02_BlockNodePairing.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import pickle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Read in data\n",
    "\n",
    "# Block to block travel population:\n",
    "\n",
    "# Total number of jobs: S000\n",
    "# Age columns: SA01, SA02, SA03 (all sum to S000)\n",
    "# Income columns: SE01, SE02, SE03 (all sum to S000)\n",
    "# Industry columns: SI01, SI02, SI03 (all sum to S000)\n",
    "\n",
    "Origin_Destination = pd.read_csv('ca_od_main_JT00_2020.csv')\n",
    "\n",
    "# Nodes with matching blocks:\n",
    "with open('Node_Block.pkl', 'rb') as f:\n",
    "    Node_Block = pickle.load(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "        w_geocode       h_geocode  S000  SA01  SA02  SA03  SE01  SE02  SE03  \\\n",
      "0  60014001001003  60014010006013     1     0     0     1     0     1     0   \n",
      "1  60014001001003  60014039003005     1     0     0     1     0     0     1   \n",
      "2  60014001001003  60014046003004     1     0     1     0     0     0     1   \n",
      "3  60014001001003  60014206003002     1     0     0     1     0     0     1   \n",
      "4  60014001001003  60014229021007     1     0     1     0     0     0     1   \n",
      "\n",
      "   SI01  SI02  SI03  createdate  \n",
      "0     0     0     1    20230321  \n",
      "1     0     0     1    20230321  \n",
      "2     0     0     1    20230321  \n",
      "3     0     0     1    20230321  \n",
      "4     0     0     1    20230321  \n"
     ]
    }
   ],
   "source": [
    "print(Origin_Destination.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[  1   2   3   4   6   5   7  11   8   9  12  10  13  17  56  46  15  14\n",
      "  16  24  18  21  29  19  26  25  22  31  30  23  32  20  49  50  37  81\n",
      "  33  27  34  44  39  36  35  71  38  48  53  28  51  45  96  47 117  75\n",
      "  58  89  94  54  43  74  55  63  65  42  79  77 120  69 106  41  62 151\n",
      "  76  68  93 136  66  40  73  84 101  88  59  52  64  95  78 113  60 131\n",
      " 102 126 119  86  70]\n"
     ]
    }
   ],
   "source": [
    "# Show unique values in the 'S000' column\n",
    "print(Origin_Destination['S000'].unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "Initial_Origin_Destination_Count = len(Origin_Destination)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/6m/88dwrhnx7m3cybxwl1p0rtq40000gn/T/ipykernel_91212/2814293574.py:6: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n",
      "  if int(block_id) not in block_node_dict:\n",
      "/var/folders/6m/88dwrhnx7m3cybxwl1p0rtq40000gn/T/ipykernel_91212/2814293574.py:8: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)\n",
      "  block_node_dict[int(block_id)].append(node_id)\n"
     ]
    }
   ],
   "source": [
    "# Create dictionary for block and node pairings (identified from BlockDetermination.ipynb)\n",
    "block_node_dict = {}\n",
    "\n",
    "# Iterate over the list and add the block ids and node coordinates to the dictionary\n",
    "for node_id, block_id, block_coord in Node_Block:\n",
    "    if int(block_id) not in block_node_dict:\n",
    "        block_node_dict[int(block_id)] = []\n",
    "    block_node_dict[int(block_id)].append(node_id)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "Origin_Destination_Node_Added = Origin_Destination.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Map nodes to work and home blocks\n",
    "\n",
    "Origin_Destination_Node_Added['w_node_id'] = Origin_Destination_Node_Added['w_geocode'].map(block_node_dict)\n",
    "Origin_Destination_Node_Added['h_node_id'] = Origin_Destination_Node_Added['h_geocode'].map(block_node_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Remove rows where the node columns are missing (i.e. the block is not in the node dictionary)\n",
    "\n",
    "Origin_Destination_Node_Added = Origin_Destination_Node_Added[Origin_Destination_Node_Added['w_node_id'].notnull()]\n",
    "Origin_Destination_Node_Added = Origin_Destination_Node_Added[Origin_Destination_Node_Added['h_node_id'].notnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Explode the node columns so that each row has a single node coordinate\n",
    "\n",
    "Origin_Destination_Node_Added = Origin_Destination_Node_Added.explode('w_node_id')\n",
    "Origin_Destination_Node_Added = Origin_Destination_Node_Added.explode('h_node_id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "Unique_Block_Combinations_Count = len(Origin_Destination_Node_Added.index.unique())\n",
    "Unique_Node_Combinations_Count = len(Origin_Destination_Node_Added)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Shift node coordinate column locations\n",
    "\n",
    "Origin_Destination_Node_Added.insert(1, 'w_node_id', Origin_Destination_Node_Added.pop('w_node_id'))\n",
    "Origin_Destination_Node_Added.insert(3, 'h_node_id', Origin_Destination_Node_Added.pop('h_node_id'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              w_geocode w_node_id       h_geocode h_node_id  S000  SA01  SA02  \\\n",
      "1931506  60371011101000     31165  60371011101007     30391     1     0     1   \n",
      "1931506  60371011101000     31165  60371011101007     30589     1     0     1   \n",
      "1931506  60371011101000     31166  60371011101007     30391     1     0     1   \n",
      "1931506  60371011101000     31166  60371011101007     30589     1     0     1   \n",
      "1931507  60371011101000     31165  60371011222004     31070     1     0     0   \n",
      "\n",
      "         SA03  SE01  SE02  SE03  SI01  SI02  SI03  createdate  \n",
      "1931506     0     0     0     1     0     0     1    20230321  \n",
      "1931506     0     0     0     1     0     0     1    20230321  \n",
      "1931506     0     0     0     1     0     0     1    20230321  \n",
      "1931506     0     0     0     1     0     0     1    20230321  \n",
      "1931507     1     0     1     0     0     0     1    20230321  \n"
     ]
    }
   ],
   "source": [
    "print(Origin_Destination_Node_Added.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "75791\n"
     ]
    }
   ],
   "source": [
    "# check if there are any rows where w_geocode and h_geocode are the same\n",
    "\n",
    "same_code = Origin_Destination_Node_Added[Origin_Destination_Node_Added['w_geocode'] == Origin_Destination_Node_Added['h_geocode']]\n",
    "print(len(same_code))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7117\n"
     ]
    }
   ],
   "source": [
    "# check if there are any rows where w_node_id and h_node_id are the same\n",
    "\n",
    "same_id = Origin_Destination_Node_Added[Origin_Destination_Node_Added['w_node_id'] == Origin_Destination_Node_Added['h_node_id']]\n",
    "print(len(same_id))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Remove rows where w_node_id and h_node_id are the same\n",
    "\n",
    "Origin_Destination_Node_Added = Origin_Destination_Node_Added[Origin_Destination_Node_Added['w_node_id'] != Origin_Destination_Node_Added['h_node_id']]\n",
    "\n",
    "Unique_Node_Combinations_Count_Final = len(Origin_Destination_Node_Added)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LODES dataset origin/destination block combination count: 14962890\n",
      "Relevant blocks combination count: 650320\n",
      "Relevant nodes combination count: 5380799\n",
      "Relevant nodes combination count (same node to node removed): 5373682\n"
     ]
    }
   ],
   "source": [
    "print('LODES dataset origin/destination block combination count: ' + str(Initial_Origin_Destination_Count) + '\\nRelevant blocks combination count: ' + str(Unique_Block_Combinations_Count) + '\\nRelevant nodes combination count: ' + str(Unique_Node_Combinations_Count) + '\\nRelevant nodes combination count (same node to node removed): ' + str(Unique_Node_Combinations_Count_Final))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
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      "text/plain": [
       "              w_geocode w_node_id       h_geocode h_node_id  S000  SA01  SA02  \\\n",
       "1931506  60371011101000     31165  60371011101007     30391     1     0     1   \n",
       "1931506  60371011101000     31165  60371011101007     30589     1     0     1   \n",
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       "...                 ...       ...             ...       ...   ...   ...   ...   \n",
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       "5953382  60379800311041     31841  60379800311040     42010     1     0     1   \n",
       "\n",
       "         SA03  SE01  SE02  SE03  SI01  SI02  SI03  createdate  \n",
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       "...       ...   ...   ...   ...   ...   ...   ...         ...  \n",
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       "\n",
       "[5373682 rows x 15 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Origin_Destination_Node_Added"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Count where 'w_geocode' and 'h_geocode' are uniquely paired\n",
    "\n",
    "Origin_Destination_Node_Added['unique_pair'] = Origin_Destination_Node_Added['w_geocode'].astype(str) + Origin_Destination_Node_Added['h_geocode'].astype(str)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Count how many times each unique pair appears, and add it as a column\n",
    "\n",
    "Origin_Destination_Node_Added['unique_pair_count'] = Origin_Destination_Node_Added.groupby('unique_pair')['unique_pair'].transform('count')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Origin_Destination_Node_Added['S000_adjusted'] = Origin_Destination_Node_Added['S000'] / Origin_Destination_Node_Added['unique_pair_count']\n",
    "# Origin_Destination_Node_Added['SA01_adjusted'] = Origin_Destination_Node_Added['SA01'] / Origin_Destination_Node_Added['unique_pair_count']\n",
    "# Origin_Destination_Node_Added['SA02_adjusted'] = Origin_Destination_Node_Added['SA02'] / Origin_Destination_Node_Added['unique_pair_count']\n",
    "# Origin_Destination_Node_Added['SA03_adjusted'] = Origin_Destination_Node_Added['SA03'] / Origin_Destination_Node_Added['unique_pair_count']\n",
    "# Origin_Destination_Node_Added['SE01_adjusted'] = Origin_Destination_Node_Added['SE01'] / Origin_Destination_Node_Added['unique_pair_count']\n",
    "# Origin_Destination_Node_Added['SE02_adjusted'] = Origin_Destination_Node_Added['SE02'] / Origin_Destination_Node_Added['unique_pair_count']\n",
    "# Origin_Destination_Node_Added['SE03_adjusted'] = Origin_Destination_Node_Added['SE03'] / Origin_Destination_Node_Added['unique_pair_count']\n",
    "# Origin_Destination_Node_Added['SI01_adjusted'] = Origin_Destination_Node_Added['SI01'] / Origin_Destination_Node_Added['unique_pair_count']\n",
    "# Origin_Destination_Node_Added['SI02_adjusted'] = Origin_Destination_Node_Added['SI02'] / Origin_Destination_Node_Added['unique_pair_count']\n",
    "# Origin_Destination_Node_Added['SI03_adjusted'] = Origin_Destination_Node_Added['SI03'] / Origin_Destination_Node_Added['unique_pair_count']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# List of column names to be adjusted\n",
    "cols_to_adjust = ['S000', 'SA01', 'SA02', 'SA03', 'SE01', 'SE02', 'SE03', 'SI01', 'SI02', 'SI03']\n",
    "\n",
    "# Iterate over the columns and create new adjusted columns\n",
    "for col in cols_to_adjust:\n",
    "    Origin_Destination_Node_Added[f'{col}_adjusted'] = Origin_Destination_Node_Added[col] / Origin_Destination_Node_Added['unique_pair_count']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
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       "      <td>...</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1931513</th>\n",
       "      <td>60371011101002</td>\n",
       "      <td>30957</td>\n",
       "      <td>60371011103003</td>\n",
       "      <td>29591</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1931513</th>\n",
       "      <td>60371011101002</td>\n",
       "      <td>30957</td>\n",
       "      <td>60371011103003</td>\n",
       "      <td>29615</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.250000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>20 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              w_geocode w_node_id       h_geocode h_node_id  S000  SA01  SA02  \\\n",
       "1931506  60371011101000     31165  60371011101007     30391     1     0     1   \n",
       "1931506  60371011101000     31165  60371011101007     30589     1     0     1   \n",
       "1931506  60371011101000     31166  60371011101007     30391     1     0     1   \n",
       "1931506  60371011101000     31166  60371011101007     30589     1     0     1   \n",
       "1931507  60371011101000     31165  60371011222004     31070     1     0     0   \n",
       "1931507  60371011101000     31165  60371011222004     31164     1     0     0   \n",
       "1931507  60371011101000     31165  60371011222004     41110     1     0     0   \n",
       "1931507  60371011101000     31165  60371011222004     41125     1     0     0   \n",
       "1931507  60371011101000     31165  60371011222004     41460     1     0     0   \n",
       "1931507  60371011101000     31165  60371011222004     43506     1     0     0   \n",
       "1931507  60371011101000     31166  60371011222004     31070     1     0     0   \n",
       "1931507  60371011101000     31166  60371011222004     31164     1     0     0   \n",
       "1931507  60371011101000     31166  60371011222004     41110     1     0     0   \n",
       "1931507  60371011101000     31166  60371011222004     41125     1     0     0   \n",
       "1931507  60371011101000     31166  60371011222004     41460     1     0     0   \n",
       "1931507  60371011101000     31166  60371011222004     43506     1     0     0   \n",
       "1931512  60371011101002     30957  60371011101008     30780     1     0     0   \n",
       "1931512  60371011101002     30957  60371011101008     30909     1     0     0   \n",
       "1931513  60371011101002     30957  60371011103003     29591     1     0     1   \n",
       "1931513  60371011101002     30957  60371011103003     29615     1     0     1   \n",
       "\n",
       "         SA03  SE01  SE02  ...  S000_adjusted  SA01_adjusted  SA02_adjusted  \\\n",
       "1931506     0     0     0  ...       0.250000            0.0           0.25   \n",
       "1931506     0     0     0  ...       0.250000            0.0           0.25   \n",
       "1931506     0     0     0  ...       0.250000            0.0           0.25   \n",
       "1931506     0     0     0  ...       0.250000            0.0           0.25   \n",
       "1931507     1     0     1  ...       0.083333            0.0           0.00   \n",
       "1931507     1     0     1  ...       0.083333            0.0           0.00   \n",
       "1931507     1     0     1  ...       0.083333            0.0           0.00   \n",
       "1931507     1     0     1  ...       0.083333            0.0           0.00   \n",
       "1931507     1     0     1  ...       0.083333            0.0           0.00   \n",
       "1931507     1     0     1  ...       0.083333            0.0           0.00   \n",
       "1931507     1     0     1  ...       0.083333            0.0           0.00   \n",
       "1931507     1     0     1  ...       0.083333            0.0           0.00   \n",
       "1931507     1     0     1  ...       0.083333            0.0           0.00   \n",
       "1931507     1     0     1  ...       0.083333            0.0           0.00   \n",
       "1931507     1     0     1  ...       0.083333            0.0           0.00   \n",
       "1931507     1     0     1  ...       0.083333            0.0           0.00   \n",
       "1931512     1     0     1  ...       0.500000            0.0           0.00   \n",
       "1931512     1     0     1  ...       0.500000            0.0           0.00   \n",
       "1931513     0     1     0  ...       0.250000            0.0           0.25   \n",
       "1931513     0     1     0  ...       0.250000            0.0           0.25   \n",
       "\n",
       "         SA03_adjusted  SE01_adjusted SE02_adjusted  SE03_adjusted  \\\n",
       "1931506       0.000000           0.00      0.000000           0.25   \n",
       "1931506       0.000000           0.00      0.000000           0.25   \n",
       "1931506       0.000000           0.00      0.000000           0.25   \n",
       "1931506       0.000000           0.00      0.000000           0.25   \n",
       "1931507       0.083333           0.00      0.083333           0.00   \n",
       "1931507       0.083333           0.00      0.083333           0.00   \n",
       "1931507       0.083333           0.00      0.083333           0.00   \n",
       "1931507       0.083333           0.00      0.083333           0.00   \n",
       "1931507       0.083333           0.00      0.083333           0.00   \n",
       "1931507       0.083333           0.00      0.083333           0.00   \n",
       "1931507       0.083333           0.00      0.083333           0.00   \n",
       "1931507       0.083333           0.00      0.083333           0.00   \n",
       "1931507       0.083333           0.00      0.083333           0.00   \n",
       "1931507       0.083333           0.00      0.083333           0.00   \n",
       "1931507       0.083333           0.00      0.083333           0.00   \n",
       "1931507       0.083333           0.00      0.083333           0.00   \n",
       "1931512       0.500000           0.00      0.500000           0.00   \n",
       "1931512       0.500000           0.00      0.500000           0.00   \n",
       "1931513       0.000000           0.25      0.000000           0.00   \n",
       "1931513       0.000000           0.25      0.000000           0.00   \n",
       "\n",
       "         SI01_adjusted  SI02_adjusted  SI03_adjusted  \n",
       "1931506            0.0            0.0       0.250000  \n",
       "1931506            0.0            0.0       0.250000  \n",
       "1931506            0.0            0.0       0.250000  \n",
       "1931506            0.0            0.0       0.250000  \n",
       "1931507            0.0            0.0       0.083333  \n",
       "1931507            0.0            0.0       0.083333  \n",
       "1931507            0.0            0.0       0.083333  \n",
       "1931507            0.0            0.0       0.083333  \n",
       "1931507            0.0            0.0       0.083333  \n",
       "1931507            0.0            0.0       0.083333  \n",
       "1931507            0.0            0.0       0.083333  \n",
       "1931507            0.0            0.0       0.083333  \n",
       "1931507            0.0            0.0       0.083333  \n",
       "1931507            0.0            0.0       0.083333  \n",
       "1931507            0.0            0.0       0.083333  \n",
       "1931507            0.0            0.0       0.083333  \n",
       "1931512            0.0            0.0       0.500000  \n",
       "1931512            0.0            0.0       0.500000  \n",
       "1931513            0.0            0.0       0.250000  \n",
       "1931513            0.0            0.0       0.250000  \n",
       "\n",
       "[20 rows x 27 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Origin_Destination_Node_Added.head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['w_geocode', 'w_node_id', 'h_geocode', 'h_node_id', 'S000', 'SA01',\n",
      "       'SA02', 'SA03', 'SE01', 'SE02', 'SE03', 'SI01', 'SI02', 'SI03',\n",
      "       'createdate', 'unique_pair', 'unique_pair_count', 'S000_adjusted',\n",
      "       'SA01_adjusted', 'SA02_adjusted', 'SA03_adjusted', 'SE01_adjusted',\n",
      "       'SE02_adjusted', 'SE03_adjusted', 'SI01_adjusted', 'SI02_adjusted',\n",
      "       'SI03_adjusted'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "# Print column names of the dataframe\n",
    "\n",
    "print(Origin_Destination_Node_Added.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Dump Origin_Destination_Node_Added_Final as a pickle file\n",
    "\n",
    "Origin_Destination_Node_Added.to_pickle('Origin_Destination_Node_Added.pkl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Export updated csv\n",
    "\n",
    "# Origin_Destination_Node_Added.to_csv('ca_od_main_JT00_2020_Node_Added.csv', index=False)"
   ]
  }
 ],
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