLXSEd/BpZGxGF5G7bIZW/rYZ29\nFhGfA7YldXOsQtIzwHdIByTr9bC47YGLasp9mjSmA6mraVxe58akpHr5GoR+PWk/rXbzfgD4dXcz\nKJ2IcD9pXyAihgP/Tnu9Xks6YeCO3AJ/itT1eXUu/wvgE5KuAMYAC0jdcAd1WHft/n0/aZ/bMy9j\nR9L3Ywu6+M7krsqHgM/neUaxcvckefrgPKa3gaSJOaa35THA2u93d9/N20njrNX6uIPUmgH4PWkM\ncEREfK6H9fUJTiqrr67bO0v6A+mL+1BEPEjaef4rf3wjcEYepD0O2DzSaYuPkQYZ/zd3r30S+FlE\nTCXtnK+xcldJ1RnAf+aul9tJX4rqztnVWMVKIuKQiOjqh6G7be742fHA+nl7Hs3bdHreno8Ck/L2\n7Fwzz23A3aRB0btZ+cj928BM0gD943l9X+li3dUz8B4n9cHfmse89iclFiQtJSWWezsb68hjF4cB\n/xURj+XYvqH200nX5PbeH+8wFrcfqXvq1W6WfQbpb149ueCmSGeVdYz756Qf+6kR8ShpcLzaBTkW\n2Cof5NwLnC/pjo7L6EbHuL4BtObl3UYaH3ymjvmOJCX7P5B+8K+SdGn+7DpS12M1ydwKDJFU7Sr6\nFnBkrrf7SV26TwEv55bOKuuUNJt0QDAh18lPgSMlPUv335lPAkfkv//XgD913LDc2j8euCwiHgKu\nAI7O+9edwIdyd/WEbtbzJeAdeT1TSKeOP0L7fvwK6XdjAulU867W1ye0+Nb3fVtuBn8dOFXpWoOR\nwK8lbVlyaIXIYwazJDX1ACciNiAlrjF5ULVfyWNVs1TidSFmnWnoQH3upphEOlpaTjpKfIV0WuBy\n0hkx1WbwKaQm7FLSBVkPRsSIess2cjvKJGlRRLxKOvJcSjqt8KM9zNbfNPXIJg/2/xK4sD8mlGwp\nPXQ1mZWhoS2ViDgUOETS5yNiL9LZHS3AGZKmRLoq+RbSgN8ESfvmgcSrJe0SEdfXW7ZhG2FmZnVr\naJdDbpofk99uA8wDRkmqnnp6M6k/eQ9yH6qk54DBEbEpsFOdZTdp5HaYmVl9Gt6PrXQF9SWki/su\nY+WzMhaRzmRqJZ3F0XE6dZRd3ElZMzMrQVMufpT0mYjYjHRede0pka2k1stCYMMO0+eTxlLqLdul\nSqVSaWlp9Bm0ZmYDTq9/OBs9UH8UsJWk75Fu/7CMNOC8l9KdUQ8gnXY3HTgtIs4gnXM+SNKcSLcC\nGZ1P4+yqbEtnp4TWamlpYdasRY3azH6lra3VdZG5Ltq5Ltq5Ltq1tbX2XKiDRrdUrgEujoi787qO\nI11UdmG+WOdJ0jnqlUg3ubuPlBnH5PnHka5n6K7s2AZvg5mZ1WltuU6l4iOPxEdh7VwX7VwX7VwX\n7draWnvd/eUr6s3MrDBOKmZmVhgnFTMzK4yTipmZFcZJxczMCuOkYmZmhXFSMTOzwjipmJlZYZxU\nzMysME4qZmZWGCcVMzMrjJOKmZkVxknFzMwK46RiZmaFcVIxM7PCOKmYmVlhnFTMzKwwTipmZlYY\nJxUzMyuMk4qZmRXGScXMzAozpOwAzMys3bJly5g5c0bZYQDQ1jaq1/M4qZiZ9SEzZ87g+Ak3sP7w\nzUqN46UF/+SBq51UzMz6vfWHb8awjbYsO4zV4jEVMzMrjJOKmZkVxknFzMwK46RiZmaFcVIxM7PC\nNOzsr4gYAlwEvAlYB/gO8FfgRuCpXOwCSVdGxKnAgcBS4ARJD0bECOASYDnwuKSxebmnAAfVlm3U\nNpiZWe80sqVyFDBb0mhSwjgPGAmcKen9+d+VETES2FPSrsARwPl5/rOAkyTtBQyKiENz2dGdlDUz\nsz6gkUnlCuDk/LqF1LLYCTg4Iu6OiEkRMQzYA7gNQNJzwOCI2BTYSdKUPP/NwH5dlN2kgdtgZma9\n0LCkIuklSS9GRCtwJfB14PfAuNz6mAGcCrQCC2pmXQQM77C46rSOZRd3UtbMzErS0CvqI2Jr4Brg\nPEm/iojhkqpJ4Trg3Pz/hjWztQLzSWMptdPmAQu7KNujtrbW1dqGgch10c510c510a7Mupg3b1hp\n6y5CIwfqNwduBcZKuitPvjUijpU0FdgHmArcA0yIiDOArYFBkuZExCMRMVrSZOAA4E5gOnBaTdkW\nSXPriWfWrEWFbl9/1dbW6rrIXBftXBftyq6LuXMXl7buIjSypTIeeB1wcj5jqwKcAJwdEa8A/wCO\nkbQ4IiYD95HGXsbk+ccBkyJiKPAkcJWkSkRMqSk7toHxm5lZL7VUKpWyY2iGio/CkrKPwvoS10U7\n10W7suti+vRpjJ94f+k3lFw873nuumhMS2/n88WPZmZWGCcVMzMrjJOKmZkVxknFzMwK46RiZmaF\ncVIxM7PCOKmYmVlhnFTMzKwwTipmZlYYJxUzMyuMk4qZmRXGScXMzArjpGJmZoVxUjEzs8I4qZiZ\nWWGcVMzMrDBOKmZmVhgnFTMzK4yTipmZFcZJxczMCuOkYmZmhXFSMTOzwjipmJlZYZxUzMysME4q\nZmZWGCcVMzMrjJOKmZkVxknFzMwK46RiZmaFGdKoBUfEEOAi4E3AOsB3gD8BlwDLgccljc1lTwEO\nApYCJ0h6MCJG1Fu2UdtgZma908iWylHAbEmjgQOA84CzgJMk7QUMiohDI2IkMFrSrsARwPl5/t6U\nNTOzPqCRSeUK4OSa9bwGjJI0JU+7GdgP2AO4DUDSc8DgiNgU2KnOsps0cBvMzKwXGpZUJL0k6cWI\naAWuBL4GtNQUWQQMB1qBBZ1Mp46yizspa2ZmJWnYmApARGwNXAOcJ+lXEXF6zcetwDxgIbBhh+nz\nSWMp9ZbtUVtba6/jH6hcF+1cF+1cF+3KrIt584aVtu4iNHKgfnPgVmCspLvy5EciYrSkyaRxljuB\n6cBpEXEGsDUwSNKciKinbIukufXEM2vWokK3r79qa2t1XWSui3aui3Zl18XcuYtLW3cRGtlSGQ+8\nDjg5n7FVAY4Hzo2IocCTwFWSKhExBbiP1D02Js8/DpjUQ9mxDYzfzMx6qaVSqZQdQzNUfBSWlH0U\n1pe4Ltq5LtqVXRfTp09j/MT7GbbRlqXFALB43vPcddGYlp5LrswXP5qZWWGcVMzMrDBOKmZmVhgn\nFTMzK4yTipmZFcZJxczMCuOkYmZmhXFSMTOzwjipmJlZYZxUzMysMHXd+ysi/g+4GLhe0quNDcnM\nzPqrelsqpwEfBJ6KiPMjYucGxmRmZv1UXS0VSXcDd0fEesC/AVdHxELgQuACSa80MEYzM+sn6h5T\niYi9Sc+Z/1/gFuA4YHPghoZEZmZm/U69Yyp/AWaQxlWOlbQkT/8tMLVh0ZmZWb9Sb0vl/cDHJV0K\nEBFvAZC0XNKoRgVnZmb9S71J5SBSlxfAZsCNEXFMY0IyM7P+qt6kcgywJ4CkvwA7AV9qVFBmZtY/\n1ZtUhgK1Z3i9SnrmvJmZ2Qp1DdQD1wF3RsQVpGRyOD7ry8zMOqirpSLpq8A5QAAjgHMkfb2RgZmZ\nWf/Tm3t/PQlcQWq1zI2I0Y0JyczM+qt6r1M5HzgEmF4zuUI61djMzAyof0xlfyCqFz2amZl1pt7u\nrxlASyMDMTOz/q/elspc4E8RcS/wcnWipM82JCozM+uX6k0qt9B+Rb2ZmVmn6r31/U8j4k3AO4Fb\nga0lPdPIwMzMrP+pa0wlIj4O3AicDWwM3BcRRzUyMDMz63/q7f76KrA7MFnSPyNiJPAb4Oc9zRgR\nuwLfk/S+PN+NwFP54wskXRkRpwIHAkuBEyQ9GBEjgEuA5cDjksbm5Z1CusHlirJ1boOZmTVYvWd/\nLZO0qPpG0t9JP/bdiogTgUnAunnSKOBMSe/P/67MiWZPSbsCRwDn57JnASdJ2gsYFBGH5rKjOylr\nZmZ9QL1J5YmIOBYYGhE7RsRE4NE65nsa+HDN+52AgyLi7oiYFBHDgD2A2wAkPQcMjohNgZ0kTcnz\n3Qzs10XZTercBjMza7B6k8pYYEtgCXARsBAY09NMkq4FXquZ9ABwYm59zABOBVqBBTVlFgHDOyyq\nOq1j2cWdlDUzs5LUe/bXi8D4/G9NXCepmhSuA87N/29YU6YVmM/K3WutwDxSMuusbI/a2lpXM+SB\nx3XRznXRznXRrsy6mDdvWGnrLkK99/5azqrPT/m7pK16ub5bI+JYSVOBfUjPt78HmBARZwBbA4Mk\nzYmIRyJitKTJwAHAnaR7j51WU7ZF0tx6Vjxr1qKeC60F2tpaXReZ66Kd66Jd2XUxd+7i0tZdhHpb\nKiu6ySJiKHAY8J7VWN8XgfMi4hXgH8AxkhZHxGTgPtKtYKrdauOASXl9TwJXSapExJSasmNXIwYz\nM2uQlkpl9R7gGBGPStqx4HgapeKjsKTso7C+xHXRznXRruy6mD59GuMn3s+wjbYsLQaAxfOe566L\nxvT6no/1dn/9e83bFtKV9Ut7uzIzMxvY6r348X01ryvAbODjxYdjZmb9Wb1jKkc3OhAzM+v/6u3+\neoZVz/6C1BVWkfTmQqMyM7N+qd7ur8uAV0i3XFkKHAnsDHytQXGZmVk/VG9S+YCkd9e8PzsiHpL0\nl0YEZWZm/VO9t2lpiYh9q28i4mDS1e1mZmYr1NtSOQa4NCJeTxpb+TPw6YZFZWZm/VK9Z389BLwz\n3z14Sb4XmJmZ2UrqffLjNhFxO+n2KK0RcWd+vLCZmdkK9Y6p/BiYQLrV/AvAL4FLGxWUmZn1T/Um\nlU0lVR+OVZE0iZVvQW9mZlZ3UlkSEVuRL4CMiD1I162YmZmtUO/ZXycAvwZGRMSjwMbARxsWlZmZ\n9Uv1JpXNSVfQvxUYDPxZ0qsNi8rMzPqlepPK6ZJuAp5oZDBmZta/1ZtUpkfERcADwJLqREk+A8zM\nzFbodqA+IqqPHptDuiPxbqRnq7wP2LuhkZmZWb/TU0vlRmCUpKMj4iuSzmxGUGZm1j/1dEpx7fOJ\nj2xkIGZm1v/1lFRqH8zV0mUpMzMz6r/4ETp/8qOZmdkKPY2pvDMiZuTXW9a89mOEzcxsFT0llbc2\nJQozMxsQuk0qflywmZn1Rm/GVMzMzLrlpGJmZoVxUjEzs8I4qZiZWWGcVMzMrDD13qV4tUXErsD3\nJL0vIkYAlwDLgccljc1lTgEOApYCJ0h6sDdlG70NZmZWn4a2VCLiRGASsG6edBZwkqS9gEERcWhE\njARGS9oVOAI4fzXKmplZH9Do7q+ngQ/XvN9J0pT8+mZgP2AP4DYASc8BgyNi016U3aTB22BmZnVq\naPeXpGsjYpuaSbU3pVwEDAdaSc9r6TidOsouztPn0IO2ttb6Ax/gXBftXBftXBftyqyLefOGlbbu\nIjR8TKWD5TWvW4F5wEJgww7T5/eybI9mzVq0GuEOPG1tra6LzHXRznXRruy6mDt3cWnrLkKzz/56\nOCJG59cHAFOAe4H9I6IlIt4IDJI0B3ikjrItkuY2eRvMzKwLzW6pjAMmRcRQ4EngKkmViJgC3Efq\nHhvTi7Jjmxy/mZl1o6VSWSsek1Jx0z4pu2nfl7gu2rku2pVdF9OnT2P8xPsZttGWpcUAsHje89x1\n0ZheP5zRFz+amVlhnFTMzKwwTipmZlYYJxUzMyuMk4qZmRXGScXMzArjpGJmZoVxUjEzs8I4qZiZ\nWWGcVMzMrDBOKmZmVhgnFTMzK4yTipmZFcZJxczMCuOkYmZmhXFSMTOzwjipmJlZYZxUzMysME4q\nZmZWGCcVMzMrjJOKmZkVxknFzMwK46RiZmaFcVIxM7PCOKmYmVlhnFTMzKwwTipmZlYYJxUzMyuM\nk4qZmRVmSBkrjYiHgfn57TPAROBsYClwu6RvRUQL8ENgB+Bl4POSZkTEbsAPass2fQPMzKxTTW+p\nRMS6QEXS+/O/zwE/Aj4haU9g14jYETgMWFfS7sB44Ky8iAs6KWtmZn1AGS2VHYANIuJWYDDwTWAd\nSTPz57cC+wJvAG4BkPRAROwUEa2dlN0HeLR54ZuZWVfKGFN5CZgg6QPAF4GL87SqRcBwoBVYUDN9\nWZ62sJOyZmbWB5TRUnkKeBpA0rSIWABsXPN5KzAPWC+/rhpESigbdig7nzq0tbX2XGgt4bpo57po\n57poV2ZdzJs3rLR1F6GMpPJZ4F3A2IjYAlgfeDEitgVmAh8AvgFsDRwMXJUH5/8oaXFEvNJJ2R7N\nmrWo2K3op9raWl0XmeuineuiXdl1MXfu4tLWXYQykspPgIsjYgqwHDg6/38ZqTVym6QHI2IqsF9E\n3JPnOzr//8WOZZsavZmZdanpSUXSUuCoTj56T4dyFVIC6Tj/Ax3LmplZ3+CLH83MrDBOKmZmVhgn\nFTMzK4yTipmZFcZJxczMCuOkYmZmhXFSMTOzwjipmJlZYZxUzMysME4qZmZWGCcVMzMrjJOKmZkV\nxknFzMwK46RiZmaFcVIxM7PCOKmYmVlhnFTMzKwwTipmZlYYJxUzMyuMk4qZmRVmSNkBmK2tli1b\nxsyZM8oOA4CNN96h7BBsgHBSMSvJzJkzOH7CDaw/fLNS43hpwT/52XeHsdFGbyg1DhsYnFTMSrT+\n8M0YttGWZYdhVhgnlbXIsmXLeOqpp5g7d3GpcbzpTW9m8ODBpcZgZo3hpLIW6QvdLS/O/wfjPjGS\nN75xm9JigJRgZ88exoIFS0qL4dln/1Laus0axUllLVN2d8tLC17gzMsfY/3hfy8tBoA5f32S9Vo3\nKTXBzvnrk2yy1dtLW39VZflynnnmGbdgrRBrRVK59LKrWLzo5VJjGLnD9rxlxLalxtBXlJ3YICW3\nsuN4acELpa271pJFszhl4uxSE+xLC/7J2Sd+iBEj/rW0GKBvdBH39xbsWpFUrpg6BBhW2vory5fx\n56dv4JOHH1haDND/d1ZrnLITbGX58j6xfz777F9yS9ot2NW1ViSVlpaWUtf/4sIXeGDBa/xx4v2l\nxtHfd1YbuJYsmsWZl8/uE92im2z1drdg10C/TCoR0QL8ENgBeBn4vKS+cRVZF8o+EoT+v7PawObv\nyMDQX2/TchiwrqTdgfHAWSXHY2Zm9N+ksgdwC4CkB4B3lxuOmZlBP+3+AjYEFtS8fy0iBkla3lnh\nlgVPsOy1Tj9qiuULZvPyoNeVtv6qJYvmAuWOL/WFGPpKHH0hhr4SR1+Ioa/E0RdigHRG3uror0ll\nIdBa877LhAJww4Unlf8XMjNbC/TX7q97gAMBImI34I/lhmNmZtB/WyrXAvtFxD35/dFlBmNmZklL\npVIpOwYzMxsg+mv3l5mZ9UFOKmZmVhgnFTMzK0x/HahfRU+3bomILwDHAEuB70i6qZRAm6COujgB\n+DhQAf5P0rdLCbQJ6rmlTy5zE3CdpInNj7I56tgvDgBOIe0XD0s6tpRAm6COuhgHfAJYBnxX0nWl\nBNpEEbEr8D1J7+sw/RDgZNJv58WSLuxuOQOppdLlrVsiYnPgS8B7gA8C342IoaVE2Rzd1cW2wBGS\ndgN2Bz4QEduVE2ZT1HNLn/8BNmpqVOXobr8YBpwOHJQ/nxkRm5QTZlN0VxfDSb8XuwIfAH5QSoRN\nFBEnApOAdTtMH0Kqm32BvYFjIqLbWzgPpKTS3a1bdgF+J+k1SQuBacD2zQ+xabqri2dJiRVJFWAo\n6UhtoOr2lj4RcTjpaPTm5ofWdN3Vxe6k673OiojJwAuS5jQ/xKbpri5eBGaSLrAeRto/BrqngQ93\nMv3twDRJCyUtBX4H7NndggZSUun01i1dfLYYGN6swErQZV1IWiZpLkBETCB1czxdQozN0mVdRMQ7\ngU8Cp9IX7ovReN19RzYlHYmeCBwAnBARb2lueE3VXV0A/BX4EzAVOKeZgZVB0rXAa5181LGeFtHD\nb+dASird3bplIalyqlqB+c0KrATd3sYmItaNiF8AGwBjmh1ck3VXF/8ObAHcCXwG+HJE7N/c8Jqq\nu7qYAzyh7e9+AAAEC0lEQVQoaZakF4HJwI7NDrCJuquLA4DXA9sAbwQ+HBFr601re/3bOWAG6km3\nbjkYuKqTW7f8HvifiFgHWA94G/B480Nsmu7qAuAG4DeSJjQ9subrsi4kfbX6OiJOBf4u6bbmh9g0\n3e0XDwHbRcTGpB+S3YABe9IC3dfFPGBJ7u4hIuYD5d8Rtjk6ttifBN4SEa8DXgJGA93+bgykpLLK\nrVvyWU7TJP06Is4h9Qe2ACdJerWsQJugy7og/c33BIZGxIGkM33G537lgajb/aLEuMrQ03dkPHAb\naZ+4XNKfygq0CXqqi6kRcT9pPOV3kn5TWqTNVQGIiCOADSRdGBFfJu0XLcCFkrp9PKdv02JmZoUZ\nSGMqZmZWMicVMzMrjJOKmZkVxknFzMwK46RiZmaFcVIxM7PCDKTrVMzWSERsAzwFPJEnrQM8Dxwt\n6W8R8VtgS9KtKqr3TDtF0s15/ruArfLnLaQrkacDR0qatQZx7QV8o+PdY836IrdUzFb2vKRR+d92\npCvNz82fVYDP5s/eBfwn8LOIeFvN/NXPR0oaQUowXy4gLl9QZv2CWypm3ZsMHFLzfsVtLCQ9FBGX\nA58HxuXJKw7UIqKVdKPG+2sXmJ9P8QVJH8rvjwVGkJ5l8hNSa2gLYLKkT3eY9y7gVEmTc8vqt5K2\nzbcj/zGppbScdJeEOyNiH+C0PG0e6bEHc9ekQsy645aKWRfyM3c+Trq9T1ceJ91LrmpSRDwSEX8D\n7iPd3uL7Hea5GRiVn9sB6WFQPwcOAh6R9F7grcDuETGyhzCrLZizgZ9I2hk4FJiYn5HyNeA/JO0C\n3AiM6mF5ZmvELRWzlW0ZEQ+TWiTrkG5GOr6b8hVgSc37z0maEhHvAa4iPVlzpVuKS3otIq4FDo+I\n24GNJT0EPBQRO0fE8aTnWGxMep5HPfYFIiKqT/EcDLwZuB64LiKuA65fi+5hZSVxUjFb2fOSenM0\nvz3puRtVLQCS7ouIc0ljLtvXPnog+znwbVLi+AVARHwJ+AipG+t2YDtWvWtspWZa7dNLBwPvlzQ/\nL+v1pAdt/SEibiTdkff0iLhS0nd7sX1mveLuL7OV1f2wrojYBTgc6OqZ3WcB65MG9FeS7wq9BXAU\nOamQWhs/lvSrHMeOpGRRazbwzvy69kl9dwBjc1zvIN3Kff18p90NJZ1D6oZz95c1lJOK2cp6Osvq\nwoh4OHeRnQl8TNJznc2bH6/wdeDUPGjf0eXAIkkz8/sfAN+IiKnAeaRnfmzbYZ7TgbG5TO3zxI8D\ndouIx4Bfkk5jfpHUdXdJLv8F0lMuzRrGt743M7PCuKViZmaFcVIxM7PCOKmYmVlhnFTMzKwwTipm\nZlYYJxUzMyuMk4qZmRXGScXMzArz/4/NdRQP8HORAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x117c34908>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 35110 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_igd7['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_igd7[df_igd7['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 10002 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZUAAAEZCAYAAABfKbiYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1193d8be0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 11386 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_igd8['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_igd8[df_igd8['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 14277 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZUAAAEZCAYAAABfKbiYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nRK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11c1d85c0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 17053 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_igd9['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_igd9[df_igd9['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 7199 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZAAAAEZCAYAAAC5AHPcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nc9fp+DAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1178770f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 8043 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_igd10['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_igd10[df_igd10['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 15554 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZUAAAEZCAYAAABfKbiYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x117c4d198>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 16967 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_igd11['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_igd11[df_igd11['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 13266 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZUAAAEZCAYAAABfKbiYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1198a92b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 15398 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_igd12['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_igd12[df_igd12['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 9690 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZUAAAEZCAYAAABfKbiYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzt3XmYHFW5x/HvZAGBDJFlQFlkiddXBFmC7BCiBpBNUFRE\nVMAFlVW48MgioLgghEUQRAQEcQVBdgNBtgQFZcew/EAggMiFkISQsIZk7h/ndKan09PTITVdM+H3\neZ48ma46XfX26ep665xTS1tnZydmZmZFGFR2AGZmtuhwUjEzs8I4qZiZWWGcVMzMrDBOKmZmVhgn\nFTMzK8yQsgMYqCJiLrC8pGlV0/YCPiNp54j4PvCYpN82WMYxwH2Sru77iBdeRNwCvA94KU9qAzol\njSwtqJJExNnAtsDvJR1TNX0v4HTgCaCTdOA2Czhc0h0RcRywP/AfUv0NyWUPk/RYXsYtdK/nIcBi\nwI8k/abJ+BYHrgZ+IenPedoSwHnABnndR0i6Ms/7HHAsMDvHtr+kp2uW+VNgTUmfzK9XA34BrAbM\nBE6W9Kdm4usLEdEG3C9p3T5a/r9I9TKhyfI7AJtIOu5tru9m4GeV72+gcFJ5+3q6wKcToMkN6WPA\ng4VF1Pc6gf+VdHnZgfQD+wKrSvpvnXkTKjtegIjYCfhzRKySJ/1R0kFV878I3BgRH5I0izr1HBEb\nAn+LiD9LeqVRYBGxKfBzIEg7/YrvATMlfSgiVgVuj4g7gSVzuS0lPRQRWwGXAhtXLfNzwBeAO6qW\n92vgRknbR8Qw4OaIeETSvxrF14c2p3t8ZdsIWKbsIFrNSeXta2s0MyIuAP4l6dTcatkFeBOYCuwD\nfBr4CDA2IuYANwNnAesDc4HrgCMlzc1HPD8B3gLuB8YAWwAfBb4KLEU6qt0ZOBt4P7Ac6ejxC5Ie\ny0c9d5MSWQdwBrAisDVpp/I5SQ9GxM7ANyTttCCfOy9/GmlHdjbwG9IR+zrAUOBG0tH63IjYDTge\neBX4C3CUpKHVLb28zOqW31DgRGAUMBi4FzhI0qyIeBK4EPg4sCpwiaTv5GV8BTg0192LwN6kI/IX\nJH03l9kT+LSk3Wo+09rAz3JdzgVOkfTbiKgcqY6LiP0k/a2Huqq4kVTX7643My/zS6Sd9i/z5Np6\nHkFq8bzRy7oADgSOBg6vmf4pYI+8zmciYjzwOeAZUov5oTxvYkSsHhHvk/R0RKwFHAZ8H9iuankb\nAl/O75mVt4FPAd2SSp1t44r8/+q5yK8lnRIRlwNXSbogIjYD/kZqGU2OiKOBYaTv+Xxg8VxH50s6\nOy9nF+CK3IKaCDxMakVtnevvJ6RtfQ5wvKRrI2JJev7NrAX8ClgCUH7vfCLi07m+5+R/h5N+698E\nBkXEDOCEButZkZTUP5jf/wtJZ1YtfzDw+7zMvYBda9cn6bZ6sZXBYyoL5+aIuCf/u5e0o+wmH50e\nDGwkaWNgPLCxpJ8Dd5G6Pa4k7eRflPRhUrJZDzgsIpYFLiJtgCNJyWelqlV8CBgl6ePA9sB0SVtI\n+mBe/gFVZVfLy9iNtIO+SdJGwPWkHRGSrm6QUCAlwXsi4t78/yeq5k2TtI6ks4DTgLvy8keSEtmh\nEfEe0k7h03neG3TfDmtbgJXXRwCzJX1E0gbAc6SdRMVSkkaRku2BEbFaRKyXy2wraX3gKuAo4Exg\nn4iorHdf0g9+nvxDvhI4XdJ6wA7ACRGxSV5PGzC6iYQC8A1gUnVXaR33Ax+uel2p5ycj4v9IO8yP\nS3qrt5VJ2lPSOOZPTKuSEkjFs8AqpAS9TkSsC5APLJYF3hsRS5G2v71ISa3aHaQDJCKig1RH7+0h\nrOpt43ekFs66wJbAl3JL6DLSNgzwCdJ3PCa//mSefzgp8WwE7AhsVbWOMcBf89+rAN/Pv4M3SMnh\ni5I+Qtopn51/m41+M78DzsnbzumkBFXPScC38u/7GNJ28U9Sorg4d482Ws/ZgCStRWpt7RsRa+Z5\niwN/Ap6X9CVJc+utr4e4SuGWysIZLWl65UU+st6tpsyzwH3AvRExDhgn6aaq+ZUf/vakDQpJsyPi\nF8C3gUeBByVNyvMuiojTq97/QKU7RNJlEfFERBxAOiIaDfy9qmylb/Zx0s76+qrXWzf5mQ9v0Mc7\nservnYCNIuJr+fW78jq3IPV7K08/E/hBE+vdCRgeEdvm10OB56vmXwkg6b8R8TxppzgauK7SRSXp\njErhiHgC2DEiHgPeK+mvdPcBYPHKmIOk5yLiMtLO7h+5TE+t1VERcU/+ezHgEebfLmp1klpuFYdL\n+nNELEdqzU2RdH8vy+hNG92TdhswR9ITuUV3TkQsRqrL+0lHxucDZ0h6OCI2qVneXsBpEXE/8CRp\nDKfu0Tx528gtgy2AbQAkvRwRF5K2/0OAU3NC3xb4IbBNRFwLdEi6K7dmfp1j+StwUF7uWsDjkt6M\nCEhjQ5WusM1Iye6KPO4C6Qh/3Z5+M/lgbl1SixtJf4+Inrqq/5CXfS1wA2mn300vv82Pk1qCSHo5\nr5f8OU4htdBGLMj6yuSWysJp2AUGIKlT0mjSD/BF0o/wtDpFB9H9Bz+IlPRnM//3VF1u3tFjRHyL\ntBN4hXSU9YeaGLt1nUia01v8C6j6SHYQ8FlJG+SWxSak1tBrNTFVH3l31sxbrOrvwcDBVcvbGPhs\n1fzXamJpy8ueV1cR8a7Iv1TSmMNXga/Q1eVUbTDzt5oGkZJZbyZIGpn/rSPpM5L+3ct7NgIeqJ0o\naSrweeDrudtwYTxN91buSsB/ctfi45I2k7Qh8CNgDWAKqSVwSG6Jfx/YKiKuye9fEthb0nqSdgWG\nAz19zsq2UW+fMwgYKukl0gHYzkA7qYU0itSyuBxA0rXA/wAXk044mBQRa+QyV1Yt8418VA/pu3wo\nfx+V7WdzYHwvv5na7bFuKzG3RLYA7iR1r843rtPLemq30zUioj2/vIjUkjlvQdZXJieVPhYR60bE\nJOBhSSeSuoXWy7PfomsndR25ORzpzJ19SV1lfwf+JyLWyfN2I/14650osC1wgaQLgMdIP87BPYTW\na0JcSNeTxjKqz0TaH7id9HnWz+X2rnrPFFI3zGIRMYQUf/XyDoiIobnb6nxSP3UjNwNjcp81pD7u\nE/Pfl5J2SruRukZqPQLMjohd82dYKZcd38s6F1hEfJW0E6975pSkJ0k7+tMincH1dl1J2q4q3bLb\nkb6Xd5FOAqicSHAocJuk/0haubIzJo1FTazqHv0+sF9e3gdIXVQNz1RSOhHhDtK2QEQMJ43LVOr1\ncuDHpO6xV0gt9SNIXV9ExO+Az0u6JK97Bqlbb0fgmq41ddu+7yBtc1vlZaxP+n2sRA+/mdxVeTfw\ntfyekXTvniRPH5zH9JaS9Msc0wdzoq7+fTf6bd5AVzficNIY3PvzvH+S6n1ERHy1l/X1C04qb19T\nt3eW9ADpqOruSGfa7EPq1oL0gz45D9IeBKwY6bTF+0mDjD/O3WtfAH4TEXeRNs636N5VUnEy8M3c\n9XID6UdR2Th7GqvoJiJ2rjoSrdXoM9fOOxhYMn+e+/JnOil/ns8C5+bPs1HVe8YDt5IGRW+l+5H7\nD4DJpP7/SXl9/9vDuitn4E0i9cFfn4+0tyUlFiTNJiWWv9cb68hjF7sC387dO+OB76nrdNKFub33\n7jVjcduQulLfbLDsk0nfeeXkgmsjnVXWSO1yvge054Oc8aTxvMmSZpJ2nuNyF88mdE/2PTkM2CEi\nHiAdee8t6dkm4tiTlOwfIO3wL5V0UZ53BanrsZJkrgeGSKp0FR0P7Jnr7Q5SEnsUeD23dOZbp6QX\nSQcEYyPiPtJZa3sqnTLd6DfzBWCP/P0fDTxU+8Fya/9g4PcRcTdwCbBP3r5uAj6Zu6vHNljPgcCH\n8nomkk4dv5eu7fgN0n5jLOlU857W1y+0+db3/VtuBn8XOE7S6xGxAXCNpJVLDq0QecxgiqSWHuDk\nAehbgf3yoOqAkseqplTGfMz6iz4fqM8Daj+R9NGIGEE6JXAu6WyYShP4WFLzdTZwiKQ7F6RsX3+G\nMkmaGRFvAndFxGzS4Olne3nbQNPSI5s82P8H4LyBmFCy2XTv7jHrF/q0pRIRhwNfAmZJ2jwiriRd\ndTsx0hXJ15EGD8dKGhPpgqzLJG28IGX77AOYmdkC6esuh3+TLoaq2FBS5bTTcaS+5C3J/aeSngEG\nR8TyC1B2uT7+DGZm1qQ+TSpKt5moPg2v+oyMmaSzmNpJZ3DUTqeJsrPqlDUzs5K0+uLHuVV/twPT\ngZeBpWumv7SAZRvq7OzsbGvr6zNozcwWOQu842x1UrknIkbl0zK3J51y9zhwYkScTDrffJCkqZFu\nA9Jb2bZ6p4PWamtrY8qUmX31mQaUjo5210XmuujiuujiuujS0dHee6EarU4qh5GuTxhKug7jUkmd\nETGRdFFcG/liqibL7t/i+M3MrIF3ynUqnT7ySHwU1sV10cV10cV10aWjo73fd3+ZmVkDc+bMYfLk\nJ8oOA4COjgV//p6TiplZPzJ58hMcPPYqlhy+QqlxvDrjBf5xmZOKmdmAt+TwFRi2zMC8E5NvKGlm\nZoVxUjEzs8I4qZiZWWGcVMzMrDBOKmZmVhgnFTMzK4yTipmZFcZJxczMCuOkYmZmhXFSMTOzwjip\nmJlZYZxUzMysME4qZmZWGCcVMzMrjJOKmZkVxknFzMwK46RiZmaFcVIxM7PCOKmYmVlhnFTMzKww\nTipmZlYYJxUzMyuMk4qZmRXGScXMzArjpGJmZoVxUjEzs8I4qZiZWWGcVMzMrDBOKmZmVhgnFTMz\nK4yTipmZFcZJxczMCuOkYmZmhRnS6hVGxBDg18DqwFvA14E5wIXAXGCSpP1z2WOBHYHZwCGS7oyI\nEfXKmplZ+cpoqewADJa0BfAD4MfAqcBRkrYGBkXELhGxATBK0ibAHsBZ+f3zlW39RzAzs3rKSCqP\nAkMiog0YTmqFjJQ0Mc8fB2wDbAmMB5D0DDA4IpYHNqwpO6aVwZuZWc9a3v0FzALWAB4BlgN2Braq\nmj+TlGzagal1ptPLNDMzK0kZSeUQ4DpJR0fEysAtwGJV89uB6cDLwNI1018ijaXUTutVR0f7QoS8\naHFddHFddHFddCmzLqZPH1bauotQRlKZRurygpQQhgD3RsTWkm4FtgduAh4HToyIk4FVgUGSpkbE\nvRExStKEqrK9mjJlZtGfY0Dq6Gh3XWSuiy6uiy5l18W0abNKW3cRykgqPwV+FRETgKHAEcDdwHkR\nMRR4GLhUUmdETARuB9qA/fL7DwPOrS7b6g9gZmb1tTypSHoF2L3OrNF1yh4PHF8z7bF6Zc3MrHy+\n+NHMzArjpGJmZoVxUjEzs8I4qZiZWWGcVMzMrDBOKmZmVhgnFTMzK4yTipmZFcZJxczMCuOkYmZm\nhXFSMTOzwjipmJlZYZxUzMysME4qZmZWGCcVMzMrjJOKmZkVxknFzMwK46RiZmaFcVIxM7PCOKmY\nmVlhnFTMzKwwTipmZlYYJxUzMyuMk4qZmRXGScXMzArjpGJmZoVxUjEzs8I4qZiZWWGcVMzMrDBO\nKmZmVhgnFTMzK4yTipmZFcZJxczMCuOkYmZmhXFSMTOzwjipmJlZYZxUzMysMEPKWGlEHAF8EhgK\n/ByYAFwIzAUmSdo/lzsW2BGYDRwi6c6IGFGvrJmZla/lLZWI2BrYTNLmwGjgfcCpwFGStgYGRcQu\nEbEBMErSJsAewFl5EfOVbfVnMDOz+sro/toOmBQRVwBXAdcAIyVNzPPHAdsAWwLjASQ9AwyOiOWB\nDWvKjmll8GZm1rOmur8i4i/ABcCVkt5cyHUuT2qd7ASsSUos1cltJjAcaAem1plOL9PMzKwkzY6p\nnAh8GRgbEdcCF0q6822ucyrwsKS3gEcj4nVglar57cB04GVg6ZrpL5HGUmqn9aqjo/1thrvocV10\ncV10cV10KbMupk8fVtq6i9BUUpF0K3BrRCwBfAa4LCJeBs4Dzpb0xgKs8zbgIOC0iFgJWAq4MSK2\nzuvZHrgJeBw4MSJOBlYFBkmaGhH3RsQoSROqyvZqypSZCxDioqujo911kbkuurguupRdF9OmzSpt\n3UVo+uyviBgNfAnYljSW8UfS2MdVpHGSpki6NiK2ioh/Am3At4DJwHkRMRR4GLhUUmdETARuz+X2\ny4s4DDi3umyz6zYzs77V7JjKU8ATpHGVAyS9lqffAty1oCuVdESdyaPrlDseOL5m2mP1ypqZWfma\nPfvrY8Duki4CiIj3A0iaK2lkXwVnZmYDS7NJZUfguvz3CsDVEbFv34RkZmYDVbNJZV9gKwBJTwEb\nAgf2VVBmZjYwNZtUhgLVZ3i9CXQWH46ZmQ1kzZ79dQVwU0RcQkomu5HO+jIzM5unqZaKpO8AZwAB\njADOkPTdvgzMzMwGngW599fDwCWkVsu0iBjVNyGZmdlA1ex1KmcBO5Oucq/oJJ1qbGZmBjQ/prIt\nEJWLHs3MzOpptvvrCdKtUszMzHrUbEtlGvBQRPwdeL0yUdJX+iQqMzMbkJpNKtfRdUW9mZlZXc3e\n+v7XEbE6sDZwPbCqpCf7MjAzMxt4mhpTiYjdgauB04Flgdsj4ot9GZiZmQ08zQ7UfwfYHJgp6QVg\nA+DIPovKzMwGpGaTyhxJ8x6FJuk5uj/W18zMrOmB+gcj4gBgaESsT3oK4319F5aZmQ1EzbZU9gdW\nBl4DfgW8TNfjfc3MzIDmz/56hTSG4nEUMzPrUbP3/prL/M9PeU7SKsWHZGZmA1WzLZV53WQRMRTY\nFdisr4IyM7OBaUFufQ+ApNmS/oTvUGxmZjWa7f76ctXLNtKV9bP7JCIzMxuwmj2l+KNVf3cCLwK7\nFx+OmZkNZM2OqezT14GYmdnA12z315PMf/YXpK6wTklrFhqVmZkNSM12f/0eeAM4lzSWsiewEXB0\nH8VlZmYDULNJZTtJH6l6fXpE3C3pqb4IyszMBqZmTylui4gxlRcRsRPpVi1mZmbzNNtS2Re4KCLe\nQxpbeQTYq8+iMjOzAanZs7/uBtaOiOWB1/K9wMzMzLpp9smPq0XEDcDtQHtE3JQfL2xmZjZPs2Mq\n5wBjgVnA88AfgIv6KigzMxuYmk0qy0saDyCpU9K5wNJ9F5aZmQ1EzSaV1yJiFfIFkBGxJem6FTMz\ns3maPfvrEOAaYERE3AcsC3y2z6IyM7MBqdmksiLpCvoPAIOBRyS92WdRmZnZgNRsUjlJ0rXAg0Wt\nOCJWAO4CxgBzgAuBucAkSfvnMscCO5JuDXOIpDsjYkS9smZmVr5mx1Qej4hfRcQ3IuLLlX9vd6UR\nMQT4BfBqnnQqcJSkrYFBEbFLRGwAjJK0CbAHcFZPZd9uHGZmVqyGSSUiVs5/TiXdkXhT0rNVPgqM\nXoj1ngycDfw3L3ekpIl53jhgG2BLoHLG2TPA4Hzx5YY1ZcdgZmb9Qm/dX1eTdvj7RMT/SjplYVcY\nEXsDL0i6ISKOypOrk9tMYDjQTkpmtdPpZZqZmZWkt6TSVvX3nsBCJxVgH2BuRGwDrEe6iLKjan47\nMJ10w8qla6a/RBpLqZ3Wq46O9oUIedHiuujiuujiuuhSZl1Mnz6stHUXobekUv1grrYeSy2APBYC\nQETcBHwTGBsRoyRNALYHbgIeB06MiJOBVYFBkqZGxL11yvZqypSZRYQ/4HV0tLsuMtdFF9dFl7Lr\nYtq0WaWtuwjNnv0F9Z/8WJTDgHMjYijwMHCppM6ImEi631gbsF9PZfswLjMzWwC9JZW1I+KJ/PfK\nVX8X8hhhSR+rejm6zvzjgeNrpj1Wr6yZmZWvt6TygZZEYWZmi4SGScWPCzYzswXR7MWPZmZmvXJS\nMTOzwjipmJlZYZxUzMysME4qZmZWGCcVMzMrjJOKmZkVxknFzMwK46RiZmaFcVIxM7PCOKmYmVlh\nnFTMzKwwTipmZlYYJxUzMyuMk4qZmRXGScXMzArjpGJmZoVxUjEzs8I4qZiZWWGcVMzMrDBOKmZm\nVhgnFTMzK4yTipmZFcZJxczMCuOkYmZmhXFSMTOzwjipmJlZYZxUzMysME4qZmZWGCcVMzMrjJOK\nmZkVxknFzMwK46RiZmaFcVIxM7PCDGn1CiNiCPArYHVgMeBHwEPAhcBcYJKk/XPZY4EdgdnAIZLu\njIgR9cqamVn5ymipfBF4UdIoYHvgTOBU4ChJWwODImKXiNgAGCVpE2AP4Kz8/vnKtv4jmJlZPWUk\nlUuAY6rW/xYwUtLEPG0csA2wJTAeQNIzwOCIWB7YsKbsmFYFbmZmjbW8+0vSqwAR0Q78CTgaOLmq\nyExgONAOTK0znV6mmZlZSVqeVAAiYlXgz8CZkv4YESdVzW4HpgMvA0vXTH+JNJZSO61XHR3tCxXz\nosR10cV10cV10aXMupg+fVhp6y5CGQP1KwLXA/tLujlPvjciRkmaQBpnuQl4HDgxIk4GVgUGSZoa\nEfXK9mrKlJmFf5aBqKOj3XWRuS66uC66lF0X06bNKm3dRSijpXIk8G7gmHx2VydwMPCziBgKPAxc\nKqkzIiYCtwNtwH75/YcB51aXbfUHMDOz+soYU/k28O06s0bXKXs8cHzNtMfqlTUzs/L54kczMyuM\nk4qZmRXGScXMzArjpGJmZoVxUjEzs8I4qZiZWWGcVMzMrDBOKmZmVhgnFTMzK4yTipmZFcZJxczM\nCuOkYmZmhXFSMTOzwjipmJlZYZxUzMysME4qZmZWGCcVMzMrjJOKmZkVxknFzMwK46RiZmaFcVIx\nM7PCOKmYmVlhnFTMzKwwTipmZlYYJxUzMyuMk4qZmRXGScXMzArjpGJmZoVxUjEzs8I4qZiZWWGc\nVMzMrDBOKmZmVhgnFTMzK4yTipmZFcZJxczMCjOk7ADM3qnmzJnD5MlPlB0GAMsuu17ZIdgiwknl\nHWTOnDk8+uijTJs2q9Q4Vl99TQYPHlxqDP3B5MlPcPDYq1hy+AqlxvHqjBf4zQnDWGaZ95Yahy0a\nBmRSiYg24OfAesDrwNck9Y9Dvjr6yxHp008/xSkX31/qTuyVl/6Pwz6/Ae9732qlxQDpO3nxxWHM\nmPFaaTE8/fRTLDl8BYYts3JpMQB0zp3Lk08+6YMN+seB19NPP1XauoswIJMKsCuwuKTNI2IT4NQ8\nra7v/PAcXn99dsuCqzV96gvohUGlH5FO/c/DLLfKWqXuxF6d8XxObM+VFgOkuliifblSv5PK91G2\n12ZO4dhfvuiDDfrHgVd/2S7eroGaVLYErgOQ9I+I+Eijwg9Nf09LgurJrDcGseRwSj8ifXXG86Wu\nv6I/HJ2/OuP50uPoL98HlP+d9KeDjf5w4DWQDdSksjQwo+r1WxExSNLceoXbZjzInLfqzmqJuTNe\n5PVB7y5t/RWvzZwGtL3jY+gvcfSHGPpLHK/NnMYS7cuVGkPFqzNeKHX9/eH7gLdfDwM1qbwMtFe9\n7jGhAFx13lHlf0NmZu8AA/U6lb8BOwBExKbAv8oNx8zMYOC2VC4HtomIv+XX+5QZjJmZJW2dnZ1l\nx2BmZouIgdr9ZWZm/ZCTipmZFcZJxczMCjNQB+rn09utWyLi68C+wGzgR5KuLSXQFmiiLg4Bdgc6\ngb9I+kEpgbZAM7f0yWWuBa6Q9MvWR9kaTWwX2wPHkraLeyQdUEqgLdBEXRwGfB6YA5wg6YpSAm2h\nfHeSn0j6aM30nYFjSPvOCySd12g5i1JLZd6tW4AjSbduASAiVgQOBDYDPgGcEBFDS4myNRrVxRrA\nHpI2BTYHtouIdcoJsyV6rIsqPwSWaWlU5Wi0XQwDTgJ2zPMnR0T/uBqxbzSqi+Gk/cUmwHbAT0uJ\nsIUi4nDgXGDxmulDSHUzBhgN7BsRDe9hsygllW63bgGqb92yMXCbpLckvQw8Bqzb+hBbplFdPE1K\nrEjqBIaSjtQWVY3qgojYjXQ0Oq71obVco7rYnHS916kRMQF4XtLU1ofYMo3q4hVgMukC62Gk7WNR\n92/gU3WmrwU8JullSbOB24CtGi1oUUoqdW/d0sO8WcDwVgVWgh7rQtIcSdMAImIsqZvj3yXE2Co9\n1kVErA18ATiO/nBfjL7X6DeyPOlI9HBge+CQiHh/a8NrqUZ1AfAf4CHgLuCMVgZWBkmXA2/VmVVb\nTzPpZd+5KCWVRrdueZlUORXtwEutCqwEDW9jExGLR8TvgKWA/VodXIs1qosvAysBNwF7A4dGxLat\nDa+lGtXFVOBOSVMkvQJMANZvdYAt1KgutgfeA6wGvA/4VG83rV2ELfC+c5EZqCfdumUn4NI6t275\nJ/DDiFgMWAL4IDCp9SG2TKO6ALgK+KuksS2PrPV6rAtJ36n8HRHHAc9JGt/6EFum0XZxN7BORCxL\n2pFsCiyyJy3QuC6mA6/l7h4i4iWg/DvCtkZti/1h4P0R8W7gVWAU0HC/sSgllflu3ZLPcnpM0jUR\ncQapP7ANOErSm2UF2gI91gXpO98KGBoRO5DO9Dky9ysvihpuFyXGVYbefiNHAuNJ28TFkh4qK9AW\n6K0u7oqIO0jjKbdJ+mtpkbZWJ0BE7AEsJem8iDiUtF20AedJavh8At+mxczMCrMojamYmVnJnFTM\nzKwwTipmZlYYJxUzMyuMk4qZmRXGScXMzAqzKF2nYrZQImI14FHgwTxpMeBZYB9J/42IW4CVSbeq\nqNwz7VhJ4/L7bwZWyfPbSFciPw7sKWnKQsS1NfC92rvHmvVHbqmYdfespJH53zqkK81/lud1Al/J\n8z4MfBP4TUR8sOr9lfkbSBpBSjCHFhCXLyizAcEtFbPGJgA7V72edxsLSXdHxMXA14DD8uR5B2oR\n0U66UeMd1QvMz6f4uqRP5tcHACNIzzI5n9QaWgmYIGmvmvfeDBwnaUJuWd0iaY18O/JzSC2luaS7\nJNwUER8HTszTppMeezBtYSrErBG3VMx6kJ+5szvp9j49mUS6l1zFuRFxb0T8F7iddHuL02reMw4Y\nmZ/bAelhUL8FdgTulbQF8AFg84jYoJcwKy2Y04HzJW0E7AL8Mj8j5WjgG5I2Bq4GRvayPLOF4paK\nWXcrR8TwS1/8AAABmklEQVQ9pBbJYqSbkR7ZoHwn8FrV669KmhgRmwGXkp6s2e2W4pLeiojLgd0i\n4gZgWUl3A3dHxEYRcTDpORbLkp7n0YwxQERE5Smeg4E1gSuBKyLiCuDKd9A9rKwkTipm3T0raUGO\n5tclPXejog1A0u0R8TPSmMu61Y8eyH4L/ICUOH4HEBEHAp8mdWPdAKzD/HeN7ayaVv300sHAxyS9\nlJf1HtKDth6IiKtJd+Q9KSL+JOmEBfh8ZgvE3V9m3TX9sK6I2BjYDejpmd2nAkuSBvS7yXeFXgn4\nIjmpkFob50j6Y45jfVKyqPYisHb+u/pJfTcC++e4PkS6lfuS+U67S0s6g9QN5+4v61NOKmbd9XaW\n1XkRcU/uIjsF+JykZ+q9Nz9e4bvAcXnQvtbFwExJk/PrnwLfi4i7gDNJz/xYo+Y9JwH75zLVzxM/\nCNg0Iu4H/kA6jfkVUtfdhbn810lPuTTrM771vZmZFcYtFTMzK4yTipmZFcZJxczMCuOkYmZmhXFS\nMTOzwjipmJlZYZxUzMysME4qZmZWmP8HSbUgb4Qww7EAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x115689da0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 10949 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_igd13['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_igd13[df_igd13['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 19942 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZUAAAEZCAYAAABfKbiYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11b995358>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 22450 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_igd14['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_igd14[df_igd14['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 4077 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZAAAAEZCAYAAAC5AHPcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1193be828>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 4515 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_igd15['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_igd15[df_igd15['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 16232 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZUAAAEZCAYAAABfKbiYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x119cf9860>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 17790 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_igd16['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_igd16[df_igd16['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 8814 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZAAAAEZCAYAAAC5AHPcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1134dca20>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 10087 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_igd17['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_igd17[df_igd17['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 357 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYoAAAEZCAYAAACJjGL9AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1126fb748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 379 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_igd18['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_igd18[df_igd18['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 10521 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZUAAAEZCAYAAABfKbiYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x118d6e320>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 11962 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_igd19['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_igd19[df_igd19['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 14171 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZUAAAEZCAYAAABfKbiYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x117865dd8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 16955 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_igd20['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_igd20[df_igd20['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 8312 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZAAAAEZCAYAAAC5AHPcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x112f8d550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 9498 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_igd21['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_igd21[df_igd21['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 15890 total number of PDR values == 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZUAAAEZCAYAAABfKbiYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n46BiZmaF+f8oO69biLORaQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x117c41128>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('Histogram: Frequency of PDR, 17055 rows/read stacks')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "df_igd22['PDR'].plot(kind='hist')\n",
    "print('There are ' + str(len(df_igd22[df_igd22['PDR']==1])) + ' total number of PDR values == 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "PDR_mam_lessthan1 = df_mam1[df_mam1['PDR'] < 1.0]  # simply remove all 1.0 values\n",
    "PDR_mam_lessthan2 = df_mam2[df_mam2['PDR'] < 1.0]\n",
    "PDR_mam_lessthan3 = df_mam3[df_mam3['PDR'] < 1.0]\n",
    "PDR_mam_lessthan4 = df_mam4[df_mam4['PDR'] < 1.0]\n",
    "PDR_mam_lessthan5 = df_mam5[df_mam5['PDR'] < 1.0]\n",
    "PDR_mam_lessthan6 = df_mam6[df_mam6['PDR'] < 1.0]\n",
    "PDR_mam_lessthan7 = df_mam7[df_mam7['PDR'] < 1.0]\n",
    "PDR_mam_lessthan8 = df_mam8[df_mam8['PDR'] < 1.0]\n",
    "PDR_mam_lessthan9 = df_mam9[df_mam9['PDR'] < 1.0]\n",
    "PDR_mam_lessthan10 = df_mam10[df_mam10['PDR'] < 1.0]\n",
    "PDR_mam_lessthan11 = df_mam11[df_mam11['PDR'] < 1.0]\n",
    "PDR_mam_lessthan12 = df_mam12[df_mam12['PDR'] < 1.0]\n",
    "PDR_mam_lessthan13 = df_mam13[df_mam13['PDR'] < 1.0]\n",
    "PDR_mam_lessthan14 = df_mam14[df_mam14['PDR'] < 1.0]\n",
    "PDR_mam_lessthan15 = df_mam15[df_mam15['PDR'] < 1.0]\n",
    "PDR_mam_lessthan16 = df_mam16[df_mam16['PDR'] < 1.0]\n",
    "PDR_mam_lessthan17 = df_mam17[df_mam17['PDR'] < 1.0]\n",
    "PDR_mam_lessthan18 = df_mam18[df_mam18['PDR'] < 1.0]\n",
    "PDR_mam_lessthan19 = df_mam19[df_mam19['PDR'] < 1.0]\n",
    "PDR_mam_lessthan20 = df_mam20[df_mam20['PDR'] < 1.0]\n",
    "PDR_mam_lessthan21 = df_mam21[df_mam21['PDR'] < 1.0]\n",
    "# PDR_mam_lessthan22\n",
    "PDR_mam_lessthan23 = df_mam23[df_mam23['PDR'] < 1.0]\n",
    "PDR_mam_lessthan24 = df_mam24[df_mam24['PDR'] < 1.0]\n",
    "PDR_mam_lessthan25 = df_mam25[df_mam25['PDR'] < 1.0]\n",
    "PDR_mam_lessthan26 = df_mam26[df_mam26['PDR'] < 1.0]\n",
    "\n",
    "\n",
    "PDR_igd_lessthan1 = df_igd1[df_igd1['PDR'] < 1.0]  # simply remove all 1.0 values\n",
    "PDR_igd_lessthan2 = df_igd2[df_igd2['PDR'] < 1.0]\n",
    "PDR_igd_lessthan3 = df_igd3[df_igd3['PDR'] < 1.0]\n",
    "PDR_igd_lessthan4 = df_igd4[df_igd4['PDR'] < 1.0]\n",
    "PDR_igd_lessthan5 = df_igd5[df_igd5['PDR'] < 1.0]\n",
    "PDR_igd_lessthan6 = df_igd6[df_igd6['PDR'] < 1.0]\n",
    "PDR_igd_lessthan7 = df_igd7[df_igd7['PDR'] < 1.0]\n",
    "PDR_igd_lessthan8 = df_igd8[df_igd8['PDR'] < 1.0]\n",
    "PDR_igd_lessthan9 = df_igd9[df_igd9['PDR'] < 1.0]\n",
    "PDR_igd_lessthan10 = df_igd10[df_igd10['PDR'] < 1.0]\n",
    "PDR_igd_lessthan11 = df_igd11[df_igd11['PDR'] < 1.0]\n",
    "PDR_igd_lessthan12 = df_igd12[df_igd12['PDR'] < 1.0]\n",
    "PDR_igd_lessthan13 = df_igd13[df_igd13['PDR'] < 1.0]\n",
    "PDR_igd_lessthan14 = df_igd14[df_igd14['PDR'] < 1.0]\n",
    "PDR_igd_lessthan15 = df_igd15[df_igd15['PDR'] < 1.0]\n",
    "PDR_igd_lessthan16 = df_igd16[df_igd16['PDR'] < 1.0]\n",
    "PDR_igd_lessthan17 = df_igd17[df_igd17['PDR'] < 1.0]\n",
    "PDR_igd_lessthan18 = df_igd18[df_igd18['PDR'] < 1.0]\n",
    "PDR_igd_lessthan19 = df_igd19[df_igd19['PDR'] < 1.0]\n",
    "PDR_igd_lessthan20 = df_igd20[df_igd20['PDR'] < 1.0]\n",
    "PDR_igd_lessthan21 = df_igd21[df_igd21['PDR'] < 1.0]\n",
    "PDR_igd_lessthan22 = df_igd22[df_igd22['PDR'] < 1.0]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "xticks = [x * 0.05 for x in list(range(0, 20))]  # set xticks 0.0, 0.05, 0.1, 0.15, etc."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 395 total number of samples with PDR values < 1.0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/local/Library/Frameworks/Python.framework/Versions/3.4/lib/python3.4/site-packages/statsmodels/nonparametric/kdetools.py:20: VisibleDeprecationWarning: using a non-integer number instead of an integer will result in an error in the future\n",
      "  y = X[:m/2+1] + np.r_[0,X[m/2+1:],0]*1j\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYgAAAEZCAYAAACNebLAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nrkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x116f602b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(PDR_mam_lessthan1['PDR'], bins = xticks)  # Flexibly plot a univariate distribution against observations.\n",
    "plt.title('Distribution fitted to frequency of PDR values s.t. PDR < 1.0')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "print('There are ' + str(len(PDR_mam_lessthan1['PDR'])) + ' total number of samples with PDR values < 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/local/Library/Frameworks/Python.framework/Versions/3.4/lib/python3.4/site-packages/statsmodels/nonparametric/kdetools.py:20: VisibleDeprecationWarning: using a non-integer number instead of an integer will result in an error in the future\n",
      "  y = X[:m/2+1] + np.r_[0,X[m/2+1:],0]*1j\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 733 total number of samples with PDR values < 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYgAAAEZCAYAAACNebLAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nnSTHAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x115eae3c8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(PDR_mam_lessthan2['PDR'], bins = xticks)  # Flexibly plot a univariate distribution against observations.\n",
    "plt.title('Distribution fitted to frequency of PDR values s.t. PDR < 1.0')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "print('There are ' + str(len(PDR_mam_lessthan2['PDR'])) + ' total number of samples with PDR values < 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 2772 total number of samples with PDR values < 1.0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/local/Library/Frameworks/Python.framework/Versions/3.4/lib/python3.4/site-packages/statsmodels/nonparametric/kdetools.py:20: VisibleDeprecationWarning: using a non-integer number instead of an integer will result in an error in the future\n",
      "  y = X[:m/2+1] + np.r_[0,X[m/2+1:],0]*1j\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYgAAAEZCAYAAACNebLAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nYOEUKsLyFhYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1161a4b38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(PDR_mam_lessthan3['PDR'], bins = xticks)  # Flexibly plot a univariate distribution against observations.\n",
    "plt.title('Distribution fitted to frequency of PDR values s.t. PDR < 1.0')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "print('There are ' + str(len(PDR_mam_lessthan3['PDR'])) + ' total number of samples with PDR values < 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# sns.distplot(PDR_mam_lessthan4['PDR'], bins = xticks)  # 100% PDR == 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/local/Library/Frameworks/Python.framework/Versions/3.4/lib/python3.4/site-packages/statsmodels/nonparametric/kdetools.py:20: VisibleDeprecationWarning: using a non-integer number instead of an integer will result in an error in the future\n",
      "  y = X[:m/2+1] + np.r_[0,X[m/2+1:],0]*1j\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 634 total number of samples with PDR values < 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYgAAAEZCAYAAACNebLAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x114dd02e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(PDR_mam_lessthan5['PDR'], bins = xticks)  # Flexibly plot a univariate distribution against observations.\n",
    "plt.title('Distribution fitted to frequency of PDR values s.t. PDR < 1.0')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "print('There are ' + str(len(PDR_mam_lessthan5['PDR'])) + ' total number of samples with PDR values < 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/local/Library/Frameworks/Python.framework/Versions/3.4/lib/python3.4/site-packages/statsmodels/nonparametric/kdetools.py:20: VisibleDeprecationWarning: using a non-integer number instead of an integer will result in an error in the future\n",
      "  y = X[:m/2+1] + np.r_[0,X[m/2+1:],0]*1j\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 2640 total number of samples with PDR values < 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYgAAAEZCAYAAACNebLAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\njAnKEoQxxpigLEEYY4wJ6v8Dy+FS/YVTEGMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x116f55b00>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(PDR_mam_lessthan6['PDR'], bins = xticks)  # Flexibly plot a univariate distribution against observations.\n",
    "plt.title('Distribution fitted to frequency of PDR values s.t. PDR < 1.0')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "print('There are ' + str(len(PDR_mam_lessthan6['PDR'])) + ' total number of samples with PDR values < 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/local/Library/Frameworks/Python.framework/Versions/3.4/lib/python3.4/site-packages/statsmodels/nonparametric/kdetools.py:20: VisibleDeprecationWarning: using a non-integer number instead of an integer will result in an error in the future\n",
      "  y = X[:m/2+1] + np.r_[0,X[m/2+1:],0]*1j\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 1419 total number of samples with PDR values < 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYgAAAEZCAYAAACNebLAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzt3Xd4HOW1+PHvrnqX1Szbslzxce8FjDGQ0AKmQwipF0JI\nCEkISXhyuQkpNze/JKQCARJwgBAILfRq04sB427Lxse9yE3N6l3a3x8zMmuxkla2VruSzud5/Fg7\nbc/Ozs6Zt8w7Hp/PhzHGGNOeN9wBGGOMiUyWIIwxxgRkCcIYY0xAliCMMcYEZAnCGGNMQJYgjDHG\nBBQd7gB6moiMALYD691JUUAjcLuq/std5pfAVlV9qJPt3AKsVdXnA8w7sr6ItAJZqlrWjRhnA19X\n1etEZBbwY1X9fLDrd7HtrwH/C2wClgPb3DiPfB7/9+/mtu8AilX1f9tNHwn8QVUv6+b2fgJcC7yq\nqtd0Z92+TkTuBs4C/q2qt/hN/xpwG7AD8OFcxFUDN6nqhyLyc+B6oBDw4PyGdwA/UtWt7jbeAvKB\ncnez0UAs8Ou238Bxxn4q8FdVnXK82+qBWFKBp1X1s10s1/684HH/v11V73c/08vAZnd6NFAF/EpV\nX3G34b/vwfluUtz3/1EPfZ4HgPWq+qcO5p8H/D+c73M9zu+4uifeO5B+lyBctao6s+2FiOQDr4tI\ntao+rao/D2IbnwE2BprRbv1juZFkMjDM3dYqoEeSg+urwM2q+u920/0/z5H37yEjgXHHsN7VwJWq\n+n4PxtJXXAsMV9X9Aea9o6oXtL0QkUXAUyKS5056VFW/5zf/yzjH90T3ZOEDfqiqT/stMwtYJiJP\nqWpND8QfKTdQZQBzgly2/XlhKFAgIivcSdvazZ8KLBGRC1S1bZn2+z4dWC8iS1T11c7eXEQm4Bzv\nPwswbzxwJzCPT5JY+2WygPuAk1R1h4j8FvgdTtIKif6aII6iqntE5GfATcDTInI/sEFV/+SWBi7E\nKWWUAlcBlwCzgd+LSAtwEc6BOBp4AchtWx/nSuT/icgc9+9bVPVF90rwMlU9H45cGV4GXAf8EkgV\nkX8AD+JejblXQ3cC04FW4BWck32riNQBv8W56szFufK5zf9zisifgLnASBHJdrdTANT5fZ5E//dX\n1a+LyPnAT4AYoJZPrlZTgMXAVOAA0AIUt3tPL3AvMFREXlbVz4nIRcDP3P1RhXOyWtFuvUeBPOAf\n7pXZdUAZIMDdwL9wrqQnu3G97sbVKiKX4pSSaoGXgP9R1ZiO9rmqni8iMTg/poU4pco1wPdUtVpE\ndgIPAJ8FhgOPq+qP3W1cDfwAaAZKgP9yP1uRqv7UXeZLwCWqemm7zzgJuAPIdL/PP7qluXfcRV4W\nkW+r6jI69zowGEgPNNPd5leALwL3uJM97RYbg1MSaWgX45luXFPd12nATmAUcApwM87+zwEebH9y\n8/8ttX/tnoD/irNPY3BOrr8VkSh3v8wHmnBKQFepam27bV+Cc1y2uP9uUtX32n2u+4BEEVkNzFLV\noBOXqu4Xka04FzelAeavF5HbgRtx9m0guUACcDjQTBGJAy7HuSBI5JPvp73r3c+yu5OQzwI+UtUd\n7uu7gXWEMEEMpDaIdcBRRWL3iuwGYI6qzgWWAnNV9S5gJU6x/Vl38QRVnaKqNwfY9jZVnQV8Bfin\niGS609sfrD5VLcQ5wbyrql9vt9wdQIlbdJ8NTAPaiq5xOCelk3EOuN+KSKz/xlX1B35xtyUPX7vP\n85D/+4vIWODXwOfcz/BNnKvVBNyTsKpOwCnlSPsPrqqtwDXAdjc5jMc5cC9W1RnAz4FnRSS53Xpf\nAPYDX1TVx93JZao6WVXvBP4MrFTVOcBMIBv4gYjkAv/AOSHPwTnh+R/Hn9rn7v//DTSp6mw3rgM4\nCbdNkqouBE4GvisiI0RkmrvMWao6HXgO+B+ck95VbnIE58d/t/+buifBZ4HbVHUacC7wGxGZ576P\nBzgtiOQAzndS0EU1Zvvj+/cislpEdorIQZyLoM+qarP/Su5Vb5KItF05Xwm8oKoVOCfGr7q/jZOA\nm0UkI4h42/wL+If7Pc0DzhSRy9xtnaaq0915O3AuQtq7FbjOff9bgNMCLHMVbsmgO8kBQEROwkmc\nyztZrP1+/YK7X1VESoDbgWtVdWWA7d+EU9U7D+diZLaqBkwQqvpdVX2YTyd2f8OBvX6vC4GU9r+t\nnjQgShAuH84Vp799wFpgjYi8DLysqm/4zff/stpfufj7G4CqbhSRjTg/gGNxDs5VFaraJCJ/w0lg\nt7rzn3PnrXaTQxJOyae9jg6yQNPPxLkKel1E2uY3AyfgXFHf4L5niYg8HWD99k4HXlPV3e56b4pI\nETALeLuLmN71+3sRMEdE2tom4nG+w5OBdaqq7vS/Ar8KIq5FQJqInOW+jgEO+c1/1o13v4gcwikx\nnga80lYNpKq3ty0sIjuA89wr0CGq+lq79xsHxLVdYKjqARF5Euc7bjshdfQ9LXSviMGpa94MXNrB\nsm3aH983qepT7sXKSzhtR+s6WPd+nJLRapwTbttFyQXAIreENMGdltRFHAC4JdVTgUEi8n9+604H\nfg80i8hyYAnwVPsSpusR4BkReRF4lU9+B8eqraTR1nZTjHOBss+9UAqk/X59VFW/JyLROMfeZJyS\nfiCtOCUfn/v38fISuGqvpQe2HdBAShBzgQ3+E9wrjtPc+tkzgD+LyBuqemOA9TtrCPL/8qNwis0+\njj4BHHW134H2B4AX50TWpq7d8p1dbQQrCnhdVa9sm+CWrNrqxv3f46irz0621/4gbv85OuK/j73A\n5W2JwK1+A1jQSUyd7fMo4AZVXeJuLxEn6bQJtG+b8fssIhIPjHBjugv4OrCFwNUGx7MfjmqDCNIc\nnJLVUVS1VES+gFPX/q6qPhlg3fuAVW6VZ5qqvuvunzXAUziJ+z6cqtb2x1xH+zzK/f8kVW0AcJNV\nnarWish0nIuhzwCPicht7atMVfUWEbkP5yLmv3BKgTM5dke1QQRpDu3OG25szSLyXWAVTsL7ToBl\n/ihOx47PA3e61Zx/V9X7ux86AHtwSiNt8oDDqtr+2O0x/bWK6aiDWETGAT8F/tBu+lQRKQA+VtXf\n4VRrTHNnNxPcjxmcgxe3mN5WZC0GJotIrHu1cb7f8h1tewnugebWXV6LU+0VSHeTg/97+v/9OnCW\niIj7vufiFKvjcXp1fF1EPCIyCKeaoqttvw6cLU7PJkTkMzgHcmfF+ECW4NT9t+2L53HqWj8ATnBP\nMODue1dn+3wJ8B0RiXGrhv4B/KaLGN4EzhCRwe7rb+G0YwD8B5iBc2V/X4B1NwNNbntMW4PopXT8\nfR4zEfk6TpvBE4Hmq+pOnGrEP7tVh+3n7wdWAH/HaXMCpwSZAvxUVV/EKU3F8smJv00xTnVoWyPq\nKe42q4APcUsj4jTmLgMuFKcnzuvAB+r0iHuQT353bZ8pym0bSnKrZb4NjHdPsv6aA8TUka5+M+3P\nG3NxvvO/BFpYVZtw2s6+6VZHBlqmUVUfUtVTcDpldFRSCcZSYJ6IjHFffxO35Bsq/bUEEe9XRPfh\nXB3+WN3uau60tkaox3CunqpxipLfdZd5HviDW5XTUb1229+j3fdrBa5Q1XIRWYpTpaI4V+Nv8kk9\n64fA/7lVDrf7bet7wB0isgHnhPsKTpe29u8Z6HVX0/0/z/vAr0XkSVW9VESuBR51c0QzcL57lfcL\nnOqzj4EiOuhdgVPP6hORD1X1RBH5Nk5ngCicfbrIPWF0Fmv7uG8A/uLui2jcKgZVbRGRy4F73Sox\n/6u7zvb5r3Cu9NbgXBitBX7YwXu3HR8Fbj3yEhHx4bRbXO3OaxKR/wA5gdoG3CvMi3C+z1/inMR+\noarv+L/HMbpCRBa4f3vcz3uaqrZVNwba9h9werj9FKfht717cRJMW1Jdj9MhQ0XkMLAN53sey9HV\nmncAD4vIx8AunH3e5kvAX0VkPc7x/LCqPuIm6HNwSjXVOJ0TvuEfjPs93wD8W0SacKpRrnL3+/nA\nN1V1Ec53skZENuFUP34fp93tFwE+Y1f7vO133LZsOU6vo4KOVlDVZSLyEE7nkgUdLecuu4nA+77D\nGN3ajXvdNpZiEbkKeNJNlNtxvtOQ8dhw36Yvc6stilW1V0vDIpKEk4y+raof9eZ7G9NbQlaCcIv4\n9+H0kW+7Sed5v/k34tThFrmTvqnujT7GdFOvXuW4Dd2PAIstOZj+LJRVTF/G6bL5VXG6xq3BqeZo\nMxP4iqquCWEMpp9T1VKCr4PuqfdcinNvgzH9WigTxON80mjmwenZ428WTr/qIcCLqvpbjDHGRIyQ\n1duqaq2q1ohzN+4TfLpx5hGcHgKnAwvc3jPGGGMiREh7MYnIcJx+1H9V1cfazb5NVSvd5V7E6TL4\nUmfb8/l8Po+nJ7r+G2PMgHJMJ85QNlIPxul7fr2qvtluXipOF7fxOF1QP0OAm3za83g8FBcH6i3Z\nN2Rnp1j8YdSX4+/LsYPFH27Z2SnHtF4oSxA34wwudos4A+X5cPpaJ6nqYhG5GXgLqMe5k7ej29WN\nMcaEQcgShKp+H+emlY7mPww8HKr3N8YYc3z661AbxhhjjpMlCGOMMQFZgjDGGBOQJQhjjDEBWYIw\nxhgTkCUIY4wxAVmCMMYYE5AlCGOMMQFZgjDGGBOQJQhjjDEBWYIwxhgTkCUIY4wxAVmCMMYYE5Al\nCGOMMQFZgjDGGBOQJQhjjDEBWYIwxhgTkCUIY4wxAVmCMMYYE5AlCGOMMQFZgjDGGBOQJQhjjDEB\nWYIwxhgTkCUIY4wxAVmCMMYYE5AlCGOMMQFFhzsAY/o6n89HVVVlt9ZJSUnF4/GEKCJjeoYlCGOO\nU1VVJa8u30ZCYlJQy9fV1nDmvLGkpqaFODJjjo8lCGN6QEJiEolJKeEOw5geZW0QxhhjArIEYYwx\nJiBLEMYYYwKyBGGMMSYgSxDGGGMCsgRhjDEmIEsQxhhjAgrZfRAiEg3cB4wEYoFfq+rzfvPPB24B\nmoD7VXVxqGIxxhjTfaEsQXwZKFHVhcC5wF/bZrjJ40/AGcBpwLUikhPCWIwxxnRTKBPE4zglBAAP\nTkmhzQRgq6pWqmoT8B5wSghjMcYY000hq2JS1VoAEUkBngB+4jc7Fajwe10F2MA0xhgTQUI6FpOI\nDAeeAv6qqo/5zarESRJtUoDyYLaZnd23x7ux+MMrFPHHxraSnFRGUnJ8UMt7aSQrK4W0tO7FYvs+\nvPp6/McilI3Ug4ElwPWq+ma72R8DY0UkHagFFgK/D2a7xcVVPRpnb8rOTrH4wyhU8VdWVlFd00Ar\n9UEtX1vTQElJFY2Nwdfw2r4Pr/4Q/7EIZQniZiAduEVEfgb4gHuBJFVdLCI/AJbitE8sVtUDIYzF\nGGNMN4WyDeL7wPc7mf8i8GKo3t8YY8zxsRvljDHGBGQJwhhjTECWIIwxxgRkCcIYY0xAliCMMcYE\nZAnCGGNMQJYgjDHGBGQJwhhjTECWIIwxxgRkCcIYY0xAliCMMcYEZAnCGGNMQJYgjDHGBGQJwhhj\nTECWIIwxxgRkCcIYY0xAliCMMcYEZAnCGGNMQJYgjDHGBGQJwhhjTECWIIwxxgRkCcIYY0xAliCM\nMcYEZAnCGGNMQJYgjDHGBGQJwhhjTECWIIwxxgRkCcIYY0xAliCMMcYEFB3uAIwZaHw+H1VVld1a\nJysrOUTRGNMxSxDG9LK62hreXl1GekZm0MtfmZWCFfhNb7MEYUwYxCckkpiUEu4wjOmUXZIYY4wJ\nyBKEMcaYgKyKyQwIPp+PiooKKiurgl4nJSUVj8cTwqiMiWyWIMyAUFVVyZIP9tLqC+6Qr6ut4cx5\nY0lNTQtxZMZELksQZsBITEyildhwh2FMnxHyBCEi84Dfqurp7abfCHwdKHInfVNVt4Y6HmOMMcEJ\naYIQkZuArwDVAWbPBL6iqmtCGYMxxphjE+peTNuAizuYNwu4WUTeFZH/DnEcxoREc0srdQ0tNDS1\n0tjUgs/nC3dIxvSYoEoQIvIScD/wrKo2BrtxVX1aREZ0MPsR4E6gEnhGRM5V1ZeC3bYx4VBcXse6\nbSXonnL2l9ZwqKyOVr+kEBPtJSUxhszUePJyksnNSCQm2nqTm74p2Cqm3wFfBX4vIi8CD6jqiuN8\n79tUtRLA3eYMoMsEkZ3dt+8+tfjDIza2FXaUkZIcH9TyXhrJykohLS2F2vom3lxVyJIPd7Fz/ydj\nKCXFR3NCfjqJcV7KKurweKOprGmkorqBssoGthZWEB3lYVz+IKafkM2gVOe962pi8XpjuhUL9N19\n38bi73uCShCq+jbwtogkAJcBT4pIJbAYuFtVG7rYxFGdyUUkFSgQkfFAHfAZ4B/BxFJcHHw/9kiT\nnZ1i8YdJ2/0PVdX1QS1fW9PAzj1lvLdpO2+t3U9DYwtRXg9Tx2QyfWwWk0dnkJkaj8fjobKygvc2\nHDgydEarz0dJeR2FxTXsOlDFpp1lbNpZRv7gZGZJNg01jXi9LcQlBB8L2LEfTv0h/mMRdCO1iJyG\n0+B8FvAy8ChwJvAccHYXq/vcbVwJJKnqYhG5GXgLqAdeV9VXuhu8MaHQ2NzChl2VPPfBQRqbWxmU\nEse58/JZOG0oaclxXa7v9XjIGZRIzqBEpp+Qxd5D1WzcWcaeQ9UUFtcwOieGE4Ym9sInMeb4BNsG\nsRvYgdMO8R1VrXOnvwWs7GxdVd0NzHf/fsRv+sPAw8cUtTEh4PP52LG/ktVbiqlraCE1MYbLTx/L\nwmlDj7kdwevxMCI3hfzByew6UMUqLWbbwUYOVbRwWkI6g1K6TjjGhEuwJYjPAFWqWiQiCSIyVlW3\nqWorTndVY/q0yppG3i84SNHhOqK8HiaOSOG/zh5LVsagHtm+x+Nh1NBU8nKSWbZ2F3tKmnjpg93M\nHp/DuOFpNqSHiUjBXhadB7RVAeUAz4vItaEJyZje0+rzsXFnGc8v20XR4TryBydz4SmjmJifQmwI\neh/FRHuZnJ/A7LFJREd5Wb7pEMs3HaK11brHmsgTbAniWmAeOFVGIjILWA7cE6rATN92LE9N6+3B\n8cqrG3h/w0FKKuqJj41iwcTBjMh1GvNqa4JrQD5Wuemx5A8bzJur97FlbwWVNU2cOmMocTFRIX1f\nY7oj2AQRA/j3VGrEbXg2JpCqqkpeXb6NhMSkoJbvzcHxWn0+Nu0sY+22UlpbfYzMTWHuxBziY3t3\naLLkhBjOmZfPe+sPsLeomqUf7eWM2XkkxNkQaSYyBHskPgO8ISKP4ySGS3F6LxnToYTEpIh7alpN\nfRPvrT/AobI64mOjOHHSYPIHhy/GmGgvp80YykcfF6F7ynll+R7OnDOc5ISYsMVkTJugKllV9cfA\n7YAAY4DbVfWnoQzMmJ6262ANzy/bxaGyOobnJHPBgpFhTQ5tPB4PcyfkMGV0BlW1TbyyfA/VtU3h\nDsuYbo3F9DHwOE5pokxEFoYmJGN6Vn1jM/9+YxdvrS2ipcXHiZMGc9qMob1epdQZj8fDjHHZzBiX\nRW19M0tX7KWm3pKECa9g74O4Ezgf2O432YfT/dWYiLX7YBV/e7aAQ4fryEiN5ZSpwd3sFi5TRmfS\n2upj3bZSln60l3Pm5Yc7JDOABXsJdRYgbTfIGRPpfD4fb6zex2NvbKW5xcfp0weTl5OAxxu5yaHN\n1DGZtLT6KNhRxmsrC1k4uWfuxTCmu4JNEDtoN56SMZGqpr6J+1/azOotxSQnxHDNoomMzI5m7Y4y\nWsMdXBA8Hg8zTsiisamFLXsr+ODjMi7+TCuhH53fmKMFmyDKgE0i8j7O2EkAqOrVIYnKmGO0fV8F\nf3t2I6WV9cjwdK69YBKDUuKorKwId2jd4vF4mDtxMHUNLewtqubvz27mmvMm2R3XplcFmyBe4ZM7\nqY2JOK0+H0s+2sNTb++gtdXHBSeP5IKTR+H19t0Tqtfj4ZRpQ1iyfDcfFBSROyiJ808eFe6wzAAS\n7HDf/xSRkcAkYAkwXFV3hjIwY4JVVdvI4hc+ZsOOUtKSY7n2/ElMGNE/6u2jo7zMnzCIDzaX8/S7\nO8nLTmbGuOxwh2UGiKAqNUXkCuB54DYgA/hARL4cysCMCcb2/RX88oEVbNhRyuTRGfzyqrn9Jjm0\niYuN4sYrphAb4+WeFzZRWBzoEe/G9LxgW71+jDNkd5WqFuE8/e3mkEVlTBecXkqF/Pah1RyuauDi\nhaP5/uXTSE2KDXdoITEiN5lrzptIQ2MLt/9nPdV1do+ECb1gE0SLqh55nJKqHoA+0SHE9EMNjS3c\n+8ImHlq6hYS4aH5wxXTOnz8Sbz9vwJ09PocLTh5JSUU9dz29geYW+wma0Aq2kXqjiHwHiBGR6cC3\ngbWhC8uYwA6W1XLn0xvYV1zDmKGpXHfRZDJSg3u2c39wwYJRFBbXsHpLMY++vpUvnyXhDsn0Y8GW\nIK4HhuE8P/o+oBInSRjTa1ZpEf/7wAr2Fdfw2Zl5/PhLMwdUcgCnZ9M1iyaQl53EG6v38cHGg+EO\nyfRjwfZiqsFpc7B2B9PrWlpbefLtHbyyfA+xMV6uPX8iJ07KDXdYYRMfG831l0zhl/ev4MFXlJG5\nKQzJDG5YdWO6I9ixmFr59PMfDqhqXs+HZMwnauub+NuzGynYWcbgjESuv3gyednJ4Q4r7AYPSuSq\ncydw9zMF3PVMAT/96mx72JDpccGWII5URYlIDHARcFKogjIDT6An0BWV17P4pW0UlTcwMT+Vr5w5\nmoS4liN3Rff2E+gizZzxOejMYbyxeh8PL93C1edNCHdIpp/p9njHqtoEPCEiPwlBPGaAqqut4e3V\nZaRnZAJw8HA9yzcfpqnZx7i8JCbkJ7FqS9FRy/fWE+gi2RWfOYHt+yt5b8MBJD+dk6cMCXdIph8J\ntorpq34vPTh3VFtHbNOj4hMSSUhMZvPuclZuLsPj8XDylFzGDBvYSaAzMdFerrtoMr+8fwX/WuK0\nRwyzKjjTQ4LtxXS6379T3WlXhCQiM2D5fD5WbC5ixeYi4mKjOHvecEsOQchJT+DqcyfQ2NzKXc8U\n0NDYEu6QTD8RbBvEVaEOxAxsLa0+1u2q4WB5E+nJsXx2Vh5J9lzmoM2SbM6YncdrKwt5+LUtXH2u\ntUeY4xdsFdNOPt2LCZzqJp+qju7RqMyAUt/YzPKttZTXtJCbkchpM4YSaz1yuu3y08aydW8F760/\nwMSRgzhx4sDtCmx6RrBVTP8GHgBOBubiDNr3PnAaTrWTMcekqraRlz/cQ3lNC0MzYvns7GGWHI5R\nTLSXb104ibjYKB58RSk6XBvukEwfF2wvprNVdbbf69tEZJWq7g5FUGZgKKus57WVhdQ3tjB6cCwT\n8hKJ8tpT047H4IxEvnLWOBa/8DF3PrWeGy4RoqO63qd9uctwoC7SXenLn7c3BZsgPCJyhqq+BiAi\ni3CG2zDmmBQdruP1VYU0Nbcyd0IOWQn19oPtIZPzExmWEcPe4lrueWELU0d33tDf17sMV1VV8ury\nbSQkBnc3eV//vL0p2ARxLfCgiOTitEVsBr4WsqhMv7a/pIa31uyjpdXHgqlDGD00lZKiA+EOq1+Z\nMz6TyrWlbNlXw/Dc9H7f9TUhMYnEpJRwh9HvBNuLaRUwSUSygDp3bCZjum3PoSreWeskg1OnDyV/\ncGT+qLtTbVFVVRm4C0cYRUd5WTh9KC9/sIdlGw6yaP5IEuO7fV+sGeCC7cU0AlgMjAROEZHngatV\ndVfoQjP9zY79lSzbcIAor4fTZgxjaFbkDjDX/s7uzpSVHCIxKZXE5MhKdpmp8cySbFZsLuK9DQc4\nc3aeVeOZbgn2kuLvwO+B3wGHgEeAB4GFIYrL9DPbCit4v+AgMdFePjsrj5xBCeEOqUvxCYlBVVvU\n1kTuI0DHj0jnQGkNhcU1FOwoY8qYrhOeMW2C7TKSpapLAVTVp6r3AqmhC8v0J9v3OckhNsbLWXOH\n94nk0F94PB7mTxlCYlw0a7eVUHS4LtwhmT4k2BJEnYjk4da0isgCoCFkUZl+Y8f+CpZtcJLDmXOG\nkznAHvDTE3w+HxUVFTQ1BXc9175NJD42igXThvDqR3t5d91+Fp080oYGN0EJNkHcCLwAjBGRtUAG\ncHnIojL9wp6iWlZoObHRXs6cbcnhWNXV1rDkg+3ExgXXEylQm0huRiJTxmSyfnspHxQc5NTpQ609\nwnQp2AQxGJgDjAOigM2q2hiyqEyft3prGR9pOTHRXs6YM5zMNEsOxyMhIYm4hOAawTtqE5k6JpND\nZbXsOVTN1r0VjMtP78kQTT8UbIK4VVVfBDZ29w1EZB7wW1U9vd3084FbcIYNv19VF3d32yYyrdhc\nxEOv7SQ6ysOZc/LIsuQQEbxeDwumDeH5ZbtYsbmIrPT4AfdMb9M9wSaI7SJyH7AcONLKpaoPdraS\niNwEfAWobjc9GvgTMMvd3jIReU5Viz69FdOXrNxcxN+f3UhMtJf5EzPISgtNg3R3h1eoqqrEF2k3\nK4RBUnwMC6YM4Y3V+3hrzX7Omz8i3CGZCNZpghCRYaq6DyjFGbn1RL/ZPpyurp3ZBlwM/Kvd9AnA\nVlWtdN/nPeAU4MngQzeRZpUW8/fnNhIT4+Vbi8ayr7gqZO/VnfsUwKmXz87JIS4hLmQx9RV5OclM\nGZ3Bhh1lvLf+ACeKdUg0gXVVgngemKmqV4nID1X1j93ZuKo+7d5k114qUOH3ugqwgVH6sDVbivnb\nswVER3v5weenMTjVE9IEAcHfpwCRfa9COEw7IYvSynr2FdfwcYKXU6aGOyITibpKEP7dHL4EdCtB\ndKKSo++jSAHKg1kxOzuy7lbtrv4Y/0cbD3L3swXERHv5xTdOYtLoTCoqKkhOKiMpObg67rqaWLze\nGFJCuDwQku331dg/d9IoHn99K5v2VFF4uJFTx4T22AzVsR8b29qtY81LI1lZKaSldS+evv7bPRZd\nJQj/Stvj6RPXft2PgbEikg7U4tyR/ftgNlQc4qvSUMrOTul38a/dVsKdT20gKsrDDZdNJSclluLi\nKiorq6icte3LAAAcBUlEQVSuaaCV+qC2XVPTiNfbQlxC6JZPSYmhqrrnt9+XY184bQgvL9/NnU9t\nIis1iZxBiUG9R3eF8tjv7rFWW9NASUkVjY3BDy3fH367x6I7g+8fTwtf2w12V4rINaraDPwAWAos\nAxarqg3n2cccSQ5eD9+/bBqSPyjcIZluykyLZ+bYdOoaWvjrUwU0NNnzrM0nuipBTBKRHe7fw/z+\nDvpRo+5Dhea7fz/iN/1F4MXuh2wiwVHJ4fJpjB9hyaGvGjk4kdjoaN7fVMLiFzZx3UWT8dpNdIau\nE8S4XonC9CmWHPqfS04ZTmlVM6u0mKff2cGlp44Jd0gmAnSaIOyRoqY9Sw79U3SUl+svmcKvH1zJ\nix/sZvCgRBZMHRLusEyY2QOATdA+2nTQkkM/lpwQww2XTyMpPpp/vrKZgh2l4Q7JhJklCBOUtdtK\n+M0DH1ly6OdyMxL57qVT8Xg83Pl0ATsP2KPnBzJLEKZLbdVKXo+Hb5w3lqGDvFRWVnT6LxIfw2mC\nM254Ot+6cBKNzS38+fF1HCi1JwwPVPaQWtOpFZuLuOe5jXi9MH9iKofKqjlU1vVdyZH6GE4TnJnj\nsvnq2cI/X1FufWQN//3FmQzOCM09EiZyWYIwHXp3/X4eeHkzcTFRfOPcMVTVN9FKbFDr2tAWfd+p\n04fR0NTKo69v5dZH1vDjL80kJ92eBjiQWBWTCei1lXu5/6XNJMZFc9OVMxgz1EoCA9FZc4bz+dPH\ncriqgd89vNqqmwYYSxDmU154fxf/fm0rqUmx/PhLMxk1xEb7HMjOmZfP5aeP4XBVA795aLU1XA8g\nliDMET6fjyfe2sZT7+wgMzWOm780k7zs4B5zafq3z80bwdfOEWrqm7j1kTUU7LQusAOBtUEYAFp9\nPh5+dQtvrt7H4IxEbvrCdHvamDnKqdOHkRQfwz3Pb+TPj6/jwvl5nDo1J6hnW2dl2YVGX2QJwtDS\n2sr9L23m/YKD5GUn8cMvzCAtKbjGaDOwzB6fQ6y3ibuf28IzywpZs7WUGWPTiI7quDKirraGK7NS\nsAqLvscSxADX1NzKPc9tZNWWYkYPTeX7l08jOSEm3GGZCDYyN5kzZubwoVawu6iOsupmFkwdQrb1\ncOp3LKUPYA1NLdzx5HpWbSlmfH46P7xiuiUHE5SEuCjOmTecSaMyqKpt4pXle1ilRTQ223Dh/YmV\nIPoJn8/n3L0cpLqGFu5bspOthRVMHZPJty+aTGxMVAgjNP1NlNfLLMlmWFYSyzYcYOPOw2zfV8mM\ncVmMHppGlNeGDO/rLEH0E1VVlby6fBsJiUldLtvQ1Mo764upqG1h9vgcrj1/Yqd1yMZ0JjczkQtP\nGcWmnWVs2FHGBwWHWLe1lPEjBzF2WPe7SHf3YseGdQkdSxD9SEJiEolJnd/QVlvfzLtr9lJR28K8\n8Zl844JJeO1Kzxyn6CgvU8dmMSYvjU07D7O1sJzVWswaLSYrLZb4hATyc9IZPjiZuC5Kqt252AEb\n1iWULEEMINW1Tby6ci9VtU2MHZrEFaePsORgelRSfAxzJuQwbWwm2/ZVsPtgFcXl9Ty0dDsAHg+k\nJ8eRlhR7pL3LB+Dz4XP+o7GpifLqRmKim4iJ9hIb4yUtKZb0lDiy0xKIiz06wdiwLqFjCaKXNDY2\nsmPXHsrKghuqIMrrIW/YsB57/4rqRl5duZfa+mamjMlk3JBYe6ykCZnYmCgmjsxg4sgMSsvKGT50\nENsKq9lzsIqyqgYKi2tobmntYiuNn5ri8cCwrCRGDU1lxOAUu8AJMUsQveRgUTF7D7dS1xBcL4+a\n8mKGDR0a1E1IXSmvbmDpR3upb2xh5rgsJo/OpLam6ri3a0wwEuKiWDA1l7njP2nn8vl8NDU7CcI5\nxD20Heo11ZUsKzhIfEIyTS2tNDS2UF7dQFllA4XF1RQW11BYXMOG5FLmThhsJ7EQsn3bi6Kio4lu\nCa4x2BvVM19NRXXjkeQwd2IO4/PtQT+md/l8PioqKmhqCu7Yr66uAh94vR7ivFHExUSRmhRL/uAU\npp+QRXl1A5t2HWZbYQVLV+xl6KAYpo0Mrr3CdI8liH6sqraRpSuc5DBngiUHEx51tTUs+WA7sXHB\nDbfRVaNzenIc8yfnIsPTWb7pEPsP11PTUMWZaZkkxtsprSfZ3uynqmubWPrRXuoampkt2Uxo94jQ\nY+lK6LO+hOYYJSQkEZcQXC+jYBudM9PiOXtePm+v2klhaRMvfbibM2bnkZ4cdzyhGj+WIPqhmrom\nlq7YS019MzPGZTFxVManlqmrreHt1WWkZ2QGtc2ykkNk5+QQl2A/PhM5orwepuTHkxwfzeZ9dby2\nspBzT8wnMd5GBOgJliD6mdr6Zpau2Et1XRPTxmYyZXTHCSA+IbHL+yaObNe6EpoI5fF4GDsknoSk\nJNZsKeG1lYWcMy/fRgboAXb7bD9S39jCqyuc+xymjM5g6pjgSgfG9AeTR2Ug+emUVzfy1tr9tPqs\nSvR4WYLoJ6rrmnhnQykVNY1MHDmI6Sdk9UgXWWP6Co/Hw5wJOeTlJHOwtJaCHWXhDqnPsyqmfqC6\nrom7nttKZW0z40ekM0uyLTmYoPWnsY+8Hg8nT87l+fd3sW5bCUMyE20Y8uNgCaKPq61v4o+PrWV/\naR2jcxOZMz64J3wZ0+ZYOixE8thHcbFRLJgyhKUr9vLuugMsOnkEsdHWHnEsLEH0YXUNzfz58XXs\nPljFvPGZ5GXFWnIwx6S/dVjIzUxkyugMNuwoY7UWc+Kk3HCH1CdZG0QfVd/YzF+eWMf2/ZWcNCmX\nK04bYcnBGD/TxmaRlhzLlr0VlJTXhTucPskSRB/U0NTC7f9Zz9bCCuZOyOHq88bboGXGtOP1epg3\ncTAAH246ZL2ajoEliD6mqbmFvz65ns17ypk1LptrFk0kymtfozGB5GYkMnpoKmWVDWzZUx7ucPoc\nO7P0IU3Nrdz5dAEbdx1m+tgsvnnhJHsSnDFdmCXZxER7WbO1hPrG5nCH06fY2aWPaG5p5W/PFrB+\neymTR2dw3UWTLTkYE4SEuGimjc2kqbmVDdvt3ojusDNMH9DS2so9z21kzdYSJowYxHcunkJMtH11\nxgRL8tNJTohB9xympt5KEcEKaTdXEfEAdwHTgHrgGlXd4Tf/NmA+0Pb0mgtV1Z5k46e11cfiFz5m\npRYjw9P53mVTbYwZY7opyutl+glZvLf+AAW7qjh7Trgj6htCfR/ERUCcqs4XkXnAn9xpbWYCZ6uq\nlfva8fl8lFeU8+ibe1ihpYzKTeLqc0bSUFdNQ4Aee5F8d6sxkWDUkBQ27Spjb3Ede4trmZSaFu6Q\nIl6oE8QC4BUAVV0uIrPbZrilixOAe0QkF/iHqt4f4nj6jNraav7yRAF7S5sYlBLD1FEprNhc1OHy\nkX53qzHh5vF4mCXZvLqikJeX72PSmCHhDinihboiOxWo8HvdLCJt75kE3A58GTgH+LaITA5xPH2C\nz+fj4/2t7C1tIiM1jrPmjiAtLY3EpJQO/8Un2CMXjenKkMwkslJj2bSnkp0Hgh9/aqAKdQmiEvC/\npPWqaqv7dy1wu6rWA4jIGzhtFQWdbTA7u29eIVfXJrG/qo6U5PhOl/P5fCxbt5+9Za0MSonh4lPH\nEh/X9ddUVxOL1xvT5faPZ3kgpNvvq/H35dh7a3mInPhnSQZLVhzklRV7+dnXTwxqHei7557jEeoE\nsQxYBPxHRE4ENvjNGwc8KiIz3DgWAA90tcHi4r7Zhl1WVgN4qaqu73AZn8/H6i0lbNxZRlIcLJiY\nQVNTM01NXfe6qKlpxOttIS6h4+0f7/IpKTGdxt/b8URK/H059t5aPpLiT47zMHpIMis2HWLFhn2M\nzE3tcp3s7JQ+e+6BY09uoa5iehpoEJFlwB+BG0XkRhFZpKqbgYeA5cCbwD9V9eMQxxPR1m0rZePO\nMlITY5gzKpo4661kTI/zeDycM8dpf3juvV3hDSbChbQEoao+4Lp2k7f4zf8D8IdQxtBXFOwoZf32\nUlISYzhr7nCqSveGOyRj+q0ThqUwNi+NtdtK2H2wihG5A6/6KBh2t1UE0D3lrN5SQmJ8NGfOGW4P\nXDcmxDweDxeePAqA55btDHM0kcsSRJjt2F/B8k2HiI+N4szZw0lOsORgTG+YOHIQY4alsmZrCXsO\n9d32hVCyBBFGew5VsWzDQWKjvZwxO4+05Nhwh2TMgOHxeLhwQVspYld4g4lQliDCZH9JDe+sPUCU\n18NnZ+WRkRpcFz1jTM+ZNDKDMUNTWb2l2EoRAViCCIOSinreWrMPPHD6zGFkD7KHqhsTDh6Phwvc\nUsTzVor4FEsQvayqtpE3VhXS3OJj4bQhDMm0O6CNCafJozIYNSSVVVuK2VsU+c/b7k2WIHpRfWMz\nr6/aR31jC3Mn5JA/2LrWGRNuR7dFWI8mf5YgeklTSytLlhdSWdPIpFGDGD9iULhDMsa4pox2SxFa\nTKGVIo6wBNELWn0+nl52gENldYzMTWHmuOxwh2SM8eOUIkYC8Nz7u8IaSySxBNELHn9jG5v2VDMk\nM5GTp+bi8XjCHZIxpp0pozMZNSSFlZuLKCy2UgRYggi5d9btZ+mKvWSnxXLWvDyivLbLjYlEHo+H\nC062Hk3+7GwVQlv2lvOvJUpyQgxfPH2YDb5nTISbOiaTkblOKWKflSIsQYRKaUU9dz29AZ8Prrto\nMoPsLmljIl7bfRE+4Hlri7AEEQoNTS3c8dR6KmubuPKME5hgPZaM6TOmjclkRG4KKz4uYl9JTbjD\nCStLED3M5/Nx/0sfs+dQNQunDeUzM4eFOyRjTDe0jfTqA559b2DfF2EJooe99OFuPvq4iBPy0vjy\nWeOsx5IxfdC0sZmMGpLKys1F7Ng/cJ9dbQmiB63dWsJTb+8gIzWO6y+eQnSU7V5j+iKPx8PnTx8D\nwBNvbsPn84U5ovCwM1gP2VdSwz3PbyQm2st3L5lKapI1ShvTl0n+IKaOyUT3lrPy40PhDicsLEH0\ngJr6Ju54cj31jS1cfd4Ee3yhMf3EZaeNweOBB17cRGvrwCtFWII4Ts0trdz9TAFFh+s476QRzJ0w\nONwhGWN6SF52MidPGcKeg1W8vXZfuMPpdZYgjtMjr29l067DTB+bxcULR4c7HGNMD7t04WgS46N5\n6p0dVNY2hjucXmUJ4ji8vqqQN1fvY3hOMtdeMBGv9Vgypt9JS47jS2ePp6a+mSff2h7ucHqVJYhj\nVLCzlEde20pqYgzfu3Qq8bHR4Q7JGBMi5508irzsJN5df4Dt+yrCHU6vsQRxDA6U1nD3Mxvxej18\n59KpZKbZ86SN6c+iorx8+SwB4J+vKE3NrWGOqHdYguim6rombntiPXUNzVx17njGDksLd0jGmF4w\nbng6p04fSmFx9YB58pwliG5oaGrhjifXU1Rex6L5IzhpUm64QzLG9KLPnz6WrLR4XvpwN9sK+39V\nkyWIIDW3tPK3ZwrYWljB3Ak5XHSK9VgyZqBJiIvmmkUTwQeLX9xEfWNzuEMKKUsQQWj1+Xjg5c2s\n217KpFEZXLPIeiwZM1CNG57O2fPyKTpcx30vbe7Xw3BYguhCq8/Hg69s5v2Cg4waksr1F0+2MZaM\nGeAuWTiacXlprNxcxEsf7g53OCFjZ7pOtLY6Q3e/s+4AIwancOPnp1l3VmMM0VFerrt4CoNS4njq\n7R2s314S7pBCwhJEB5qaW7n3hU0s23CQUUNS+NGV00lOiAl3WMaYCJGWFMt3LplCVJSXu54pYMve\n8nCH1OMsQQRQXdfEHx9dw/JNhxg7LI0fXjGDpHhLDsaYo40aksp1F06ipcXHX55Yx/b9/atnkyWI\ndgqLq/n1gyvZUljB7PE5/OgL00mMt2olY0xgM8Zlc+0Fk2hoauFPj61D9xwOd0g9xhKEy+fz8eaa\nffzqnys5dLiOc08cwbcunERsTFS4QzPGRLg543P4xqKJNDa18IdH1/abkV/t0hgoKa/j369tZe22\nEpLio/nWBZOYMS473GEZY/qQEyflkpYcx11Pb+Cfryi7D1Zx+eljSYjru6fZvht5D6hvbGbpR3t5\n8cPdNDW3Mj4/nWsWTSQj1cZWMsZ034QRg7jlv+Zwx5PreWvtfjbsKOUrZ49n6pjMcId2TAZkgqiu\na+KNVYW8tqqQ6rom0pJi+fznxnLixMF47AY4Y8xxyElP4Gdfm83z7+/m5Q9385cn1jFx5CDOnz+S\nccPT+9Q5JqQJQkQ8wF3ANKAeuEZVd/jN/wZwLdAE/FpVXwxVLA1NLWzaVcYHBQdZu62E5hYfSfHR\nXHDySM6em9+ni4HGmMgSEx3FJQtHM3d8Do++4TxUbNOuw4waksr8ybnMmZBDamLkP7c+1GfFi4A4\nVZ0vIvOAP7nTEJHBwHeBmUAi8J6ILFXVpuN9U5/PR2VNI7sPVbP7YCWb95SztbCC5hZniN6hWUks\nnDqEhdOH2o1vxpiQyctJ5kdfmMH2/RW8+P5u1m0vYeeBSh55bSsjh6QwPn8Q44ankZedzKCUuIgr\nXYT67LgAeAVAVZeLyGy/eXOB91S1GagUka3AVGBVMBveeaCS3YeqqKlroqaumeq6Jqrrmiirqqe4\nvI66hpajls/PSWbSqAzmThhM/uDkiPsijDH915ihaXzvsqmUVzfw0cdFrNh8iJ37q9ixv5KXPnSW\nSYiLJjM1jrTkONKSYklLjiUtMZb4uGiiozxER3mJifYSE+UFD+CD9OQ48nKSQxZ3qBNEKuB/50iz\niHhVtTXAvGogqIcrtPp8/P6RNdQ3tnxqXmy0l+z0BHLyExiek8yI3BRGD00jLSm8xbnoKC91VSXU\n1QU3+mNLQzV1tYnOgRCE+roavN5oamuqQrZ8dDS0tAYXUG/EEynx9+XYe2v5SIq/rrYmqOVCIT05\njrPmDOesOcOpa2hma2EFuw5UUlhczb6SGkorGygsDj4+D3DbDaeEbJSHUCeISiDF73Vbcmibl+o3\nLwXo6l51T3a2s7knfrOop2LsFdnZKUybOi7cYRhjjlHbuacn5ecN6vFt9qRQ3yi3DDgXQEROBDb4\nzfsIWCAisSKSBowHCkIcjzHGmCB5QjmWuV8vpqnupKuA84CtqvqCiHwd+CZOSenXqvpMyIIxxhjT\nLSFNEMYYY/ouG4vJGGNMQJYgjDHGBGQJwhhjTEARfRuxiMQDDwE5ON1iv6aqpe2WuRXnhrwo4F5V\nXdzrgR4dT8QML3Isgoj/RuAKwAe8pKq/CkugHegqfr9lXgSeUdV7ej/KjgWx/z8H/Axn/69W1e+E\nJdAOBBH/j4AvAC3AbyKxY4o76sNvVfX0dtPPB27B+e3eH+5zTUc6if9K4AagGVivqt/ualuRXoK4\nDueDLAT+hfPlHCEipwFjVHU+cArwY7fLbDgdGV4EuBlneBHgqOFFTgLOAX4jIpH2qLrO4h8FXKmq\nJwLzgbNFZHJ4wuxQh/H7+T8gUjugd7b/k4FbgfPc+btEJNKGCe0s/jSc438ecDbwl7BE2AkRuQm4\nF4hrNz0a57OcAZwGXCsiOb0eYBc6iT8e+F/gVFVdAKSLSJc3k0V6gjgyVAfwMs6X4+994Gq/116c\n7B5ORw0vAgQcXkRVK4G24UUiSWfx78FJbKiqD4jBuUqMJJ3Fj4hcinP1+nLvhxaUzuKfj3Mv0Z9E\n5B3gUPsSdQToLP4aYBfOTbHJON9DpNkGXBxg+gSc7vmV7nhx7+FclEaajuJvAOaraoP7OpogfrsR\nkyBE5GoR2SAi691/Gzh6OI4qjr7zGlVtVNUKN7s/APxdVWt7NfBPCzi8SAfzgh5epBd1GL+qtqhq\nGYCI/B6nimNbGGLsTIfxi8gk4IvAzwl6EJNe19nxk4Vz9XoT8DngRhEZ27vhdamz+AEKgU3ASuD2\n3gwsGKr6NE4VTHvtP1cVkffb7TB+VfWpajGAiHwXSFLV17raXsS0QajqfcB9/tNE5Ek+Gaoj4FAc\nIpIO/Ad4Q1VvDXWcQejp4UV6W2fxIyJxON9TBdBlHWYYdBb/V4GhwBvASKBBRHap6tLeDbFTncVf\nCqzw+6G/A0zHuWqMFJ3F/zkgFxiBk6CXisgyVV3ZyzEei77w2+2U2z50K3ACcEkw60RMguhA21Ad\nK93/3/Wf6darvQ78QVUf6f3wAloGLAL+08HwIv8nIrFAApE5vEhn8QM8B7ymqr/v9ciC02H8qvrj\ntr9F5OfAgQhLDtD5/l8FTBaRDJwT1olARDWy03n8h4G6tiH9RaQcSO/9EIPSvoT5MTDWvSCtBRYC\nkfobgMAl5Htw9v9FwW4k0hPE3cA/ReRdnDq0LwKIyO+AJ3DqO0cB3xCRa3F6dlylqrvDFC/A08CZ\nIrLMfX2V2/OnbXiR23HqLz3A/6hqY7gC7UCH8eMcL6cAMSJyLs7+vtmta44Une7/MMYVrK6On5uB\npTj7/jFV3RSuQDvQVfwrReRDnPaH94Kp5ggTHxzp+ZOkqotF5Ac4+94DLFbVA+EMsAtHxY9zcXEV\n8K6IvOnOv01Vn+1sIzbUhjHGmIAippHaGGNMZLEEYYwxJiBLEMYYYwKyBGGMMSYgSxDGGGMCsgRh\njDEmoEi/D8KYbhOREcAWYKM7KRbYh3OPzH4ReQsYhjNcQtt4Uj9T1Zfd9d8E8tz5Hpw7aLcDX2q7\ni/kY4zoV+EX7UTaNiVRWgjD91T5Vnen+m4xzo9Ad7jwfcLU7bwrwLeBfIjLeb/22+TNUdQxOsvhB\nD8RlNx6ZPsNKEGageAc43+/1kaEIVHWViDwGXAP8yJ185OJJRFJwBsr70H+D7vMBvqGqF7ivvwOM\nwXlewz9wSilDgXdU9Wvt1n0T+LmqvuOWeN5S1VHuENJ/xynBtOLcqf6GiHwW+J077TDOsOtlx7ND\njOmKlSBMv+c+c+MKnCFOOlKAMzZWm3tFZI2I7Ac+wBli4c/t1nkZmOn3DJIv4Dzg6jxgjaqeDIwD\n5ovIjC7CbCtZ3Ab8Q1XnABcC97jPgfgJ8E1VnQs8D8zsYnvGHDcrQZj+apiIrMYpKcTiDJR4cyfL\n+4A6v9dfV9V3ReQknNGCX1LVo4ZRVtVmEXkauFREXgUyVHUVsEpE5ojIDTjPEcjAef5BMM4ARETa\nntQXBYwGngWeEZFngGcjeAwj049YgjD91T5V7c5V9lSc5xS08QCo6gcicgdOG8VU/6HPXQ8Bv8JJ\nAg/DkfH2L8GpKnoVmMynR9f0+U3zf6pgFPAZVS13t5WL82Cg9SLyPM5IqbeKyBOq+ptufD5jus2q\nmEx/FfQDgURkLnAp0NEzhv8EJOI0Zh/FHcl2KPBl3ASBUwr4u6o+6sYxHefE768EmOT+7f8EsNeB\n6924JuIMl53ojoCaqqq341R1WRWTCTlLEKa/6qq30GIRWe1WQ/0R+Lyq7g20rjsk+0+Bn7sN1u09\nBlSp6i739V+AX4jISuCvOM9IGNVunVuB691l/J8f/D3gRBFZBzyC07W2Bqd67AF3+W/gPBXPmJCy\n4b6NMcYEZCUIY4wxAVmCMMYYE5AlCGOMMQFZgjDGGBOQJQhjjDEBWYIwxhgTkCUIY4wxAVmCMMYY\nE9D/B4PdtpovWOI6AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11ca4db00>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(PDR_mam_lessthan7['PDR'], bins = xticks)  # Flexibly plot a univariate distribution against observations.\n",
    "plt.title('Distribution fitted to frequency of PDR values s.t. PDR < 1.0')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "print('There are ' + str(len(PDR_mam_lessthan7['PDR'])) + ' total number of samples with PDR values < 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/local/Library/Frameworks/Python.framework/Versions/3.4/lib/python3.4/site-packages/statsmodels/nonparametric/kdetools.py:20: VisibleDeprecationWarning: using a non-integer number instead of an integer will result in an error in the future\n",
      "  y = X[:m/2+1] + np.r_[0,X[m/2+1:],0]*1j\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 2820 total number of samples with PDR values < 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYgAAAEZCAYAAACNebLAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1142f1940>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(PDR_mam_lessthan8['PDR'], bins = xticks)  # Flexibly plot a univariate distribution against observations.\n",
    "plt.title('Distribution fitted to frequency of PDR values s.t. PDR < 1.0')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "print('There are ' + str(len(PDR_mam_lessthan8['PDR'])) + ' total number of samples with PDR values < 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/local/Library/Frameworks/Python.framework/Versions/3.4/lib/python3.4/site-packages/statsmodels/nonparametric/kdetools.py:20: VisibleDeprecationWarning: using a non-integer number instead of an integer will result in an error in the future\n",
      "  y = X[:m/2+1] + np.r_[0,X[m/2+1:],0]*1j\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 1143 total number of samples with PDR values < 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYgAAAEZCAYAAACNebLAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11597d4e0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(PDR_mam_lessthan9['PDR'], bins = xticks)  # Flexibly plot a univariate distribution against observations.\n",
    "plt.title('Distribution fitted to frequency of PDR values s.t. PDR < 1.0')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "print('There are ' + str(len(PDR_mam_lessthan9['PDR'])) + ' total number of samples with PDR values < 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/local/Library/Frameworks/Python.framework/Versions/3.4/lib/python3.4/site-packages/statsmodels/nonparametric/kdetools.py:20: VisibleDeprecationWarning: using a non-integer number instead of an integer will result in an error in the future\n",
      "  y = X[:m/2+1] + np.r_[0,X[m/2+1:],0]*1j\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 3 total number of samples with PDR values < 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAX8AAAEZCAYAAAB/6SUgAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\ngg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x116d8c0f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(PDR_mam_lessthan10['PDR'], bins = xticks)  # Only 3\n",
    "plt.title('Distribution fitted to frequency of PDR values s.t. PDR < 1.0')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "print('There are ' + str(len(PDR_mam_lessthan10['PDR'])) + ' total number of samples with PDR values < 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/local/Library/Frameworks/Python.framework/Versions/3.4/lib/python3.4/site-packages/statsmodels/nonparametric/kdetools.py:20: VisibleDeprecationWarning: using a non-integer number instead of an integer will result in an error in the future\n",
      "  y = X[:m/2+1] + np.r_[0,X[m/2+1:],0]*1j\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 2190 total number of samples with PDR values < 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYgAAAEZCAYAAACNebLAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x115eb4ef0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(PDR_mam_lessthan11['PDR'], bins = xticks)  # Flexibly plot a univariate distribution against observations.\n",
    "plt.title('Distribution fitted to frequency of PDR values s.t. PDR < 1.0')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "print('There are ' + str(len(PDR_mam_lessthan11['PDR'])) + ' total number of samples with PDR values < 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/local/Library/Frameworks/Python.framework/Versions/3.4/lib/python3.4/site-packages/statsmodels/nonparametric/kdetools.py:20: VisibleDeprecationWarning: using a non-integer number instead of an integer will result in an error in the future\n",
      "  y = X[:m/2+1] + np.r_[0,X[m/2+1:],0]*1j\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 1054 total number of samples with PDR values < 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYgAAAEZCAYAAACNebLAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nkjRkQEiShgwISdKQASFJGjIgJElDXwAaBcS3uBU3owAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11b53f710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(PDR_mam_lessthan12['PDR'], bins = xticks)  # Flexibly plot a univariate distribution against observations.\n",
    "plt.title('Distribution fitted to frequency of PDR values s.t. PDR < 1.0')\n",
    "plt.xlabel('PDR values')\n",
    "plt.ylabel('Frequency')\n",
    "print('There are ' + str(len(PDR_mam_lessthan12['PDR'])) + ' total number of samples with PDR values < 1.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/local/Library/Frameworks/Python.framework/Versions/3.4/lib/python3.4/site-packages/statsmodels/nonparametric/kdetools.py:20: VisibleDeprecationWarning: using a non-integer number instead of an integer will result in an error in the future\n",
      "  y = X[:m/2+1] + np.r_[0,X[m/2+1:],0]*1j\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 872 total number of samples with PDR values < 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYgAAAEZCAYAAACNebLAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nslLaOX/WCLKzcyirbmTDzgrWbC1jzdbjrNl6nJEFGS