CA_ADP_2021_Compare.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "dbc84907",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9002"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import csv,math\n",
    "from IPython.display import display, HTML\n",
    "import tabulate\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "# In this notebook we compare 2021 submitted groupoings as provided by NKH for California\n",
    "# with optimized groupings done by Meals Count\n",
    "# Comparison is Like-for-Like, as in only schools that were submitted to CEP will be grouped\n",
    "\n",
    "# First, we load ADP data\n",
    "sites = {}\n",
    "for row in csv.DictReader(open(\"working/CA ADP Data 2.csv\")):\n",
    "    sites[row[\"Site_ID\"]] = {\n",
    "        \"district_code\":row[\"Sponsor_ID\"],\n",
    "        \"school_code\": row[\"Site_ID\"],\n",
    "        \"district_name\":row[\"Sponsor_Name\"],\n",
    "        \"school_name\":row[\"Site_Name\"],\n",
    "        \"daily_breakfast_served\":float(row[\"Breakfast_ADP_F\"]) + float(row[\"Breakfast_ADP_R\"]) + float(row[\"Breakfast_ADP_P\"]),\n",
    "        \"daily_lunch_served\":float(row[\"Lunch_ADP_F\"]) + float(row[\"Lunch_ADP_R\"]) + float(row[\"Lunch_ADP_P\"]),\n",
    "        \"adp_enroll\": row[\"Enrollment_Total\"] and float(row[\"Enrollment_Total\"]) or None\n",
    "    }\n",
    "\n",
    "len(sites)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "1b8d4799",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(289, 8713)"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "missing_adp_enroll = len([s for s in sites.values() if s['adp_enroll'] == None])\n",
    "missing_adp_enroll,len(sites) - missing_adp_enroll"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "9b4b88d0",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('3185 of 9002 Grouped', '35.381026 %')"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Then Load Grouping Data and enrollment/ISP data\n",
    "for row in csv.reader(open(\"working/CA_CEP_2021.csv\")):\n",
    "    if row[2] in sites and row[5]: # skip if no ISP\n",
    "        site = sites[row[2]]\n",
    "        site[\"total_enrolled\"] = int(row[13].replace(\",\",\"\"))\n",
    "        site[\"total_eligible\"] = int(float(row[5].replace(\"%\",\"\"))/100 * site[\"total_enrolled\"])\n",
    "        site[\"grouping\"] = row[10] or row[12] or None\n",
    "        if site[\"adp_enroll\"]:\n",
    "            # If we have enrollment matching the ADP data, use this to create an ADP% and apply to our grouping \n",
    "            # enrollment. Otherwise we are stuck with what we have\n",
    "            site[\"daily_breakfast_served\"] = site[\"daily_breakfast_served\"]/site[\"adp_enroll\"] * site[\"total_enrolled\"]\n",
    "            site[\"daily_lunch_served\"] = site[\"daily_lunch_served\"]/site[\"adp_enroll\"] * site[\"total_enrolled\"]\n",
    "\n",
    "schools = [s for s in sites.values() if s.get(\"grouping\",False)]\n",
    "\"%i of %i Grouped\" % (len(schools),len(sites)),\"%f %%\" % (len(schools)/len(sites) * 100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "9eb93374",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Sites Per District')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# chart % of sites per district submitted to CEP vs # of overall sites per district\n",
    "\n",
    "overall_districts = {}\n",
    "for site in sites.values():\n",
    "    overall_districts.setdefault(site[\"district_code\"],[])\n",
    "    overall_districts[site[\"district_code\"]].append(site)\n",
    "\n",
    "fig,ax = plt.subplots()\n",
    "ax.scatter(\n",
    "    [int(len([s for s in d if s.get(\"grouping\",False)])/len(d) * 100) for d in overall_districts.values()], # % submitted to CEP per district\n",
    "    [len(d) for d in overall_districts.values()], # overall sites per district\n",
    ")\n",
    "ax.set_xlabel('% submitted to CEP')\n",
    "ax.set_ylabel('Sites Per District')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "6da96027",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'ISP %')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax = plt.subplots()\n",
    "ax.scatter(\n",
    "    [(s[\"daily_lunch_served\"]/s[\"total_enrolled\"] * 100) for s in schools], # Lunch ADP %\n",
    "    [(s[\"total_eligible\"]/s[\"total_enrolled\"] * 100.0) for s in schools], # ISP\n",
    ")\n",
    "ax.set_xlabel('Luch ADP %')\n",
    "ax.set_ylabel('ISP %')\n",
    "#plt.hist([(s[\"daily_lunch_served\"]/s[\"total_enrolled\"] * 100) for s in schools], 20, label='Lunch ADP')\n",
    "#plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "26d15049",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(73.12374789734832, 46.46360890861966)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "upsidedown = [s for s in schools if s[\"total_enrolled\"] <= s[\"daily_lunch_served\"]]\n",
    "\"%i of %i schools have more lunches than enrolled\" % (len(upsidedown),len(schools))\n",
    "\n",
    "sum([(s[\"daily_lunch_served\"]/s[\"total_enrolled\"] * 100) for s in schools])/len(schools),sum([(s[\"daily_breakfast_served\"]/s[\"total_enrolled\"] * 100) for s in schools])/len(schools)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "8c4b2ff9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'132 of 3185 schools have more lunches than enrolled and have mismatched enrollment data'"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "upsidedown_mismatch = [s for s in schools if s[\"total_enrolled\"] <= s[\"daily_lunch_served\"] and s[\"adp_enroll\"] == None]\n",
    "\"%i of %i schools have more lunches than enrolled and have mismatched enrollment data\" % (len(upsidedown),len(schools))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "43623a20",
   "metadata": {},
   "outputs": [],
   "source": [
    "annual = lambda x: \"${:,} / yr\".format(int(x * 180))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "c8994608",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(254, 3185)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Build our CEP District for San Diego as a test case\n",
    "from strategies.base import CEPSchool,CEPDistrict\n",
    "\n",
    "districts = {}\n",
    "for s in schools:\n",
    "    school = CEPSchool(s)\n",
    "    if s[\"district_code\"] not in districts:\n",
    "        districts[s[\"district_code\"]] = CEPDistrict(s[\"district_name\"],s[\"district_code\"])\n",
    "    districts[s[\"district_code\"]].add_school(school)\n",
    "districts = list(districts.values())\n",
    "districts.sort(key=lambda d:len(d.schools))\n",
    "\n",
    "len(districts),len(schools)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "7f63a37c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('San Diego Unified School District',\n",
       " 133,\n",
       " '3768338',\n",
       " 0.44208626655530364,\n",
       " 67048)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "district = [d for d in districts if \"San Diego\" in d.name][0]\n",
    "district.name,len(district.schools),district.code,district.overall_isp,district.total_enrolled"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "d36d7e67",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<tbody>\n",
       "<tr><td>School                            </td><td>Total Enrolled</td><td>ISP%  </td><td>Breakfast</td><td>Lunch</td><td>Orig Grouping</td><td>%Lunch ADP</td></tr>\n",
       "<tr><td>WALKER ELEMENTARY                 </td><td>434           </td><td>50.46%</td><td>424      </td><td>390  </td><td>G1           </td><td>89.86%    </td></tr>\n",
       "<tr><td>Madison High                      </td><td>932           </td><td>37.77%</td><td>309      </td><td>308  </td><td>G2           </td><td>33.05%    </td></tr>\n",
       "<tr><td>ANGIER ELEMENTARY                 </td><td>419           </td><td>22.43%</td><td>70       </td><td>220  </td><td>G2           </td><td>52.51%    </td></tr>\n",
       "<tr><td>King-Chavez Academy of Excellence </td><td>277           </td><td>48.74%</td><td>254      </td><td>248  </td><td>G3           </td><td>89.53%    </td></tr>\n",
       "<tr><td>CROWN POINT ELEMENTARY            </td><td>273           </td><td>28.21%</td><td>77       </td><td>151  </td><td>G2           </td><td>55.31%    </td></tr>\n",
       "<tr><td>EDISON ELEMENTARY                 </td><td>366           </td><td>69.40%</td><td>385      </td><td>383  </td><td>G1           </td><td>104.64%   </td></tr>\n",
       "<tr><td>EMERSON/BANDINI ELEMENTARY        </td><td>411           </td><td>72.02%</td><td>261      </td><td>241  </td><td>G2           </td><td>58.64%    </td></tr>\n",
       "<tr><td>HORTON ELEMENTARY                 </td><td>389           </td><td>80.46%</td><td>391      </td><td>382  </td><td>G1           </td><td>98.20%    </td></tr>\n",
       "<tr><td>OCEAN BEACH ELEMENTARY            </td><td>401           </td><td>29.93%</td><td>69       </td><td>251  </td><td>G2           </td><td>62.59%    </td></tr>\n",
       "<tr><td>McGill School of Success          </td><td>142           </td><td>42.96%</td><td>134      </td><td>112  </td><td>G3           </td><td>78.87%    </td></tr>\n",
       "<tr><td>GARFIELD ELEMENTARY               </td><td>253           </td><td>41.90%</td><td>300      </td><td>256  </td><td>G2           </td><td>101.19%   </td></tr>\n",
       "<tr><td>Mann Middle                       </td><td>824           </td><td>69.66%</td><td>315      </td><td>441  </td><td>G2           </td><td>53.52%    </td></tr>\n",
       "<tr><td>Marston Middle                    </td><td>673           </td><td>24.52%</td><td>48       </td><td>144  </td><td>G2           </td><td>21.40%    </td></tr>\n",
       "<tr><td>MARSHALL ELEMENTARY               </td><td>398           </td><td>64.57%</td><td>412      </td><td>382  </td><td>G2           </td><td>95.98%    </td></tr>\n",
       "<tr><td>ROLANDO PARK ELEMENTARY           </td><td>253           </td><td>47.83%</td><td>266      </td><td>267  </td><td>G1           </td><td>105.53%   </td></tr>\n",
       "<tr><td>Standley Middle                   </td><td>900           </td><td>20.78%</td><td>55       </td><td>255  </td><td>G2           </td><td>28.33%    </td></tr>\n",
       "<tr><td>Knox Middle                       </td><td>574           </td><td>78.05%</td><td>430      </td><td>268  </td><td>G1           </td><td>46.69%    </td></tr>\n",
       "<tr><td>SANDBURG ELEMENTARY               </td><td>512           </td><td>23.05%</td><td>50       </td><td>256  </td><td>G2           </td><td>50.00%    </td></tr>\n",
       "<tr><td>CHAVEZ ELEMENTARY                 </td><td>466           </td><td>56.01%</td><td>456      </td><td>478  </td><td>G1           </td><td>102.58%   </td></tr>\n",
       "<tr><td>BURBANK ELEMENTARY                </td><td>365           </td><td>55.62%</td><td>364      </td><td>344  </td><td>G1           </td><td>94.25%    </td></tr>\n",
       "<tr><td>Oak Park Elementary               </td><td>535           </td><td>44.86%</td><td>517      </td><td>503  </td><td>G1           </td><td>94.02%    </td></tr>\n",
       "<tr><td>Bethune K-8                       </td><td>564           </td><td>31.03%</td><td>74       </td><td>262  </td><td>G2           </td><td>46.45%    </td></tr>\n",
       "<tr><td>Keiller Leadership Academy        </td><td>593           </td><td>38.79%</td><td>109      </td><td>374  </td><td>G3           </td><td>63.07%    </td></tr>\n",
       "<tr><td>TAFT MIDDLE                       </td><td>430           </td><td>38.14%</td><td>65       </td><td>170  </td><td>G2           </td><td>39.53%    </td></tr>\n",
       "<tr><td>Sequoia Elementary                </td><td>185           </td><td>39.46%</td><td>27       </td><td>85   </td><td>G2           </td><td>45.95%    </td></tr>\n",
       "<tr><td>HANCOCK ELEMENTARY                </td><td>655           </td><td>3.36% </td><td>130      </td><td>408  </td><td>G2           </td><td>62.29%    </td></tr>\n",
       "<tr><td>Millennial Tech Middle            </td><td>402           </td><td>76.37%</td><td>79       </td><td>232  </td><td>G2           </td><td>57.71%    </td></tr>\n",
       "<tr><td>CHEROKEE POINT ELEMENTARY         </td><td>306           </td><td>57.19%</td><td>335      </td><td>335  </td><td>G1           </td><td>109.48%   </td></tr>\n",
       "<tr><td>GARFIELD HIGH                     </td><td>224           </td><td>71.88%</td><td>38       </td><td>74   </td><td>G2           </td><td>33.04%    </td></tr>\n",
       "<tr><td>Fay Elementary                    </td><td>517           </td><td>62.48%</td><td>529      </td><td>506  </td><td>G1           </td><td>97.87%    </td></tr>\n",
       "<tr><td>WEGEFORTH ELEMENTARY              </td><td>195           </td><td>34.36%</td><td>85       </td><td>175  </td><td>G1           </td><td>89.74%    </td></tr>\n",
       "<tr><td>Pacific View Leadership Elementary</td><td>237           </td><td>45.99%</td><td>246      </td><td>212  </td><td>G1           </td><td>89.45%    </td></tr>\n",
       "<tr><td>Gompers Preparatory Academy       </td><td>1337          </td><td>46.00%</td><td>301      </td><td>905  </td><td>G3           </td><td>67.69%    </td></tr>\n",
       "<tr><td>HARDY ELEMENTARY                  </td><td>345           </td><td>30.72%</td><td>57       </td><td>181  </td><td>G1           </td><td>52.46%    </td></tr>\n",
       "<tr><td>E3 Civic High                     </td><td>425           </td><td>42.12%</td><td>149      </td><td>273  </td><td>G3           </td><td>64.24%    </td></tr>\n",
       "<tr><td>San Diego Business/Leadership     </td><td>523           </td><td>58.32%</td><td>761      </td><td>943  </td><td>G1           </td><td>180.31%   </td></tr>\n",
       "<tr><td>NORMAL HEIGHTS ELEMENTARY         </td><td>261           </td><td>47.13%</td><td>281      </td><td>230  </td><td>G1           </td><td>88.12%    </td></tr>\n",
       "<tr><td>ENCANTO ELEMENTARY                </td><td>484           </td><td>80.58%</td><td>449      </td><td>462  </td><td>G2           </td><td>95.45%    </td></tr>\n",
       "<tr><td>CADMAN ELEMENTARY                 </td><td>151           </td><td>29.14%</td><td>142      </td><td>101  </td><td>G2           </td><td>66.89%    </td></tr>\n",
       "<tr><td>San Diego Metro Career and Tech   </td><td>137           </td><td>29.93%</td><td>0        </td><td>0    </td><td>G1           </td><td>0.00%     </td></tr>\n",
       "<tr><td>MIRA MESA HIGH                    </td><td>2337          </td><td>21.35%</td><td>132      </td><td>600  </td><td>G2           </td><td>25.67%    </td></tr>\n",
       "<tr><td>JEFFERSON ELEMENTARY              </td><td>390           </td><td>37.95%</td><td>420      </td><td>303  </td><td>G1           </td><td>77.69%    </td></tr>\n",
       "<tr><td>Whittier K-12                     </td><td>48            </td><td>31.25%</td><td>44       </td><td>42   </td><td>G1           </td><td>87.50%    </td></tr>\n",
       "<tr><td>GAGE ELEMENTARY                   </td><td>662           </td><td>21.75%</td><td>35       </td><td>253  </td><td>G2           </td><td>38.22%    </td></tr>\n",
       "<tr><td>PERRY ELEMENTARY                  </td><td>392           </td><td>18.37%</td><td>97       </td><td>274  </td><td>G2           </td><td>69.90%    </td></tr>\n",
       "<tr><td>ADAMS ELEMENTARY                  </td><td>291           </td><td>48.80%</td><td>690      </td><td>508  </td><td>G1           </td><td>174.57%   </td></tr>\n",
       "<tr><td>Roosevelt International Middle    </td><td>825           </td><td>37.94%</td><td>279      </td><td>252  </td><td>G2           </td><td>30.55%    </td></tr>\n",
       "<tr><td>IBARRA ELEMENTARY                 </td><td>421           </td><td>73.40%</td><td>438      </td><td>417  </td><td>G1           </td><td>99.05%    </td></tr>\n",
       "<tr><td>FARB MIDDLE                       </td><td>454           </td><td>15.42%</td><td>67       </td><td>254  </td><td>G2           </td><td>55.95%    </td></tr>\n",
       "<tr><td>HAGE ELEMENTARY                   </td><td>593           </td><td>17.54%</td><td>60       </td><td>286  </td><td>G2           </td><td>48.23%    </td></tr>\n",
       "<tr><td>Audubon K-8                       </td><td>442           </td><td>69.00%</td><td>422      </td><td>347  </td><td>G1           </td><td>78.51%    </td></tr>\n",
       "<tr><td>LANGUAGE ACADEMY                  </td><td>1022          </td><td>23.39%</td><td>94       </td><td>326  </td><td>G1           </td><td>31.90%    </td></tr>\n",
       "<tr><td>CARVER ELEMENTARY                 </td><td>184           </td><td>43.48%</td><td>173      </td><td>168  </td><td>G1           </td><td>91.30%    </td></tr>\n",
       "<tr><td>Health Sciences High              </td><td>615           </td><td>46.34%</td><td>23       </td><td>54   </td><td>G3           </td><td>8.78%     </td></tr>\n",
       "<tr><td>Rodriguez Elementary              </td><td>383           </td><td>64.23%</td><td>348      </td><td>351  </td><td>G2           </td><td>91.64%    </td></tr>\n",
       "<tr><td>FRANKLIN ELEMENTARY               </td><td>383           </td><td>37.08%</td><td>364      </td><td>282  </td><td>G1           </td><td>73.63%    </td></tr>\n",
       "<tr><td>BIRNEY ELEMENTARY                 </td><td>538           </td><td>23.61%</td><td>119      </td><td>330  </td><td>G2           </td><td>61.34%    </td></tr>\n",
       "<tr><td>Lincoln High                      </td><td>1399          </td><td>65.69%</td><td>496      </td><td>612  </td><td>G1           </td><td>43.75%    </td></tr>\n",
       "<tr><td>Montgomery Middle                 </td><td>419           </td><td>55.85%</td><td>166      </td><td>211  </td><td>G1           </td><td>50.36%    </td></tr>\n",
       "<tr><td>ALCOTT ELEMENTARY                 </td><td>196           </td><td>21.43%</td><td>59       </td><td>153  </td><td>G1           </td><td>78.06%    </td></tr>\n",
       "<tr><td>PORTER ELEMENTARY                 </td><td>656           </td><td>63.72%</td><td>331      </td><td>333  </td><td>G1           </td><td>50.76%    </td></tr>\n",
       "<tr><td>WEBSTER ELEMENTARY                </td><td>219           </td><td>72.15%</td><td>226      </td><td>203  </td><td>G2           </td><td>92.69%    </td></tr>\n",
       "<tr><td>Perkins K-8                       </td><td>419           </td><td>81.15%</td><td>411      </td><td>334  </td><td>G2           </td><td>79.71%    </td></tr>\n",
       "<tr><td>Creative Performing and Media Arts</td><td>825           </td><td>51.27%</td><td>347      </td><td>364  </td><td>G1           </td><td>44.12%    </td></tr>\n",
       "<tr><td>Harriet Tubman Village Charter    </td><td>414           </td><td>57.49%</td><td>371      </td><td>302  </td><td>G4           </td><td>72.95%    </td></tr>\n",
       "<tr><td>Sherman Elementary                </td><td>581           </td><td>59.21%</td><td>588      </td><td>540  </td><td>G1           </td><td>92.94%    </td></tr>\n",
       "<tr><td>Challenger Middle                 </td><td>894           </td><td>22.26%</td><td>36       </td><td>265  </td><td>G2           </td><td>29.64%    </td></tr>\n",
       "<tr><td>East Village High                 </td><td>127           </td><td>44.09%</td><td>25       </td><td>52   </td><td>G2           </td><td>40.94%    </td></tr>\n",
       "<tr><td>FLETCHER ELEMENTARY               </td><td>144           </td><td>41.67%</td><td>151      </td><td>142  </td><td>G2           </td><td>98.61%    </td></tr>\n",
       "<tr><td>CHESTERTON ELEMENTARY             </td><td>482           </td><td>18.46%</td><td>47       </td><td>287  </td><td>G2           </td><td>59.54%    </td></tr>\n",
       "<tr><td>LAFAYETTE ELEMENTARY              </td><td>254           </td><td>43.31%</td><td>109      </td><td>217  </td><td>G2           </td><td>85.43%    </td></tr>\n",
       "<tr><td>Wilson Middle                     </td><td>660           </td><td>64.55%</td><td>380      </td><td>314  </td><td>G2           </td><td>47.58%    </td></tr>\n",
       "<tr><td>Kearny College Connections        </td><td>353           </td><td>35.98%</td><td>177      </td><td>557  </td><td>G2           </td><td>157.79%   </td></tr>\n",
       "<tr><td>JOHNSON ELEMENTARY                </td><td>264           </td><td>61.74%</td><td>260      </td><td>252  </td><td>G2           </td><td>95.45%    </td></tr>\n",
       "<tr><td>Clairemont High                   </td><td>900           </td><td>25.00%</td><td>50       </td><td>205  </td><td>G2           </td><td>22.78%    </td></tr>\n",
       "<tr><td>WHITMAN ELEMENTARY                </td><td>106           </td><td>37.74%</td><td>37       </td><td>76   </td><td>G2           </td><td>71.70%    </td></tr>\n",
       "<tr><td>Linda Vista Elementary            </td><td>374           </td><td>56.42%</td><td>430      </td><td>450  </td><td>G1           </td><td>120.32%   </td></tr>\n",
       "<tr><td>MILLER ELEMENTARY                 </td><td>641           </td><td>3.59% </td><td>113      </td><td>359  </td><td>G2           </td><td>56.01%    </td></tr>\n",
       "<tr><td>De Portola Middle                 </td><td>746           </td><td>16.49%</td><td>53       </td><td>213  </td><td>G2           </td><td>28.55%    </td></tr>\n",
       "<tr><td>JONES ELEMENTARY                  </td><td>279           </td><td>17.56%</td><td>33       </td><td>144  </td><td>G2           </td><td>51.61%    </td></tr>\n",
       "<tr><td>Riley/New Dawn                    </td><td>155           </td><td>70.97%</td><td>106      </td><td>93   </td><td>G2           </td><td>60.00%    </td></tr>\n",
       "<tr><td>King-Chavez Community High        </td><td>310           </td><td>50.65%</td><td>62       </td><td>147  </td><td>G3           </td><td>47.42%    </td></tr>\n",
       "<tr><td>Hoover High                       </td><td>2147          </td><td>56.82%</td><td>763      </td><td>943  </td><td>G1           </td><td>43.92%    </td></tr>\n",
       "<tr><td>The O&#x27;Farrell Charter             </td><td>1929          </td><td>34.99%</td><td>1227     </td><td>1290 </td><td>G4           </td><td>66.87%    </td></tr>\n",
       "<tr><td>VALENCIA PARK ELEMENTARY          </td><td>438           </td><td>50.68%</td><td>452      </td><td>453  </td><td>G1           </td><td>103.42%   </td></tr>\n",
       "<tr><td>DEWEY ELEMENTARY                  </td><td>318           </td><td>17.61%</td><td>51       </td><td>194  </td><td>G1           </td><td>61.01%    </td></tr>\n",
       "<tr><td>FOSTER ELEMENTARY                 </td><td>395           </td><td>28.61%</td><td>37       </td><td>196  </td><td>G2           </td><td>49.62%    </td></tr>\n",
       "<tr><td>BOONE ELEMENTARY                  </td><td>378           </td><td>55.82%</td><td>357      </td><td>332  </td><td>G2           </td><td>87.83%    </td></tr>\n",
       "<tr><td>Bandini Elementary                </td><td>282           </td><td>60.64%</td><td>320      </td><td>227  </td><td>G1           </td><td>80.50%    </td></tr>\n",
       "<tr><td>Clark Middle                      </td><td>910           </td><td>64.18%</td><td>408      </td><td>538  </td><td>G2           </td><td>59.12%    </td></tr>\n",
       "<tr><td>ROSS ELEMENTARY                   </td><td>181           </td><td>43.65%</td><td>167      </td><td>164  </td><td>G2           </td><td>90.61%    </td></tr>\n",
       "<tr><td>San Diego SCPA                    </td><td>1313          </td><td>26.88%</td><td>68       </td><td>270  </td><td>G2           </td><td>20.56%    </td></tr>\n",
       "<tr><td>CENTRAL ELEMENTARY                </td><td>586           </td><td>64.85%</td><td>590      </td><td>572  </td><td>G1           </td><td>97.61%    </td></tr>\n",
       "<tr><td>CHOLLAS/MEAD ELEMENTARY           </td><td>546           </td><td>55.68%</td><td>605      </td><td>575  </td><td>G2           </td><td>105.31%   </td></tr>\n",
       "<tr><td>Holly Drive Leadership Academy    </td><td>128           </td><td>57.03%</td><td>135      </td><td>107  </td><td>G3           </td><td>83.59%    </td></tr>\n",
       "<tr><td>ZAMORANO ELEMENTARY               </td><td>955           </td><td>44.19%</td><td>903      </td><td>865  </td><td>G1           </td><td>90.58%    </td></tr>\n",
       "<tr><td>Mission Bay High                  </td><td>1187          </td><td>25.19%</td><td>97       </td><td>312  </td><td>G2           </td><td>26.28%    </td></tr>\n",
       "<tr><td>ROSA PARKS ELEMENTARY             </td><td>823           </td><td>69.99%</td><td>882      </td><td>842  </td><td>G1           </td><td>102.31%   </td></tr>\n",
       "<tr><td>HAMILTON ELEMENTARY               </td><td>451           </td><td>66.08%</td><td>457      </td><td>441  </td><td>G1           </td><td>97.78%    </td></tr>\n",
       "<tr><td>Lindbergh/Schweitzer Elementary   </td><td>269           </td><td>48.33%</td><td>368      </td><td>258  </td><td>G1           </td><td>95.91%    </td></tr>\n",
       "<tr><td>King-Chavez Primary Academy       </td><td>327           </td><td>47.71%</td><td>597      </td><td>588  </td><td>G3           </td><td>179.82%   </td></tr>\n",
       "<tr><td>Crawford High                     </td><td>1117          </td><td>63.12%</td><td>604      </td><td>472  </td><td>G2           </td><td>42.26%    </td></tr>\n",
       "<tr><td>Golden Hill K-8                   </td><td>408           </td><td>53.68%</td><td>400      </td><td>380  </td><td>G1           </td><td>93.14%    </td></tr>\n",
       "<tr><td>BAKER ELEMENTARY                  </td><td>392           </td><td>63.78%</td><td>379      </td><td>365  </td><td>G1           </td><td>93.11%    </td></tr>\n",
       "<tr><td>WASHINGTON ELEMENTARY             </td><td>279           </td><td>45.88%</td><td>265      </td><td>224  </td><td>G1           </td><td>80.29%    </td></tr>\n",
       "<tr><td>Joyner Elementary                 </td><td>467           </td><td>64.67%</td><td>464      </td><td>417  </td><td>G1           </td><td>89.29%    </td></tr>\n",
       "<tr><td>CARSON ELEMENTARY                 </td><td>373           </td><td>51.21%</td><td>384      </td><td>382  </td><td>G2           </td><td>102.41%   </td></tr>\n",
       "<tr><td>Twain High                        </td><td>251           </td><td>53.39%</td><td>31       </td><td>33   </td><td>G2           </td><td>13.15%    </td></tr>\n",
       "<tr><td>Bell Middle                       </td><td>783           </td><td>54.92%</td><td>433      </td><td>349  </td><td>G2           </td><td>44.57%    </td></tr>\n",
       "<tr><td>Lewis Middle                      </td><td>1042          </td><td>25.82%</td><td>52       </td><td>253  </td><td>G2           </td><td>24.28%    </td></tr>\n",
       "<tr><td>WANGENHEIM MIDDLE                 </td><td>818           </td><td>28.73%</td><td>50       </td><td>292  </td><td>G2           </td><td>35.70%    </td></tr>\n",
       "<tr><td>KIMBROUGH ELEMENTARY              </td><td>320           </td><td>72.50%</td><td>351      </td><td>307  </td><td>G1           </td><td>95.94%    </td></tr>\n",
       "<tr><td>BALBOA ELEMENTARY                 </td><td>441           </td><td>69.39%</td><td>430      </td><td>434  </td><td>G2           </td><td>98.41%    </td></tr>\n",
       "<tr><td>ROWAN ELEMENTARY                  </td><td>213           </td><td>37.56%</td><td>218      </td><td>210  </td><td>G1           </td><td>98.59%    </td></tr>\n",
       "<tr><td>Fulton K-8                        </td><td>315           </td><td>54.60%</td><td>345      </td><td>282  </td><td>G1           </td><td>89.52%    </td></tr>\n",
       "<tr><td>PERSHING MIDDLE                   </td><td>745           </td><td>19.33%</td><td>21       </td><td>156  </td><td>G2           </td><td>20.94%    </td></tr>\n",
       "<tr><td>ALBA                              </td><td>27            </td><td>55.56%</td><td>20       </td><td>30   </td><td>G2           </td><td>111.11%   </td></tr>\n",
       "<tr><td>Innovation Middle                 </td><td>434           </td><td>47.70%</td><td>192      </td><td>166  </td><td>G2           </td><td>38.25%    </td></tr>\n",
       "<tr><td>King-Chavez Preparatory Academy   </td><td>346           </td><td>49.13%</td><td>127      </td><td>281  </td><td>G3           </td><td>81.21%    </td></tr>\n",
       "<tr><td>EUCLID ELEMENTARY                 </td><td>447           </td><td>61.30%</td><td>479      </td><td>448  </td><td>G1           </td><td>100.22%   </td></tr>\n",
       "<tr><td>TOLER ELEMENTARY                  </td><td>219           </td><td>26.48%</td><td>68       </td><td>152  </td><td>G2           </td><td>69.41%    </td></tr>\n",
       "<tr><td>FIELD ELEMENTARY                  </td><td>294           </td><td>40.82%</td><td>311      </td><td>229  </td><td>G1           </td><td>77.89%    </td></tr>\n",
       "<tr><td>McKINLEY ELEMENTARY               </td><td>511           </td><td>17.03%</td><td>44       </td><td>188  </td><td>G2           </td><td>36.79%    </td></tr>\n",
       "<tr><td>Preuss School UCSD                </td><td>848           </td><td>54.25%</td><td>263      </td><td>460  </td><td>G3           </td><td>54.25%    </td></tr>\n",
       "<tr><td>PARADISE HILLS ELEMENTARY         </td><td>274           </td><td>42.34%</td><td>282      </td><td>252  </td><td>G1           </td><td>91.97%    </td></tr>\n",
       "<tr><td>CUBBERLEY ELEMENTARY              </td><td>155           </td><td>37.42%</td><td>29       </td><td>92   </td><td>G2           </td><td>59.35%    </td></tr>\n",
       "<tr><td>Darnall Charter                   </td><td>610           </td><td>52.46%</td><td>526      </td><td>517  </td><td>G3           </td><td>84.75%    </td></tr>\n",
       "<tr><td>CLAY ELEMENTARY                   </td><td>349           </td><td>52.15%</td><td>363      </td><td>293  </td><td>G1           </td><td>83.95%    </td></tr>\n",
       "<tr><td>America&#x27;s Finest Charter          </td><td>406           </td><td>67.00%</td><td>321      </td><td>358  </td><td>G3           </td><td>88.18%    </td></tr>\n",
       "<tr><td>John Muir Language Academy        </td><td>189           </td><td>39.68%</td><td>36       </td><td>104  </td><td>G2           </td><td>55.03%    </td></tr>\n",
       "<tr><td>FLORENCE ELEMENTARY               </td><td>228           </td><td>35.53%</td><td>113      </td><td>211  </td><td>G2           </td><td>92.54%    </td></tr>\n",
       "<tr><td>PENN ELEMENTARY                   </td><td>364           </td><td>36.54%</td><td>337      </td><td>287  </td><td>G1           </td><td>78.85%    </td></tr>\n",
       "<tr><td>FREESE ELEMENTARY                 </td><td>255           </td><td>62.75%</td><td>238      </td><td>219  </td><td>G1           </td><td>85.88%    </td></tr>\n",
       "</tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# View San Diego school data\n",
    "\n",
    "school_table = [('School','Total Enrolled','ISP%','Breakfast','Lunch','Orig Grouping','%Lunch ADP')] + \\\n",
    "            [ (\n",
    "                s.name,\n",
    "                s.total_enrolled,\n",
    "                ('%0.2f%%' % (s.isp*100.0)),\n",
    "                s.bfast_served,\n",
    "                s.lunch_served, \n",
    "                sites.get(s.code).get(\"grouping\"),\n",
    "                '%0.2f%%' % (s.lunch_served/s.total_enrolled * 100),\n",
    "            ) \n",
    "              for s in district.schools ]\n",
    "\n",
    "display(HTML(tabulate.tabulate(school_table,tablefmt='html')))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "dcd65c57",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Build two strategies: Custom Group to represent what was submitted, and NYCMODA for optimal\n",
    "from strategies.naive import CustomGroupsCEPStrategy\n",
    "\n",
    "# What was submitted to USDA in 2021\n",
    "orig_strategy = CustomGroupsCEPStrategy()\n",
    "orig_strategy.set_groups([('%s-%s'%(s[\"district_code\"],s[\"grouping\"]),s[\"school_code\"]) for s in schools])\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "985c1853",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       " 'GD513': 32324.44999999999,\n",
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       " '1964725': 65765.15000000001,\n",
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       " '3667819': 44760.11,\n",
       " '4469799': 40042.70999999999,\n",
       " '2065243': 65919.72000000003,\n",
       " '3667850': 67957.84999999998,\n",
       " '1973437': 55130.270000000004,\n",
       " '3968585': 35491.22000000001,\n",
       " '3367124': 66490.94999999998,\n",
       " '5071167': 46051.909999999996,\n",
       " '5472256': 52221.61999999999,\n",
       " '1964907': 60772.93,\n",
       " '3868478': 30349.050000000007,\n",
       " '1563321': 110161.98000000003,\n",
       " '3476505': 77680.67000000001,\n",
       " '3066670': 135157.36000000004,\n",
       " '3467439': 73200.65000000001,\n",
       " '0161259': 52894.19000000001,\n",
       " '3066522': 65106.62999999999,\n",
       " '3667876': 132854.85,\n",
       " '1062166': 218069.55000000002,\n",
       " '3768338': 112450.53000000001,\n",
       " '1964733': 1042707.9299999999}"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculate reimbursement for groupings submitted to USDA\n",
    "submitted_reimbursements = {}\n",
    "submitted_group_counts = {}\n",
    "\n",
    "for d in districts:\n",
    "    orig_strategy.create_groups(d)\n",
    "    submitted_reimbursements[d.code] = orig_strategy.reimbursement\n",
    "    submitted_group_counts[d.code] = len([g for g in orig_strategy.groups if len(g.schools)])\n",
    "submitted_reimbursements"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "913a683f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "9f16f65036934294b5781f8bc9a16f1e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(Label(value=''), IntProgress(value=0, max=133), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import ipywidgets as widgets\n",
    "from IPython.display import display\n",
    "from cep_estimatory import add_strategies\n",
    "import multiprocessing\n",
    "import time\n",
    "\n",
    "t0 = time.time()\n",
    "\n",
    "# SD Only\n",
    "to_eval = [d for d in districts if d == district] # if len(d.schools) < 500]\n",
    "\n",
    "cur = widgets.Label(\"\")\n",
    "out = widgets.HTML(\"\")\n",
    "f = widgets.IntProgress(min=0, max=sum([len(d.schools) for d in to_eval]))\n",
    "x = widgets.VBox([cur,f,out])\n",
    "display(x)\n",
    "\n",
    "from lambda_function import lambda_handler\n",
    "\n",
    "district_map = dict([(d.code,d) for d in to_eval])\n",
    "STRATEGIES = [\n",
    "    \"Pairs\",\n",
    "    \"OneToOne\",\n",
    "    \"Exhaustive\",\n",
    "    \"OneGroup\",\n",
    "    \"Spread\",\n",
    "    \"Binning\",\n",
    "    \"NYCMODA?fresh_starts=50&iterations=1000&ngroups=10\",\n",
    "    \"NYCMODA?fresh_starts=50&iterations=1000&ngroups=10&evaluate_by=schools\",\n",
    "    \"GreedyLP\"]\n",
    "\n",
    "def processor(district):\n",
    "    add_strategies(district,STRATEGIES)\n",
    "    district.run_strategies()\n",
    "    district.evaluate_strategies()\n",
    "    return {\n",
    "        \"code\":district.code,\n",
    "        \"reimb\":district.best_strategy.reimbursement,\n",
    "        \"best\":district.best_strategy.name,\n",
    "        \"groupings\": [g.as_dict() for g in district.best_strategy.groups]\n",
    "    }\n",
    "\n",
    "total_change = 0\n",
    "\n",
    "PROCESSES = multiprocessing.cpu_count() - 1\n",
    "with multiprocessing.Pool(PROCESSES) as pool:\n",
    "    results = [pool.apply_async(processor, (d,)) for d in to_eval]\n",
    "    for r in results:\n",
    "        result = r.get()\n",
    "        _d = district_map[result[\"code\"]]\n",
    "        f.value += len(_d.schools)\n",
    "        change = result[\"reimb\"] - submitted_reimbursements[_d.code]\n",
    "        if change != 0:\n",
    "            out.value += \"%s (%i schools) MC: %s - %0.0f => %0.0f (%0.0f)<br>\" % (\n",
    "                _d.name,\n",
    "                len(_d.schools),\n",
    "                result[\"best\"],\n",
    "                submitted_reimbursements[_d.code],\n",
    "                result[\"reimb\"],\n",
    "                change\n",
    "            )\n",
    "        total_change += change\n",
    "\n",
    "total_time = time.time() - t0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "25213644",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'$11,398,210 / yr'"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"${:,} / yr\".format(int(total_change * 180))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "24680bb4",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Top 20 Biggest Changes of 1 districts\n",
      "San Diego Unified School District  (133 schools submitted) $20,241,095 / yr => $31,639,305 / yr +$11,398,210 / yr / yr  +56.3%\n"
     ]
    }
   ],
   "source": [
    "changes = []\n",
    "def m(x): return \"${:,}\".format(int(x))\n",
    "\n",
    "result_data = [r.get() for r in results] \n",
    "\n",
    "for r in result_data:\n",
    "    _d = district_map[r[\"code\"]]\n",
    "    change = r[\"reimb\"] - submitted_reimbursements[_d.code]\n",
    "    if submitted_reimbursements[_d.code] == 0:\n",
    "        pchange = 1.0\n",
    "    else:\n",
    "        pchange = change / submitted_reimbursements[_d.code]\n",
    "    changes.append( (_d,change,pchange,r))\n",
    "changes.sort(key=lambda x:x[1],reverse=True)\n",
    "print(\"Top 20 Biggest Changes of %i districts\" % len(to_eval))\n",
    "for d in changes[:20]:\n",
    "    print(\n",
    "        d[0].name,\n",
    "        \" (%i schools submitted)\" % len(d[0].schools),\n",
    "        annual(submitted_reimbursements[d[0].code]),\"=>\",annual(d[3][\"reimb\"]),\n",
    "        \"+%s / yr\" % annual(d[1]),\" +%0.1f%%\" % (d[2]*100)\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "566f6edf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1, 133)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(district_map),sum([len(d.schools) for d in district_map.values()])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "c7d17afa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(254, 1)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "optimized_reimbursements = [r.get()[\"reimb\"] for r in results]\n",
    "submitted = [r[1] for r in submitted_reimbursements.items()]\n",
    "\n",
    "len(submitted),len(optimized_reimbursements)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "4d72b272",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('$928,665,360 / yr', '$31,639,305 / yr')"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "annual(sum(submitted_reimbursements.values())),annual(sum(optimized_reimbursements))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ea5ad4d5",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "d0d5f89f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<tbody>\n",
       "<tr><td>District                         </td><td>District Code</td><td>Schools</td><td>Submitted Schools</td><td>Submitted       </td><td>Optimized       </td><td>%increase</td><td>Algo                                              </td></tr>\n",
       "<tr><td>San Diego Unified School District</td><td>3768338      </td><td>196    </td><td>67%              </td><td>$20,241,095 / yr</td><td>$31,639,305 / yr</td><td>36%      </td><td>NYCMODA?fresh_starts=50&amp;iterations=1000&amp;ngroups=10</td></tr>\n",
       "</tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "result_data.sort(key=lambda r: r[\"reimb\"],reverse=True)\n",
    "result_table = [ ('District','District Code','Schools','Submitted Schools','Submitted','Optimized','%increase','Algo') ] + [\n",
    "    (  district_map[r['code']].name,\n",
    "       r['code'],\n",
    "       len(overall_districts[r['code']]),\n",
    "       \"%i%%\" % int(len(district_map[r['code']].schools)/len(overall_districts[r['code']]) * 100), \n",
    "       annual(submitted_reimbursements[r['code']]),\n",
    "       annual(r['reimb']),\n",
    "       r['reimb'] and \"%i%%\" % int((1 - submitted_reimbursements[r['code']]/r['reimb']) * 100) or '',\n",
    "       r['best']\n",
    "    )\n",
    "    for r in result_data\n",
    "]\n",
    "\n",
    "display(HTML(tabulate.tabulate(result_table,tablefmt='html')))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "dcb42647",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'$-897,026,054 / yr'"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "annual((sum(optimized_reimbursements) - sum(submitted_reimbursements.values())))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "8d9f380e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, '3.65')"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "submitted_reimbursements[\"4770466\"],\"%0.2f\" % (total_time/60)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2051d301",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "04373cd7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax = plt.subplots()\n",
    "ax.pie(\n",
    "    [c[1] for c in changes], labels= [(i<8 and c[0].name or '') for i,c in enumerate(changes)]\n",
    ")\n",
    "ax"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "5c8fcce3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'number of schools')"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax = plt.subplots()\n",
    "\n",
    "normal_changes = [ c for c in changes if c[2] < 1.0 ]\n",
    "ax.scatter(\n",
    "    [c[2] for c in normal_changes ],\n",
    "    [len(c[0].schools) for c in normal_changes ],\n",
    ")\n",
    "ax.set_xlabel('% change')\n",
    "ax.set_ylabel('number of schools')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "c29e97b2",
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyError",
     "evalue": "'1263024'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32m/tmp/ipykernel_11/1437806859.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      4\u001b[0m ax.scatter(\n\u001b[1;32m      5\u001b[0m     \u001b[0;34m[\u001b[0m\u001b[0mcnt\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mcnt\u001b[0m \u001b[0;32min\u001b[0m \u001b[0msubmitted_group_counts\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 6\u001b[0;31m     \u001b[0;34m[\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdistrict_map\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mg\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mschools\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mg\u001b[0m \u001b[0;32min\u001b[0m \u001b[0msubmitted_group_counts\u001b[0m \u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      7\u001b[0m )\n\u001b[1;32m      8\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_xlabel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'number of groups'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/tmp/ipykernel_11/1437806859.py\u001b[0m in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m      4\u001b[0m ax.scatter(\n\u001b[1;32m      5\u001b[0m     \u001b[0;34m[\u001b[0m\u001b[0mcnt\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mcnt\u001b[0m \u001b[0;32min\u001b[0m \u001b[0msubmitted_group_counts\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 6\u001b[0;31m     \u001b[0;34m[\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdistrict_map\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mg\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mschools\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mg\u001b[0m \u001b[0;32min\u001b[0m \u001b[0msubmitted_group_counts\u001b[0m \u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      7\u001b[0m )\n\u001b[1;32m      8\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_xlabel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'number of groups'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyError\u001b[0m: '1263024'"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax = plt.subplots()\n",
    "\n",
    "\n",
    "ax.scatter(\n",
    "    [cnt for cnt in submitted_group_counts.values() ],\n",
    "    [len(district_map[g].schools) for g in submitted_group_counts ],\n",
    ")\n",
    "ax.set_xlabel('number of groups')\n",
    "ax.set_ylabel('number of schools')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "a3424e52",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'number of schools')"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax = plt.subplots()\n",
    "\n",
    "\n",
    "ax.scatter(\n",
    "    [len(r['groupings']) for r in result_data ],\n",
    "    [len(district_map[r['code']].schools) for r in result_data ],\n",
    ")\n",
    "ax.set_xlabel('number of groups')\n",
    "ax.set_ylabel('number of schools')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "97cb09ad",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<strategies.base.CEPDistrict at 0x7f16b421cfd0>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "district"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "7bb01449",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'code': '3768338',\n",
       " 'reimb': 175773.91999999998,\n",
       " 'best': 'NYCMODA?fresh_starts=50&iterations=1000&ngroups=10',\n",
       " 'groupings': [{'name': 'Group 0',\n",
       "   'school_codes': ['37683386059588',\n",
       "    '37683380107177',\n",
       "    '37683383730116',\n",
       "    '37683380114025',\n",
       "    '37683380118851',\n",
       "    '37683386039598',\n",
       "    '37683386093256',\n",
       "    '37683386039713',\n",
       "    '37683386039796',\n",
       "    '37683386109599',\n",
       "    '37683386061980',\n",
       "    '37683386106173',\n",
       "    '37683383734431',\n",
       "    '37683380116939',\n",
       "    '37683386039309',\n",
       "    '37683380111906',\n",
       "    '37683386096051'],\n",
       "   'school_reimbursements': [('37683380111906', 859.04),\n",
       "    ('37683386039309', 436.53),\n",
       "    ('37683386039598', 530.78),\n",
       "    ('37683380118851', 443.5),\n",
       "    ('37683386061980', 1275.63),\n",
       "    ('37683386059588', 1431.93),\n",
       "    ('37683380107177', 1960.99),\n",
       "    ('37683380116939', 662.59),\n",
       "    ('37683386039713', 520.44),\n",
       "    ('37683386096051', 1175.15),\n",
       "    ('37683386109599', 782.48),\n",
       "    ('37683383730116', 303.34),\n",
       "    ('37683380114025', 2161.86),\n",
       "    ('37683386039796', 397.67),\n",
       "    ('37683386106173', 742.06),\n",
       "    ('37683383734431', 895.44),\n",
       "    ('37683386093256', 1032.17)],\n",
       "   'isp': 0.4005,\n",
       "   'free_rate': 0.6408,\n",
       "   'paid_rate': 0.35919999999999996,\n",
       "   'total_eligible': 4024,\n",
       "   'total_enrolled': 10048,\n",
       "   'free_rate_students': 6439.0,\n",
       "   'paid_rate_students': 3609,\n",
       "   'cep_eligible': True,\n",
       "   'est_reimbursement': 15611.600000000002,\n",
       "   'daily_breakfast_served': 3073,\n",
       "   'daily_lunch_served': 4694},\n",
       "  {'name': 'Group 1',\n",
       "   'school_codes': ['37683386040307',\n",
       "    '37683386113211',\n",
       "    '37683386059653',\n",
       "    '37683386059679',\n",
       "    '37683386089049',\n",
       "    '37683383731213',\n",
       "    '37683383732997',\n",
       "    '37683386040281',\n",
       "    '37683386039135',\n",
       "    '37683386039432',\n",
       "    '37683386040018',\n",
       "    '37683386039648',\n",
       "    '37683386040034',\n",
       "    '37683386039457',\n",
       "    '37683380117325',\n",
       "    '37683383731551',\n",
       "    '37683386040224',\n",
       "    '37683386039812',\n",
       "    '37683386040133',\n",
       "    '37683386097844',\n",
       "    '37683386099063'],\n",
       "   'school_reimbursements': [('37683383731213', 569.56),\n",
       "    ('37683386089049', 694.77),\n",
       "    ('37683383732997', 3326.08),\n",
       "    ('37683386039432', 264.3),\n",
       "    ('37683383731551', 1353.4),\n",
       "    ('37683386039457', 1966.18),\n",
       "    ('37683386039648', 667.53),\n",
       "    ('37683380117325', 674.27),\n",
       "    ('37683386113211', 452.51),\n",
       "    ('37683386097844', 783.16),\n",
       "    ('37683386040307', 235.61),\n",
       "    ('37683386040034', 707.67),\n",
       "    ('37683386040018', 1232.97),\n",
       "    ('37683386099063', 712.38),\n",
       "    ('37683386059679', 737.96),\n",
       "    ('37683386040224', 463.28),\n",
       "    ('37683386059653', 417.14),\n",
       "    ('37683386040133', 244.46),\n",
       "    ('37683386040281', 542.27),\n",
       "    ('37683386039812', 1062.65),\n",
       "    ('37683386039135', 632.88)],\n",
       "   'isp': 0.4,\n",
       "   'free_rate': 0.6400000000000001,\n",
       "   'paid_rate': 0.3599999999999999,\n",
       "   'total_eligible': 4500,\n",
       "   'total_enrolled': 11251,\n",
       "   'free_rate_students': 7201.0,\n",
       "   'paid_rate_students': 4050,\n",
       "   'cep_eligible': True,\n",
       "   'est_reimbursement': 17741.03,\n",
       "   'daily_breakfast_served': 3180,\n",
       "   'daily_lunch_served': 5510},\n",
       "  {'name': 'Group 2',\n",
       "   'school_codes': ['37683380124206',\n",
       "    '37683386039499',\n",
       "    '37683386040190',\n",
       "    '37683386039366',\n",
       "    '37683386114375',\n",
       "    '37683386039341',\n",
       "    '37683386039705',\n",
       "    '37683386039655'],\n",
       "   'school_reimbursements': [('37683386039655', 1484.28),\n",
       "    ('37683380124206', 1889.97),\n",
       "    ('37683386039341', 2094.85),\n",
       "    ('37683386040190', 3235.7),\n",
       "    ('37683386039499', 2100.33),\n",
       "    ('37683386039366', 3165.08),\n",
       "    ('37683386114375', 4684.53),\n",
       "    ('37683386039705', 2444.21)],\n",
       "   'isp': 0.6229,\n",
       "   'free_rate': 0.9966400000000001,\n",
       "   'paid_rate': 0.0033599999999999186,\n",
       "   'total_eligible': 2233,\n",
       "   'total_enrolled': 3585,\n",
       "   'free_rate_students': 3573.0,\n",
       "   'paid_rate_students': 12,\n",
       "   'cep_eligible': True,\n",
       "   'est_reimbursement': 21098.949999999997,\n",
       "   'daily_breakfast_served': 3916,\n",
       "   'daily_lunch_served': 3822},\n",
       "  {'name': 'Group 3',\n",
       "   'school_codes': ['37683386039630',\n",
       "    '37683380114041',\n",
       "    '37683380108290',\n",
       "    '37683386039382',\n",
       "    '37683386039887',\n",
       "    '37683386039283',\n",
       "    '37683386117279',\n",
       "    '37683386114300',\n",
       "    '37683386039176',\n",
       "    '37683386039150',\n",
       "    '37683386040257',\n",
       "    '37683386040158',\n",
       "    '37683386039614',\n",
       "    '37683386039143',\n",
       "    '37683386039515',\n",
       "    '37683386040273',\n",
       "    '37683386040091',\n",
       "    '37683386039754',\n",
       "    '37683386039879',\n",
       "    '37683383731130',\n",
       "    '37683380108282',\n",
       "    '37683386040059'],\n",
       "   'school_reimbursements': [('37683386040158', 2998.71),\n",
       "    ('37683383731130', 143.08),\n",
       "    ('37683386039879', 2387.55),\n",
       "    ('37683380108282', 1805.03),\n",
       "    ('37683386039614', 1215.28),\n",
       "    ('37683386039630', 1636.41),\n",
       "    ('37683386039283', 1890.65),\n",
       "    ('37683386039176', 1395.75),\n",
       "    ('37683386039143', 2008.92),\n",
       "    ('37683386039887', 1594.34),\n",
       "    ('37683386039754', 2074.98),\n",
       "    ('37683386040059', 1413.51),\n",
       "    ('37683386117279', 628.51),\n",
       "    ('37683380114041', 2334.11),\n",
       "    ('37683386039382', 3153.88),\n",
       "    ('37683386039150', 1992.67),\n",
       "    ('37683386039515', 2465.2),\n",
       "    ('37683380108290', 2285.85),\n",
       "    ('37683386040091', 1436.78),\n",
       "    ('37683386040257', 2438.98),\n",
       "    ('37683386114300', 2534.7),\n",
       "    ('37683386040273', 1136.49)],\n",
       "   'isp': 0.6116,\n",
       "   'free_rate': 0.9785600000000001,\n",
       "   'paid_rate': 0.021439999999999904,\n",
       "   'total_eligible': 4705,\n",
       "   'total_enrolled': 7693,\n",
       "   'free_rate_students': 7528.0,\n",
       "   'paid_rate_students': 164,\n",
       "   'cep_eligible': True,\n",
       "   'est_reimbursement': 40971.37999999999,\n",
       "   'daily_breakfast_served': 7973,\n",
       "   'daily_lunch_served': 7410},\n",
       "  {'name': 'Group 4',\n",
       "   'school_codes': ['37683386039481',\n",
       "    '37683386040067',\n",
       "    '37683386039853',\n",
       "    '37683380108274',\n",
       "    '37683380119610',\n",
       "    '37683386040109',\n",
       "    '37683380127647',\n",
       "    '37683386039374'],\n",
       "   'school_reimbursements': [('37683386039853', 677.18),\n",
       "    ('37683386040109', 623.89),\n",
       "    ('37683386040067', 801.23),\n",
       "    ('37683386039481', 543.87),\n",
       "    ('37683380108274', 1256.09),\n",
       "    ('37683386039374', 766.91),\n",
       "    ('37683380127647', 867.66),\n",
       "    ('37683380119610', 2620.72)],\n",
       "   'isp': 0.4,\n",
       "   'free_rate': 0.6400000000000001,\n",
       "   'paid_rate': 0.3599999999999999,\n",
       "   'total_eligible': 1618,\n",
       "   'total_enrolled': 4045,\n",
       "   'free_rate_students': 2589.0,\n",
       "   'paid_rate_students': 1456,\n",
       "   'cep_eligible': True,\n",
       "   'est_reimbursement': 8157.550000000001,\n",
       "   'daily_breakfast_served': 1252,\n",
       "   'daily_lunch_served': 2647},\n",
       "  {'name': 'Group 5',\n",
       "   'school_codes': ['37683386106181',\n",
       "    '37683383730371',\n",
       "    '37683386061972',\n",
       "    '37683386096598',\n",
       "    '37683383730181',\n",
       "    '37683380107482'],\n",
       "   'school_reimbursements': [('37683383730181', 0),\n",
       "    ('37683386061972', 0),\n",
       "    ('37683386096598', 0),\n",
       "    ('37683386106181', 0),\n",
       "    ('37683380107482', 0),\n",
       "    ('37683383730371', 0)],\n",
       "   'isp': 0.218,\n",
       "   'free_rate': 0,\n",
       "   'paid_rate': 0,\n",
       "   'total_eligible': 1347,\n",
       "   'total_enrolled': 6178,\n",
       "   'free_rate_students': 0,\n",
       "   'paid_rate_students': 0,\n",
       "   'cep_eligible': False,\n",
       "   'est_reimbursement': 0,\n",
       "   'daily_breakfast_served': 329,\n",
       "   'daily_lunch_served': 1494},\n",
       "  {'name': 'Group 6',\n",
       "   'school_codes': ['37683386039267',\n",
       "    '37683386040083',\n",
       "    '37683386039507',\n",
       "    '37683386106199',\n",
       "    '37683386039358',\n",
       "    '37683386119598',\n",
       "    '37683386040026',\n",
       "    '37683383737962',\n",
       "    '37683386040117',\n",
       "    '37683380111864',\n",
       "    '37683386039556',\n",
       "    '37683386039861',\n",
       "    '37683386039564',\n",
       "    '37683386040265'],\n",
       "   'school_reimbursements': [('37683386119598', 1135.95),\n",
       "    ('37683386040265', 1082.12),\n",
       "    ('37683380111864', 1125.14),\n",
       "    ('37683386039358', 770.99),\n",
       "    ('37683386039507', 1126.22),\n",
       "    ('37683386039556', 1169.48),\n",
       "    ('37683386040026', 2306.84),\n",
       "    ('37683386106199', 3988.99),\n",
       "    ('37683386039861', 1016.57),\n",
       "    ('37683383737962', 279.37),\n",
       "    ('37683386040117', 966.49),\n",
       "    ('37683386039267', 1547.46),\n",
       "    ('37683386039564', 659.19),\n",
       "    ('37683386040083', 442.93)],\n",
       "   'isp': 0.5003,\n",
       "   'free_rate': 0.80048,\n",
       "   'paid_rate': 0.19952000000000003,\n",
       "   'total_eligible': 2275,\n",
       "   'total_enrolled': 4547,\n",
       "   'free_rate_students': 3640.0,\n",
       "   'paid_rate_students': 907,\n",
       "   'cep_eligible': True,\n",
       "   'est_reimbursement': 17617.739999999998,\n",
       "   'daily_breakfast_served': 4081,\n",
       "   'daily_lunch_served': 3771},\n",
       "  {'name': 'Group 7',\n",
       "   'school_codes': ['37683380114033',\n",
       "    '37683386061964',\n",
       "    '37683380118315',\n",
       "    '37683386039788',\n",
       "    '37683386039424',\n",
       "    '37683386039523',\n",
       "    '37683386039978',\n",
       "    '37683386040000',\n",
       "    '37683380108266',\n",
       "    '37683386107056',\n",
       "    '37683380114462',\n",
       "    '37683386059646'],\n",
       "   'school_reimbursements': [('37683380118315', 161.45),\n",
       "    ('37683386039788', 967.03),\n",
       "    ('37683386039523', 1741.47),\n",
       "    ('37683380108266', 1468.77),\n",
       "    ('37683380114033', 1328.13),\n",
       "    ('37683386059646', 1506.13),\n",
       "    ('37683386039978', 522.0),\n",
       "    ('37683380114462', 163.72),\n",
       "    ('37683386040000', 928.72),\n",
       "    ('37683386061964', 4812.03),\n",
       "    ('37683386107056', 701.2),\n",
       "    ('37683386039424', 474.67)],\n",
       "   'isp': 0.402,\n",
       "   'free_rate': 0.6432000000000001,\n",
       "   'paid_rate': 0.3567999999999999,\n",
       "   'total_eligible': 3094,\n",
       "   'total_enrolled': 7697,\n",
       "   'free_rate_students': 4951.0,\n",
       "   'paid_rate_students': 2746,\n",
       "   'cep_eligible': True,\n",
       "   'est_reimbursement': 14775.32,\n",
       "   'daily_breakfast_served': 3328,\n",
       "   'daily_lunch_served': 4198},\n",
       "  {'name': 'Group 8',\n",
       "   'school_codes': ['37683386039168',\n",
       "    '37683386114292',\n",
       "    '37683386039390',\n",
       "    '37683386089064',\n",
       "    '37683386039952',\n",
       "    '37683386039762',\n",
       "    '37683380107052',\n",
       "    '37683386039101',\n",
       "    '37683386039929',\n",
       "    '37683380107094',\n",
       "    '37683380124115'],\n",
       "   'school_reimbursements': [('37683386039762', 2816.34),\n",
       "    ('37683386114292', 1765.41),\n",
       "    ('37683386039929', 1975.64),\n",
       "    ('37683386039390', 1737.75),\n",
       "    ('37683380107094', 2335.47),\n",
       "    ('37683386039952', 2150.01),\n",
       "    ('37683380124115', 1774.32),\n",
       "    ('37683386039101', 3127.29),\n",
       "    ('37683386089064', 2201.4),\n",
       "    ('37683386039168', 2370.83),\n",
       "    ('37683380107052', 4824.37)],\n",
       "   'isp': 0.6237,\n",
       "   'free_rate': 0.9979200000000001,\n",
       "   'paid_rate': 0.0020799999999998597,\n",
       "   'total_eligible': 2881,\n",
       "   'total_enrolled': 4619,\n",
       "   'free_rate_students': 4609.0,\n",
       "   'paid_rate_students': 9,\n",
       "   'cep_eligible': True,\n",
       "   'est_reimbursement': 27078.829999999998,\n",
       "   'daily_breakfast_served': 4978,\n",
       "   'daily_lunch_served': 4922},\n",
       "  {'name': 'Group 9',\n",
       "   'school_codes': ['37683383730363',\n",
       "    '37683386039770',\n",
       "    '37683383730231',\n",
       "    '37683383733698',\n",
       "    '37683386059638',\n",
       "    '37683386039259',\n",
       "    '37683386114060',\n",
       "    '37683383731189',\n",
       "    '37683386039606',\n",
       "    '37683386059703',\n",
       "    '37683386077317',\n",
       "    '37683386039119',\n",
       "    '37683386039572',\n",
       "    '37683386059711'],\n",
       "   'school_reimbursements': [('37683386077317', 1154.33),\n",
       "    ('37683386039606', 1177.88),\n",
       "    ('37683386114060', 1866.68),\n",
       "    ('37683386059638', 692.04),\n",
       "    ('37683386039572', 669.65),\n",
       "    ('37683383730363', 161.86),\n",
       "    ('37683386039119', 455.11),\n",
       "    ('37683386059703', 991.11),\n",
       "    ('37683383733698', 1168.85),\n",
       "    ('37683383730231', 122.43),\n",
       "    ('37683383731189', 1482.02),\n",
       "    ('37683386039770', 1303.98),\n",
       "    ('37683386039259', 970.64),\n",
       "    ('37683386059711', 504.94)],\n",
       "   'isp': 0.4014,\n",
       "   'free_rate': 0.64224,\n",
       "   'paid_rate': 0.35775999999999997,\n",
       "   'total_eligible': 2964,\n",
       "   'total_enrolled': 7385,\n",
       "   'free_rate_students': 4743.0,\n",
       "   'paid_rate_students': 2642,\n",
       "   'cep_eligible': True,\n",
       "   'est_reimbursement': 12721.52,\n",
       "   'daily_breakfast_served': 2863,\n",
       "   'daily_lunch_served': 3622}]}"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result_data[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "0d74d856",
   "metadata": {},
   "outputs": [],
   "source": [
    "orig_strategy.create_groups(district)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "d7c0a6de",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(<strategies.base.CEPDistrict object at 0x7f16b421cfd0> / Group 3768338-G1 ISP=54% ENROLLED=24180 FREE_RATE=86.83%,\n",
       "  53),\n",
       " (<strategies.base.CEPDistrict object at 0x7f16b421cfd0> / Group 3768338-G2 ISP=37% ENROLLED=34161 FREE_RATE=0.00%,\n",
       "  65),\n",
       " (<strategies.base.CEPDistrict object at 0x7f16b421cfd0> / Group 3768338-G3 ISP=49% ENROLLED=6364 FREE_RATE=78.27%,\n",
       "  13),\n",
       " (<strategies.base.CEPDistrict object at 0x7f16b421cfd0> / Group 3768338-G4 ISP=39% ENROLLED=2343 FREE_RATE=0.00%,\n",
       "  2)]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[(g,len(g.schools)) for g in orig_strategy.groups if g.schools]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "38d5067e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "112450.53000000001"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "orig_strategy.reimbursement"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "44048570",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10575006.129999995"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(result_data[0]['reimb'] - orig_strategy.reimbursement) * 167"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "3bb55b99",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<strategies.base.CEPDistrict object at 0x7f16b421cfd0> / Group 0 ISP=40% ENROLLED=10048 FREE_RATE=64.08%,\n",
       " <strategies.base.CEPDistrict object at 0x7f16b421cfd0> / Group 1 ISP=40% ENROLLED=11251 FREE_RATE=64.00%,\n",
       " <strategies.base.CEPDistrict object at 0x7f16b421cfd0> / Group 2 ISP=62% ENROLLED=3585 FREE_RATE=99.66%,\n",
       " <strategies.base.CEPDistrict object at 0x7f16b421cfd0> / Group 3 ISP=61% ENROLLED=7693 FREE_RATE=97.86%,\n",
       " <strategies.base.CEPDistrict object at 0x7f16b421cfd0> / Group 4 ISP=40% ENROLLED=4045 FREE_RATE=64.00%,\n",
       " <strategies.base.CEPDistrict object at 0x7f16b421cfd0> / Group 5 ISP=22% ENROLLED=6178 FREE_RATE=0.00%,\n",
       " <strategies.base.CEPDistrict object at 0x7f16b421cfd0> / Group 6 ISP=50% ENROLLED=4547 FREE_RATE=80.05%,\n",
       " <strategies.base.CEPDistrict object at 0x7f16b421cfd0> / Group 7 ISP=40% ENROLLED=7697 FREE_RATE=64.32%,\n",
       " <strategies.base.CEPDistrict object at 0x7f16b421cfd0> / Group 8 ISP=62% ENROLLED=4619 FREE_RATE=99.79%,\n",
       " <strategies.base.CEPDistrict object at 0x7f16b421cfd0> / Group 9 ISP=40% ENROLLED=7385 FREE_RATE=64.22%]"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from strategies.base import CEPGroup\n",
    "groups = []\n",
    "i=0\n",
    "for g in result_data[0][\"groupings\"]:\n",
    "    group = CEPGroup(district,g[\"name\"],schools=[s for s in district.schools if s.code in g[\"school_codes\"]])\n",
    "    groups.append(group)\n",
    "    i+=1\n",
    "\n",
    "groups"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "d5af096c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('Standley Middle', 0.2078),\n",
       " ('San Diego Metro Career and Tech', 0.2993),\n",
       " ('MIRA MESA HIGH', 0.2135),\n",
       " ('De Portola Middle', 0.1649),\n",
       " ('San Diego SCPA', 0.2688),\n",
       " ('PERSHING MIDDLE', 0.1933)]"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[(s.name,s.isp) for s in [g for g in groups if g.est_reimbursement() == 0][0].schools]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8f0c9d54",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.8"
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 },
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