imaging-asset-replacement.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import and wrangle data into a usable format"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Code below to import the dataset and the libraries we need. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>OrganisationCode</th>\n",
       "      <th>OrganisationName</th>\n",
       "      <th>NIDC Asset ID</th>\n",
       "      <th>Local Equipment Identifier</th>\n",
       "      <th>ODS Site Code</th>\n",
       "      <th>Location_Der</th>\n",
       "      <th>Machine_Type_Der</th>\n",
       "      <th>Modality_Der</th>\n",
       "      <th>Equipment Detail Der</th>\n",
       "      <th>Manufacture_Der</th>\n",
       "      <th>...</th>\n",
       "      <th>OOH_Operational_Hours_Mon_Fri</th>\n",
       "      <th>Core_Operational_Hours_Sat</th>\n",
       "      <th>OOH_Operational_Hours_Sat</th>\n",
       "      <th>Core_Operational_Hours_Sun</th>\n",
       "      <th>OOH_Operational_Hours_Sun</th>\n",
       "      <th>Ownership Structure</th>\n",
       "      <th>Ownership_Structure_Der</th>\n",
       "      <th>Capital Purchase Cost</th>\n",
       "      <th>Asset Status</th>\n",
       "      <th>Maintenance Type_Der</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>RDU</td>\n",
       "      <td>Frimley Health NHS Foundation Trust</td>\n",
       "      <td>A160</td>\n",
       "      <td>G3132152</td>\n",
       "      <td>RDU01</td>\n",
       "      <td>Angiography Suite</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>Ultrasound</td>\n",
       "      <td>Ultrasound - General</td>\n",
       "      <td>Hitachi Medical Systems</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>56704</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Asset Under Warranty</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>RDU</td>\n",
       "      <td>Frimley Health NHS Foundation Trust</td>\n",
       "      <td>A159</td>\n",
       "      <td>E49106</td>\n",
       "      <td>RDU54</td>\n",
       "      <td>Imaging Department</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>Ultrasound</td>\n",
       "      <td>Ultrasound - General</td>\n",
       "      <td>GE Medical Systems</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>56704</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Asset Under Warranty</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>RDU</td>\n",
       "      <td>Frimley Health NHS Foundation Trust</td>\n",
       "      <td>A158</td>\n",
       "      <td>IPX039543</td>\n",
       "      <td>RDU52</td>\n",
       "      <td>Imaging Department</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>Dental</td>\n",
       "      <td>Intraoral</td>\n",
       "      <td>Xograph</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>NaN</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Asset Under Warranty</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>RDU</td>\n",
       "      <td>Frimley Health NHS Foundation Trust</td>\n",
       "      <td>A157</td>\n",
       "      <td>TRI2100460</td>\n",
       "      <td>RDU52</td>\n",
       "      <td>Imaging Department</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>X ray Units Mobile</td>\n",
       "      <td>Plain X-Ray-DR Mobile</td>\n",
       "      <td>Hologic</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>NaN</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Asset Under Warranty</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>RDU</td>\n",
       "      <td>Frimley Health NHS Foundation Trust</td>\n",
       "      <td>A156</td>\n",
       "      <td>3DM160700888</td>\n",
       "      <td>RDU52</td>\n",
       "      <td>Imaging Department</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>Mammography</td>\n",
       "      <td>Symptomatic - Digital Mammography 2D + 3D Tomo...</td>\n",
       "      <td>Hologic</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>403800</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Asset Under Warranty</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  OrganisationCode                     OrganisationName NIDC Asset ID  \\\n",
       "0              RDU  Frimley Health NHS Foundation Trust          A160   \n",
       "1              RDU  Frimley Health NHS Foundation Trust          A159   \n",
       "2              RDU  Frimley Health NHS Foundation Trust          A158   \n",
       "3              RDU  Frimley Health NHS Foundation Trust          A157   \n",
       "4              RDU  Frimley Health NHS Foundation Trust          A156   \n",
       "\n",
       "  Local Equipment Identifier ODS Site Code        Location_Der  \\\n",
       "0                   G3132152         RDU01   Angiography Suite   \n",
       "1                     E49106         RDU54  Imaging Department   \n",
       "2                  IPX039543         RDU52  Imaging Department   \n",
       "3                 TRI2100460         RDU52  Imaging Department   \n",
       "4               3DM160700888         RDU52  Imaging Department   \n",
       "\n",
       "    Machine_Type_Der        Modality_Der  \\\n",
       "0  Image Acquisition          Ultrasound   \n",
       "1  Image Acquisition          Ultrasound   \n",
       "2  Image Acquisition              Dental   \n",
       "3  Image Acquisition  X ray Units Mobile   \n",
       "4  Image Acquisition         Mammography   \n",
       "\n",
       "                                Equipment Detail Der          Manufacture_Der  \\\n",
       "0                               Ultrasound - General  Hitachi Medical Systems   \n",
       "1                               Ultrasound - General       GE Medical Systems   \n",
       "2                                          Intraoral                  Xograph   \n",
       "3                              Plain X-Ray-DR Mobile                  Hologic   \n",
       "4  Symptomatic - Digital Mammography 2D + 3D Tomo...                  Hologic   \n",
       "\n",
       "   ... OOH_Operational_Hours_Mon_Fri  Core_Operational_Hours_Sat  \\\n",
       "0  ...                           0.0                         0.0   \n",
       "1  ...                           0.0                         0.0   \n",
       "2  ...                           0.0                        12.0   \n",
       "3  ...                           0.0                         0.0   \n",
       "4  ...                           0.0                         0.0   \n",
       "\n",
       "   OOH_Operational_Hours_Sat  Core_Operational_Hours_Sun  \\\n",
       "0                        0.0                         0.0   \n",
       "1                        0.0                         0.0   \n",
       "2                        0.0                        12.0   \n",
       "3                        0.0                         0.0   \n",
       "4                        0.0                         0.0   \n",
       "\n",
       "   OOH_Operational_Hours_Sun     Ownership Structure  Ownership_Structure_Der  \\\n",
       "0                        0.0  Capital purchase - new   Capital purchase - new   \n",
       "1                        0.0  Capital purchase - new   Capital purchase - new   \n",
       "2                        0.0  Capital purchase - new   Capital purchase - new   \n",
       "3                        0.0  Capital purchase - new   Capital purchase - new   \n",
       "4                        0.0  Capital purchase - new   Capital purchase - new   \n",
       "\n",
       "   Capital Purchase Cost Asset Status  Maintenance Type_Der  \n",
       "0                  56704   In Service  Asset Under Warranty  \n",
       "1                  56704   In Service  Asset Under Warranty  \n",
       "2                    NaN   In Service  Asset Under Warranty  \n",
       "3                    NaN   In Service  Asset Under Warranty  \n",
       "4                 403800   In Service  Asset Under Warranty  \n",
       "\n",
       "[5 rows x 23 columns]"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import msoffcrypto\n",
    "import io\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "# import for dash app ## this is a trial...\n",
    "import dash\n",
    "from dash import dcc, html\n",
    "import plotly.express as px\n",
    "import plotly.graph_objects as go\n",
    "from plotly.subplots import make_subplots\n",
    "import dash_core_components as dcc\n",
    "\n",
    "# Create an in-memory buffer\n",
    "temp = io.BytesIO()\n",
    "\n",
    "# Open the encrypted Excel file\n",
    "with open('C:/Users/martin.bloyce2/OneDrive - NHS/Documents - Regional ' +\n",
    "          'Analytics - South East/South East/Analysis/Diagnostics/Assets/' +\n",
    "          '2023-24/imaging-assets-replacements/imaging-assets-replacement/' +\n",
    "          'data/NIDC_South East_202324.xlsx', 'rb') as f:\n",
    "    excel = msoffcrypto.OfficeFile(f)\n",
    "    excel.load_key(password='Snidc24dow6')\n",
    "    excel.decrypt(temp)\n",
    "\n",
    "# Read the decrypted file into a pandas DataFrame\n",
    "df = pd.read_excel(temp, sheet_name='3. Asset Register')\n",
    "\n",
    "# Drop columns: '2023/2024 Part 1', 'CollectionName' and 6 other columns\n",
    "df = df.drop(columns=['2023/2024 Part 1', \n",
    "                      'CollectionName', \n",
    "                      'RegionCode', \n",
    "                      'RegionName', \n",
    "                      'ReportingPeriodStart', \n",
    "                      'ReportingPeriodEnd', \n",
    "                      'SubmittedDatetime', \n",
    "                      'SubmissionStatus'])\n",
    "\n",
    "df['Age'] = pd.to_numeric(df['Age'], errors='coerce')\n",
    "\n",
    "# Display the DataFrame\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1871 entries, 0 to 1870\n",
      "Data columns (total 23 columns):\n",
      " #   Column                          Non-Null Count  Dtype         \n",
      "---  ------                          --------------  -----         \n",
      " 0   OrganisationCode                1871 non-null   object        \n",
      " 1   OrganisationName                1871 non-null   object        \n",
      " 2   NIDC Asset ID                   1869 non-null   object        \n",
      " 3   Local Equipment Identifier      1840 non-null   object        \n",
      " 4   ODS Site Code                   1871 non-null   object        \n",
      " 5   Location_Der                    1871 non-null   object        \n",
      " 6   Machine_Type_Der                1871 non-null   object        \n",
      " 7   Modality_Der                    1871 non-null   object        \n",
      " 8   Equipment Detail Der            1865 non-null   object        \n",
      " 9   Manufacture_Der                 1871 non-null   object        \n",
      " 10  Date of Manufacture             1843 non-null   datetime64[ns]\n",
      " 11  Age                             1843 non-null   float64       \n",
      " 12  Core_Operational_Hours_Mon_Fri  1753 non-null   float64       \n",
      " 13  OOH_Operational_Hours_Mon_Fri   1689 non-null   float64       \n",
      " 14  Core_Operational_Hours_Sat      1699 non-null   float64       \n",
      " 15  OOH_Operational_Hours_Sat       1689 non-null   float64       \n",
      " 16  Core_Operational_Hours_Sun      1698 non-null   float64       \n",
      " 17  OOH_Operational_Hours_Sun       1688 non-null   float64       \n",
      " 18  Ownership Structure             1868 non-null   object        \n",
      " 19  Ownership_Structure_Der         1868 non-null   object        \n",
      " 20  Capital Purchase Cost           1066 non-null   object        \n",
      " 21  Asset Status                    1867 non-null   object        \n",
      " 22  Maintenance Type_Der            1845 non-null   object        \n",
      "dtypes: datetime64[ns](1), float64(7), object(15)\n",
      "memory usage: 336.3+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Bring in ods lookup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [],
   "source": [
    "# load in file\n",
    "etrust = pd.read_csv('C:/Users/martin.bloyce2/OneDrive - NHS/Documents - ' +\n",
    "                     'Regional Analytics - South East/South East/Analysis/' +\n",
    "                     'Diagnostics/Assets/2023-24/imaging-assets-replacements/' +\n",
    "                     'imaging-assets-replacement/etrust.csv', \n",
    "                     header=None,\n",
    "                     usecols=[0,1],\n",
    "                     names=['ODS Site Code','name'])\n",
    "\n",
    "# # convert to dictionary\n",
    "etrust_dict = etrust.set_index('ODS Site Code')['name'].to_dict()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>OrganisationCode</th>\n",
       "      <th>OrganisationName</th>\n",
       "      <th>NIDC Asset ID</th>\n",
       "      <th>Local Equipment Identifier</th>\n",
       "      <th>ODS Site Code</th>\n",
       "      <th>Location_Der</th>\n",
       "      <th>Machine_Type_Der</th>\n",
       "      <th>Modality_Der</th>\n",
       "      <th>Equipment Detail Der</th>\n",
       "      <th>Manufacture_Der</th>\n",
       "      <th>...</th>\n",
       "      <th>Core_Operational_Hours_Sat</th>\n",
       "      <th>OOH_Operational_Hours_Sat</th>\n",
       "      <th>Core_Operational_Hours_Sun</th>\n",
       "      <th>OOH_Operational_Hours_Sun</th>\n",
       "      <th>Ownership Structure</th>\n",
       "      <th>Ownership_Structure_Der</th>\n",
       "      <th>Capital Purchase Cost</th>\n",
       "      <th>Asset Status</th>\n",
       "      <th>Maintenance Type_Der</th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>RDU</td>\n",
       "      <td>Frimley Health NHS Foundation Trust</td>\n",
       "      <td>A160</td>\n",
       "      <td>G3132152</td>\n",
       "      <td>RDU01</td>\n",
       "      <td>Angiography Suite</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>Ultrasound</td>\n",
       "      <td>Ultrasound - General</td>\n",
       "      <td>Hitachi Medical Systems</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>56704</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Asset Under Warranty</td>\n",
       "      <td>FRIMLEY PARK HOSPITAL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>RDU</td>\n",
       "      <td>Frimley Health NHS Foundation Trust</td>\n",
       "      <td>A159</td>\n",
       "      <td>E49106</td>\n",
       "      <td>RDU54</td>\n",
       "      <td>Imaging Department</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>Ultrasound</td>\n",
       "      <td>Ultrasound - General</td>\n",
       "      <td>GE Medical Systems</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>56704</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Asset Under Warranty</td>\n",
       "      <td>ST MARK'S HOSPITAL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>RDU</td>\n",
       "      <td>Frimley Health NHS Foundation Trust</td>\n",
       "      <td>A158</td>\n",
       "      <td>IPX039543</td>\n",
       "      <td>RDU52</td>\n",
       "      <td>Imaging Department</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>Dental</td>\n",
       "      <td>Intraoral</td>\n",
       "      <td>Xograph</td>\n",
       "      <td>...</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>NaN</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Asset Under Warranty</td>\n",
       "      <td>HEATHERWOOD HOSPITAL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>RDU</td>\n",
       "      <td>Frimley Health NHS Foundation Trust</td>\n",
       "      <td>A157</td>\n",
       "      <td>TRI2100460</td>\n",
       "      <td>RDU52</td>\n",
       "      <td>Imaging Department</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>X ray Units Mobile</td>\n",
       "      <td>Plain X-Ray-DR Mobile</td>\n",
       "      <td>Hologic</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>NaN</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Asset Under Warranty</td>\n",
       "      <td>HEATHERWOOD HOSPITAL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>RDU</td>\n",
       "      <td>Frimley Health NHS Foundation Trust</td>\n",
       "      <td>A156</td>\n",
       "      <td>3DM160700888</td>\n",
       "      <td>RDU52</td>\n",
       "      <td>Imaging Department</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>Mammography</td>\n",
       "      <td>Symptomatic - Digital Mammography 2D + 3D Tomo...</td>\n",
       "      <td>Hologic</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>403800</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Asset Under Warranty</td>\n",
       "      <td>HEATHERWOOD HOSPITAL</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  OrganisationCode                     OrganisationName NIDC Asset ID  \\\n",
       "0              RDU  Frimley Health NHS Foundation Trust          A160   \n",
       "1              RDU  Frimley Health NHS Foundation Trust          A159   \n",
       "2              RDU  Frimley Health NHS Foundation Trust          A158   \n",
       "3              RDU  Frimley Health NHS Foundation Trust          A157   \n",
       "4              RDU  Frimley Health NHS Foundation Trust          A156   \n",
       "\n",
       "  Local Equipment Identifier ODS Site Code        Location_Der  \\\n",
       "0                   G3132152         RDU01   Angiography Suite   \n",
       "1                     E49106         RDU54  Imaging Department   \n",
       "2                  IPX039543         RDU52  Imaging Department   \n",
       "3                 TRI2100460         RDU52  Imaging Department   \n",
       "4               3DM160700888         RDU52  Imaging Department   \n",
       "\n",
       "    Machine_Type_Der        Modality_Der  \\\n",
       "0  Image Acquisition          Ultrasound   \n",
       "1  Image Acquisition          Ultrasound   \n",
       "2  Image Acquisition              Dental   \n",
       "3  Image Acquisition  X ray Units Mobile   \n",
       "4  Image Acquisition         Mammography   \n",
       "\n",
       "                                Equipment Detail Der          Manufacture_Der  \\\n",
       "0                               Ultrasound - General  Hitachi Medical Systems   \n",
       "1                               Ultrasound - General       GE Medical Systems   \n",
       "2                                          Intraoral                  Xograph   \n",
       "3                              Plain X-Ray-DR Mobile                  Hologic   \n",
       "4  Symptomatic - Digital Mammography 2D + 3D Tomo...                  Hologic   \n",
       "\n",
       "   ... Core_Operational_Hours_Sat  OOH_Operational_Hours_Sat  \\\n",
       "0  ...                        0.0                        0.0   \n",
       "1  ...                        0.0                        0.0   \n",
       "2  ...                       12.0                        0.0   \n",
       "3  ...                        0.0                        0.0   \n",
       "4  ...                        0.0                        0.0   \n",
       "\n",
       "   Core_Operational_Hours_Sun  OOH_Operational_Hours_Sun  \\\n",
       "0                         0.0                        0.0   \n",
       "1                         0.0                        0.0   \n",
       "2                        12.0                        0.0   \n",
       "3                         0.0                        0.0   \n",
       "4                         0.0                        0.0   \n",
       "\n",
       "      Ownership Structure  Ownership_Structure_Der  Capital Purchase Cost  \\\n",
       "0  Capital purchase - new   Capital purchase - new                  56704   \n",
       "1  Capital purchase - new   Capital purchase - new                  56704   \n",
       "2  Capital purchase - new   Capital purchase - new                    NaN   \n",
       "3  Capital purchase - new   Capital purchase - new                    NaN   \n",
       "4  Capital purchase - new   Capital purchase - new                 403800   \n",
       "\n",
       "   Asset Status  Maintenance Type_Der                   name  \n",
       "0    In Service  Asset Under Warranty  FRIMLEY PARK HOSPITAL  \n",
       "1    In Service  Asset Under Warranty     ST MARK'S HOSPITAL  \n",
       "2    In Service  Asset Under Warranty   HEATHERWOOD HOSPITAL  \n",
       "3    In Service  Asset Under Warranty   HEATHERWOOD HOSPITAL  \n",
       "4    In Service  Asset Under Warranty   HEATHERWOOD HOSPITAL  \n",
       "\n",
       "[5 rows x 24 columns]"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# merge to get site names\n",
    "df = pd.merge(df, etrust, on='ODS Site Code', how='inner')\n",
    "\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>OrganisationCode</th>\n",
       "      <th>OrganisationName</th>\n",
       "      <th>NIDC Asset ID</th>\n",
       "      <th>Local Equipment Identifier</th>\n",
       "      <th>ODS Site Code</th>\n",
       "      <th>Location_Der</th>\n",
       "      <th>Machine_Type_Der</th>\n",
       "      <th>Modality_Der</th>\n",
       "      <th>Equipment Detail Der</th>\n",
       "      <th>Manufacture_Der</th>\n",
       "      <th>...</th>\n",
       "      <th>Core_Operational_Hours_Sat</th>\n",
       "      <th>OOH_Operational_Hours_Sat</th>\n",
       "      <th>Core_Operational_Hours_Sun</th>\n",
       "      <th>OOH_Operational_Hours_Sun</th>\n",
       "      <th>Ownership Structure</th>\n",
       "      <th>Ownership_Structure_Der</th>\n",
       "      <th>Capital Purchase Cost</th>\n",
       "      <th>Asset Status</th>\n",
       "      <th>Maintenance Type_Der</th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>RYR</td>\n",
       "      <td>University Hospitals Sussex NHS Foundation Trust</td>\n",
       "      <td>A240</td>\n",
       "      <td>BRMRI1</td>\n",
       "      <td>E8L5B</td>\n",
       "      <td>Community Diagnostic Centre Independent Sector...</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>MRI</td>\n",
       "      <td>Close Bore 1.5T</td>\n",
       "      <td>Siemens Healthcare</td>\n",
       "      <td>...</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Independent Provider Asset</td>\n",
       "      <td>Independent Provider Asset</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Independent Sector Asset</td>\n",
       "      <td>Independent Sector Asset</td>\n",
       "      <td>UNIVERSITY OF CHICHESTER BOGNOR CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>RYR</td>\n",
       "      <td>University Hospitals Sussex NHS Foundation Trust</td>\n",
       "      <td>A239</td>\n",
       "      <td>SLMR1</td>\n",
       "      <td>L6O9O</td>\n",
       "      <td>Community Diagnostic Centre NHS Asset</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>MRI</td>\n",
       "      <td>Close Bore 1.5T</td>\n",
       "      <td>Siemens Healthcare</td>\n",
       "      <td>...</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>1100000</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Manufacturer provides maintenance</td>\n",
       "      <td>SOUTHLANDS CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>RYR</td>\n",
       "      <td>University Hospitals Sussex NHS Foundation Trust</td>\n",
       "      <td>A237</td>\n",
       "      <td>BRCT1</td>\n",
       "      <td>E8L5B</td>\n",
       "      <td>Community Diagnostic Centre Independent Sector...</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>CT</td>\n",
       "      <td>64 detector rows or more but less than 256 det...</td>\n",
       "      <td>Canon</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Independent Provider Asset</td>\n",
       "      <td>Independent Provider Asset</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Independent Sector Asset</td>\n",
       "      <td>Independent Sector Asset</td>\n",
       "      <td>UNIVERSITY OF CHICHESTER BOGNOR CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>RHW</td>\n",
       "      <td>Royal Berkshire NHS Foundation Trust</td>\n",
       "      <td>A064</td>\n",
       "      <td>Aplioi 700 Bracknell Rm2</td>\n",
       "      <td>Y2X1G</td>\n",
       "      <td>Community Diagnostic Centre NHS Asset</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>Ultrasound</td>\n",
       "      <td>2D with CEUS / Elastography / Fusion Capabilit...</td>\n",
       "      <td>Canon</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>63600</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Manufacturer provides maintenance</td>\n",
       "      <td>BRACKNELL HEALTHSPACE CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>RYR</td>\n",
       "      <td>University Hospitals Sussex NHS Foundation Trust</td>\n",
       "      <td>A241</td>\n",
       "      <td>SLRAD1</td>\n",
       "      <td>L6O9O</td>\n",
       "      <td>Community Diagnostic Centre NHS Asset</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>X ray Units Static</td>\n",
       "      <td>Plain X-Ray-DR Static</td>\n",
       "      <td>Siemens Healthcare</td>\n",
       "      <td>...</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>175000</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Manufacturer provides maintenance</td>\n",
       "      <td>SOUTHLANDS CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>RHW</td>\n",
       "      <td>Royal Berkshire NHS Foundation Trust</td>\n",
       "      <td>A063</td>\n",
       "      <td>Samsung RS85 Prestige Bracknell Rm1</td>\n",
       "      <td>Y2X1G</td>\n",
       "      <td>Community Diagnostic Centre NHS Asset</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>Ultrasound</td>\n",
       "      <td>2D with CEUS / Elastography / Fusion Capabilit...</td>\n",
       "      <td>Samsung</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>97944</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Asset Under Warranty</td>\n",
       "      <td>BRACKNELL HEALTHSPACE CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>RYR</td>\n",
       "      <td>University Hospitals Sussex NHS Foundation Trust</td>\n",
       "      <td>A243</td>\n",
       "      <td>SLRAD3</td>\n",
       "      <td>L6O9O</td>\n",
       "      <td>Community Diagnostic Centre NHS Asset</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>X ray Units Static</td>\n",
       "      <td>Plain X-Ray-DR Static</td>\n",
       "      <td>Siemens Healthcare</td>\n",
       "      <td>...</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>150000</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Manufacturer provides maintenance</td>\n",
       "      <td>SOUTHLANDS CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>RYR</td>\n",
       "      <td>University Hospitals Sussex NHS Foundation Trust</td>\n",
       "      <td>A242</td>\n",
       "      <td>SLRAD2</td>\n",
       "      <td>L6O9O</td>\n",
       "      <td>Community Diagnostic Centre NHS Asset</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>X ray Units Static</td>\n",
       "      <td>Plain X-Ray-DR Static</td>\n",
       "      <td>Siemens Healthcare</td>\n",
       "      <td>...</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>175000</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Manufacturer provides maintenance</td>\n",
       "      <td>SOUTHLANDS CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>RHU</td>\n",
       "      <td>Portsmouth Hospitals University National Healt...</td>\n",
       "      <td>A111</td>\n",
       "      <td>OAKP US</td>\n",
       "      <td>G2E0X</td>\n",
       "      <td>Community Diagnostic Centre Independent Sector...</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>Ultrasound</td>\n",
       "      <td>Ultrasound - General</td>\n",
       "      <td>Other</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Independent Provider Asset</td>\n",
       "      <td>Independent Provider Asset</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Independent Sector Asset</td>\n",
       "      <td>Independent Sector Asset</td>\n",
       "      <td>OAK PARK CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>RYR</td>\n",
       "      <td>University Hospitals Sussex NHS Foundation Trust</td>\n",
       "      <td>A206</td>\n",
       "      <td>SLCT1</td>\n",
       "      <td>L6O9O</td>\n",
       "      <td>Community Diagnostic Centre NHS Asset</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>CT</td>\n",
       "      <td>256 detector rows or more with iterative recon...</td>\n",
       "      <td>Canon</td>\n",
       "      <td>...</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>900000</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Manufacturer provides maintenance</td>\n",
       "      <td>SOUTHLANDS CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>RHU</td>\n",
       "      <td>Portsmouth Hospitals University National Healt...</td>\n",
       "      <td>A110</td>\n",
       "      <td>FCH MRI</td>\n",
       "      <td>I1K6X</td>\n",
       "      <td>Community Diagnostic Centre Independent Sector...</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>MRI</td>\n",
       "      <td>Close Bore 1.5T</td>\n",
       "      <td>Other</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Independent Provider Asset</td>\n",
       "      <td>Independent Provider Asset</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Independent Sector Asset</td>\n",
       "      <td>Independent Sector Asset</td>\n",
       "      <td>FAREHAM COMMUNITY HOSPITAL CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>162</th>\n",
       "      <td>RHU</td>\n",
       "      <td>Portsmouth Hospitals University National Healt...</td>\n",
       "      <td>A084</td>\n",
       "      <td>USFSZ72M3HT200018N</td>\n",
       "      <td>I1K6X</td>\n",
       "      <td>Community Diagnostic Centre NHS Asset</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>Ultrasound</td>\n",
       "      <td>2D with CEUS / Elastography / Fusion Capabilit...</td>\n",
       "      <td>Samsung</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>101431</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Manufacturer provides maintenance</td>\n",
       "      <td>FAREHAM COMMUNITY HOSPITAL CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>RYR</td>\n",
       "      <td>University Hospitals Sussex NHS Foundation Trust</td>\n",
       "      <td>A202</td>\n",
       "      <td>SUS3</td>\n",
       "      <td>L6O9O</td>\n",
       "      <td>Community Diagnostic Centre NHS Asset</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>Ultrasound</td>\n",
       "      <td>Ultrasound - General</td>\n",
       "      <td>Samsung</td>\n",
       "      <td>...</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>68000</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Manufacturer provides maintenance</td>\n",
       "      <td>SOUTHLANDS CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>RYR</td>\n",
       "      <td>University Hospitals Sussex NHS Foundation Trust</td>\n",
       "      <td>A102</td>\n",
       "      <td>NaN</td>\n",
       "      <td>E8K3D</td>\n",
       "      <td>Community Diagnostic Centre Independent Sector...</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>CT</td>\n",
       "      <td>64 detector rows or more but less than 256 det...</td>\n",
       "      <td>Philips Healthcare</td>\n",
       "      <td>...</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Independent Provider Asset</td>\n",
       "      <td>Independent Provider Asset</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Independent Sector Asset</td>\n",
       "      <td>Independent Sector Asset</td>\n",
       "      <td>FALMER COMMUNITY STADIUM CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>222</th>\n",
       "      <td>RYR</td>\n",
       "      <td>University Hospitals Sussex NHS Foundation Trust</td>\n",
       "      <td>A155</td>\n",
       "      <td>SUS2</td>\n",
       "      <td>L6O9O</td>\n",
       "      <td>Community Diagnostic Centre NHS Asset</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>Ultrasound</td>\n",
       "      <td>Ultrasound - General</td>\n",
       "      <td>Samsung</td>\n",
       "      <td>...</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>60000</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Manufacturer provides maintenance</td>\n",
       "      <td>SOUTHLANDS CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>263</th>\n",
       "      <td>RA2</td>\n",
       "      <td>Royal Surrey County Hospital NHS Foundation Trust</td>\n",
       "      <td>A041</td>\n",
       "      <td>MHR100600</td>\n",
       "      <td>I9V5Q</td>\n",
       "      <td>Community Diagnostic Centre NHS Asset</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>X ray Units Static</td>\n",
       "      <td>Plain X-Ray-DR Static</td>\n",
       "      <td>Samsung</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>180000</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Manufacturer provides maintenance</td>\n",
       "      <td>MILFORD COMMUNITY HOSPITAL CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>264</th>\n",
       "      <td>RYR</td>\n",
       "      <td>University Hospitals Sussex NHS Foundation Trust</td>\n",
       "      <td>A101</td>\n",
       "      <td>NaN</td>\n",
       "      <td>E8K3D</td>\n",
       "      <td>Community Diagnostic Centre Independent Sector...</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>MRI</td>\n",
       "      <td>Close Bore 1.5T</td>\n",
       "      <td>Philips Healthcare</td>\n",
       "      <td>...</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Independent Provider Asset</td>\n",
       "      <td>Independent Provider Asset</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Independent Sector Asset</td>\n",
       "      <td>Independent Sector Asset</td>\n",
       "      <td>FALMER COMMUNITY STADIUM CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>361</th>\n",
       "      <td>RYR</td>\n",
       "      <td>University Hospitals Sussex NHS Foundation Trust</td>\n",
       "      <td>A103</td>\n",
       "      <td>NaN</td>\n",
       "      <td>E8K3D</td>\n",
       "      <td>Community Diagnostic Centre Independent Sector...</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>Ultrasound</td>\n",
       "      <td>Ultrasound - General</td>\n",
       "      <td>GE Medical Systems</td>\n",
       "      <td>...</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Independent Provider Asset</td>\n",
       "      <td>Independent Provider Asset</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Independent Sector Asset</td>\n",
       "      <td>Independent Sector Asset</td>\n",
       "      <td>FALMER COMMUNITY STADIUM CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>363</th>\n",
       "      <td>RYR</td>\n",
       "      <td>University Hospitals Sussex NHS Foundation Trust</td>\n",
       "      <td>A104</td>\n",
       "      <td>NaN</td>\n",
       "      <td>E8K3D</td>\n",
       "      <td>Community Diagnostic Centre Independent Sector...</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>Ultrasound</td>\n",
       "      <td>Ultrasound - General</td>\n",
       "      <td>Philips Healthcare</td>\n",
       "      <td>...</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Independent Provider Asset</td>\n",
       "      <td>Independent Provider Asset</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Independent Sector Asset</td>\n",
       "      <td>Independent Sector Asset</td>\n",
       "      <td>FALMER COMMUNITY STADIUM CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>368</th>\n",
       "      <td>RXC</td>\n",
       "      <td>East Sussex Healthcare NHS Trust</td>\n",
       "      <td>A083</td>\n",
       "      <td>120789</td>\n",
       "      <td>U4H2G</td>\n",
       "      <td>Community Diagnostic Centre NHS Asset</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>X ray Units Static</td>\n",
       "      <td>Plain X-Ray-DR Static</td>\n",
       "      <td>GE Medical Systems</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>NaN</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Manufacturer provides maintenance</td>\n",
       "      <td>BEXHILL CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>376</th>\n",
       "      <td>RYR</td>\n",
       "      <td>University Hospitals Sussex NHS Foundation Trust</td>\n",
       "      <td>A154</td>\n",
       "      <td>SUS1</td>\n",
       "      <td>L6O9O</td>\n",
       "      <td>Community Diagnostic Centre NHS Asset</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>Ultrasound</td>\n",
       "      <td>Ultrasound - General</td>\n",
       "      <td>Canon</td>\n",
       "      <td>...</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>80000</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Manufacturer provides maintenance</td>\n",
       "      <td>SOUTHLANDS CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>407</th>\n",
       "      <td>RXC</td>\n",
       "      <td>East Sussex Healthcare NHS Trust</td>\n",
       "      <td>A082</td>\n",
       "      <td>120791</td>\n",
       "      <td>U4H2G</td>\n",
       "      <td>Community Diagnostic Centre NHS Asset</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>X ray Units Static</td>\n",
       "      <td>Plain X-Ray-DR Static</td>\n",
       "      <td>GE Medical Systems</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>NaN</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Manufacturer provides maintenance</td>\n",
       "      <td>BEXHILL CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>497</th>\n",
       "      <td>RHU</td>\n",
       "      <td>Portsmouth Hospitals University National Healt...</td>\n",
       "      <td>A094</td>\n",
       "      <td>BD CDC RR 1</td>\n",
       "      <td>L7P6U</td>\n",
       "      <td>Community Diagnostic Centre NHS Asset</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>Mammography</td>\n",
       "      <td>Symptomatic - Digital Mammography 2D + 3D Tomo...</td>\n",
       "      <td>Siemens Healthcare</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>202800</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Asset Under Warranty</td>\n",
       "      <td>PORTSMOUTH CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>540</th>\n",
       "      <td>RHU</td>\n",
       "      <td>Portsmouth Hospitals University National Healt...</td>\n",
       "      <td>A093</td>\n",
       "      <td>BD CDC OakP</td>\n",
       "      <td>G2E0X</td>\n",
       "      <td>Community Diagnostic Centre NHS Asset</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>Mammography</td>\n",
       "      <td>Symptomatic - Digital Mammography 2D + 3D Tomo...</td>\n",
       "      <td>Siemens Healthcare</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>202800</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Asset Under Warranty</td>\n",
       "      <td>OAK PARK CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>890</th>\n",
       "      <td>RTH</td>\n",
       "      <td>Oxford University Hospitals NHS Foundation Trust</td>\n",
       "      <td>A155</td>\n",
       "      <td>CT</td>\n",
       "      <td>J9F8D</td>\n",
       "      <td>Community Diagnostic Centre Independent Sector...</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>CT</td>\n",
       "      <td>64 detector rows or more but less than 256 det...</td>\n",
       "      <td>GE Medical Systems</td>\n",
       "      <td>...</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Independent Provider Asset</td>\n",
       "      <td>Independent Provider Asset</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Independent Sector Asset</td>\n",
       "      <td>Independent Sector Asset</td>\n",
       "      <td>OXFORD CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>960</th>\n",
       "      <td>RTH</td>\n",
       "      <td>Oxford University Hospitals NHS Foundation Trust</td>\n",
       "      <td>A157</td>\n",
       "      <td>US</td>\n",
       "      <td>J9F8D</td>\n",
       "      <td>Community Diagnostic Centre Independent Sector...</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>Ultrasound</td>\n",
       "      <td>Ultrasound - General</td>\n",
       "      <td>GE Medical Systems</td>\n",
       "      <td>...</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Independent Provider Asset</td>\n",
       "      <td>Independent Provider Asset</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Independent Sector Asset</td>\n",
       "      <td>Independent Sector Asset</td>\n",
       "      <td>OXFORD CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1042</th>\n",
       "      <td>RTH</td>\n",
       "      <td>Oxford University Hospitals NHS Foundation Trust</td>\n",
       "      <td>A154</td>\n",
       "      <td>MR</td>\n",
       "      <td>J9F8D</td>\n",
       "      <td>Community Diagnostic Centre Independent Sector...</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>MRI</td>\n",
       "      <td>Wide Bore 1.5T</td>\n",
       "      <td>GE Medical Systems</td>\n",
       "      <td>...</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Independent Provider Asset</td>\n",
       "      <td>Independent Provider Asset</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Independent Sector Asset</td>\n",
       "      <td>Independent Sector Asset</td>\n",
       "      <td>OXFORD CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1061</th>\n",
       "      <td>RN5</td>\n",
       "      <td>Hampshire Hospitals NHS Foundation Trust</td>\n",
       "      <td>A092</td>\n",
       "      <td>92</td>\n",
       "      <td>D9T0G</td>\n",
       "      <td>Community Diagnostic Centre NHS Asset</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>Ultrasound</td>\n",
       "      <td>2D with Elastography Capability - General</td>\n",
       "      <td>GE Medical Systems</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Managed Equipment Service</td>\n",
       "      <td>Managed Equipment Service</td>\n",
       "      <td>NaN</td>\n",
       "      <td>New replacement asset</td>\n",
       "      <td>Manufacturer provides maintenance</td>\n",
       "      <td>ANDOVER CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1103</th>\n",
       "      <td>RTH</td>\n",
       "      <td>Oxford University Hospitals NHS Foundation Trust</td>\n",
       "      <td>A156</td>\n",
       "      <td>PF</td>\n",
       "      <td>J9F8D</td>\n",
       "      <td>Community Diagnostic Centre Independent Sector...</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>X ray Units Static</td>\n",
       "      <td>Plain X-Ray-DR Static</td>\n",
       "      <td>GE Medical Systems</td>\n",
       "      <td>...</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Independent Provider Asset</td>\n",
       "      <td>Independent Provider Asset</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Independent Sector Asset</td>\n",
       "      <td>Independent Sector Asset</td>\n",
       "      <td>OXFORD CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1264</th>\n",
       "      <td>RHM</td>\n",
       "      <td>University Hospital Southampton NHS Foundation...</td>\n",
       "      <td>A010</td>\n",
       "      <td>RSH CDC CT Examination Room CDVC0140581</td>\n",
       "      <td>X4F7Z</td>\n",
       "      <td>Community Diagnostic Centre NHS Asset</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>CT</td>\n",
       "      <td>64 detector rows or more but less than 256 det...</td>\n",
       "      <td>Siemens Healthcare</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Managed Equipment Service</td>\n",
       "      <td>Managed Equipment Service</td>\n",
       "      <td>NaN</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Manufacturer provides maintenance</td>\n",
       "      <td>ROYAL SOUTH HANTS CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1278</th>\n",
       "      <td>RN5</td>\n",
       "      <td>Hampshire Hospitals NHS Foundation Trust</td>\n",
       "      <td>A038</td>\n",
       "      <td>38</td>\n",
       "      <td>D9T0G</td>\n",
       "      <td>Community Diagnostic Centre Independent Sector...</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>MRI</td>\n",
       "      <td>Close Bore 1.5T with scan time reduction software</td>\n",
       "      <td>Siemens Healthcare</td>\n",
       "      <td>...</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Independent Provider Asset</td>\n",
       "      <td>Independent Provider Asset</td>\n",
       "      <td>NaN</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Manufacturer provides maintenance</td>\n",
       "      <td>ANDOVER CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1286</th>\n",
       "      <td>RXC</td>\n",
       "      <td>East Sussex Healthcare NHS Trust</td>\n",
       "      <td>A034</td>\n",
       "      <td>122480</td>\n",
       "      <td>U4H2G</td>\n",
       "      <td>Community Diagnostic Centre NHS Asset</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>Ultrasound</td>\n",
       "      <td>2D with 3D Capability – General</td>\n",
       "      <td>GE Medical Systems</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>75000</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Manufacturer provides maintenance</td>\n",
       "      <td>BEXHILL CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1315</th>\n",
       "      <td>RXC</td>\n",
       "      <td>East Sussex Healthcare NHS Trust</td>\n",
       "      <td>A032</td>\n",
       "      <td>116497</td>\n",
       "      <td>U4H2G</td>\n",
       "      <td>Community Diagnostic Centre NHS Asset</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>Ultrasound</td>\n",
       "      <td>2D with 3D Capability – General</td>\n",
       "      <td>Samsung</td>\n",
       "      <td>...</td>\n",
       "      <td>7.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>84000</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Manufacturer provides maintenance</td>\n",
       "      <td>BEXHILL CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1317</th>\n",
       "      <td>RPC</td>\n",
       "      <td>Queen Victoria Hospital NHS Foundation Trust</td>\n",
       "      <td>A026</td>\n",
       "      <td>6LC21Y2097</td>\n",
       "      <td>K9X8O</td>\n",
       "      <td>Community Diagnostic Centre NHS Asset</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>Ultrasound</td>\n",
       "      <td>2D with 4D Capability – General</td>\n",
       "      <td>Canon</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>109308</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Manufacturer provides maintenance</td>\n",
       "      <td>QUEEN VICTORIA HOSPITAL CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1364</th>\n",
       "      <td>RN5</td>\n",
       "      <td>Hampshire Hospitals NHS Foundation Trust</td>\n",
       "      <td>A086</td>\n",
       "      <td>86</td>\n",
       "      <td>D9T0G</td>\n",
       "      <td>Community Diagnostic Centre NHS Asset</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>X ray Units Static</td>\n",
       "      <td>Plain X-Ray-DR Static</td>\n",
       "      <td>Siemens Healthcare</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>238363</td>\n",
       "      <td>New additional asset</td>\n",
       "      <td>Asset Under Warranty</td>\n",
       "      <td>ANDOVER CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1371</th>\n",
       "      <td>RXC</td>\n",
       "      <td>East Sussex Healthcare NHS Trust</td>\n",
       "      <td>A031</td>\n",
       "      <td>109520</td>\n",
       "      <td>U4H2G</td>\n",
       "      <td>Community Diagnostic Centre NHS Asset</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>Ultrasound</td>\n",
       "      <td>2D with 3D Capability – General</td>\n",
       "      <td>Samsung</td>\n",
       "      <td>...</td>\n",
       "      <td>7.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>84000</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Manufacturer provides maintenance</td>\n",
       "      <td>BEXHILL CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1376</th>\n",
       "      <td>RXC</td>\n",
       "      <td>East Sussex Healthcare NHS Trust</td>\n",
       "      <td>A033</td>\n",
       "      <td>116498</td>\n",
       "      <td>U4H2G</td>\n",
       "      <td>Community Diagnostic Centre NHS Asset</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>Ultrasound</td>\n",
       "      <td>2D with 3D Capability – General</td>\n",
       "      <td>Samsung</td>\n",
       "      <td>...</td>\n",
       "      <td>7.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>84000</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Manufacturer provides maintenance</td>\n",
       "      <td>BEXHILL CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1443</th>\n",
       "      <td>RA2</td>\n",
       "      <td>Royal Surrey County Hospital NHS Foundation Trust</td>\n",
       "      <td>A071</td>\n",
       "      <td>MHR100565</td>\n",
       "      <td>I9V5Q</td>\n",
       "      <td>Community Diagnostic Centre NHS Asset</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>Ultrasound</td>\n",
       "      <td>Ultrasound - General</td>\n",
       "      <td>GE Medical Systems</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>65344</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Asset Under Warranty</td>\n",
       "      <td>MILFORD COMMUNITY HOSPITAL CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1527</th>\n",
       "      <td>RA2</td>\n",
       "      <td>Royal Surrey County Hospital NHS Foundation Trust</td>\n",
       "      <td>A104</td>\n",
       "      <td>MHR100601</td>\n",
       "      <td>I9V5Q</td>\n",
       "      <td>Imaging Department</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>Other</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Samsung</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>38000</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Manufacturer provides maintenance</td>\n",
       "      <td>MILFORD COMMUNITY HOSPITAL CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1584</th>\n",
       "      <td>RA2</td>\n",
       "      <td>Royal Surrey County Hospital NHS Foundation Trust</td>\n",
       "      <td>A103</td>\n",
       "      <td>MHR100602</td>\n",
       "      <td>I9V5Q</td>\n",
       "      <td>Imaging Department</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>Other</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Samsung</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>38000</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Manufacturer provides maintenance</td>\n",
       "      <td>MILFORD COMMUNITY HOSPITAL CDC</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>40 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     OrganisationCode                                   OrganisationName  \\\n",
       "18                RYR   University Hospitals Sussex NHS Foundation Trust   \n",
       "23                RYR   University Hospitals Sussex NHS Foundation Trust   \n",
       "26                RYR   University Hospitals Sussex NHS Foundation Trust   \n",
       "32                RHW               Royal Berkshire NHS Foundation Trust   \n",
       "51                RYR   University Hospitals Sussex NHS Foundation Trust   \n",
       "65                RHW               Royal Berkshire NHS Foundation Trust   \n",
       "83                RYR   University Hospitals Sussex NHS Foundation Trust   \n",
       "84                RYR   University Hospitals Sussex NHS Foundation Trust   \n",
       "113               RHU  Portsmouth Hospitals University National Healt...   \n",
       "140               RYR   University Hospitals Sussex NHS Foundation Trust   \n",
       "145               RHU  Portsmouth Hospitals University National Healt...   \n",
       "162               RHU  Portsmouth Hospitals University National Healt...   \n",
       "166               RYR   University Hospitals Sussex NHS Foundation Trust   \n",
       "195               RYR   University Hospitals Sussex NHS Foundation Trust   \n",
       "222               RYR   University Hospitals Sussex NHS Foundation Trust   \n",
       "263               RA2  Royal Surrey County Hospital NHS Foundation Trust   \n",
       "264               RYR   University Hospitals Sussex NHS Foundation Trust   \n",
       "361               RYR   University Hospitals Sussex NHS Foundation Trust   \n",
       "363               RYR   University Hospitals Sussex NHS Foundation Trust   \n",
       "368               RXC                   East Sussex Healthcare NHS Trust   \n",
       "376               RYR   University Hospitals Sussex NHS Foundation Trust   \n",
       "407               RXC                   East Sussex Healthcare NHS Trust   \n",
       "497               RHU  Portsmouth Hospitals University National Healt...   \n",
       "540               RHU  Portsmouth Hospitals University National Healt...   \n",
       "890               RTH   Oxford University Hospitals NHS Foundation Trust   \n",
       "960               RTH   Oxford University Hospitals NHS Foundation Trust   \n",
       "1042              RTH   Oxford University Hospitals NHS Foundation Trust   \n",
       "1061              RN5           Hampshire Hospitals NHS Foundation Trust   \n",
       "1103              RTH   Oxford University Hospitals NHS Foundation Trust   \n",
       "1264              RHM  University Hospital Southampton NHS Foundation...   \n",
       "1278              RN5           Hampshire Hospitals NHS Foundation Trust   \n",
       "1286              RXC                   East Sussex Healthcare NHS Trust   \n",
       "1315              RXC                   East Sussex Healthcare NHS Trust   \n",
       "1317              RPC       Queen Victoria Hospital NHS Foundation Trust   \n",
       "1364              RN5           Hampshire Hospitals NHS Foundation Trust   \n",
       "1371              RXC                   East Sussex Healthcare NHS Trust   \n",
       "1376              RXC                   East Sussex Healthcare NHS Trust   \n",
       "1443              RA2  Royal Surrey County Hospital NHS Foundation Trust   \n",
       "1527              RA2  Royal Surrey County Hospital NHS Foundation Trust   \n",
       "1584              RA2  Royal Surrey County Hospital NHS Foundation Trust   \n",
       "\n",
       "     NIDC Asset ID               Local Equipment Identifier ODS Site Code  \\\n",
       "18            A240                                   BRMRI1         E8L5B   \n",
       "23            A239                                    SLMR1         L6O9O   \n",
       "26            A237                                    BRCT1         E8L5B   \n",
       "32            A064                 Aplioi 700 Bracknell Rm2         Y2X1G   \n",
       "51            A241                                   SLRAD1         L6O9O   \n",
       "65            A063      Samsung RS85 Prestige Bracknell Rm1         Y2X1G   \n",
       "83            A243                                   SLRAD3         L6O9O   \n",
       "84            A242                                   SLRAD2         L6O9O   \n",
       "113           A111                                  OAKP US         G2E0X   \n",
       "140           A206                                    SLCT1         L6O9O   \n",
       "145           A110                                  FCH MRI         I1K6X   \n",
       "162           A084                       USFSZ72M3HT200018N         I1K6X   \n",
       "166           A202                                     SUS3         L6O9O   \n",
       "195           A102                                      NaN         E8K3D   \n",
       "222           A155                                     SUS2         L6O9O   \n",
       "263           A041                                MHR100600         I9V5Q   \n",
       "264           A101                                      NaN         E8K3D   \n",
       "361           A103                                      NaN         E8K3D   \n",
       "363           A104                                      NaN         E8K3D   \n",
       "368           A083                                   120789         U4H2G   \n",
       "376           A154                                     SUS1         L6O9O   \n",
       "407           A082                                   120791         U4H2G   \n",
       "497           A094                              BD CDC RR 1         L7P6U   \n",
       "540           A093                              BD CDC OakP         G2E0X   \n",
       "890           A155                                       CT         J9F8D   \n",
       "960           A157                                       US         J9F8D   \n",
       "1042          A154                                       MR         J9F8D   \n",
       "1061          A092                                       92         D9T0G   \n",
       "1103          A156                                       PF         J9F8D   \n",
       "1264          A010  RSH CDC CT Examination Room CDVC0140581         X4F7Z   \n",
       "1278          A038                                       38         D9T0G   \n",
       "1286          A034                                   122480         U4H2G   \n",
       "1315          A032                                   116497         U4H2G   \n",
       "1317          A026                               6LC21Y2097         K9X8O   \n",
       "1364          A086                                       86         D9T0G   \n",
       "1371          A031                                   109520         U4H2G   \n",
       "1376          A033                                   116498         U4H2G   \n",
       "1443          A071                                MHR100565         I9V5Q   \n",
       "1527          A104                                MHR100601         I9V5Q   \n",
       "1584          A103                                MHR100602         I9V5Q   \n",
       "\n",
       "                                           Location_Der   Machine_Type_Der  \\\n",
       "18    Community Diagnostic Centre Independent Sector...  Image Acquisition   \n",
       "23                Community Diagnostic Centre NHS Asset  Image Acquisition   \n",
       "26    Community Diagnostic Centre Independent Sector...  Image Acquisition   \n",
       "32                Community Diagnostic Centre NHS Asset  Image Acquisition   \n",
       "51                Community Diagnostic Centre NHS Asset  Image Acquisition   \n",
       "65                Community Diagnostic Centre NHS Asset  Image Acquisition   \n",
       "83                Community Diagnostic Centre NHS Asset  Image Acquisition   \n",
       "84                Community Diagnostic Centre NHS Asset  Image Acquisition   \n",
       "113   Community Diagnostic Centre Independent Sector...  Image Acquisition   \n",
       "140               Community Diagnostic Centre NHS Asset  Image Acquisition   \n",
       "145   Community Diagnostic Centre Independent Sector...  Image Acquisition   \n",
       "162               Community Diagnostic Centre NHS Asset  Image Acquisition   \n",
       "166               Community Diagnostic Centre NHS Asset  Image Acquisition   \n",
       "195   Community Diagnostic Centre Independent Sector...  Image Acquisition   \n",
       "222               Community Diagnostic Centre NHS Asset  Image Acquisition   \n",
       "263               Community Diagnostic Centre NHS Asset  Image Acquisition   \n",
       "264   Community Diagnostic Centre Independent Sector...  Image Acquisition   \n",
       "361   Community Diagnostic Centre Independent Sector...  Image Acquisition   \n",
       "363   Community Diagnostic Centre Independent Sector...  Image Acquisition   \n",
       "368               Community Diagnostic Centre NHS Asset  Image Acquisition   \n",
       "376               Community Diagnostic Centre NHS Asset  Image Acquisition   \n",
       "407               Community Diagnostic Centre NHS Asset  Image Acquisition   \n",
       "497               Community Diagnostic Centre NHS Asset  Image Acquisition   \n",
       "540               Community Diagnostic Centre NHS Asset  Image Acquisition   \n",
       "890   Community Diagnostic Centre Independent Sector...  Image Acquisition   \n",
       "960   Community Diagnostic Centre Independent Sector...  Image Acquisition   \n",
       "1042  Community Diagnostic Centre Independent Sector...  Image Acquisition   \n",
       "1061              Community Diagnostic Centre NHS Asset  Image Acquisition   \n",
       "1103  Community Diagnostic Centre Independent Sector...  Image Acquisition   \n",
       "1264              Community Diagnostic Centre NHS Asset  Image Acquisition   \n",
       "1278  Community Diagnostic Centre Independent Sector...  Image Acquisition   \n",
       "1286              Community Diagnostic Centre NHS Asset  Image Acquisition   \n",
       "1315              Community Diagnostic Centre NHS Asset  Image Acquisition   \n",
       "1317              Community Diagnostic Centre NHS Asset  Image Acquisition   \n",
       "1364              Community Diagnostic Centre NHS Asset  Image Acquisition   \n",
       "1371              Community Diagnostic Centre NHS Asset  Image Acquisition   \n",
       "1376              Community Diagnostic Centre NHS Asset  Image Acquisition   \n",
       "1443              Community Diagnostic Centre NHS Asset  Image Acquisition   \n",
       "1527                                 Imaging Department  Image Acquisition   \n",
       "1584                                 Imaging Department  Image Acquisition   \n",
       "\n",
       "            Modality_Der                               Equipment Detail Der  \\\n",
       "18                   MRI                                    Close Bore 1.5T   \n",
       "23                   MRI                                    Close Bore 1.5T   \n",
       "26                    CT  64 detector rows or more but less than 256 det...   \n",
       "32            Ultrasound  2D with CEUS / Elastography / Fusion Capabilit...   \n",
       "51    X ray Units Static                              Plain X-Ray-DR Static   \n",
       "65            Ultrasound  2D with CEUS / Elastography / Fusion Capabilit...   \n",
       "83    X ray Units Static                              Plain X-Ray-DR Static   \n",
       "84    X ray Units Static                              Plain X-Ray-DR Static   \n",
       "113           Ultrasound                               Ultrasound - General   \n",
       "140                   CT  256 detector rows or more with iterative recon...   \n",
       "145                  MRI                                    Close Bore 1.5T   \n",
       "162           Ultrasound  2D with CEUS / Elastography / Fusion Capabilit...   \n",
       "166           Ultrasound                               Ultrasound - General   \n",
       "195                   CT  64 detector rows or more but less than 256 det...   \n",
       "222           Ultrasound                               Ultrasound - General   \n",
       "263   X ray Units Static                              Plain X-Ray-DR Static   \n",
       "264                  MRI                                    Close Bore 1.5T   \n",
       "361           Ultrasound                               Ultrasound - General   \n",
       "363           Ultrasound                               Ultrasound - General   \n",
       "368   X ray Units Static                              Plain X-Ray-DR Static   \n",
       "376           Ultrasound                               Ultrasound - General   \n",
       "407   X ray Units Static                              Plain X-Ray-DR Static   \n",
       "497          Mammography  Symptomatic - Digital Mammography 2D + 3D Tomo...   \n",
       "540          Mammography  Symptomatic - Digital Mammography 2D + 3D Tomo...   \n",
       "890                   CT  64 detector rows or more but less than 256 det...   \n",
       "960           Ultrasound                               Ultrasound - General   \n",
       "1042                 MRI                                     Wide Bore 1.5T   \n",
       "1061          Ultrasound          2D with Elastography Capability - General   \n",
       "1103  X ray Units Static                              Plain X-Ray-DR Static   \n",
       "1264                  CT  64 detector rows or more but less than 256 det...   \n",
       "1278                 MRI  Close Bore 1.5T with scan time reduction software   \n",
       "1286          Ultrasound                    2D with 3D Capability – General   \n",
       "1315          Ultrasound                    2D with 3D Capability – General   \n",
       "1317          Ultrasound                    2D with 4D Capability – General   \n",
       "1364  X ray Units Static                              Plain X-Ray-DR Static   \n",
       "1371          Ultrasound                    2D with 3D Capability – General   \n",
       "1376          Ultrasound                    2D with 3D Capability – General   \n",
       "1443          Ultrasound                               Ultrasound - General   \n",
       "1527               Other                                            Unknown   \n",
       "1584               Other                                            Unknown   \n",
       "\n",
       "         Manufacture_Der  ... Core_Operational_Hours_Sat  \\\n",
       "18    Siemens Healthcare  ...                       12.0   \n",
       "23    Siemens Healthcare  ...                       12.0   \n",
       "26                 Canon  ...                        0.0   \n",
       "32                 Canon  ...                        0.0   \n",
       "51    Siemens Healthcare  ...                        8.0   \n",
       "65               Samsung  ...                        0.0   \n",
       "83    Siemens Healthcare  ...                        8.0   \n",
       "84    Siemens Healthcare  ...                        8.0   \n",
       "113                Other  ...                        0.0   \n",
       "140                Canon  ...                       12.0   \n",
       "145                Other  ...                        0.0   \n",
       "162              Samsung  ...                        0.0   \n",
       "166              Samsung  ...                        8.0   \n",
       "195   Philips Healthcare  ...                       12.0   \n",
       "222              Samsung  ...                        8.0   \n",
       "263              Samsung  ...                        0.0   \n",
       "264   Philips Healthcare  ...                       12.0   \n",
       "361   GE Medical Systems  ...                       12.0   \n",
       "363   Philips Healthcare  ...                       12.0   \n",
       "368   GE Medical Systems  ...                        0.0   \n",
       "376                Canon  ...                        8.0   \n",
       "407   GE Medical Systems  ...                        0.0   \n",
       "497   Siemens Healthcare  ...                        0.0   \n",
       "540   Siemens Healthcare  ...                        0.0   \n",
       "890   GE Medical Systems  ...                       12.0   \n",
       "960   GE Medical Systems  ...                       12.0   \n",
       "1042  GE Medical Systems  ...                       12.0   \n",
       "1061  GE Medical Systems  ...                        0.0   \n",
       "1103  GE Medical Systems  ...                       12.0   \n",
       "1264  Siemens Healthcare  ...                        0.0   \n",
       "1278  Siemens Healthcare  ...                       12.0   \n",
       "1286  GE Medical Systems  ...                        0.0   \n",
       "1315             Samsung  ...                        7.5   \n",
       "1317               Canon  ...                        0.0   \n",
       "1364  Siemens Healthcare  ...                        0.0   \n",
       "1371             Samsung  ...                        7.5   \n",
       "1376             Samsung  ...                        7.5   \n",
       "1443  GE Medical Systems  ...                        0.0   \n",
       "1527             Samsung  ...                        0.0   \n",
       "1584             Samsung  ...                        0.0   \n",
       "\n",
       "      OOH_Operational_Hours_Sat  Core_Operational_Hours_Sun  \\\n",
       "18                          0.0                        12.0   \n",
       "23                          0.0                         0.0   \n",
       "26                          0.0                         0.0   \n",
       "32                          0.0                         0.0   \n",
       "51                          0.0                         0.0   \n",
       "65                          0.0                         0.0   \n",
       "83                          0.0                         0.0   \n",
       "84                          0.0                         0.0   \n",
       "113                         0.0                         0.0   \n",
       "140                         0.0                         0.0   \n",
       "145                         0.0                         0.0   \n",
       "162                         0.0                         0.0   \n",
       "166                         0.0                         8.0   \n",
       "195                         0.0                        12.0   \n",
       "222                         0.0                         8.0   \n",
       "263                         0.0                         0.0   \n",
       "264                         0.0                        12.0   \n",
       "361                         0.0                        12.0   \n",
       "363                         0.0                        12.0   \n",
       "368                         0.0                         0.0   \n",
       "376                         0.0                         8.0   \n",
       "407                         0.0                         0.0   \n",
       "497                         0.0                         0.0   \n",
       "540                         0.0                         0.0   \n",
       "890                         0.0                        12.0   \n",
       "960                         0.0                        12.0   \n",
       "1042                        0.0                        12.0   \n",
       "1061                        0.0                         0.0   \n",
       "1103                        0.0                        12.0   \n",
       "1264                        0.0                         0.0   \n",
       "1278                        0.0                        12.0   \n",
       "1286                        0.0                         0.0   \n",
       "1315                        0.0                         7.5   \n",
       "1317                        0.0                         0.0   \n",
       "1364                        0.0                         0.0   \n",
       "1371                        0.0                         7.5   \n",
       "1376                        0.0                         7.5   \n",
       "1443                        0.0                         0.0   \n",
       "1527                        0.0                         0.0   \n",
       "1584                        0.0                         0.0   \n",
       "\n",
       "      OOH_Operational_Hours_Sun         Ownership Structure  \\\n",
       "18                          0.0  Independent Provider Asset   \n",
       "23                          0.0      Capital purchase - new   \n",
       "26                          0.0  Independent Provider Asset   \n",
       "32                          0.0      Capital purchase - new   \n",
       "51                          0.0      Capital purchase - new   \n",
       "65                          0.0      Capital purchase - new   \n",
       "83                          0.0      Capital purchase - new   \n",
       "84                          0.0      Capital purchase - new   \n",
       "113                         0.0  Independent Provider Asset   \n",
       "140                         0.0      Capital purchase - new   \n",
       "145                         0.0  Independent Provider Asset   \n",
       "162                         0.0      Capital purchase - new   \n",
       "166                         0.0      Capital purchase - new   \n",
       "195                         0.0  Independent Provider Asset   \n",
       "222                         0.0      Capital purchase - new   \n",
       "263                         0.0      Capital purchase - new   \n",
       "264                         0.0  Independent Provider Asset   \n",
       "361                         0.0  Independent Provider Asset   \n",
       "363                         0.0  Independent Provider Asset   \n",
       "368                         0.0      Capital purchase - new   \n",
       "376                         0.0      Capital purchase - new   \n",
       "407                         0.0      Capital purchase - new   \n",
       "497                         0.0      Capital purchase - new   \n",
       "540                         0.0      Capital purchase - new   \n",
       "890                         0.0  Independent Provider Asset   \n",
       "960                         0.0  Independent Provider Asset   \n",
       "1042                        0.0  Independent Provider Asset   \n",
       "1061                        0.0   Managed Equipment Service   \n",
       "1103                        0.0  Independent Provider Asset   \n",
       "1264                        0.0   Managed Equipment Service   \n",
       "1278                        0.0  Independent Provider Asset   \n",
       "1286                        0.0      Capital purchase - new   \n",
       "1315                        0.0      Capital purchase - new   \n",
       "1317                        0.0      Capital purchase - new   \n",
       "1364                        0.0      Capital purchase - new   \n",
       "1371                        0.0      Capital purchase - new   \n",
       "1376                        0.0      Capital purchase - new   \n",
       "1443                        0.0      Capital purchase - new   \n",
       "1527                        0.0      Capital purchase - new   \n",
       "1584                        0.0      Capital purchase - new   \n",
       "\n",
       "         Ownership_Structure_Der  Capital Purchase Cost  \\\n",
       "18    Independent Provider Asset                    NaN   \n",
       "23        Capital purchase - new                1100000   \n",
       "26    Independent Provider Asset                    NaN   \n",
       "32        Capital purchase - new                  63600   \n",
       "51        Capital purchase - new                 175000   \n",
       "65        Capital purchase - new                  97944   \n",
       "83        Capital purchase - new                 150000   \n",
       "84        Capital purchase - new                 175000   \n",
       "113   Independent Provider Asset                    NaN   \n",
       "140       Capital purchase - new                 900000   \n",
       "145   Independent Provider Asset                    NaN   \n",
       "162       Capital purchase - new                 101431   \n",
       "166       Capital purchase - new                  68000   \n",
       "195   Independent Provider Asset                    NaN   \n",
       "222       Capital purchase - new                  60000   \n",
       "263       Capital purchase - new                 180000   \n",
       "264   Independent Provider Asset                    NaN   \n",
       "361   Independent Provider Asset                    NaN   \n",
       "363   Independent Provider Asset                    NaN   \n",
       "368       Capital purchase - new                    NaN   \n",
       "376       Capital purchase - new                  80000   \n",
       "407       Capital purchase - new                    NaN   \n",
       "497       Capital purchase - new                 202800   \n",
       "540       Capital purchase - new                 202800   \n",
       "890   Independent Provider Asset                    NaN   \n",
       "960   Independent Provider Asset                    NaN   \n",
       "1042  Independent Provider Asset                    NaN   \n",
       "1061   Managed Equipment Service                    NaN   \n",
       "1103  Independent Provider Asset                    NaN   \n",
       "1264   Managed Equipment Service                    NaN   \n",
       "1278  Independent Provider Asset                    NaN   \n",
       "1286      Capital purchase - new                  75000   \n",
       "1315      Capital purchase - new                  84000   \n",
       "1317      Capital purchase - new                 109308   \n",
       "1364      Capital purchase - new                 238363   \n",
       "1371      Capital purchase - new                  84000   \n",
       "1376      Capital purchase - new                  84000   \n",
       "1443      Capital purchase - new                  65344   \n",
       "1527      Capital purchase - new                  38000   \n",
       "1584      Capital purchase - new                  38000   \n",
       "\n",
       "                  Asset Status               Maintenance Type_Der  \\\n",
       "18    Independent Sector Asset           Independent Sector Asset   \n",
       "23                  In Service  Manufacturer provides maintenance   \n",
       "26    Independent Sector Asset           Independent Sector Asset   \n",
       "32                  In Service  Manufacturer provides maintenance   \n",
       "51                  In Service  Manufacturer provides maintenance   \n",
       "65                  In Service               Asset Under Warranty   \n",
       "83                  In Service  Manufacturer provides maintenance   \n",
       "84                  In Service  Manufacturer provides maintenance   \n",
       "113   Independent Sector Asset           Independent Sector Asset   \n",
       "140                 In Service  Manufacturer provides maintenance   \n",
       "145   Independent Sector Asset           Independent Sector Asset   \n",
       "162                 In Service  Manufacturer provides maintenance   \n",
       "166                 In Service  Manufacturer provides maintenance   \n",
       "195   Independent Sector Asset           Independent Sector Asset   \n",
       "222                 In Service  Manufacturer provides maintenance   \n",
       "263                 In Service  Manufacturer provides maintenance   \n",
       "264   Independent Sector Asset           Independent Sector Asset   \n",
       "361   Independent Sector Asset           Independent Sector Asset   \n",
       "363   Independent Sector Asset           Independent Sector Asset   \n",
       "368                 In Service  Manufacturer provides maintenance   \n",
       "376                 In Service  Manufacturer provides maintenance   \n",
       "407                 In Service  Manufacturer provides maintenance   \n",
       "497                 In Service               Asset Under Warranty   \n",
       "540                 In Service               Asset Under Warranty   \n",
       "890   Independent Sector Asset           Independent Sector Asset   \n",
       "960   Independent Sector Asset           Independent Sector Asset   \n",
       "1042  Independent Sector Asset           Independent Sector Asset   \n",
       "1061     New replacement asset  Manufacturer provides maintenance   \n",
       "1103  Independent Sector Asset           Independent Sector Asset   \n",
       "1264                In Service  Manufacturer provides maintenance   \n",
       "1278                In Service  Manufacturer provides maintenance   \n",
       "1286                In Service  Manufacturer provides maintenance   \n",
       "1315                In Service  Manufacturer provides maintenance   \n",
       "1317                In Service  Manufacturer provides maintenance   \n",
       "1364      New additional asset               Asset Under Warranty   \n",
       "1371                In Service  Manufacturer provides maintenance   \n",
       "1376                In Service  Manufacturer provides maintenance   \n",
       "1443                In Service               Asset Under Warranty   \n",
       "1527                In Service  Manufacturer provides maintenance   \n",
       "1584                In Service  Manufacturer provides maintenance   \n",
       "\n",
       "                                     name  \n",
       "18    UNIVERSITY OF CHICHESTER BOGNOR CDC  \n",
       "23                         SOUTHLANDS CDC  \n",
       "26    UNIVERSITY OF CHICHESTER BOGNOR CDC  \n",
       "32              BRACKNELL HEALTHSPACE CDC  \n",
       "51                         SOUTHLANDS CDC  \n",
       "65              BRACKNELL HEALTHSPACE CDC  \n",
       "83                         SOUTHLANDS CDC  \n",
       "84                         SOUTHLANDS CDC  \n",
       "113                          OAK PARK CDC  \n",
       "140                        SOUTHLANDS CDC  \n",
       "145        FAREHAM COMMUNITY HOSPITAL CDC  \n",
       "162        FAREHAM COMMUNITY HOSPITAL CDC  \n",
       "166                        SOUTHLANDS CDC  \n",
       "195          FALMER COMMUNITY STADIUM CDC  \n",
       "222                        SOUTHLANDS CDC  \n",
       "263        MILFORD COMMUNITY HOSPITAL CDC  \n",
       "264          FALMER COMMUNITY STADIUM CDC  \n",
       "361          FALMER COMMUNITY STADIUM CDC  \n",
       "363          FALMER COMMUNITY STADIUM CDC  \n",
       "368                           BEXHILL CDC  \n",
       "376                        SOUTHLANDS CDC  \n",
       "407                           BEXHILL CDC  \n",
       "497                        PORTSMOUTH CDC  \n",
       "540                          OAK PARK CDC  \n",
       "890                            OXFORD CDC  \n",
       "960                            OXFORD CDC  \n",
       "1042                           OXFORD CDC  \n",
       "1061                          ANDOVER CDC  \n",
       "1103                           OXFORD CDC  \n",
       "1264                ROYAL SOUTH HANTS CDC  \n",
       "1278                          ANDOVER CDC  \n",
       "1286                          BEXHILL CDC  \n",
       "1315                          BEXHILL CDC  \n",
       "1317          QUEEN VICTORIA HOSPITAL CDC  \n",
       "1364                          ANDOVER CDC  \n",
       "1371                          BEXHILL CDC  \n",
       "1376                          BEXHILL CDC  \n",
       "1443       MILFORD COMMUNITY HOSPITAL CDC  \n",
       "1527       MILFORD COMMUNITY HOSPITAL CDC  \n",
       "1584       MILFORD COMMUNITY HOSPITAL CDC  \n",
       "\n",
       "[40 rows x 24 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# check cdc rows\n",
    "df[df[\"name\"].str.contains(\"CDC\")]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>OrganisationCode</th>\n",
       "      <th>OrganisationName</th>\n",
       "      <th>NIDC Asset ID</th>\n",
       "      <th>Local Equipment Identifier</th>\n",
       "      <th>ODS Site Code</th>\n",
       "      <th>Location_Der</th>\n",
       "      <th>Machine_Type_Der</th>\n",
       "      <th>Modality_Der</th>\n",
       "      <th>Equipment Detail Der</th>\n",
       "      <th>Manufacture_Der</th>\n",
       "      <th>...</th>\n",
       "      <th>OOH_Operational_Hours_Sat</th>\n",
       "      <th>Core_Operational_Hours_Sun</th>\n",
       "      <th>OOH_Operational_Hours_Sun</th>\n",
       "      <th>Ownership Structure</th>\n",
       "      <th>Ownership_Structure_Der</th>\n",
       "      <th>Capital Purchase Cost</th>\n",
       "      <th>Asset Status</th>\n",
       "      <th>Maintenance Type_Der</th>\n",
       "      <th>name</th>\n",
       "      <th>type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>RDU</td>\n",
       "      <td>Frimley Health NHS Foundation Trust</td>\n",
       "      <td>A160</td>\n",
       "      <td>G3132152</td>\n",
       "      <td>RDU01</td>\n",
       "      <td>Angiography Suite</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>Ultrasound</td>\n",
       "      <td>Ultrasound - General</td>\n",
       "      <td>Hitachi Medical Systems</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>56704</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Asset Under Warranty</td>\n",
       "      <td>FRIMLEY PARK HOSPITAL</td>\n",
       "      <td>non-CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>RDU</td>\n",
       "      <td>Frimley Health NHS Foundation Trust</td>\n",
       "      <td>A159</td>\n",
       "      <td>E49106</td>\n",
       "      <td>RDU54</td>\n",
       "      <td>Imaging Department</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>Ultrasound</td>\n",
       "      <td>Ultrasound - General</td>\n",
       "      <td>GE Medical Systems</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>56704</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Asset Under Warranty</td>\n",
       "      <td>ST MARK'S HOSPITAL</td>\n",
       "      <td>non-CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>RDU</td>\n",
       "      <td>Frimley Health NHS Foundation Trust</td>\n",
       "      <td>A158</td>\n",
       "      <td>IPX039543</td>\n",
       "      <td>RDU52</td>\n",
       "      <td>Imaging Department</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>Dental</td>\n",
       "      <td>Intraoral</td>\n",
       "      <td>Xograph</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>NaN</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Asset Under Warranty</td>\n",
       "      <td>HEATHERWOOD HOSPITAL</td>\n",
       "      <td>non-CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>RDU</td>\n",
       "      <td>Frimley Health NHS Foundation Trust</td>\n",
       "      <td>A157</td>\n",
       "      <td>TRI2100460</td>\n",
       "      <td>RDU52</td>\n",
       "      <td>Imaging Department</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>X ray Units Mobile</td>\n",
       "      <td>Plain X-Ray-DR Mobile</td>\n",
       "      <td>Hologic</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>NaN</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Asset Under Warranty</td>\n",
       "      <td>HEATHERWOOD HOSPITAL</td>\n",
       "      <td>non-CDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>RDU</td>\n",
       "      <td>Frimley Health NHS Foundation Trust</td>\n",
       "      <td>A156</td>\n",
       "      <td>3DM160700888</td>\n",
       "      <td>RDU52</td>\n",
       "      <td>Imaging Department</td>\n",
       "      <td>Image Acquisition</td>\n",
       "      <td>Mammography</td>\n",
       "      <td>Symptomatic - Digital Mammography 2D + 3D Tomo...</td>\n",
       "      <td>Hologic</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>Capital purchase - new</td>\n",
       "      <td>403800</td>\n",
       "      <td>In Service</td>\n",
       "      <td>Asset Under Warranty</td>\n",
       "      <td>HEATHERWOOD HOSPITAL</td>\n",
       "      <td>non-CDC</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  OrganisationCode                     OrganisationName NIDC Asset ID  \\\n",
       "0              RDU  Frimley Health NHS Foundation Trust          A160   \n",
       "1              RDU  Frimley Health NHS Foundation Trust          A159   \n",
       "2              RDU  Frimley Health NHS Foundation Trust          A158   \n",
       "3              RDU  Frimley Health NHS Foundation Trust          A157   \n",
       "4              RDU  Frimley Health NHS Foundation Trust          A156   \n",
       "\n",
       "  Local Equipment Identifier ODS Site Code        Location_Der  \\\n",
       "0                   G3132152         RDU01   Angiography Suite   \n",
       "1                     E49106         RDU54  Imaging Department   \n",
       "2                  IPX039543         RDU52  Imaging Department   \n",
       "3                 TRI2100460         RDU52  Imaging Department   \n",
       "4               3DM160700888         RDU52  Imaging Department   \n",
       "\n",
       "    Machine_Type_Der        Modality_Der  \\\n",
       "0  Image Acquisition          Ultrasound   \n",
       "1  Image Acquisition          Ultrasound   \n",
       "2  Image Acquisition              Dental   \n",
       "3  Image Acquisition  X ray Units Mobile   \n",
       "4  Image Acquisition         Mammography   \n",
       "\n",
       "                                Equipment Detail Der          Manufacture_Der  \\\n",
       "0                               Ultrasound - General  Hitachi Medical Systems   \n",
       "1                               Ultrasound - General       GE Medical Systems   \n",
       "2                                          Intraoral                  Xograph   \n",
       "3                              Plain X-Ray-DR Mobile                  Hologic   \n",
       "4  Symptomatic - Digital Mammography 2D + 3D Tomo...                  Hologic   \n",
       "\n",
       "   ... OOH_Operational_Hours_Sat  Core_Operational_Hours_Sun  \\\n",
       "0  ...                       0.0                         0.0   \n",
       "1  ...                       0.0                         0.0   \n",
       "2  ...                       0.0                        12.0   \n",
       "3  ...                       0.0                         0.0   \n",
       "4  ...                       0.0                         0.0   \n",
       "\n",
       "   OOH_Operational_Hours_Sun     Ownership Structure  Ownership_Structure_Der  \\\n",
       "0                        0.0  Capital purchase - new   Capital purchase - new   \n",
       "1                        0.0  Capital purchase - new   Capital purchase - new   \n",
       "2                        0.0  Capital purchase - new   Capital purchase - new   \n",
       "3                        0.0  Capital purchase - new   Capital purchase - new   \n",
       "4                        0.0  Capital purchase - new   Capital purchase - new   \n",
       "\n",
       "   Capital Purchase Cost  Asset Status  Maintenance Type_Der  \\\n",
       "0                  56704    In Service  Asset Under Warranty   \n",
       "1                  56704    In Service  Asset Under Warranty   \n",
       "2                    NaN    In Service  Asset Under Warranty   \n",
       "3                    NaN    In Service  Asset Under Warranty   \n",
       "4                 403800    In Service  Asset Under Warranty   \n",
       "\n",
       "                    name     type  \n",
       "0  FRIMLEY PARK HOSPITAL  non-CDC  \n",
       "1     ST MARK'S HOSPITAL  non-CDC  \n",
       "2   HEATHERWOOD HOSPITAL  non-CDC  \n",
       "3   HEATHERWOOD HOSPITAL  non-CDC  \n",
       "4   HEATHERWOOD HOSPITAL  non-CDC  \n",
       "\n",
       "[5 rows x 25 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# flag for CDCs\n",
    "df[\"type\"] = df[\"name\"].apply(lambda x: \"CDC\" if \"CDC\" in x else \"non-CDC\")\n",
    "\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Count of machine type by asset status"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\local_martin.bloyce2\\Temp\\ipykernel_18488\\3507703160.py:5: FutureWarning:\n",
      "\n",
      "The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Remove 'decommissioned'\n",
    "count_data = df[df['Asset Status'] != \"Decommissioned\"]\n",
    "\n",
    "# Count the occurrences\n",
    "count_data = count_data.groupby(['Modality_Der', 'Asset Status']).size().unstack().fillna(0)\n",
    "\n",
    "# NHS colour palette dictionary\n",
    "nhs_colours = {\n",
    "    'Asset in storage': '#003087', # NHS Dark Blue\n",
    "    'Covered by MES': '#212b32', # black\n",
    "    # 'Decommissioned': '#768692', # grey 1  ## no longer needed\n",
    "    'Due for replacement': '#DA291C', # red\n",
    "    'In Service': '#005EB8', # NHS Blue\n",
    "    'Independent Sector Asset': '#768692', # grey 1\n",
    "    'New additional asset': '#0072CE', # NHS Bright Blue\n",
    "    'New replacement asset': '#41B6E6', # NHS Light Blue\n",
    "    'Omitted from previous return': '#00A9CE' # NHS Aqua Blue\n",
    "}\n",
    "\n",
    "# Desired order of 'Asset Status'\n",
    "desired_order = ['Asset in storage',\n",
    "                 'In Service',\n",
    "                 'New additional asset',\n",
    "                 'New replacement asset',\n",
    "                 'Omitted from previous return',\n",
    "                 'Covered by MES',\n",
    "                 'Independent Sector Asset',\n",
    "                 'Due for replacement'\n",
    "                ]\n",
    "\n",
    "# Reindex the DataFrame to match the desired order\n",
    "count_data = count_data.reindex(columns=desired_order)\n",
    "\n",
    "# Plotting\n",
    "count_data.plot(kind='barh', stacked=True, color=[nhs_colours[col] for col in count_data.columns])\n",
    "plt.title('Count of Asset Status by Modality_Der')\n",
    "plt.xlabel('Count')\n",
    "plt.ylabel('Modality')\n",
    "plt.legend(title='Asset Status')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Asset Status</th>\n",
       "      <th>Asset in storage</th>\n",
       "      <th>Covered by MES</th>\n",
       "      <th>Decommissioned</th>\n",
       "      <th>Due for replacement</th>\n",
       "      <th>In Service</th>\n",
       "      <th>Independent Sector Asset</th>\n",
       "      <th>New additional asset</th>\n",
       "      <th>New replacement asset</th>\n",
       "      <th>Omitted from previous return</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Modality_Der</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Accessory</th>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>113.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CT</th>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Catheter Lab</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DEXA</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dental</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fluoroscopy</th>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Interventional Radiology</th>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MRI</th>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mammography</th>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mobile C arm</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>127.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nuclear Medicine</th>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Other</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ultrasound</th>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>363.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>X ray Units Mobile</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>144.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>X ray Units Static</th>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>203.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Asset Status              Asset in storage  Covered by MES  Decommissioned  \\\n",
       "Modality_Der                                                                 \n",
       "Accessory                              3.0             0.0             8.0   \n",
       "CT                                     2.0             2.0             5.0   \n",
       "Catheter Lab                           0.0             1.0             2.0   \n",
       "DEXA                                   1.0             0.0             3.0   \n",
       "Dental                                 0.0             0.0             4.0   \n",
       "Fluoroscopy                            1.0             2.0             5.0   \n",
       "Interventional Radiology               2.0             2.0             0.0   \n",
       "MRI                                    3.0             0.0             3.0   \n",
       "Mammography                            0.0             4.0             6.0   \n",
       "Mobile C arm                           0.0             0.0            19.0   \n",
       "Nuclear Medicine                       1.0             2.0             2.0   \n",
       "Other                                  0.0             0.0             3.0   \n",
       "Ultrasound                             0.0             8.0            27.0   \n",
       "X ray Units Mobile                     0.0             0.0             6.0   \n",
       "X ray Units Static                     1.0             4.0            14.0   \n",
       "\n",
       "Asset Status              Due for replacement  In Service  \\\n",
       "Modality_Der                                                \n",
       "Accessory                                 1.0       113.0   \n",
       "CT                                        3.0        69.0   \n",
       "Catheter Lab                              0.0        17.0   \n",
       "DEXA                                      0.0         7.0   \n",
       "Dental                                    2.0        45.0   \n",
       "Fluoroscopy                               4.0        30.0   \n",
       "Interventional Radiology                  5.0        28.0   \n",
       "MRI                                       0.0        59.0   \n",
       "Mammography                               1.0        41.0   \n",
       "Mobile C arm                              2.0       127.0   \n",
       "Nuclear Medicine                          8.0        19.0   \n",
       "Other                                     0.0        43.0   \n",
       "Ultrasound                                4.0       363.0   \n",
       "X ray Units Mobile                        9.0       144.0   \n",
       "X ray Units Static                       12.0       203.0   \n",
       "\n",
       "Asset Status              Independent Sector Asset  New additional asset  \\\n",
       "Modality_Der                                                               \n",
       "Accessory                                      0.0                   4.0   \n",
       "CT                                             5.0                   0.0   \n",
       "Catheter Lab                                   0.0                   0.0   \n",
       "DEXA                                           0.0                   0.0   \n",
       "Dental                                         0.0                   0.0   \n",
       "Fluoroscopy                                    0.0                   0.0   \n",
       "Interventional Radiology                       0.0                   0.0   \n",
       "MRI                                            7.0                   0.0   \n",
       "Mammography                                    0.0                   1.0   \n",
       "Mobile C arm                                   0.0                   3.0   \n",
       "Nuclear Medicine                               0.0                   0.0   \n",
       "Other                                          0.0                   0.0   \n",
       "Ultrasound                                     4.0                   1.0   \n",
       "X ray Units Mobile                             0.0                   0.0   \n",
       "X ray Units Static                             1.0                   1.0   \n",
       "\n",
       "Asset Status              New replacement asset  Omitted from previous return  \n",
       "Modality_Der                                                                   \n",
       "Accessory                                   8.0                           0.0  \n",
       "CT                                          2.0                           1.0  \n",
       "Catheter Lab                                2.0                           0.0  \n",
       "DEXA                                        2.0                           3.0  \n",
       "Dental                                      1.0                           0.0  \n",
       "Fluoroscopy                                 2.0                           0.0  \n",
       "Interventional Radiology                    0.0                           0.0  \n",
       "MRI                                         0.0                           0.0  \n",
       "Mammography                                 6.0                           0.0  \n",
       "Mobile C arm                               15.0                           1.0  \n",
       "Nuclear Medicine                            1.0                           0.0  \n",
       "Other                                       0.0                           0.0  \n",
       "Ultrasound                                 10.0                          15.0  \n",
       "X ray Units Mobile                          1.0                           2.0  \n",
       "X ray Units Static                          8.0                           0.0  "
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "count_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"100%\"\n",
       "            height=\"650\"\n",
       "            src=\"http://127.0.0.1:8050/\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "            \n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.IFrame at 0x17d8207cd10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# trial with dash app...\n",
    "\n",
    "# Initialize the Dash app\n",
    "app = dash.Dash(__name__)\n",
    "\n",
    "# Create a list of tabs for each Modality_Der\n",
    "tabs = []\n",
    "modalities = sorted(df['Modality_Der'].unique())\n",
    "for modality in modalities:\n",
    "    df_modality = df[df['Modality_Der'] == modality]\n",
    "    df_count = df_modality.groupby(['OrganisationName', 'type']).size().reset_index(name='count')\n",
    "    \n",
    "    # Calculate the percentage of \"CDC\"\n",
    "    df_total = df_count.groupby('OrganisationName')['count'].sum().reset_index(name='total_count')\n",
    "    df_cdc = df_count[df_count['type'] == 'CDC'].merge(df_total, on='OrganisationName')\n",
    "    df_cdc['percentage'] = (df_cdc['count'] / df_cdc['total_count']) * 100\n",
    "    \n",
    "    # Create subplots with secondary y-axis\n",
    "    fig = make_subplots(specs=[[{\"secondary_y\": True}]])\n",
    "    \n",
    "    # Add bar chart for counts\n",
    "    for t in df_count['type'].unique():\n",
    "        df_type = df_count[df_count['type'] == t]\n",
    "        fig.add_trace(\n",
    "            go.Bar(x=df_type['OrganisationName'], y=df_type['count'], name=t),\n",
    "            secondary_y=False,\n",
    "        )\n",
    "    \n",
    "    # Add line chart for percentage of \"CDC\"\n",
    "    fig.add_trace(\n",
    "        go.Scatter(x=df_cdc['OrganisationName'], y=df_cdc['percentage'], name='CDC %', mode='markers', line=dict(color='black')),\n",
    "        secondary_y=True,\n",
    "    )\n",
    "    \n",
    "    # Update layout\n",
    "    fig.update_layout(\n",
    "        title_text=f'Count of Assets by location type for {modality}',\n",
    "        barmode='group',\n",
    "        yaxis_title='Count',\n",
    "        yaxis2_title='Percentage of CDC',\n",
    "        legend_title='Type'\n",
    "    )\n",
    "    \n",
    "    tabs.append(dcc.Tab(label=modality, children=[\n",
    "        dcc.Graph(figure=fig)\n",
    "    ]))\n",
    "\n",
    "# Define the layout of the app\n",
    "app.layout = html.Div([\n",
    "    dcc.Tabs(tabs)\n",
    "])\n",
    "\n",
    "# Run the app\n",
    "if __name__ == '__main__':\n",
    "    app.run_server(debug=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# # Define the color palette with CDC as blue and non-CDC as orange\n",
    "# colors = {'non-CDC': '#1f77b4', 'CDC': '#ff7f0e'}\n",
    "\n",
    "# # Assuming 'Modality_Der' is a column in your DataFrame\n",
    "# modalities = df['Modality_Der'].unique()\n",
    "\n",
    "# for modality in modalities:\n",
    "#     # Filter the DataFrame for the current modality\n",
    "#     df_modality = df[df['Modality_Der'] == modality]\n",
    "    \n",
    "#     # Group by 'OrganisationName' and 'type', then count\n",
    "#     count_cdc = df_modality.groupby(['OrganisationName', 'type']).size().unstack().fillna(0)\n",
    "    \n",
    "#     # # Ensure the columns are in the correct order\n",
    "#     # count_cdc = count_cdc[['CDC', 'non-CDC']]\n",
    "    \n",
    "#     # Plotting\n",
    "#     count_cdc.plot(kind='bar', stacked=True, color=colors)\n",
    "#     plt.title(f'Count of Assets by location type for {modality}')\n",
    "#     plt.xlabel('Org Name')\n",
    "#     plt.ylabel('Count')\n",
    "#     plt.legend(title='Location Type')\n",
    "#     plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Scatterplot count of modality vs avg age of asset, by provider"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# remove decommissioned assets\n",
    "df = df[df['Asset Status'] != 'Decommissioned']\n",
    "\n",
    "# Group by OrganisationName to get the count and average age_of_asset\n",
    "grouped_df = df.groupby('Modality_Der').agg(\n",
    "    count_modality=('Modality_Der', 'count'),\n",
    "    avg_age_of_asset=('Age', 'mean')\n",
    ").reset_index()\n",
    "\n",
    "\n",
    "# Create a scatter plot\n",
    "plt.scatter(grouped_df['count_modality'], grouped_df['avg_age_of_asset'])\n",
    "\n",
    "# Add labels and title\n",
    "plt.xlabel('Count of Assets')\n",
    "plt.ylabel('Average Age of Asset')\n",
    "plt.title('Scatterplot of Count of Assets vs Average Age of Asset by Org')\n",
    "\n",
    "# Label dots with OrganisationName\n",
    "for i, row in grouped_df.iterrows():\n",
    "    plt.text(row['count_modality'], row['avg_age_of_asset'], row['Modality_Der'])\n",
    "\n",
    "# Show the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Asset type by age"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Replacement schedule and cost dictionaries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "replacement_schedule = {\n",
    "'Accessory': 5,\n",
    "'CT': 8,\n",
    "'Catheter Lab': 8,\n",
    "'DEXA': 10,\n",
    "'Dental': 10,\n",
    "'Fluoroscopy': 8,\n",
    "'Interventional Radiology': 8,\n",
    "'MRI': 8,\n",
    "'Mammography': 5,\n",
    "'Mobile C arm': 8,\n",
    "'Nuclear Medicine': 8,\n",
    "'Other': 0,\n",
    "'Ultrasound': 5,\n",
    "'X ray Units Mobile': 8,\n",
    "'X ray Units Static': 8,\n",
    "}\n",
    "\n",
    "replacement_cost = {\n",
    "'Accessory': 25000,\n",
    "'CT': 850000,\n",
    "'Catheter Lab': 1000000,\n",
    "'DEXA': 950000,\n",
    "'Dental': 45000,\n",
    "'Fluoroscopy': 800000,\n",
    "'Interventional Radiology': 1000000,\n",
    "'MRI': 1200000,\n",
    "'Mammography': 400000,\n",
    "'Mobile C arm': 95000,\n",
    "'Nuclear Medicine': 900000,\n",
    "'Other': np.nan,\n",
    "'Ultrasound': 90000,\n",
    "'X ray Units Mobile': 90000,\n",
    "'X ray Units Static': 125000,\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Stacked bar chart by provider"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\local_martin.bloyce2\\Temp\\ipykernel_18488\\43947674.py:12: FutureWarning:\n",
      "\n",
      "The default value of observed=False is deprecated and will change to observed=True in a future version of pandas. Specify observed=False to silence this warning and retain the current behavior\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# remove decommissioned assets\n",
    "df = df[df['Asset Status'] != 'Decommissioned']\n",
    "\n",
    "# Add replacement_cost to the DataFrame\n",
    "df['replacement_cost'] = df.apply(lambda row: replacement_cost[(row['Modality_Der'])], axis=1)\n",
    "df['replacement_schedule'] = df.apply(lambda row: replacement_schedule[(row['Modality_Der'])], axis=1)\n",
    "\n",
    "# Only where Age > replacement_schedule\n",
    "outdated_assets = df[df['Age'] > df['replacement_schedule']]\n",
    "\n",
    "# Pivot the DataFrame to get the data in the format required for a stacked bar chart\n",
    "pivot_df = outdated_assets.pivot_table(index='OrganisationName', columns='Modality_Der', values='replacement_cost', aggfunc='sum').fillna(0)\n",
    "\n",
    "# Calculate the total replacement cost per organisation\n",
    "pivot_df['Total'] = pivot_df.sum(axis=1)\n",
    "\n",
    "# Sort by total replacement cost\n",
    "pivot_df = pivot_df.sort_values('Total', ascending=False).drop('Total', axis=1)\n",
    "\n",
    "# Create a stacked bar chart\n",
    "pivot_df.plot(kind='barh', stacked=True)\n",
    "\n",
    "# Add labels and title\n",
    "plt.xlabel('Replacement Cost (£mil)')\n",
    "plt.ylabel('OrganisationName')\n",
    "plt.title('Replacement Cost by Organisation and Modality')\n",
    "plt.legend(loc='center left', bbox_to_anchor=(1, 0.5))\n",
    "\n",
    "# Invert y-axis\n",
    "plt.gca().invert_yaxis()\n",
    "\n",
    "# Show the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Modality_Der</th>\n",
       "      <th>Accessory</th>\n",
       "      <th>CT</th>\n",
       "      <th>Catheter Lab</th>\n",
       "      <th>DEXA</th>\n",
       "      <th>Dental</th>\n",
       "      <th>Fluoroscopy</th>\n",
       "      <th>Interventional Radiology</th>\n",
       "      <th>MRI</th>\n",
       "      <th>Mammography</th>\n",
       "      <th>Mobile C arm</th>\n",
       "      <th>Nuclear Medicine</th>\n",
       "      <th>Other</th>\n",
       "      <th>Ultrasound</th>\n",
       "      <th>X ray Units Mobile</th>\n",
       "      <th>X ray Units Static</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OrganisationName</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Ashford and St Peter's Hospitals NHS Foundation Trust</th>\n",
       "      <td>75000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1600000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>450000.0</td>\n",
       "      <td>750000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Buckinghamshire Healthcare NHS Trust</th>\n",
       "      <td>0.0</td>\n",
       "      <td>850000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>45000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>285000.0</td>\n",
       "      <td>900000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>540000.0</td>\n",
       "      <td>180000.0</td>\n",
       "      <td>625000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dartford and Gravesham NHS Trust</th>\n",
       "      <td>0.0</td>\n",
       "      <td>850000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>800000.0</td>\n",
       "      <td>1000000.0</td>\n",
       "      <td>1200000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>95000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>90000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>625000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>East Kent Hospitals University NHS Foundation Trust</th>\n",
       "      <td>225000.0</td>\n",
       "      <td>2550000.0</td>\n",
       "      <td>2000000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>45000.0</td>\n",
       "      <td>800000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2400000.0</td>\n",
       "      <td>1200000.0</td>\n",
       "      <td>285000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>180000.0</td>\n",
       "      <td>180000.0</td>\n",
       "      <td>375000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>East Sussex Healthcare NHS Trust</th>\n",
       "      <td>50000.0</td>\n",
       "      <td>850000.0</td>\n",
       "      <td>1000000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>45000.0</td>\n",
       "      <td>800000.0</td>\n",
       "      <td>2000000.0</td>\n",
       "      <td>1200000.0</td>\n",
       "      <td>800000.0</td>\n",
       "      <td>95000.0</td>\n",
       "      <td>900000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>90000.0</td>\n",
       "      <td>90000.0</td>\n",
       "      <td>625000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Frimley Health NHS Foundation Trust</th>\n",
       "      <td>175000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000000.0</td>\n",
       "      <td>950000.0</td>\n",
       "      <td>90000.0</td>\n",
       "      <td>800000.0</td>\n",
       "      <td>2000000.0</td>\n",
       "      <td>1200000.0</td>\n",
       "      <td>800000.0</td>\n",
       "      <td>380000.0</td>\n",
       "      <td>1800000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1350000.0</td>\n",
       "      <td>360000.0</td>\n",
       "      <td>3250000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hampshire Hospitals NHS Foundation Trust</th>\n",
       "      <td>200000.0</td>\n",
       "      <td>2550000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>800000.0</td>\n",
       "      <td>2000000.0</td>\n",
       "      <td>4800000.0</td>\n",
       "      <td>800000.0</td>\n",
       "      <td>95000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>90000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>875000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Maidstone and Tunbridge Wells NHS Trust</th>\n",
       "      <td>75000.0</td>\n",
       "      <td>1700000.0</td>\n",
       "      <td>1000000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>45000.0</td>\n",
       "      <td>800000.0</td>\n",
       "      <td>1000000.0</td>\n",
       "      <td>1200000.0</td>\n",
       "      <td>400000.0</td>\n",
       "      <td>285000.0</td>\n",
       "      <td>900000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>90000.0</td>\n",
       "      <td>180000.0</td>\n",
       "      <td>750000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Medway NHS Foundation Trust</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>45000.0</td>\n",
       "      <td>2400000.0</td>\n",
       "      <td>1000000.0</td>\n",
       "      <td>2400000.0</td>\n",
       "      <td>400000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2700000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>750000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Oxford University Hospitals NHS Foundation Trust</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>90000.0</td>\n",
       "      <td>4000000.0</td>\n",
       "      <td>4000000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>380000.0</td>\n",
       "      <td>4500000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1800000.0</td>\n",
       "      <td>1260000.0</td>\n",
       "      <td>1000000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Portsmouth Hospitals University National Health Service Trust</th>\n",
       "      <td>125000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>800000.0</td>\n",
       "      <td>1000000.0</td>\n",
       "      <td>2400000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2700000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>630000.0</td>\n",
       "      <td>270000.0</td>\n",
       "      <td>1750000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Queen Victoria Hospital NHS Foundation Trust</th>\n",
       "      <td>0.0</td>\n",
       "      <td>850000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>135000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>90000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Royal Berkshire NHS Foundation Trust</th>\n",
       "      <td>75000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>800000.0</td>\n",
       "      <td>1000000.0</td>\n",
       "      <td>2400000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>95000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>630000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1125000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Royal Surrey County Hospital NHS Foundation Trust</th>\n",
       "      <td>25000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>90000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>400000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Surrey and Sussex Healthcare NHS Trust</th>\n",
       "      <td>100000.0</td>\n",
       "      <td>850000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>45000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>400000.0</td>\n",
       "      <td>190000.0</td>\n",
       "      <td>1800000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1170000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>625000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>University Hospital Southampton NHS Foundation Trust</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1000000.0</td>\n",
       "      <td>3600000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>95000.0</td>\n",
       "      <td>900000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>180000.0</td>\n",
       "      <td>540000.0</td>\n",
       "      <td>750000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>University Hospitals Sussex NHS Foundation Trust</th>\n",
       "      <td>125000.0</td>\n",
       "      <td>850000.0</td>\n",
       "      <td>1000000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>800000.0</td>\n",
       "      <td>1000000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>900000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>720000.0</td>\n",
       "      <td>180000.0</td>\n",
       "      <td>125000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Modality_Der                                        Accessory         CT  \\\n",
       "OrganisationName                                                           \n",
       "Ashford and St Peter's Hospitals NHS Foundation...    75000.0        0.0   \n",
       "Buckinghamshire Healthcare NHS Trust                      0.0   850000.0   \n",
       "Dartford and Gravesham NHS Trust                          0.0   850000.0   \n",
       "East Kent Hospitals University NHS Foundation T...   225000.0  2550000.0   \n",
       "East Sussex Healthcare NHS Trust                      50000.0   850000.0   \n",
       "Frimley Health NHS Foundation Trust                  175000.0        0.0   \n",
       "Hampshire Hospitals NHS Foundation Trust             200000.0  2550000.0   \n",
       "Maidstone and Tunbridge Wells NHS Trust               75000.0  1700000.0   \n",
       "Medway NHS Foundation Trust                               0.0        0.0   \n",
       "Oxford University Hospitals NHS Foundation Trust          0.0        0.0   \n",
       "Portsmouth Hospitals University National Health...   125000.0        0.0   \n",
       "Queen Victoria Hospital NHS Foundation Trust              0.0   850000.0   \n",
       "Royal Berkshire NHS Foundation Trust                  75000.0        0.0   \n",
       "Royal Surrey County Hospital NHS Foundation Trust     25000.0        0.0   \n",
       "Surrey and Sussex Healthcare NHS Trust               100000.0   850000.0   \n",
       "University Hospital Southampton NHS Foundation ...        0.0        0.0   \n",
       "University Hospitals Sussex NHS Foundation Trust     125000.0   850000.0   \n",
       "\n",
       "Modality_Der                                        Catheter Lab      DEXA  \\\n",
       "OrganisationName                                                             \n",
       "Ashford and St Peter's Hospitals NHS Foundation...           0.0       0.0   \n",
       "Buckinghamshire Healthcare NHS Trust                         0.0       0.0   \n",
       "Dartford and Gravesham NHS Trust                             0.0       0.0   \n",
       "East Kent Hospitals University NHS Foundation T...     2000000.0       0.0   \n",
       "East Sussex Healthcare NHS Trust                       1000000.0       0.0   \n",
       "Frimley Health NHS Foundation Trust                    1000000.0  950000.0   \n",
       "Hampshire Hospitals NHS Foundation Trust                     0.0       0.0   \n",
       "Maidstone and Tunbridge Wells NHS Trust                1000000.0       0.0   \n",
       "Medway NHS Foundation Trust                                  0.0       0.0   \n",
       "Oxford University Hospitals NHS Foundation Trust             0.0       0.0   \n",
       "Portsmouth Hospitals University National Health...           0.0       0.0   \n",
       "Queen Victoria Hospital NHS Foundation Trust                 0.0       0.0   \n",
       "Royal Berkshire NHS Foundation Trust                         0.0       0.0   \n",
       "Royal Surrey County Hospital NHS Foundation Trust            0.0       0.0   \n",
       "Surrey and Sussex Healthcare NHS Trust                       0.0       0.0   \n",
       "University Hospital Southampton NHS Foundation ...           0.0       0.0   \n",
       "University Hospitals Sussex NHS Foundation Trust       1000000.0       0.0   \n",
       "\n",
       "Modality_Der                                          Dental  Fluoroscopy  \\\n",
       "OrganisationName                                                            \n",
       "Ashford and St Peter's Hospitals NHS Foundation...       0.0    1600000.0   \n",
       "Buckinghamshire Healthcare NHS Trust                 45000.0          0.0   \n",
       "Dartford and Gravesham NHS Trust                         0.0     800000.0   \n",
       "East Kent Hospitals University NHS Foundation T...   45000.0     800000.0   \n",
       "East Sussex Healthcare NHS Trust                     45000.0     800000.0   \n",
       "Frimley Health NHS Foundation Trust                  90000.0     800000.0   \n",
       "Hampshire Hospitals NHS Foundation Trust                 0.0     800000.0   \n",
       "Maidstone and Tunbridge Wells NHS Trust              45000.0     800000.0   \n",
       "Medway NHS Foundation Trust                          45000.0    2400000.0   \n",
       "Oxford University Hospitals NHS Foundation Trust     90000.0    4000000.0   \n",
       "Portsmouth Hospitals University National Health...       0.0     800000.0   \n",
       "Queen Victoria Hospital NHS Foundation Trust        135000.0          0.0   \n",
       "Royal Berkshire NHS Foundation Trust                     0.0     800000.0   \n",
       "Royal Surrey County Hospital NHS Foundation Trust    90000.0          0.0   \n",
       "Surrey and Sussex Healthcare NHS Trust               45000.0          0.0   \n",
       "University Hospital Southampton NHS Foundation ...       0.0          0.0   \n",
       "University Hospitals Sussex NHS Foundation Trust         0.0     800000.0   \n",
       "\n",
       "Modality_Der                                        Interventional Radiology  \\\n",
       "OrganisationName                                                               \n",
       "Ashford and St Peter's Hospitals NHS Foundation...                       0.0   \n",
       "Buckinghamshire Healthcare NHS Trust                                     0.0   \n",
       "Dartford and Gravesham NHS Trust                                   1000000.0   \n",
       "East Kent Hospitals University NHS Foundation T...                       0.0   \n",
       "East Sussex Healthcare NHS Trust                                   2000000.0   \n",
       "Frimley Health NHS Foundation Trust                                2000000.0   \n",
       "Hampshire Hospitals NHS Foundation Trust                           2000000.0   \n",
       "Maidstone and Tunbridge Wells NHS Trust                            1000000.0   \n",
       "Medway NHS Foundation Trust                                        1000000.0   \n",
       "Oxford University Hospitals NHS Foundation Trust                   4000000.0   \n",
       "Portsmouth Hospitals University National Health...                 1000000.0   \n",
       "Queen Victoria Hospital NHS Foundation Trust                             0.0   \n",
       "Royal Berkshire NHS Foundation Trust                               1000000.0   \n",
       "Royal Surrey County Hospital NHS Foundation Trust                        0.0   \n",
       "Surrey and Sussex Healthcare NHS Trust                             1000000.0   \n",
       "University Hospital Southampton NHS Foundation ...                 1000000.0   \n",
       "University Hospitals Sussex NHS Foundation Trust                   1000000.0   \n",
       "\n",
       "Modality_Der                                              MRI  Mammography  \\\n",
       "OrganisationName                                                             \n",
       "Ashford and St Peter's Hospitals NHS Foundation...        0.0          0.0   \n",
       "Buckinghamshire Healthcare NHS Trust                      0.0          0.0   \n",
       "Dartford and Gravesham NHS Trust                    1200000.0          0.0   \n",
       "East Kent Hospitals University NHS Foundation T...  2400000.0    1200000.0   \n",
       "East Sussex Healthcare NHS Trust                    1200000.0     800000.0   \n",
       "Frimley Health NHS Foundation Trust                 1200000.0     800000.0   \n",
       "Hampshire Hospitals NHS Foundation Trust            4800000.0     800000.0   \n",
       "Maidstone and Tunbridge Wells NHS Trust             1200000.0     400000.0   \n",
       "Medway NHS Foundation Trust                         2400000.0     400000.0   \n",
       "Oxford University Hospitals NHS Foundation Trust          0.0          0.0   \n",
       "Portsmouth Hospitals University National Health...  2400000.0          0.0   \n",
       "Queen Victoria Hospital NHS Foundation Trust              0.0          0.0   \n",
       "Royal Berkshire NHS Foundation Trust                2400000.0          0.0   \n",
       "Royal Surrey County Hospital NHS Foundation Trust         0.0     400000.0   \n",
       "Surrey and Sussex Healthcare NHS Trust                    0.0     400000.0   \n",
       "University Hospital Southampton NHS Foundation ...  3600000.0          0.0   \n",
       "University Hospitals Sussex NHS Foundation Trust          0.0          0.0   \n",
       "\n",
       "Modality_Der                                        Mobile C arm  \\\n",
       "OrganisationName                                                   \n",
       "Ashford and St Peter's Hospitals NHS Foundation...           0.0   \n",
       "Buckinghamshire Healthcare NHS Trust                    285000.0   \n",
       "Dartford and Gravesham NHS Trust                         95000.0   \n",
       "East Kent Hospitals University NHS Foundation T...      285000.0   \n",
       "East Sussex Healthcare NHS Trust                         95000.0   \n",
       "Frimley Health NHS Foundation Trust                     380000.0   \n",
       "Hampshire Hospitals NHS Foundation Trust                 95000.0   \n",
       "Maidstone and Tunbridge Wells NHS Trust                 285000.0   \n",
       "Medway NHS Foundation Trust                                  0.0   \n",
       "Oxford University Hospitals NHS Foundation Trust        380000.0   \n",
       "Portsmouth Hospitals University National Health...           0.0   \n",
       "Queen Victoria Hospital NHS Foundation Trust                 0.0   \n",
       "Royal Berkshire NHS Foundation Trust                     95000.0   \n",
       "Royal Surrey County Hospital NHS Foundation Trust            0.0   \n",
       "Surrey and Sussex Healthcare NHS Trust                  190000.0   \n",
       "University Hospital Southampton NHS Foundation ...       95000.0   \n",
       "University Hospitals Sussex NHS Foundation Trust             0.0   \n",
       "\n",
       "Modality_Der                                        Nuclear Medicine  Other  \\\n",
       "OrganisationName                                                              \n",
       "Ashford and St Peter's Hospitals NHS Foundation...               0.0    0.0   \n",
       "Buckinghamshire Healthcare NHS Trust                        900000.0    0.0   \n",
       "Dartford and Gravesham NHS Trust                                 0.0    0.0   \n",
       "East Kent Hospitals University NHS Foundation T...               0.0    0.0   \n",
       "East Sussex Healthcare NHS Trust                            900000.0    0.0   \n",
       "Frimley Health NHS Foundation Trust                        1800000.0    0.0   \n",
       "Hampshire Hospitals NHS Foundation Trust                         0.0    0.0   \n",
       "Maidstone and Tunbridge Wells NHS Trust                     900000.0    0.0   \n",
       "Medway NHS Foundation Trust                                2700000.0    0.0   \n",
       "Oxford University Hospitals NHS Foundation Trust           4500000.0    0.0   \n",
       "Portsmouth Hospitals University National Health...         2700000.0    0.0   \n",
       "Queen Victoria Hospital NHS Foundation Trust                     0.0    0.0   \n",
       "Royal Berkshire NHS Foundation Trust                             0.0    0.0   \n",
       "Royal Surrey County Hospital NHS Foundation Trust                0.0    0.0   \n",
       "Surrey and Sussex Healthcare NHS Trust                     1800000.0    0.0   \n",
       "University Hospital Southampton NHS Foundation ...          900000.0    0.0   \n",
       "University Hospitals Sussex NHS Foundation Trust            900000.0    0.0   \n",
       "\n",
       "Modality_Der                                        Ultrasound  \\\n",
       "OrganisationName                                                 \n",
       "Ashford and St Peter's Hospitals NHS Foundation...         0.0   \n",
       "Buckinghamshire Healthcare NHS Trust                  540000.0   \n",
       "Dartford and Gravesham NHS Trust                       90000.0   \n",
       "East Kent Hospitals University NHS Foundation T...    180000.0   \n",
       "East Sussex Healthcare NHS Trust                       90000.0   \n",
       "Frimley Health NHS Foundation Trust                  1350000.0   \n",
       "Hampshire Hospitals NHS Foundation Trust               90000.0   \n",
       "Maidstone and Tunbridge Wells NHS Trust                90000.0   \n",
       "Medway NHS Foundation Trust                                0.0   \n",
       "Oxford University Hospitals NHS Foundation Trust     1800000.0   \n",
       "Portsmouth Hospitals University National Health...    630000.0   \n",
       "Queen Victoria Hospital NHS Foundation Trust           90000.0   \n",
       "Royal Berkshire NHS Foundation Trust                  630000.0   \n",
       "Royal Surrey County Hospital NHS Foundation Trust          0.0   \n",
       "Surrey and Sussex Healthcare NHS Trust               1170000.0   \n",
       "University Hospital Southampton NHS Foundation ...    180000.0   \n",
       "University Hospitals Sussex NHS Foundation Trust      720000.0   \n",
       "\n",
       "Modality_Der                                        X ray Units Mobile  \\\n",
       "OrganisationName                                                         \n",
       "Ashford and St Peter's Hospitals NHS Foundation...            450000.0   \n",
       "Buckinghamshire Healthcare NHS Trust                          180000.0   \n",
       "Dartford and Gravesham NHS Trust                                   0.0   \n",
       "East Kent Hospitals University NHS Foundation T...            180000.0   \n",
       "East Sussex Healthcare NHS Trust                               90000.0   \n",
       "Frimley Health NHS Foundation Trust                           360000.0   \n",
       "Hampshire Hospitals NHS Foundation Trust                           0.0   \n",
       "Maidstone and Tunbridge Wells NHS Trust                       180000.0   \n",
       "Medway NHS Foundation Trust                                        0.0   \n",
       "Oxford University Hospitals NHS Foundation Trust             1260000.0   \n",
       "Portsmouth Hospitals University National Health...            270000.0   \n",
       "Queen Victoria Hospital NHS Foundation Trust                       0.0   \n",
       "Royal Berkshire NHS Foundation Trust                               0.0   \n",
       "Royal Surrey County Hospital NHS Foundation Trust                  0.0   \n",
       "Surrey and Sussex Healthcare NHS Trust                             0.0   \n",
       "University Hospital Southampton NHS Foundation ...            540000.0   \n",
       "University Hospitals Sussex NHS Foundation Trust              180000.0   \n",
       "\n",
       "Modality_Der                                        X ray Units Static  \n",
       "OrganisationName                                                        \n",
       "Ashford and St Peter's Hospitals NHS Foundation...            750000.0  \n",
       "Buckinghamshire Healthcare NHS Trust                          625000.0  \n",
       "Dartford and Gravesham NHS Trust                              625000.0  \n",
       "East Kent Hospitals University NHS Foundation T...            375000.0  \n",
       "East Sussex Healthcare NHS Trust                              625000.0  \n",
       "Frimley Health NHS Foundation Trust                          3250000.0  \n",
       "Hampshire Hospitals NHS Foundation Trust                      875000.0  \n",
       "Maidstone and Tunbridge Wells NHS Trust                       750000.0  \n",
       "Medway NHS Foundation Trust                                   750000.0  \n",
       "Oxford University Hospitals NHS Foundation Trust             1000000.0  \n",
       "Portsmouth Hospitals University National Health...           1750000.0  \n",
       "Queen Victoria Hospital NHS Foundation Trust                       0.0  \n",
       "Royal Berkshire NHS Foundation Trust                         1125000.0  \n",
       "Royal Surrey County Hospital NHS Foundation Trust                  0.0  \n",
       "Surrey and Sussex Healthcare NHS Trust                        625000.0  \n",
       "University Hospital Southampton NHS Foundation ...            750000.0  \n",
       "University Hospitals Sussex NHS Foundation Trust              125000.0  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pivot_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Boxplot to show age of asset by modality"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\local_martin.bloyce2\\Temp\\ipykernel_18488\\2485505417.py:2: FutureWarning:\n",
      "\n",
      "The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Calculate avg replacement age (for scatter plot purpose)\n",
    "average_replacement_schedule = df.groupby('Modality_Der')['replacement_schedule'].mean().reset_index()\n",
    "\n",
    "# Sort data by Modality_Der alphabetically\n",
    "df['Modality_Der'] = pd.Categorical(df['Modality_Der'], categories=sorted(df['Modality_Der'].unique()), ordered=True)\n",
    "\n",
    "# Create figure and axis\n",
    "fig, ax = plt.subplots(figsize=(10, 6))\n",
    "\n",
    "# Plot boxplot\n",
    "sns.boxplot(x='Modality_Der', \n",
    "            y='Age', \n",
    "            data=df, \n",
    "            ax=ax, \n",
    "            zorder=1)\n",
    "\n",
    "# Filter out zeros and NaNs for plotting red dots\n",
    "plot_data = average_replacement_schedule[\n",
    "    average_replacement_schedule['replacement_schedule'] > 0].dropna()\n",
    "\n",
    "# Rotate x labels\n",
    "plt.xticks(rotation=90)\n",
    "\n",
    "# Plot replacement schedule as red dots\n",
    "sns.scatterplot(x='Modality_Der', \n",
    "                y='replacement_schedule', \n",
    "                data=plot_data, \n",
    "                color='red', \n",
    "                s=50, \n",
    "                marker='o', \n",
    "                ax=ax, \n",
    "                label='Replace after (years)',\n",
    "                zorder=2\n",
    "                )\n",
    "\n",
    "# Set plot title and labels\n",
    "ax.set_xlabel(\"Modality\")\n",
    "ax.set_ylabel(\"Age of asset (years)\")\n",
    "ax.set_title(\"Age of asset boxplot\")\n",
    "\n",
    "# Show plot\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}