1b_pca_new_draft_integrate.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# PCA Amendments Drafts\n",
    "\n",
    "\n",
    "This script integrates PCA Amendments Draft Geographies from multiple Shapefiles, onto a single dataset and exports to file\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Info: Found credentials at: /Users/lelias/Library/CloudStorage/Box-Box/dvutils-creds-lelias.json\n",
      "Admin ArcGIS client created\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import geopandas as gpd\n",
    "\n",
    "from utils import *"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Set variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Define the file download directories\n",
    "dirs = [\n",
    "    \"MTC-ABAG SALC Planning Grant/8. Implementation/GIS_Amendment_Edits/Drafts\",\n",
    "    \"MTC-ABAG SALC Planning Grant/8. Implementation/GIS_Amendment_Edits/Drafts/JurisdictionLedFiles\"\n",
    "]\n",
    "\n",
    "status_list_dir = \"MTC-ABAG SALC Planning Grant/8. Implementation/GIS_Amendment_Edits/Amendment_Status_1121.xlsx\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Read Shapefiles and integrate to PCA Geographies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "101\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/LElias/Documents/GH_repos/PCA-Refresh/utils.py:134: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.\n",
      "  gdf = gpd.GeoDataFrame(pd.concat(gdfs, ignore_index=True), crs=26910)\n"
     ]
    }
   ],
   "source": [
    "# Get a list of all shapefiles in the directories\n",
    "shapefiles = shapefiles_list(dirs)\n",
    "print(len(shapefiles))\n",
    "\n",
    "# Read all shapefiles into a single GeoDataFrame\n",
    "pca = read_shapefiles(shapefiles)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Run Checks and additional fixes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pca.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Apply Override"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Remove features from the PBA50_PCA_Polygons shapefile dataset\n",
    "pca = pca[pca['source']!='PBA50_PCA_Polygons.shp']\n",
    "\n",
    "pca.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Apply Table columns schema"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Define schema and transformations for the PCA shapefile attributes\n",
    "columns_schema = [\n",
    "    'joinkey', 'source', 'fipco', 'name', 'lead',\n",
    "    'amend_stat', 'amend_lead',\n",
    "    'typenl', 'typeal', 'typeug', 'typerr', 'typeca',\n",
    "    'nomination_year', 'lastupdate', 'Version', 'Edit_Notes',\n",
    "    'acres', 'INSIDE_X', 'INSIDE_Y', 'geometry'\n",
    "    ]\n",
    "\n",
    "columns_consolidate = {\n",
    "    'amend_stat': ['Status_24', 'Status2024', 'Status24', 'Status_202'],\n",
    "    'amend_lead': ['MapLead', 'Amend_Map_', 'Amend_Lead', 'Map_Lead']\n",
    "    }\n",
    "\n",
    "columns_rename = {\n",
    "    'adopted': 'nomination_year'\n",
    "    }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "EPSG:26910\n"
     ]
    }
   ],
   "source": [
    "## Recalculate Geospatial attributes\n",
    "print(pca.crs)\n",
    "pca.loc[: , 'acres'] = pca.area / 4046.8564224\n",
    "## Recalculate the centroid\n",
    "# pca['INSIDE_X'] = pca.centroid.x\n",
    "# pca['INSIDE_Y'] = pca.centroid.y\n",
    "# pca['contains_point'] = pca.geometry.contains(pca.centroid)\n",
    "# print(len(pca[pca['contains_point'] == False]))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       Status_24 Status2024 Status24 Status_202\n",
      "count         94          1        2          3\n",
      "unique         1          1        1          1\n",
      "top        Draft      Draft    Draft      Draft\n",
      "freq          94          1        2          3\n",
      "       MapLead Amend_Map_ Amend_Lead Map_Lead\n",
      "count        2          1          1      110\n",
      "unique       1          1          1        2\n",
      "top        MTC        MTC        MTC      MTC\n",
      "freq         2          1          1       82\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "    .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>joinkey</th>\n",
       "      <th>source</th>\n",
       "      <th>fipco</th>\n",
       "      <th>name</th>\n",
       "      <th>lead</th>\n",
       "      <th>amend_stat</th>\n",
       "      <th>amend_lead</th>\n",
       "      <th>typenl</th>\n",
       "      <th>typeal</th>\n",
       "      <th>typeug</th>\n",
       "      <th>typerr</th>\n",
       "      <th>typeca</th>\n",
       "      <th>nomination_year</th>\n",
       "      <th>lastupdate</th>\n",
       "      <th>Version</th>\n",
       "      <th>Edit_Notes</th>\n",
       "      <th>acres</th>\n",
       "      <th>INSIDE_X</th>\n",
       "      <th>INSIDE_Y</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AL1</td>\n",
       "      <td>AL1_Draft.shp</td>\n",
       "      <td>06001</td>\n",
       "      <td>Leona Canyon Creek Tributaries</td>\n",
       "      <td>City of Oakland</td>\n",
       "      <td>Draft</td>\n",
       "      <td>MTC</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2008</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>44.311692</td>\n",
       "      <td>-122.149872</td>\n",
       "      <td>37.787304</td>\n",
       "      <td>POLYGON ((574709.805 4182765.007, 574741.328 4...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AL22</td>\n",
       "      <td>AL22_Draft_2.shp</td>\n",
       "      <td>06001</td>\n",
       "      <td>Chain of Lakes Area</td>\n",
       "      <td>East Bay Regional Park District (EBRPD)</td>\n",
       "      <td>Draft</td>\n",
       "      <td>MTC</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2008</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1450.789738</td>\n",
       "      <td>-121.838819</td>\n",
       "      <td>37.682917</td>\n",
       "      <td>MULTIPOLYGON (((602890.288 4170039.009, 602885...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AL24</td>\n",
       "      <td>AL24_Draft.shp</td>\n",
       "      <td>06001</td>\n",
       "      <td>Cedar Mountain Area</td>\n",
       "      <td>East Bay Regional Park District (EBRPD)</td>\n",
       "      <td>Draft</td>\n",
       "      <td>MTC</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2008</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>16399.417663</td>\n",
       "      <td>-121.613960</td>\n",
       "      <td>37.570924</td>\n",
       "      <td>MULTIPOLYGON (((625158.673 4155010.536, 625024...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AL25</td>\n",
       "      <td>AL25_Draft.shp</td>\n",
       "      <td>06001</td>\n",
       "      <td>Duarte Canyon Area</td>\n",
       "      <td>East Bay Regional Park District (EBRPD)</td>\n",
       "      <td>Draft</td>\n",
       "      <td>MTC</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2008</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>11956.889254</td>\n",
       "      <td>-121.540641</td>\n",
       "      <td>37.504374</td>\n",
       "      <td>POLYGON ((629066.459 4154642.481, 629967.864 4...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AL28</td>\n",
       "      <td>AL28_Draft2.shp</td>\n",
       "      <td>06001</td>\n",
       "      <td>Potential Tesla Area</td>\n",
       "      <td>East Bay Regional Park District (EBRPD)</td>\n",
       "      <td>Draft</td>\n",
       "      <td>MTC</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2008</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>12524.135768</td>\n",
       "      <td>-121.606700</td>\n",
       "      <td>37.621388</td>\n",
       "      <td>POLYGON ((624385.673 4161227.404, 624305.630 4...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  joinkey            source  fipco                            name  \\\n",
       "0     AL1     AL1_Draft.shp  06001  Leona Canyon Creek Tributaries   \n",
       "1    AL22  AL22_Draft_2.shp  06001             Chain of Lakes Area   \n",
       "2    AL24    AL24_Draft.shp  06001             Cedar Mountain Area   \n",
       "3    AL25    AL25_Draft.shp  06001              Duarte Canyon Area   \n",
       "4    AL28   AL28_Draft2.shp  06001            Potential Tesla Area   \n",
       "\n",
       "                                      lead amend_stat amend_lead  typenl  \\\n",
       "0                          City of Oakland      Draft        MTC       0   \n",
       "1  East Bay Regional Park District (EBRPD)      Draft        MTC       1   \n",
       "2  East Bay Regional Park District (EBRPD)      Draft        MTC       1   \n",
       "3  East Bay Regional Park District (EBRPD)      Draft        MTC       1   \n",
       "4  East Bay Regional Park District (EBRPD)      Draft        MTC       1   \n",
       "\n",
       "   typeal  typeug  typerr  typeca nomination_year lastupdate Version  \\\n",
       "0       0       0       1     1.0            2008          0       0   \n",
       "1       0       0       0     1.0            2008          0       0   \n",
       "2       0       0       0     1.0            2008          0       0   \n",
       "3       0       0       0     1.0            2008          0       0   \n",
       "4       1       0       0     1.0            2008          0       0   \n",
       "\n",
       "  Edit_Notes         acres    INSIDE_X   INSIDE_Y  \\\n",
       "0          0     44.311692 -122.149872  37.787304   \n",
       "1          0   1450.789738 -121.838819  37.682917   \n",
       "2          0  16399.417663 -121.613960  37.570924   \n",
       "3          0  11956.889254 -121.540641  37.504374   \n",
       "4          0  12524.135768 -121.606700  37.621388   \n",
       "\n",
       "                                            geometry  \n",
       "0  POLYGON ((574709.805 4182765.007, 574741.328 4...  \n",
       "1  MULTIPOLYGON (((602890.288 4170039.009, 602885...  \n",
       "2  MULTIPOLYGON (((625158.673 4155010.536, 625024...  \n",
       "3  POLYGON ((629066.459 4154642.481, 629967.864 4...  \n",
       "4  POLYGON ((624385.673 4161227.404, 624305.630 4...  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## Rename columns\n",
    "pca = pca.rename(columns=columns_rename)\n",
    "## Fix NAN values\n",
    "replace_nulls(pca, columns_consolidate['amend_stat']+columns_consolidate['amend_lead'])\n",
    "print(pca[columns_consolidate['amend_stat']].describe())\n",
    "print(pca[columns_consolidate['amend_lead']].describe())\n",
    "## Consolidate columns\n",
    "pca['amend_stat'] = pca['Status_24'].fillna(pca['Status2024']).fillna(pca['Status24']).fillna(pca['Status_202'])\n",
    "pca['amend_lead'] = pca['MapLead'].fillna(pca['Amend_Map_']).fillna(pca['Amend_Lead']).fillna(pca['Map_Lead'])\n",
    "## Drop columns\n",
    "pca = pca[columns_schema]\n",
    "pca.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def replace_nulls(df, columns, replace_dict=None):\n",
    "    if replace_dict is None:\n",
    "        replace_dict = {0: np.nan, '0': np.nan, 'nan': np.nan}\n",
    "    df[columns] = df[columns].replace(replace_dict)\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Run some checks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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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>256</th>\n",
       "      <th>43</th>\n",
       "      <th>247</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Edit_Notes</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INSIDE_X</th>\n",
       "      <td>0.0</td>\n",
       "      <td>-122.587456</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INSIDE_Y</th>\n",
       "      <td>0.0</td>\n",
       "      <td>37.997542</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Version</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>acres</th>\n",
       "      <td>704.263571</td>\n",
       "      <td>467.662006</td>\n",
       "      <td>14989.552979</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>amend_lead</th>\n",
       "      <td>Local Lead</td>\n",
       "      <td>MTC</td>\n",
       "      <td>Local Lead</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>amend_stat</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Draft</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fipco</th>\n",
       "      <td>06081</td>\n",
       "      <td>06041</td>\n",
       "      <td>06081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>geometry</th>\n",
       "      <td>MULTIPOLYGON Z (((565020.7070000004 4140806.20...</td>\n",
       "      <td>MULTIPOLYGON (((536437.8180999998 4206332.6223...</td>\n",
       "      <td>POLYGON Z ((549983.0802999996 4157041.50159999...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>joinkey</th>\n",
       "      <td>SM8</td>\n",
       "      <td>MR21</td>\n",
       "      <td>SM1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lastupdate</th>\n",
       "      <td>9/4/2024</td>\n",
       "      <td>07/14/2015</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>lead</th>\n",
       "      <td>Midpeninsula Regional Open Space District</td>\n",
       "      <td>Fairfax, San Anselmo</td>\n",
       "      <td>Peninsula Open Space Trust</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <td>Teague Hill Urban Area</td>\n",
       "      <td>Multi-Jurisdictional: Northern Fairfax/Sleepy ...</td>\n",
       "      <td>Montara Mountain Complex</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nomination_year</th>\n",
       "      <td>2015</td>\n",
       "      <td>2015</td>\n",
       "      <td>2008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>source</th>\n",
       "      <td>PCA_Midpen_2024Refresh_SanMateoCounty.shp</td>\n",
       "      <td>MR21_Draft.shp</td>\n",
       "      <td>PCA_Midpen_2024Refresh_SanMateoCounty.shp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>typeal</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>typeca</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>typenl</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>typerr</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>typeug</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                               256  \\\n",
       "Edit_Notes                                                       0   \n",
       "INSIDE_X                                                       0.0   \n",
       "INSIDE_Y                                                       0.0   \n",
       "Version                                                          0   \n",
       "acres                                                   704.263571   \n",
       "amend_lead                                              Local Lead   \n",
       "amend_stat                                                     NaN   \n",
       "fipco                                                        06081   \n",
       "geometry         MULTIPOLYGON Z (((565020.7070000004 4140806.20...   \n",
       "joinkey                                                        SM8   \n",
       "lastupdate                                                9/4/2024   \n",
       "lead                     Midpeninsula Regional Open Space District   \n",
       "name                                        Teague Hill Urban Area   \n",
       "nomination_year                                               2015   \n",
       "source                   PCA_Midpen_2024Refresh_SanMateoCounty.shp   \n",
       "typeal                                                           0   \n",
       "typeca                                                         0.0   \n",
       "typenl                                                           1   \n",
       "typerr                                                           1   \n",
       "typeug                                                           0   \n",
       "\n",
       "                                                               43   \\\n",
       "Edit_Notes                                                       0   \n",
       "INSIDE_X                                               -122.587456   \n",
       "INSIDE_Y                                                 37.997542   \n",
       "Version                                                          0   \n",
       "acres                                                   467.662006   \n",
       "amend_lead                                                     MTC   \n",
       "amend_stat                                                   Draft   \n",
       "fipco                                                        06041   \n",
       "geometry         MULTIPOLYGON (((536437.8180999998 4206332.6223...   \n",
       "joinkey                                                       MR21   \n",
       "lastupdate                                              07/14/2015   \n",
       "lead                                          Fairfax, San Anselmo   \n",
       "name             Multi-Jurisdictional: Northern Fairfax/Sleepy ...   \n",
       "nomination_year                                               2015   \n",
       "source                                              MR21_Draft.shp   \n",
       "typeal                                                           0   \n",
       "typeca                                                         0.0   \n",
       "typenl                                                           0   \n",
       "typerr                                                           1   \n",
       "typeug                                                           0   \n",
       "\n",
       "                                                               247  \n",
       "Edit_Notes                                                       0  \n",
       "INSIDE_X                                                       0.0  \n",
       "INSIDE_Y                                                       0.0  \n",
       "Version                                                          0  \n",
       "acres                                                 14989.552979  \n",
       "amend_lead                                              Local Lead  \n",
       "amend_stat                                                     NaN  \n",
       "fipco                                                        06081  \n",
       "geometry         POLYGON Z ((549983.0802999996 4157041.50159999...  \n",
       "joinkey                                                        SM1  \n",
       "lastupdate                                                       0  \n",
       "lead                                    Peninsula Open Space Trust  \n",
       "name                                      Montara Mountain Complex  \n",
       "nomination_year                                               2008  \n",
       "source                   PCA_Midpen_2024Refresh_SanMateoCounty.shp  \n",
       "typeal                                                           0  \n",
       "typeca                                                         0.0  \n",
       "typenl                                                           1  \n",
       "typerr                                                           0  \n",
       "typeug                                                           0  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pca[sorted(pca.columns)].sample(3).T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>joinkey</th>\n",
       "      <th>parts</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>SF106</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>AL8</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>SC34</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>SM10</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>MR11</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>MR10</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>DELETE</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>CC3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>CC24</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>SN9</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>106 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    joinkey  parts\n",
       "81    SF106      3\n",
       "17      AL8      3\n",
       "64     SC34      2\n",
       "90     SM10      2\n",
       "34     MR11      2\n",
       "..      ...    ...\n",
       "33     MR10      1\n",
       "32   DELETE      1\n",
       "31      CC3      1\n",
       "30     CC24      1\n",
       "105     SN9      1\n",
       "\n",
       "[106 rows x 2 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## Check for dups in joinkey\n",
    "pca.groupby(['joinkey']).size().reset_index(name='parts').sort_values('parts', ascending=False)#.to_clipboard(index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "      <th>source</th>\n",
       "      <th>parts</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>PCA_Midpen_2024Refresh_SanMateoCounty.shp</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>PCA_Midpen_2024Refresh_SantaClaraCounty.shp</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>Proposed_Amended_Priority_Conservation_Areas_S...</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>SC102_Draft.shp</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>SC38_Draft.shp</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>CC22_Draft.shp</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>CC21_Draft.shp</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>CC20_Draft.shp</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>CC19_Draft_2.shp</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>SN101_Draft.shp</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                               source  parts\n",
       "60          PCA_Midpen_2024Refresh_SanMateoCounty.shp     12\n",
       "61        PCA_Midpen_2024Refresh_SantaClaraCounty.shp      9\n",
       "62  Proposed_Amended_Priority_Conservation_Areas_S...      5\n",
       "64                                    SC102_Draft.shp      1\n",
       "73                                     SC38_Draft.shp      1\n",
       "..                                                ...    ...\n",
       "30                                     CC22_Draft.shp      1\n",
       "29                                     CC21_Draft.shp      1\n",
       "28                                     CC20_Draft.shp      1\n",
       "27                                   CC19_Draft_2.shp      1\n",
       "99                                    SN101_Draft.shp      1\n",
       "\n",
       "[100 rows x 2 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## Check for dups in source\n",
    "pca.groupby(['source']).size().reset_index(name='parts').sort_values('parts', ascending=False)#.to_clipboard(index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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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>joinkey</th>\n",
       "      <th>source</th>\n",
       "      <th>fipco</th>\n",
       "      <th>name</th>\n",
       "      <th>lead</th>\n",
       "      <th>amend_stat</th>\n",
       "      <th>amend_lead</th>\n",
       "      <th>typenl</th>\n",
       "      <th>typeal</th>\n",
       "      <th>typeug</th>\n",
       "      <th>typerr</th>\n",
       "      <th>typeca</th>\n",
       "      <th>nomination_year</th>\n",
       "      <th>lastupdate</th>\n",
       "      <th>Version</th>\n",
       "      <th>Edit_Notes</th>\n",
       "      <th>acres</th>\n",
       "      <th>INSIDE_X</th>\n",
       "      <th>INSIDE_Y</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>295</th>\n",
       "      <td>SF106</td>\n",
       "      <td>SF106_Draft.shp</td>\n",
       "      <td>06075</td>\n",
       "      <td>Lake Merced</td>\n",
       "      <td>City and County of San Francisco</td>\n",
       "      <td>Draft</td>\n",
       "      <td>MTC</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2019</td>\n",
       "      <td>6/10/2021</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1215.567804</td>\n",
       "      <td>-122.498596</td>\n",
       "      <td>37.728446</td>\n",
       "      <td>POLYGON ((543517.469 4176605.761, 543548.555 4...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>296</th>\n",
       "      <td>SF106</td>\n",
       "      <td>SF106_E_Draft.shp</td>\n",
       "      <td>06075</td>\n",
       "      <td>Lake Merced</td>\n",
       "      <td>City and County of San Francisco</td>\n",
       "      <td>Draft</td>\n",
       "      <td>MTC</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2019</td>\n",
       "      <td>6/10/2021</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>937.525425</td>\n",
       "      <td>-122.498596</td>\n",
       "      <td>37.728446</td>\n",
       "      <td>POLYGON ((543815.790 4173948.777, 543617.049 4...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>297</th>\n",
       "      <td>SF106</td>\n",
       "      <td>SF106_W_Draft.shp</td>\n",
       "      <td>06075</td>\n",
       "      <td>Ocean Beach</td>\n",
       "      <td>City and County of San Francisco</td>\n",
       "      <td>Draft</td>\n",
       "      <td>MTC</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2019</td>\n",
       "      <td>6/10/2021</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>278.042379</td>\n",
       "      <td>-122.498596</td>\n",
       "      <td>37.728446</td>\n",
       "      <td>POLYGON ((543504.665 4176624.247, 543423.417 4...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    joinkey             source  fipco         name  \\\n",
       "295   SF106    SF106_Draft.shp  06075  Lake Merced   \n",
       "296   SF106  SF106_E_Draft.shp  06075  Lake Merced   \n",
       "297   SF106  SF106_W_Draft.shp  06075  Ocean Beach   \n",
       "\n",
       "                                 lead amend_stat amend_lead  typenl  typeal  \\\n",
       "295  City and County of San Francisco      Draft        MTC       0       0   \n",
       "296  City and County of San Francisco      Draft        MTC       0       0   \n",
       "297  City and County of San Francisco      Draft        MTC       0       0   \n",
       "\n",
       "     typeug  typerr  typeca nomination_year lastupdate Version Edit_Notes  \\\n",
       "295       0       1     0.0            2019  6/10/2021       0          0   \n",
       "296       0       1     0.0            2019  6/10/2021       0          0   \n",
       "297       0       1     1.0            2019  6/10/2021       0          0   \n",
       "\n",
       "           acres    INSIDE_X   INSIDE_Y  \\\n",
       "295  1215.567804 -122.498596  37.728446   \n",
       "296   937.525425 -122.498596  37.728446   \n",
       "297   278.042379 -122.498596  37.728446   \n",
       "\n",
       "                                              geometry  \n",
       "295  POLYGON ((543517.469 4176605.761, 543548.555 4...  \n",
       "296  POLYGON ((543815.790 4173948.777, 543617.049 4...  \n",
       "297  POLYGON ((543504.665 4176624.247, 543423.417 4...  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## Look at a specific joinkey \n",
    "pca[pca['joinkey']=='SF106']#.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>joinkey</th>\n",
       "      <th>source</th>\n",
       "      <th>fipco</th>\n",
       "      <th>name</th>\n",
       "      <th>lead</th>\n",
       "      <th>amend_stat</th>\n",
       "      <th>amend_lead</th>\n",
       "      <th>typenl</th>\n",
       "      <th>typeal</th>\n",
       "      <th>typeug</th>\n",
       "      <th>typerr</th>\n",
       "      <th>typeca</th>\n",
       "      <th>nomination_year</th>\n",
       "      <th>lastupdate</th>\n",
       "      <th>Version</th>\n",
       "      <th>Edit_Notes</th>\n",
       "      <th>acres</th>\n",
       "      <th>INSIDE_X</th>\n",
       "      <th>INSIDE_Y</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>247</th>\n",
       "      <td>SM1</td>\n",
       "      <td>PCA_Midpen_2024Refresh_SanMateoCounty.shp</td>\n",
       "      <td>06081</td>\n",
       "      <td>Montara Mountain Complex</td>\n",
       "      <td>Peninsula Open Space Trust</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Local Lead</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2008</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>14989.552979</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>POLYGON Z ((549983.080 4157041.502 0.000, 5502...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    joinkey                                     source  fipco  \\\n",
       "247     SM1  PCA_Midpen_2024Refresh_SanMateoCounty.shp  06081   \n",
       "\n",
       "                         name                        lead amend_stat  \\\n",
       "247  Montara Mountain Complex  Peninsula Open Space Trust        NaN   \n",
       "\n",
       "     amend_lead  typenl  typeal  typeug  typerr  typeca nomination_year  \\\n",
       "247  Local Lead       1       0       0       0     0.0            2008   \n",
       "\n",
       "    lastupdate Version Edit_Notes         acres  INSIDE_X  INSIDE_Y  \\\n",
       "247          0       0          0  14989.552979       0.0       0.0   \n",
       "\n",
       "                                              geometry  \n",
       "247  POLYGON Z ((549983.080 4157041.502 0.000, 5502...  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## Look at a specific joinkey\n",
    "pca[pca['joinkey']=='SM1']#.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Look at a specific source\n",
    "# pca[pca['source']=='PCA_Midpen_2024Refresh_SanMateoCounty.shp']#.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Look at a specific source\n",
    "# pca[pca['source']=='Proposed_Amended_Priority_Conservation_Areas_Sonoma_County_AOS_2024.shp']#.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create Comparison Check List"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Status List:  95\n",
      "Load List:  100\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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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>status_list</th>\n",
       "      <th>load_list</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AL1_Draft.shp</td>\n",
       "      <td>AL1_Draft.shp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AL22_Draft_2.shp</td>\n",
       "      <td>AL22_Draft_2.shp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AL24_Draft.shp</td>\n",
       "      <td>AL24_Draft.shp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AL25_Draft.shp</td>\n",
       "      <td>AL25_Draft.shp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AL28_Draft2.shp</td>\n",
       "      <td>AL28_Draft2.shp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>SF12_Draft.shp</td>\n",
       "      <td>SF12_Draft.shp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>SF9_Draft.shp</td>\n",
       "      <td>SF9_Draft.shp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>SM10_Draft.shp</td>\n",
       "      <td>SM10_Draft.shp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>SM19_Draft.shp</td>\n",
       "      <td>SM19_Draft.shp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>SN101_Draft.shp</td>\n",
       "      <td>SN101_Draft.shp</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         status_list         load_list\n",
       "0      AL1_Draft.shp     AL1_Draft.shp\n",
       "1   AL22_Draft_2.shp  AL22_Draft_2.shp\n",
       "2     AL24_Draft.shp    AL24_Draft.shp\n",
       "3     AL25_Draft.shp    AL25_Draft.shp\n",
       "4    AL28_Draft2.shp   AL28_Draft2.shp\n",
       "..               ...               ...\n",
       "95    SF12_Draft.shp    SF12_Draft.shp\n",
       "96     SF9_Draft.shp     SF9_Draft.shp\n",
       "97    SM10_Draft.shp    SM10_Draft.shp\n",
       "98    SM19_Draft.shp    SM19_Draft.shp\n",
       "99   SN101_Draft.shp   SN101_Draft.shp\n",
       "\n",
       "[100 rows x 2 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## Status List will be used to filter the PCA datasets to be used for integration\n",
    "## Open the Status List\n",
    "status_list = pd.read_excel(os.path.join(box_path, status_list_dir))\n",
    "## Filter the Status List to only include the datasets that should be run\n",
    "status_list = status_list[(status_list['Run']=='Y')&(status_list['File name']!='[No changes]')]['File name']\n",
    "\n",
    "## Clean-up the status list\n",
    "## Remove the .shp extension\n",
    "status_list = [item + '.shp' if not item.endswith('.shp') else item for item in status_list]\n",
    "## Remove the 'See ' prefix\n",
    "status_list = [itm.replace('See ', '') for itm in status_list]\n",
    "## Remove duplicates\n",
    "status_list = pd.DataFrame(status_list, columns=['status_list']).drop_duplicates()\n",
    "print('Status List: ', len(status_list))\n",
    "\n",
    "## Load List represents the actual PCA datasets that have been loaded for integration\n",
    "load_list = pca[['source']].rename(columns={'source':'load_list'}).drop_duplicates()\n",
    "print('Load List: ', len(load_list))\n",
    "\n",
    "## Merge the Status List and Load List to check for completeness\n",
    "check_list = pd.merge(status_list, load_list, left_on='status_list', right_on='load_list', how='outer').sort_values('load_list')\n",
    "\n",
    "## Export the check list to a csv file\n",
    "check_list.to_csv(\"_data/amendments_drafts/Amendment_Status_shp_check_list.csv\", index=False)\n",
    "check_list.to_clipboard()\n",
    "check_list"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Finalize Integrated PCA Amendments Draft dataset and export to files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Integrated:  110\n"
     ]
    }
   ],
   "source": [
    "## Filter the PCA datasets using the status list\n",
    "pca_integrated = pca[pca['source'].isin(list(status_list['status_list']))].copy()\n",
    "print('Integrated: ', len(pca_integrated))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/s2/81kklxls0kb077vdkdq8jdv00000gp/T/ipykernel_83877/723367467.py:3: UserWarning: Column names longer than 10 characters will be truncated when saved to ESRI Shapefile.\n",
      "  pca_integrated.to_file(\"_data/amendments_drafts/GIS_Amendment_integration_DRAFT.shp\", index=False)\n"
     ]
    }
   ],
   "source": [
    "## Export the integrated PCA dataset\n",
    "# pca_integrated.to_csv(\"_data/amendments_drafts/pca_shp_integration_DRAFT.csv\", index=Fa##lse)\n",
    "pca_integrated.to_file(\"_data/amendments_drafts/GIS_Amendment_integration_DRAFT.shp\", index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Define the data types dictionary\n",
    "data_types = {\n",
    "    'nomination_year': 'int',\n",
    "    'Version': 'str',\n",
    "    'Edit_Notes': 'str',\n",
    "    'amend_stat': 'str',\n",
    "    'amend_lead': 'str',\n",
    "    'lastupdate': 'str',\n",
    "}\n",
    "\n",
    "## Apply the data types to the DataFrame\n",
    "pca_integrated = pca_integrated.astype(data_types)\n",
    "\n",
    "## Export the integrated PCA dataset to a Feather file\n",
    "pca_integrated.to_feather(\"_data/feather_files/pca_shp_integration.feather\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Run some checks on finalized dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>joinkey</th>\n",
       "      <th>parts</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>SF106</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>MR7</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>AL33</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>SM10</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>AL8</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>MR10</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>DELETE</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>CC3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>CC24</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>SN9</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>105 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    joinkey  parts\n",
       "80    SF106      2\n",
       "45      MR7      2\n",
       "11     AL33      2\n",
       "89     SM10      2\n",
       "17      AL8      2\n",
       "..      ...    ...\n",
       "33     MR10      1\n",
       "32   DELETE      1\n",
       "31      CC3      1\n",
       "30     CC24      1\n",
       "104     SN9      1\n",
       "\n",
       "[105 rows x 2 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## Check for dups in joinkey\n",
    "pca_integrated.groupby(['joinkey']).size().reset_index(name='parts').sort_values('parts', ascending=False)#.to_clipboard(index=False)"
   ]
  },
  {
   "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>source</th>\n",
       "      <th>parts</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>PCA_Midpen_2024Refresh_SanMateoCounty.shp</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>Proposed_Amended_Priority_Conservation_Areas_S...</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AL1_Draft.shp</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>SC10_Draft.shp</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>SC38_Draft.shp</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>CC22_Draft.shp</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>CC21_Draft.shp</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>CC20_Draft.shp</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>CC19_Draft_2.shp</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>SN101_Draft.shp</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>95 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                               source  parts\n",
       "57          PCA_Midpen_2024Refresh_SanMateoCounty.shp     12\n",
       "58  Proposed_Amended_Priority_Conservation_Areas_S...      5\n",
       "0                                       AL1_Draft.shp      1\n",
       "61                                     SC10_Draft.shp      1\n",
       "69                                     SC38_Draft.shp      1\n",
       "..                                                ...    ...\n",
       "29                                     CC22_Draft.shp      1\n",
       "28                                     CC21_Draft.shp      1\n",
       "27                                     CC20_Draft.shp      1\n",
       "26                                   CC19_Draft_2.shp      1\n",
       "94                                    SN101_Draft.shp      1\n",
       "\n",
       "[95 rows x 2 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## Check for dups in source\n",
    "pca_integrated.groupby(['source']).size().reset_index(name='parts').sort_values('parts', ascending=False)#.to_clipboard(index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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