Data_Analysis_Notebook_5_Figure3_coinitiations.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import pandas\n",
    "import numpy\n",
    "import seaborn\n",
    "import scipy\n",
    "import matplotlib.pyplot as plt\n",
    "seaborn.set_context(font_scale=1.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Anova 4161 vs 3824 (Number of coinitiations Stem1): F_onewayResult(statistic=10.62618595825427, pvalue=0.002646212440671163)\n"
     ]
    },
    {
     "data": {
      "image/png": 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TDz/8kI8++ojx48fz1VdfMWXKFKZPn17lOjk5BVXOD1fROe8Tu2+xf7o0oTXl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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xc8eab70>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data=pandas.read_excel('/Users/arjun/Google Drive/HDCTF/Data/170914_ABS44_PIN1_phenotyping/Number_coinitiations.xlsx')\n",
    "\n",
    "fig = seaborn.FacetGrid(data=data,size=5)\n",
    "fig = fig.map(seaborn.boxplot,'Nem#','Number_coinitations',palette='Greys')\n",
    "fig = fig.map(seaborn.swarmplot,'Nem#','Number_coinitations','Nem#',palette='YlOrRd')\n",
    "\n",
    "# looking at anova\n",
    "\n",
    "anova = scipy.stats.f_oneway(Stem1[Stem1['Nem#']=='ABS44_PIN1_4161']['Number_coinitations'],Stem1[Stem1['Nem#']=='ABS44_3824']['Number_coinitations'])\n",
    "print('Anova 4161 vs 3824 (Number of coinitiations Stem1): '+str(anova))\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}