2_2_allocations and usages by units.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Introduction"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%run include/required_libs.py\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {
    "collapsed": true,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "unit = pd.read_csv('rawdata/accts_vs_units.csv')\n",
    "le = pd.read_csv('rawdata/legacy_summary.csv')\n",
    "le['cycle']=2018\n",
    "cycles = list(range(2013,2019))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Allocation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Firstly, get a list of TOP 5 that have the highest total allocation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cycle</th>\n",
       "      <th>unit</th>\n",
       "      <th>allocation</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2013</td>\n",
       "      <td>IME</td>\n",
       "      <td>2000000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2013</td>\n",
       "      <td>PSD</td>\n",
       "      <td>1325000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2013</td>\n",
       "      <td>PSD</td>\n",
       "      <td>700000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2013</td>\n",
       "      <td>PSD</td>\n",
       "      <td>500000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2013</td>\n",
       "      <td>PSD</td>\n",
       "      <td>500000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2013</td>\n",
       "      <td>PSD</td>\n",
       "      <td>500000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2013</td>\n",
       "      <td>BSD</td>\n",
       "      <td>500000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2013</td>\n",
       "      <td>BSD</td>\n",
       "      <td>500000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2013</td>\n",
       "      <td>CI</td>\n",
       "      <td>500000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2013</td>\n",
       "      <td>PSD</td>\n",
       "      <td>300000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2013</td>\n",
       "      <td>PSD</td>\n",
       "      <td>160000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2013</td>\n",
       "      <td>PSD</td>\n",
       "      <td>150000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2013</td>\n",
       "      <td>PSD</td>\n",
       "      <td>142000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2013</td>\n",
       "      <td>PSD</td>\n",
       "      <td>110000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2013</td>\n",
       "      <td>BSD</td>\n",
       "      <td>100000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2013</td>\n",
       "      <td>BSD</td>\n",
       "      <td>100000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2013</td>\n",
       "      <td>PSD</td>\n",
       "      <td>100000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2013</td>\n",
       "      <td>PSD</td>\n",
       "      <td>98000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2013</td>\n",
       "      <td>PSD</td>\n",
       "      <td>96000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2013</td>\n",
       "      <td>PSD</td>\n",
       "      <td>90000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2013</td>\n",
       "      <td>Booth</td>\n",
       "      <td>75000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2013</td>\n",
       "      <td>Booth</td>\n",
       "      <td>75000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2013</td>\n",
       "      <td>PSD</td>\n",
       "      <td>63000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2013</td>\n",
       "      <td>CI</td>\n",
       "      <td>50000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2013</td>\n",
       "      <td>PSD</td>\n",
       "      <td>50000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2013</td>\n",
       "      <td>PSD</td>\n",
       "      <td>50000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2013</td>\n",
       "      <td>Humanities</td>\n",
       "      <td>50000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2013</td>\n",
       "      <td>Booth</td>\n",
       "      <td>50000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2013</td>\n",
       "      <td>BSD</td>\n",
       "      <td>50000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2013</td>\n",
       "      <td>PSD</td>\n",
       "      <td>50000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1028</th>\n",
       "      <td>2018</td>\n",
       "      <td>Harris</td>\n",
       "      <td>4572.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1029</th>\n",
       "      <td>2018</td>\n",
       "      <td>Medicine</td>\n",
       "      <td>4510.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1030</th>\n",
       "      <td>2018</td>\n",
       "      <td>BSD</td>\n",
       "      <td>4499.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1031</th>\n",
       "      <td>2018</td>\n",
       "      <td>Booth</td>\n",
       "      <td>4488.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1032</th>\n",
       "      <td>2018</td>\n",
       "      <td>PSD</td>\n",
       "      <td>4478.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1033</th>\n",
       "      <td>2018</td>\n",
       "      <td>Booth</td>\n",
       "      <td>4417.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1034</th>\n",
       "      <td>2018</td>\n",
       "      <td>CARS</td>\n",
       "      <td>4254.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1035</th>\n",
       "      <td>2018</td>\n",
       "      <td>Booth</td>\n",
       "      <td>4200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1036</th>\n",
       "      <td>2018</td>\n",
       "      <td>CI</td>\n",
       "      <td>4108.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1037</th>\n",
       "      <td>2018</td>\n",
       "      <td>BSD</td>\n",
       "      <td>4053.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1038</th>\n",
       "      <td>2018</td>\n",
       "      <td>SSD</td>\n",
       "      <td>3630.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1039</th>\n",
       "      <td>2018</td>\n",
       "      <td>IME</td>\n",
       "      <td>2869.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1040</th>\n",
       "      <td>2018</td>\n",
       "      <td>Harris</td>\n",
       "      <td>2601.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1041</th>\n",
       "      <td>2018</td>\n",
       "      <td>EPIC</td>\n",
       "      <td>1864.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1042</th>\n",
       "      <td>2018</td>\n",
       "      <td>PSD</td>\n",
       "      <td>1528.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1043</th>\n",
       "      <td>2018</td>\n",
       "      <td>Booth</td>\n",
       "      <td>922.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1044</th>\n",
       "      <td>2018</td>\n",
       "      <td>Harris</td>\n",
       "      <td>428.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1045</th>\n",
       "      <td>2018</td>\n",
       "      <td>PSD</td>\n",
       "      <td>84.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018</td>\n",
       "      <td>PSD</td>\n",
       "      <td>650000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018</td>\n",
       "      <td>BSD</td>\n",
       "      <td>1000000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018</td>\n",
       "      <td>PSD</td>\n",
       "      <td>250000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018</td>\n",
       "      <td>Booth</td>\n",
       "      <td>1000000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018</td>\n",
       "      <td>IME</td>\n",
       "      <td>1000000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2018</td>\n",
       "      <td>PSD</td>\n",
       "      <td>1000000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2018</td>\n",
       "      <td>IME</td>\n",
       "      <td>1000000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2018</td>\n",
       "      <td>CI</td>\n",
       "      <td>1000000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2018</td>\n",
       "      <td>PSD</td>\n",
       "      <td>1000000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2018</td>\n",
       "      <td>BSD</td>\n",
       "      <td>1000000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2018</td>\n",
       "      <td>PSD</td>\n",
       "      <td>500000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2018</td>\n",
       "      <td>PSD</td>\n",
       "      <td>1000000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1058 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      cycle        unit  allocation\n",
       "0      2013         IME   2000000.0\n",
       "1      2013         PSD   1325000.0\n",
       "2      2013         PSD    700000.0\n",
       "3      2013         PSD    500000.0\n",
       "4      2013         PSD    500000.0\n",
       "5      2013         PSD    500000.0\n",
       "6      2013         BSD    500000.0\n",
       "7      2013         BSD    500000.0\n",
       "8      2013          CI    500000.0\n",
       "9      2013         PSD    300000.0\n",
       "10     2013         PSD    160000.0\n",
       "11     2013         PSD    150000.0\n",
       "12     2013         PSD    142000.0\n",
       "13     2013         PSD    110000.0\n",
       "14     2013         BSD    100000.0\n",
       "15     2013         BSD    100000.0\n",
       "16     2013         PSD    100000.0\n",
       "17     2013         PSD     98000.0\n",
       "18     2013         PSD     96000.0\n",
       "19     2013         PSD     90000.0\n",
       "20     2013       Booth     75000.0\n",
       "21     2013       Booth     75000.0\n",
       "22     2013         PSD     63000.0\n",
       "23     2013          CI     50000.0\n",
       "24     2013         PSD     50000.0\n",
       "25     2013         PSD     50000.0\n",
       "26     2013  Humanities     50000.0\n",
       "27     2013       Booth     50000.0\n",
       "28     2013         BSD     50000.0\n",
       "29     2013         PSD     50000.0\n",
       "...     ...         ...         ...\n",
       "1028   2018      Harris      4572.0\n",
       "1029   2018    Medicine      4510.0\n",
       "1030   2018         BSD      4499.0\n",
       "1031   2018       Booth      4488.0\n",
       "1032   2018         PSD      4478.0\n",
       "1033   2018       Booth      4417.0\n",
       "1034   2018        CARS      4254.0\n",
       "1035   2018       Booth      4200.0\n",
       "1036   2018          CI      4108.0\n",
       "1037   2018         BSD      4053.0\n",
       "1038   2018         SSD      3630.0\n",
       "1039   2018         IME      2869.0\n",
       "1040   2018      Harris      2601.0\n",
       "1041   2018        EPIC      1864.0\n",
       "1042   2018         PSD      1528.0\n",
       "1043   2018       Booth       922.0\n",
       "1044   2018      Harris       428.0\n",
       "1045   2018         PSD        84.0\n",
       "0      2018         PSD    650000.0\n",
       "1      2018         BSD   1000000.0\n",
       "2      2018         PSD    250000.0\n",
       "3      2018       Booth   1000000.0\n",
       "4      2018         IME   1000000.0\n",
       "5      2018         PSD   1000000.0\n",
       "6      2018         IME   1000000.0\n",
       "7      2018          CI   1000000.0\n",
       "8      2018         PSD   1000000.0\n",
       "9      2018         BSD   1000000.0\n",
       "10     2018         PSD    500000.0\n",
       "11     2018         PSD   1000000.0\n",
       "\n",
       "[1058 rows x 3 columns]"
      ]
     },
     "execution_count": 172,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "alc = pd.read_csv('rawdata/allocs_by_cycle_group.csv')\n",
    "change = alc[alc.account.isin(list(le['account'])) & alc.cycle.isin(['2018'])].groupby('account')['allocation'].sum().to_frame().reset_index()\n",
    "    \n",
    "alc = alc.append(le)[['account','allocation','cycle']]\n",
    "alc = alc.join(unit.set_index('account'), on='account')\n",
    "alloc_unit =alc[['cycle','unit','allocation']]\n",
    "alloc_unit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['PSD', 'BSD', 'Booth', 'IME', 'CI', 'Others']"
      ]
     },
     "execution_count": 173,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ua = alloc_unit.groupby('unit')['allocation'].sum().to_frame().\\\n",
    "sort_values('allocation', ascending=False).reset_index()\n",
    "\n",
    "\n",
    "leng = list(ua.count())[0]\n",
    "other = ua.loc[5:leng, ['unit','allocation']].sum().to_frame().T\n",
    "other['unit'][0]='Others'\n",
    "\n",
    "top = ua.drop(ua.index[range(5,leng)])\n",
    "top = top.append(other, ignore_index=True)\n",
    "alloc_top_5 =  list(top['unit'])\n",
    "alloc_top_5 "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### The we will make changes to acc_unit  table (have cycle and all units), sorting them to top_5 and 'other'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cycle</th>\n",
       "      <th>unit</th>\n",
       "      <th>allocation</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2013</td>\n",
       "      <td>BSD</td>\n",
       "      <td>1.310000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2013</td>\n",
       "      <td>Booth</td>\n",
       "      <td>0.205000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2013</td>\n",
       "      <td>CI</td>\n",
       "      <td>0.550000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2013</td>\n",
       "      <td>IME</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2013</td>\n",
       "      <td>Others</td>\n",
       "      <td>0.050000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2013</td>\n",
       "      <td>PSD</td>\n",
       "      <td>5.130000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2014</td>\n",
       "      <td>BSD</td>\n",
       "      <td>3.939000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2014</td>\n",
       "      <td>Booth</td>\n",
       "      <td>3.581000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2014</td>\n",
       "      <td>CI</td>\n",
       "      <td>1.450000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2014</td>\n",
       "      <td>IME</td>\n",
       "      <td>1.480000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2014</td>\n",
       "      <td>Others</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2014</td>\n",
       "      <td>PSD</td>\n",
       "      <td>14.379000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2015</td>\n",
       "      <td>BSD</td>\n",
       "      <td>6.154000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2015</td>\n",
       "      <td>Booth</td>\n",
       "      <td>4.965000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2015</td>\n",
       "      <td>CI</td>\n",
       "      <td>3.024000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2015</td>\n",
       "      <td>IME</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2015</td>\n",
       "      <td>Others</td>\n",
       "      <td>1.902000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2015</td>\n",
       "      <td>PSD</td>\n",
       "      <td>24.585671</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2016</td>\n",
       "      <td>BSD</td>\n",
       "      <td>14.941000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2016</td>\n",
       "      <td>Booth</td>\n",
       "      <td>5.385775</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2016</td>\n",
       "      <td>CI</td>\n",
       "      <td>2.294000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2016</td>\n",
       "      <td>IME</td>\n",
       "      <td>4.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2016</td>\n",
       "      <td>Others</td>\n",
       "      <td>4.467100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2016</td>\n",
       "      <td>PSD</td>\n",
       "      <td>19.898500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2017</td>\n",
       "      <td>BSD</td>\n",
       "      <td>19.838381</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2017</td>\n",
       "      <td>Booth</td>\n",
       "      <td>8.534344</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2017</td>\n",
       "      <td>CI</td>\n",
       "      <td>2.480508</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2017</td>\n",
       "      <td>IME</td>\n",
       "      <td>9.618487</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2017</td>\n",
       "      <td>Others</td>\n",
       "      <td>6.262881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2017</td>\n",
       "      <td>PSD</td>\n",
       "      <td>37.535825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>2018</td>\n",
       "      <td>BSD</td>\n",
       "      <td>25.522911</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>2018</td>\n",
       "      <td>Booth</td>\n",
       "      <td>12.987813</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>2018</td>\n",
       "      <td>CI</td>\n",
       "      <td>5.129563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>2018</td>\n",
       "      <td>IME</td>\n",
       "      <td>11.164758</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>2018</td>\n",
       "      <td>Others</td>\n",
       "      <td>11.904631</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>2018</td>\n",
       "      <td>PSD</td>\n",
       "      <td>46.442381</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    cycle    unit  allocation\n",
       "0    2013     BSD    1.310000\n",
       "1    2013   Booth    0.205000\n",
       "2    2013      CI    0.550000\n",
       "3    2013     IME    2.000000\n",
       "4    2013  Others    0.050000\n",
       "5    2013     PSD    5.130000\n",
       "6    2014     BSD    3.939000\n",
       "7    2014   Booth    3.581000\n",
       "8    2014      CI    1.450000\n",
       "9    2014     IME    1.480000\n",
       "10   2014  Others    1.000000\n",
       "11   2014     PSD   14.379000\n",
       "12   2015     BSD    6.154000\n",
       "13   2015   Booth    4.965000\n",
       "14   2015      CI    3.024000\n",
       "15   2015     IME    3.000000\n",
       "16   2015  Others    1.902000\n",
       "17   2015     PSD   24.585671\n",
       "18   2016     BSD   14.941000\n",
       "19   2016   Booth    5.385775\n",
       "20   2016      CI    2.294000\n",
       "21   2016     IME    4.750000\n",
       "22   2016  Others    4.467100\n",
       "23   2016     PSD   19.898500\n",
       "24   2017     BSD   19.838381\n",
       "25   2017   Booth    8.534344\n",
       "26   2017      CI    2.480508\n",
       "27   2017     IME    9.618487\n",
       "28   2017  Others    6.262881\n",
       "29   2017     PSD   37.535825\n",
       "30   2018     BSD   25.522911\n",
       "31   2018   Booth   12.987813\n",
       "32   2018      CI    5.129563\n",
       "33   2018     IME   11.164758\n",
       "34   2018  Others   11.904631\n",
       "35   2018     PSD   46.442381"
      ]
     },
     "execution_count": 174,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unit_all = alloc_unit\n",
    "unit_all['unit2'] = unit_all['unit']\n",
    "unit_all['unit'] = list(unit_all.unit2.astype(\"category\", ordered = True, categories = alloc_top_5))\n",
    "unit_all = unit_all.fillna('Others').groupby(['cycle','unit'])['allocation'].sum().to_frame()\n",
    "unit_all = unit_all.reset_index()\n",
    "unit_all['allocation'] = unit_all['allocation'] /1000000\n",
    "unit_all"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Od+jatSsvvfQSN910Ey+++CL3339/ESuVJEmlZMhrI6ZNm8a1117LLbfcwkkn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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f973a8d4048>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "unit_by_cycle = unit_all.pivot(index='cycle', columns='unit', values='allocation')\n",
    "\n",
    "mmm = unit_by_cycle.loc[:,alloc_top_5].plot(kind='bar', stacked=True, title='Allocation',colormap='Paired')\n",
    "mmm.title.set_size(30)\n",
    "fig = mmm.get_figure()\n",
    "\n",
    "plt.ylabel('Allocation in millions', fontsize=18)\n",
    "plt.xlabel('Cycle', fontsize=16)\n",
    "plt.legend(fontsize=15);                                                         ## lengend size\n",
    "mmm.xaxis.set_tick_params(labelsize=15)                                             ## tick size\n",
    "mmm.yaxis.set_tick_params(labelsize=15)\n",
    "fig.set_size_inches(10, 8)                                                        ## figure size \n",
    "\n",
    "fig.savefig('image/2_2_allocs_amounts.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Allocation : Portion "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cycle</th>\n",
       "      <th>unit</th>\n",
       "      <th>allocation</th>\n",
       "      <th>Allocation_Portion</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2013</td>\n",
       "      <td>BSD</td>\n",
       "      <td>1.310000</td>\n",
       "      <td>0.141698</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2013</td>\n",
       "      <td>Booth</td>\n",
       "      <td>0.205000</td>\n",
       "      <td>0.022174</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2013</td>\n",
       "      <td>CI</td>\n",
       "      <td>0.550000</td>\n",
       "      <td>0.059492</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2013</td>\n",
       "      <td>IME</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.216333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2013</td>\n",
       "      <td>Others</td>\n",
       "      <td>0.050000</td>\n",
       "      <td>0.005408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2013</td>\n",
       "      <td>PSD</td>\n",
       "      <td>5.130000</td>\n",
       "      <td>0.554895</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2014</td>\n",
       "      <td>BSD</td>\n",
       "      <td>3.939000</td>\n",
       "      <td>0.152503</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2014</td>\n",
       "      <td>Booth</td>\n",
       "      <td>3.581000</td>\n",
       "      <td>0.138643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2014</td>\n",
       "      <td>CI</td>\n",
       "      <td>1.450000</td>\n",
       "      <td>0.056138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2014</td>\n",
       "      <td>IME</td>\n",
       "      <td>1.480000</td>\n",
       "      <td>0.057300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2014</td>\n",
       "      <td>Others</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.038716</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2014</td>\n",
       "      <td>PSD</td>\n",
       "      <td>14.379000</td>\n",
       "      <td>0.556700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2015</td>\n",
       "      <td>BSD</td>\n",
       "      <td>6.154000</td>\n",
       "      <td>0.141048</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2015</td>\n",
       "      <td>Booth</td>\n",
       "      <td>4.965000</td>\n",
       "      <td>0.113796</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2015</td>\n",
       "      <td>CI</td>\n",
       "      <td>3.024000</td>\n",
       "      <td>0.069309</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2015</td>\n",
       "      <td>IME</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.068759</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2015</td>\n",
       "      <td>Others</td>\n",
       "      <td>1.902000</td>\n",
       "      <td>0.043593</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2015</td>\n",
       "      <td>PSD</td>\n",
       "      <td>24.585671</td>\n",
       "      <td>0.563495</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2016</td>\n",
       "      <td>BSD</td>\n",
       "      <td>14.941000</td>\n",
       "      <td>0.288791</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2016</td>\n",
       "      <td>Booth</td>\n",
       "      <td>5.385775</td>\n",
       "      <td>0.104100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2016</td>\n",
       "      <td>CI</td>\n",
       "      <td>2.294000</td>\n",
       "      <td>0.044340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2016</td>\n",
       "      <td>IME</td>\n",
       "      <td>4.750000</td>\n",
       "      <td>0.091812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2016</td>\n",
       "      <td>Others</td>\n",
       "      <td>4.467100</td>\n",
       "      <td>0.086344</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2016</td>\n",
       "      <td>PSD</td>\n",
       "      <td>19.898500</td>\n",
       "      <td>0.384613</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2017</td>\n",
       "      <td>BSD</td>\n",
       "      <td>19.838381</td>\n",
       "      <td>0.235413</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2017</td>\n",
       "      <td>Booth</td>\n",
       "      <td>8.534344</td>\n",
       "      <td>0.101273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2017</td>\n",
       "      <td>CI</td>\n",
       "      <td>2.480508</td>\n",
       "      <td>0.029435</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2017</td>\n",
       "      <td>IME</td>\n",
       "      <td>9.618487</td>\n",
       "      <td>0.114138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2017</td>\n",
       "      <td>Others</td>\n",
       "      <td>6.262881</td>\n",
       "      <td>0.074319</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2017</td>\n",
       "      <td>PSD</td>\n",
       "      <td>37.535825</td>\n",
       "      <td>0.445421</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>2018</td>\n",
       "      <td>BSD</td>\n",
       "      <td>25.522911</td>\n",
       "      <td>0.225563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>2018</td>\n",
       "      <td>Booth</td>\n",
       "      <td>12.987813</td>\n",
       "      <td>0.114782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>2018</td>\n",
       "      <td>CI</td>\n",
       "      <td>5.129563</td>\n",
       "      <td>0.045333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>2018</td>\n",
       "      <td>IME</td>\n",
       "      <td>11.164758</td>\n",
       "      <td>0.098670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>2018</td>\n",
       "      <td>Others</td>\n",
       "      <td>11.904631</td>\n",
       "      <td>0.105209</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>2018</td>\n",
       "      <td>PSD</td>\n",
       "      <td>46.442381</td>\n",
       "      <td>0.410442</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    cycle    unit  allocation  Allocation_Portion\n",
       "0    2013     BSD    1.310000            0.141698\n",
       "1    2013   Booth    0.205000            0.022174\n",
       "2    2013      CI    0.550000            0.059492\n",
       "3    2013     IME    2.000000            0.216333\n",
       "4    2013  Others    0.050000            0.005408\n",
       "5    2013     PSD    5.130000            0.554895\n",
       "6    2014     BSD    3.939000            0.152503\n",
       "7    2014   Booth    3.581000            0.138643\n",
       "8    2014      CI    1.450000            0.056138\n",
       "9    2014     IME    1.480000            0.057300\n",
       "10   2014  Others    1.000000            0.038716\n",
       "11   2014     PSD   14.379000            0.556700\n",
       "12   2015     BSD    6.154000            0.141048\n",
       "13   2015   Booth    4.965000            0.113796\n",
       "14   2015      CI    3.024000            0.069309\n",
       "15   2015     IME    3.000000            0.068759\n",
       "16   2015  Others    1.902000            0.043593\n",
       "17   2015     PSD   24.585671            0.563495\n",
       "18   2016     BSD   14.941000            0.288791\n",
       "19   2016   Booth    5.385775            0.104100\n",
       "20   2016      CI    2.294000            0.044340\n",
       "21   2016     IME    4.750000            0.091812\n",
       "22   2016  Others    4.467100            0.086344\n",
       "23   2016     PSD   19.898500            0.384613\n",
       "24   2017     BSD   19.838381            0.235413\n",
       "25   2017   Booth    8.534344            0.101273\n",
       "26   2017      CI    2.480508            0.029435\n",
       "27   2017     IME    9.618487            0.114138\n",
       "28   2017  Others    6.262881            0.074319\n",
       "29   2017     PSD   37.535825            0.445421\n",
       "30   2018     BSD   25.522911            0.225563\n",
       "31   2018   Booth   12.987813            0.114782\n",
       "32   2018      CI    5.129563            0.045333\n",
       "33   2018     IME   11.164758            0.098670\n",
       "34   2018  Others   11.904631            0.105209\n",
       "35   2018     PSD   46.442381            0.410442"
      ]
     },
     "execution_count": 176,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "totals = list(unit_all.groupby(['cycle'])['allocation'].sum())\n",
    "unit_portion = unit_all  # copy table for portion part\n",
    "for i in cycles:  #unit_portion is from previous copy of unit_all\n",
    "    unit_portion.loc[unit_portion['cycle'] == i , 'Allocation_Portion'] = unit_portion.loc[unit_portion['cycle'] == i , 'allocation']/ totals[i-2013]\n",
    "unit_portion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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aohJnklK37f07NNLskLauLUrGqzEVnCXrV8hIA88L8USJ1acZZ6lHJRYbhwbO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T3P2l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\nrkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f973a13f898>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "por = unit_portion.pivot(index='cycle', columns='unit', values='Allocation_Portion')  \n",
    "ax = por.loc[:,alloc_top_5].plot.area(title='Allocation Proportion',colormap='Paired')\n",
    "ax.title.set_size(30)\n",
    "fig=ax.get_figure();\n",
    "plt.ylabel('Allocation Proportion', fontsize=18)\n",
    "plt.xlabel('Cycle', fontsize=16)\n",
    "plt.legend(fontsize=15);                                                         ## lengend size\n",
    "ax.xaxis.set_tick_params(labelsize=15)                                             ## tick size\n",
    "ax.yaxis.set_tick_params(labelsize=15)\n",
    "fig.set_size_inches(10, 8)                                                        ## figure size \n",
    "\n",
    "fig.savefig('image/2_2_allocs_fractions.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Usage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {
    "collapsed": true,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "usa = pd.read_csv('rawdata/usages_by_cycle_group.csv')\n",
    "\n",
    "le = le.rename(columns={'usage':'su'})\n",
    "usa = usa.append(le)[['account','su','cycle']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cycle</th>\n",
       "      <th>unit</th>\n",
       "      <th>su</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2013</td>\n",
       "      <td>BSD</td>\n",
       "      <td>2220635.78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2013</td>\n",
       "      <td>Booth</td>\n",
       "      <td>507253.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2013</td>\n",
       "      <td>CI</td>\n",
       "      <td>268501.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2013</td>\n",
       "      <td>Harris</td>\n",
       "      <td>6798.22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2013</td>\n",
       "      <td>Humanities</td>\n",
       "      <td>940.58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2013</td>\n",
       "      <td>IME</td>\n",
       "      <td>5747291.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2013</td>\n",
       "      <td>PSD</td>\n",
       "      <td>8181956.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2013</td>\n",
       "      <td>RCC</td>\n",
       "      <td>220127.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2013</td>\n",
       "      <td>SSD</td>\n",
       "      <td>31942.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2014</td>\n",
       "      <td>BFI</td>\n",
       "      <td>878.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2014</td>\n",
       "      <td>BSD</td>\n",
       "      <td>3050530.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2014</td>\n",
       "      <td>Booth</td>\n",
       "      <td>829034.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2014</td>\n",
       "      <td>CI</td>\n",
       "      <td>1203668.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2014</td>\n",
       "      <td>College</td>\n",
       "      <td>52118.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2014</td>\n",
       "      <td>Harris</td>\n",
       "      <td>5225.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2014</td>\n",
       "      <td>Humanities</td>\n",
       "      <td>18572.52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2014</td>\n",
       "      <td>IME</td>\n",
       "      <td>6919511.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2014</td>\n",
       "      <td>PSD</td>\n",
       "      <td>11440321.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2014</td>\n",
       "      <td>RCC</td>\n",
       "      <td>571642.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2014</td>\n",
       "      <td>SSD</td>\n",
       "      <td>950824.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2015</td>\n",
       "      <td>BFI</td>\n",
       "      <td>980.53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2015</td>\n",
       "      <td>BSD</td>\n",
       "      <td>4102389.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2015</td>\n",
       "      <td>Booth</td>\n",
       "      <td>1469951.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2015</td>\n",
       "      <td>CI</td>\n",
       "      <td>1478827.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2015</td>\n",
       "      <td>College</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2015</td>\n",
       "      <td>EPIC</td>\n",
       "      <td>114.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2015</td>\n",
       "      <td>Graham</td>\n",
       "      <td>55718.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2015</td>\n",
       "      <td>Harris</td>\n",
       "      <td>99699.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2015</td>\n",
       "      <td>Humanities</td>\n",
       "      <td>15644.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2015</td>\n",
       "      <td>IME</td>\n",
       "      <td>5498667.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>2016</td>\n",
       "      <td>SSD</td>\n",
       "      <td>494290.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>2017</td>\n",
       "      <td>BSD</td>\n",
       "      <td>10992230.79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>2017</td>\n",
       "      <td>Booth</td>\n",
       "      <td>2663407.69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>2017</td>\n",
       "      <td>CARS</td>\n",
       "      <td>746.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>2017</td>\n",
       "      <td>CI</td>\n",
       "      <td>1865960.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>2017</td>\n",
       "      <td>College</td>\n",
       "      <td>201616.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>2017</td>\n",
       "      <td>EPIC</td>\n",
       "      <td>3136.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>2017</td>\n",
       "      <td>Graham</td>\n",
       "      <td>54783.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>2017</td>\n",
       "      <td>Harris</td>\n",
       "      <td>34298.92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>2017</td>\n",
       "      <td>Humanities</td>\n",
       "      <td>12765.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>2017</td>\n",
       "      <td>IME</td>\n",
       "      <td>13931184.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>2017</td>\n",
       "      <td>Medicine</td>\n",
       "      <td>1307154.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>2017</td>\n",
       "      <td>PSD</td>\n",
       "      <td>28711896.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>2017</td>\n",
       "      <td>RCC</td>\n",
       "      <td>732699.62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>2017</td>\n",
       "      <td>SSD</td>\n",
       "      <td>3304004.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>2018</td>\n",
       "      <td>BFI</td>\n",
       "      <td>31.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>2018</td>\n",
       "      <td>BSD</td>\n",
       "      <td>8873267.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>2018</td>\n",
       "      <td>Booth</td>\n",
       "      <td>5313257.88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>2018</td>\n",
       "      <td>CI</td>\n",
       "      <td>1382778.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>2018</td>\n",
       "      <td>College</td>\n",
       "      <td>131550.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>2018</td>\n",
       "      <td>EPIC</td>\n",
       "      <td>2.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>2018</td>\n",
       "      <td>Graham</td>\n",
       "      <td>168446.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>2018</td>\n",
       "      <td>Harris</td>\n",
       "      <td>53207.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>2018</td>\n",
       "      <td>Humanities</td>\n",
       "      <td>1713.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>2018</td>\n",
       "      <td>IME</td>\n",
       "      <td>8457674.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>2018</td>\n",
       "      <td>Law</td>\n",
       "      <td>24.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>2018</td>\n",
       "      <td>Medicine</td>\n",
       "      <td>3125881.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>2018</td>\n",
       "      <td>PSD</td>\n",
       "      <td>22989163.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>2018</td>\n",
       "      <td>RCC</td>\n",
       "      <td>145180.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>2018</td>\n",
       "      <td>SSD</td>\n",
       "      <td>635256.66</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>76 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    cycle        unit           su\n",
       "0    2013         BSD   2220635.78\n",
       "1    2013       Booth    507253.94\n",
       "2    2013          CI    268501.94\n",
       "3    2013      Harris      6798.22\n",
       "4    2013  Humanities       940.58\n",
       "5    2013         IME   5747291.37\n",
       "6    2013         PSD   8181956.05\n",
       "7    2013         RCC    220127.27\n",
       "8    2013         SSD     31942.47\n",
       "9    2014         BFI       878.50\n",
       "10   2014         BSD   3050530.40\n",
       "11   2014       Booth    829034.84\n",
       "12   2014          CI   1203668.21\n",
       "13   2014     College     52118.11\n",
       "14   2014      Harris      5225.11\n",
       "15   2014  Humanities     18572.52\n",
       "16   2014         IME   6919511.97\n",
       "17   2014         PSD  11440321.87\n",
       "18   2014         RCC    571642.44\n",
       "19   2014         SSD    950824.94\n",
       "20   2015         BFI       980.53\n",
       "21   2015         BSD   4102389.08\n",
       "22   2015       Booth   1469951.37\n",
       "23   2015          CI   1478827.03\n",
       "24   2015     College         0.00\n",
       "25   2015        EPIC       114.17\n",
       "26   2015      Graham     55718.50\n",
       "27   2015      Harris     99699.05\n",
       "28   2015  Humanities     15644.04\n",
       "29   2015         IME   5498667.09\n",
       "..    ...         ...          ...\n",
       "46   2016         SSD    494290.66\n",
       "47   2017         BSD  10992230.79\n",
       "48   2017       Booth   2663407.69\n",
       "49   2017        CARS       746.32\n",
       "50   2017          CI   1865960.57\n",
       "51   2017     College    201616.73\n",
       "52   2017        EPIC      3136.10\n",
       "53   2017      Graham     54783.73\n",
       "54   2017      Harris     34298.92\n",
       "55   2017  Humanities     12765.98\n",
       "56   2017         IME  13931184.57\n",
       "57   2017    Medicine   1307154.23\n",
       "58   2017         PSD  28711896.35\n",
       "59   2017         RCC    732699.62\n",
       "60   2017         SSD   3304004.80\n",
       "61   2018         BFI        31.98\n",
       "62   2018         BSD   8873267.41\n",
       "63   2018       Booth   5313257.88\n",
       "64   2018          CI   1382778.17\n",
       "65   2018     College    131550.12\n",
       "66   2018        EPIC         2.00\n",
       "67   2018      Graham    168446.50\n",
       "68   2018      Harris     53207.29\n",
       "69   2018  Humanities      1713.86\n",
       "70   2018         IME   8457674.95\n",
       "71   2018         Law        24.01\n",
       "72   2018    Medicine   3125881.08\n",
       "73   2018         PSD  22989163.37\n",
       "74   2018         RCC    145180.68\n",
       "75   2018         SSD    635256.66\n",
       "\n",
       "[76 rows x 3 columns]"
      ]
     },
     "execution_count": 179,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ss = usa.join(unit.set_index('account'), on='account')\n",
    "usage_unit = ss[['cycle','unit','su']]\n",
    "usage_unit = usage_unit.groupby(['cycle','unit'])['su'].sum().to_frame().reset_index()\n",
    "usage_unit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['PSD', 'IME', 'BSD', 'Booth', 'CI', 'Others']"
      ]
     },
     "execution_count": 180,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "us = usage_unit.groupby('unit')['su'].sum().to_frame().\\\n",
    "sort_values('su', ascending=False).reset_index()\n",
    "\n",
    "leng = list(us.count())[0]\n",
    "other = us.loc[5:leng, ['unit','su']].sum().to_frame().T\n",
    "other['unit'][0]='Others'\n",
    "\n",
    "top = us.drop(us.index[range(5,leng)])\n",
    "top = top.append(other, ignore_index=True)\n",
    "usage_top_5 = list(top['unit'])                      # Important Note:\n",
    "usage_top_5   # since we find the top 5 of allocations and usages are the same, we use \"alloc_top_5\" \n",
    "              # in place of \"usage_top_5\" for color in later part to keep the order of divisions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "metadata": {
    "collapsed": true,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "unit_con = usage_unit\n",
    "unit_con['unit'] = list(usage_unit.unit.astype(\"category\", ordered=True, categories=usage_top_5))\n",
    "unit_con = unit_con.fillna('Others').groupby(['cycle','unit'])['su'].sum().to_frame()\n",
    "unit_con = unit_con.reset_index()\n",
    "unit_con['su'] = unit_con['su'] /1000000\n",
    "\n",
    "import os.path, time\n",
    "Last_data = time.ctime(os.path.getmtime('rawdata/usages_by_cycle_group.csv')) #'Mon May  7 16:29:32 2018'\n",
    "Last_data = datetime.strptime(Last_data,'%c').strftime('%x') #change format\n",
    "from datetime import datetime\n",
    "a = datetime.strptime(Last_data, '%x') # days up to the usage record\n",
    "b = datetime.strptime('9/30/17', '%x') # beginning of last year\n",
    "gap_day = (a - b).days  # gap_day = 219\n",
    "\n",
    "unit_con['su_projected'] = unit_con['su']\n",
    "unit_con.iloc[-6:-1, -1] = unit_con['su'].iloc[-6:-1] * 365 / gap_day\n",
    "usage_portion = unit_con # for portion part"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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JaiEGuDYiIkpdgiRJaiEGuJzr3r07HTp0YOHChaUuRZIktRADXM6VlZVx4IEH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\n6zL/Az8ekg0kWZUFAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f973a1acf98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "unit_by_cycle = unit_con.pivot(index='cycle', columns='unit', values='su_projected')\n",
    "\n",
    "mmm = unit_by_cycle.loc[:,alloc_top_5].plot(kind='bar', stacked=True, title='Usage',colormap='Paired')\n",
    "mmm.title.set_size(30)\n",
    "fig = mmm.get_figure()\n",
    "\n",
    "plt.ylabel('Usage in millions', fontsize=18)\n",
    "plt.xlabel('Cycle', fontsize=16)\n",
    "plt.legend(fontsize=15);                                                         ## lengend size\n",
    "mmm.xaxis.set_tick_params(labelsize=15)                                             ## tick size\n",
    "mmm.yaxis.set_tick_params(labelsize=15)\n",
    "fig.set_size_inches(10, 8)                                                        ## figure size \n",
    "\n",
    "fig.savefig('image/2_2_usages_amounts.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Usage Portion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cycle</th>\n",
       "      <th>unit</th>\n",
       "      <th>su</th>\n",
       "      <th>su_projected</th>\n",
       "      <th>Portion</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2013</td>\n",
       "      <td>BSD</td>\n",
       "      <td>2.220636</td>\n",
       "      <td>2.220636</td>\n",
       "      <td>0.129216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2013</td>\n",
       "      <td>Booth</td>\n",
       "      <td>0.507254</td>\n",
       "      <td>0.507254</td>\n",
       "      <td>0.029516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2013</td>\n",
       "      <td>CI</td>\n",
       "      <td>0.268502</td>\n",
       "      <td>0.268502</td>\n",
       "      <td>0.015624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2013</td>\n",
       "      <td>IME</td>\n",
       "      <td>5.747291</td>\n",
       "      <td>5.747291</td>\n",
       "      <td>0.334428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2013</td>\n",
       "      <td>Others</td>\n",
       "      <td>0.259809</td>\n",
       "      <td>0.259809</td>\n",
       "      <td>0.015118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2013</td>\n",
       "      <td>PSD</td>\n",
       "      <td>8.181956</td>\n",
       "      <td>8.181956</td>\n",
       "      <td>0.476098</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2014</td>\n",
       "      <td>BSD</td>\n",
       "      <td>3.050530</td>\n",
       "      <td>3.050530</td>\n",
       "      <td>0.121815</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2014</td>\n",
       "      <td>Booth</td>\n",
       "      <td>0.829035</td>\n",
       "      <td>0.829035</td>\n",
       "      <td>0.033105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2014</td>\n",
       "      <td>CI</td>\n",
       "      <td>1.203668</td>\n",
       "      <td>1.203668</td>\n",
       "      <td>0.048065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2014</td>\n",
       "      <td>IME</td>\n",
       "      <td>6.919512</td>\n",
       "      <td>6.919512</td>\n",
       "      <td>0.276313</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2014</td>\n",
       "      <td>Others</td>\n",
       "      <td>1.599262</td>\n",
       "      <td>1.599262</td>\n",
       "      <td>0.063862</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2014</td>\n",
       "      <td>PSD</td>\n",
       "      <td>11.440322</td>\n",
       "      <td>11.440322</td>\n",
       "      <td>0.456839</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2015</td>\n",
       "      <td>BSD</td>\n",
       "      <td>4.102389</td>\n",
       "      <td>4.102389</td>\n",
       "      <td>0.150364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2015</td>\n",
       "      <td>Booth</td>\n",
       "      <td>1.469951</td>\n",
       "      <td>1.469951</td>\n",
       "      <td>0.053878</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2015</td>\n",
       "      <td>CI</td>\n",
       "      <td>1.478827</td>\n",
       "      <td>1.478827</td>\n",
       "      <td>0.054203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2015</td>\n",
       "      <td>IME</td>\n",
       "      <td>5.498667</td>\n",
       "      <td>5.498667</td>\n",
       "      <td>0.201542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2015</td>\n",
       "      <td>Others</td>\n",
       "      <td>1.494205</td>\n",
       "      <td>1.494205</td>\n",
       "      <td>0.054767</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2015</td>\n",
       "      <td>PSD</td>\n",
       "      <td>13.238976</td>\n",
       "      <td>13.238976</td>\n",
       "      <td>0.485246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2016</td>\n",
       "      <td>BSD</td>\n",
       "      <td>5.235670</td>\n",
       "      <td>5.235670</td>\n",
       "      <td>0.195815</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2016</td>\n",
       "      <td>Booth</td>\n",
       "      <td>4.747054</td>\n",
       "      <td>4.747054</td>\n",
       "      <td>0.177541</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2016</td>\n",
       "      <td>CI</td>\n",
       "      <td>0.863687</td>\n",
       "      <td>0.863687</td>\n",
       "      <td>0.032302</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2016</td>\n",
       "      <td>IME</td>\n",
       "      <td>2.805836</td>\n",
       "      <td>2.805836</td>\n",
       "      <td>0.104939</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2016</td>\n",
       "      <td>Others</td>\n",
       "      <td>2.100525</td>\n",
       "      <td>2.100525</td>\n",
       "      <td>0.078560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2016</td>\n",
       "      <td>PSD</td>\n",
       "      <td>10.985008</td>\n",
       "      <td>10.985008</td>\n",
       "      <td>0.410842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2017</td>\n",
       "      <td>BSD</td>\n",
       "      <td>10.992231</td>\n",
       "      <td>10.992231</td>\n",
       "      <td>0.172249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2017</td>\n",
       "      <td>Booth</td>\n",
       "      <td>2.663408</td>\n",
       "      <td>2.663408</td>\n",
       "      <td>0.041736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2017</td>\n",
       "      <td>CI</td>\n",
       "      <td>1.865961</td>\n",
       "      <td>1.865961</td>\n",
       "      <td>0.029240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2017</td>\n",
       "      <td>IME</td>\n",
       "      <td>13.931185</td>\n",
       "      <td>13.931185</td>\n",
       "      <td>0.218303</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2017</td>\n",
       "      <td>Others</td>\n",
       "      <td>5.651206</td>\n",
       "      <td>5.651206</td>\n",
       "      <td>0.088555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2017</td>\n",
       "      <td>PSD</td>\n",
       "      <td>28.711896</td>\n",
       "      <td>28.711896</td>\n",
       "      <td>0.449918</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>2018</td>\n",
       "      <td>BSD</td>\n",
       "      <td>8.873267</td>\n",
       "      <td>14.788779</td>\n",
       "      <td>0.210858</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>2018</td>\n",
       "      <td>Booth</td>\n",
       "      <td>5.313258</td>\n",
       "      <td>8.855430</td>\n",
       "      <td>0.126260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>2018</td>\n",
       "      <td>CI</td>\n",
       "      <td>1.382778</td>\n",
       "      <td>2.304630</td>\n",
       "      <td>0.032859</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>2018</td>\n",
       "      <td>IME</td>\n",
       "      <td>8.457675</td>\n",
       "      <td>14.096125</td>\n",
       "      <td>0.200982</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>2018</td>\n",
       "      <td>Others</td>\n",
       "      <td>4.261294</td>\n",
       "      <td>7.102157</td>\n",
       "      <td>0.101262</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>2018</td>\n",
       "      <td>PSD</td>\n",
       "      <td>22.989163</td>\n",
       "      <td>22.989163</td>\n",
       "      <td>0.327778</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    cycle    unit         su  su_projected   Portion\n",
       "0    2013     BSD   2.220636      2.220636  0.129216\n",
       "1    2013   Booth   0.507254      0.507254  0.029516\n",
       "2    2013      CI   0.268502      0.268502  0.015624\n",
       "3    2013     IME   5.747291      5.747291  0.334428\n",
       "4    2013  Others   0.259809      0.259809  0.015118\n",
       "5    2013     PSD   8.181956      8.181956  0.476098\n",
       "6    2014     BSD   3.050530      3.050530  0.121815\n",
       "7    2014   Booth   0.829035      0.829035  0.033105\n",
       "8    2014      CI   1.203668      1.203668  0.048065\n",
       "9    2014     IME   6.919512      6.919512  0.276313\n",
       "10   2014  Others   1.599262      1.599262  0.063862\n",
       "11   2014     PSD  11.440322     11.440322  0.456839\n",
       "12   2015     BSD   4.102389      4.102389  0.150364\n",
       "13   2015   Booth   1.469951      1.469951  0.053878\n",
       "14   2015      CI   1.478827      1.478827  0.054203\n",
       "15   2015     IME   5.498667      5.498667  0.201542\n",
       "16   2015  Others   1.494205      1.494205  0.054767\n",
       "17   2015     PSD  13.238976     13.238976  0.485246\n",
       "18   2016     BSD   5.235670      5.235670  0.195815\n",
       "19   2016   Booth   4.747054      4.747054  0.177541\n",
       "20   2016      CI   0.863687      0.863687  0.032302\n",
       "21   2016     IME   2.805836      2.805836  0.104939\n",
       "22   2016  Others   2.100525      2.100525  0.078560\n",
       "23   2016     PSD  10.985008     10.985008  0.410842\n",
       "24   2017     BSD  10.992231     10.992231  0.172249\n",
       "25   2017   Booth   2.663408      2.663408  0.041736\n",
       "26   2017      CI   1.865961      1.865961  0.029240\n",
       "27   2017     IME  13.931185     13.931185  0.218303\n",
       "28   2017  Others   5.651206      5.651206  0.088555\n",
       "29   2017     PSD  28.711896     28.711896  0.449918\n",
       "30   2018     BSD   8.873267     14.788779  0.210858\n",
       "31   2018   Booth   5.313258      8.855430  0.126260\n",
       "32   2018      CI   1.382778      2.304630  0.032859\n",
       "33   2018     IME   8.457675     14.096125  0.200982\n",
       "34   2018  Others   4.261294      7.102157  0.101262\n",
       "35   2018     PSD  22.989163     22.989163  0.327778"
      ]
     },
     "execution_count": 183,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "totals = list(unit_con.groupby(['cycle'])['su_projected'].sum())\n",
    "\n",
    "for i in cycles:  #usage_portion is from previous copy of unit_all, cycles is from Allocation Portion\n",
    "    usage_portion.loc[usage_portion['cycle'] == i , 'Portion'] = usage_portion.loc[usage_portion['cycle'] == i , 'su_projected']/ totals[i-2013]\n",
    "usage_portion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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09btAaFp+fOJcxhtnMFyc4NV7P8fr9n2GicYw3x67gnvHDvLAsUuYSZRlE+mH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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f973a9eb0f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "por = usage_portion.pivot(index='cycle', columns='unit', values='Portion')  \n",
    "ax = por.loc[:,alloc_top_5].plot.area(title='Usage Proportion',colormap='Paired')\n",
    "ax.title.set_size(30)\n",
    "fig=ax.get_figure();\n",
    "plt.ylabel('Usage Proportion', fontsize=18)\n",
    "plt.xlabel('Cycle', fontsize=16)\n",
    "plt.legend(fontsize=15);                                                         ## lengend size\n",
    "ax.xaxis.set_tick_params(labelsize=15)                                             ## tick size\n",
    "ax.yaxis.set_tick_params(labelsize=15)\n",
    "fig.set_size_inches(10, 8)                                                        ## figure size \n",
    "\n",
    "fig.savefig('image/2_2_usages_fractions.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### put allocation and usage table together"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cycle</th>\n",
       "      <th>unit</th>\n",
       "      <th>Allocation</th>\n",
       "      <th>Allocation_Portion</th>\n",
       "      <th>Consumed</th>\n",
       "      <th>Comsumed_portion</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2013</td>\n",
       "      <td>BSD</td>\n",
       "      <td>1.310000</td>\n",
       "      <td>0.141698</td>\n",
       "      <td>2.220636</td>\n",
       "      <td>0.129216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2013</td>\n",
       "      <td>Booth</td>\n",
       "      <td>0.205000</td>\n",
       "      <td>0.022174</td>\n",
       "      <td>0.507254</td>\n",
       "      <td>0.029516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2013</td>\n",
       "      <td>CI</td>\n",
       "      <td>0.550000</td>\n",
       "      <td>0.059492</td>\n",
       "      <td>0.268502</td>\n",
       "      <td>0.015624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2013</td>\n",
       "      <td>IME</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.216333</td>\n",
       "      <td>5.747291</td>\n",
       "      <td>0.334428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2013</td>\n",
       "      <td>Others</td>\n",
       "      <td>0.050000</td>\n",
       "      <td>0.005408</td>\n",
       "      <td>0.259809</td>\n",
       "      <td>0.015118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2013</td>\n",
       "      <td>PSD</td>\n",
       "      <td>5.130000</td>\n",
       "      <td>0.554895</td>\n",
       "      <td>8.181956</td>\n",
       "      <td>0.476098</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2014</td>\n",
       "      <td>BSD</td>\n",
       "      <td>3.939000</td>\n",
       "      <td>0.152503</td>\n",
       "      <td>3.050530</td>\n",
       "      <td>0.121815</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2014</td>\n",
       "      <td>Booth</td>\n",
       "      <td>3.581000</td>\n",
       "      <td>0.138643</td>\n",
       "      <td>0.829035</td>\n",
       "      <td>0.033105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2014</td>\n",
       "      <td>CI</td>\n",
       "      <td>1.450000</td>\n",
       "      <td>0.056138</td>\n",
       "      <td>1.203668</td>\n",
       "      <td>0.048065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2014</td>\n",
       "      <td>IME</td>\n",
       "      <td>1.480000</td>\n",
       "      <td>0.057300</td>\n",
       "      <td>6.919512</td>\n",
       "      <td>0.276313</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2014</td>\n",
       "      <td>Others</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.038716</td>\n",
       "      <td>1.599262</td>\n",
       "      <td>0.063862</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2014</td>\n",
       "      <td>PSD</td>\n",
       "      <td>14.379000</td>\n",
       "      <td>0.556700</td>\n",
       "      <td>11.440322</td>\n",
       "      <td>0.456839</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2015</td>\n",
       "      <td>BSD</td>\n",
       "      <td>6.154000</td>\n",
       "      <td>0.141048</td>\n",
       "      <td>4.102389</td>\n",
       "      <td>0.150364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2015</td>\n",
       "      <td>Booth</td>\n",
       "      <td>4.965000</td>\n",
       "      <td>0.113796</td>\n",
       "      <td>1.469951</td>\n",
       "      <td>0.053878</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2015</td>\n",
       "      <td>CI</td>\n",
       "      <td>3.024000</td>\n",
       "      <td>0.069309</td>\n",
       "      <td>1.478827</td>\n",
       "      <td>0.054203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2015</td>\n",
       "      <td>IME</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.068759</td>\n",
       "      <td>5.498667</td>\n",
       "      <td>0.201542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2015</td>\n",
       "      <td>Others</td>\n",
       "      <td>1.902000</td>\n",
       "      <td>0.043593</td>\n",
       "      <td>1.494205</td>\n",
       "      <td>0.054767</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2015</td>\n",
       "      <td>PSD</td>\n",
       "      <td>24.585671</td>\n",
       "      <td>0.563495</td>\n",
       "      <td>13.238976</td>\n",
       "      <td>0.485246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2016</td>\n",
       "      <td>BSD</td>\n",
       "      <td>14.941000</td>\n",
       "      <td>0.288791</td>\n",
       "      <td>5.235670</td>\n",
       "      <td>0.195815</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2016</td>\n",
       "      <td>Booth</td>\n",
       "      <td>5.385775</td>\n",
       "      <td>0.104100</td>\n",
       "      <td>4.747054</td>\n",
       "      <td>0.177541</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2016</td>\n",
       "      <td>CI</td>\n",
       "      <td>2.294000</td>\n",
       "      <td>0.044340</td>\n",
       "      <td>0.863687</td>\n",
       "      <td>0.032302</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2016</td>\n",
       "      <td>IME</td>\n",
       "      <td>4.750000</td>\n",
       "      <td>0.091812</td>\n",
       "      <td>2.805836</td>\n",
       "      <td>0.104939</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2016</td>\n",
       "      <td>Others</td>\n",
       "      <td>4.467100</td>\n",
       "      <td>0.086344</td>\n",
       "      <td>2.100525</td>\n",
       "      <td>0.078560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2016</td>\n",
       "      <td>PSD</td>\n",
       "      <td>19.898500</td>\n",
       "      <td>0.384613</td>\n",
       "      <td>10.985008</td>\n",
       "      <td>0.410842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2017</td>\n",
       "      <td>BSD</td>\n",
       "      <td>19.838381</td>\n",
       "      <td>0.235413</td>\n",
       "      <td>10.992231</td>\n",
       "      <td>0.172249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2017</td>\n",
       "      <td>Booth</td>\n",
       "      <td>8.534344</td>\n",
       "      <td>0.101273</td>\n",
       "      <td>2.663408</td>\n",
       "      <td>0.041736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2017</td>\n",
       "      <td>CI</td>\n",
       "      <td>2.480508</td>\n",
       "      <td>0.029435</td>\n",
       "      <td>1.865961</td>\n",
       "      <td>0.029240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2017</td>\n",
       "      <td>IME</td>\n",
       "      <td>9.618487</td>\n",
       "      <td>0.114138</td>\n",
       "      <td>13.931185</td>\n",
       "      <td>0.218303</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2017</td>\n",
       "      <td>Others</td>\n",
       "      <td>6.262881</td>\n",
       "      <td>0.074319</td>\n",
       "      <td>5.651206</td>\n",
       "      <td>0.088555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2017</td>\n",
       "      <td>PSD</td>\n",
       "      <td>37.535825</td>\n",
       "      <td>0.445421</td>\n",
       "      <td>28.711896</td>\n",
       "      <td>0.449918</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>2018</td>\n",
       "      <td>BSD</td>\n",
       "      <td>25.522911</td>\n",
       "      <td>0.225563</td>\n",
       "      <td>14.788779</td>\n",
       "      <td>0.210858</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>2018</td>\n",
       "      <td>Booth</td>\n",
       "      <td>12.987813</td>\n",
       "      <td>0.114782</td>\n",
       "      <td>8.855430</td>\n",
       "      <td>0.126260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>2018</td>\n",
       "      <td>CI</td>\n",
       "      <td>5.129563</td>\n",
       "      <td>0.045333</td>\n",
       "      <td>2.304630</td>\n",
       "      <td>0.032859</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>2018</td>\n",
       "      <td>IME</td>\n",
       "      <td>11.164758</td>\n",
       "      <td>0.098670</td>\n",
       "      <td>14.096125</td>\n",
       "      <td>0.200982</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>2018</td>\n",
       "      <td>Others</td>\n",
       "      <td>11.904631</td>\n",
       "      <td>0.105209</td>\n",
       "      <td>7.102157</td>\n",
       "      <td>0.101262</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>2018</td>\n",
       "      <td>PSD</td>\n",
       "      <td>46.442381</td>\n",
       "      <td>0.410442</td>\n",
       "      <td>22.989163</td>\n",
       "      <td>0.327778</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    cycle    unit  Allocation  Allocation_Portion   Consumed  Comsumed_portion\n",
       "0    2013     BSD    1.310000            0.141698   2.220636          0.129216\n",
       "1    2013   Booth    0.205000            0.022174   0.507254          0.029516\n",
       "2    2013      CI    0.550000            0.059492   0.268502          0.015624\n",
       "3    2013     IME    2.000000            0.216333   5.747291          0.334428\n",
       "4    2013  Others    0.050000            0.005408   0.259809          0.015118\n",
       "5    2013     PSD    5.130000            0.554895   8.181956          0.476098\n",
       "6    2014     BSD    3.939000            0.152503   3.050530          0.121815\n",
       "7    2014   Booth    3.581000            0.138643   0.829035          0.033105\n",
       "8    2014      CI    1.450000            0.056138   1.203668          0.048065\n",
       "9    2014     IME    1.480000            0.057300   6.919512          0.276313\n",
       "10   2014  Others    1.000000            0.038716   1.599262          0.063862\n",
       "11   2014     PSD   14.379000            0.556700  11.440322          0.456839\n",
       "12   2015     BSD    6.154000            0.141048   4.102389          0.150364\n",
       "13   2015   Booth    4.965000            0.113796   1.469951          0.053878\n",
       "14   2015      CI    3.024000            0.069309   1.478827          0.054203\n",
       "15   2015     IME    3.000000            0.068759   5.498667          0.201542\n",
       "16   2015  Others    1.902000            0.043593   1.494205          0.054767\n",
       "17   2015     PSD   24.585671            0.563495  13.238976          0.485246\n",
       "18   2016     BSD   14.941000            0.288791   5.235670          0.195815\n",
       "19   2016   Booth    5.385775            0.104100   4.747054          0.177541\n",
       "20   2016      CI    2.294000            0.044340   0.863687          0.032302\n",
       "21   2016     IME    4.750000            0.091812   2.805836          0.104939\n",
       "22   2016  Others    4.467100            0.086344   2.100525          0.078560\n",
       "23   2016     PSD   19.898500            0.384613  10.985008          0.410842\n",
       "24   2017     BSD   19.838381            0.235413  10.992231          0.172249\n",
       "25   2017   Booth    8.534344            0.101273   2.663408          0.041736\n",
       "26   2017      CI    2.480508            0.029435   1.865961          0.029240\n",
       "27   2017     IME    9.618487            0.114138  13.931185          0.218303\n",
       "28   2017  Others    6.262881            0.074319   5.651206          0.088555\n",
       "29   2017     PSD   37.535825            0.445421  28.711896          0.449918\n",
       "30   2018     BSD   25.522911            0.225563  14.788779          0.210858\n",
       "31   2018   Booth   12.987813            0.114782   8.855430          0.126260\n",
       "32   2018      CI    5.129563            0.045333   2.304630          0.032859\n",
       "33   2018     IME   11.164758            0.098670  14.096125          0.200982\n",
       "34   2018  Others   11.904631            0.105209   7.102157          0.101262\n",
       "35   2018     PSD   46.442381            0.410442  22.989163          0.327778"
      ]
     },
     "execution_count": 185,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unit_stat = unit_portion[['cycle','unit']]\n",
    "unit_stat['Allocation']         = unit_portion['allocation']\n",
    "unit_stat['Allocation_Portion'] = unit_portion['Allocation_Portion']\n",
    "unit_stat['Consumed']           = unit_con['su_projected']\n",
    "unit_stat['Comsumed_portion']   = usage_portion['Portion']\n",
    "unit_stat.to_csv('result/2_2_allocs_usags_by_units.csv')\n",
    "unit_stat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
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   "outputs": [],
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  {
   "cell_type": "code",
   "execution_count": null,
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   "source": []
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