{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "ae298fd7-5865-40d5-b231-7ac9742529f8",
   "metadata": {},
   "source": [
    "# Session 4: Assignment explanation and answers\n",
    "\n",
    "View datasets and create visualization."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "f861ef30-21df-4f41-a706-ec33d575c122",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Import modules\n",
    "from pyincore import FragilityService, IncoreClient, FragilityCurveSet, MappingSet, Dataset\n",
    "\n",
    "from pyincore_viz.plotutil import PlotUtil as plot\n",
    "from pyincore_viz.geoutil import GeoUtil as geoviz"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8b73dad9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Connection successful to IN-CORE services. pyIncore version detected: 0.9.3\n"
     ]
    }
   ],
   "source": [
    "# Connect to IN-CORE serivce by creating IncoreClient\n",
    "client = IncoreClient()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "39724d53-842f-4a47-bb9b-f2e464e972da",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pyincore.dataset.Dataset'>\n",
      "<class 'geopandas.geodataframe.GeoDataFrame'>\n"
     ]
    },
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>parid</th>\n",
       "      <th>struct_typ</th>\n",
       "      <th>year_built</th>\n",
       "      <th>no_stories</th>\n",
       "      <th>a_stories</th>\n",
       "      <th>b_stories</th>\n",
       "      <th>bsmt_type</th>\n",
       "      <th>sq_foot</th>\n",
       "      <th>gsq_foot</th>\n",
       "      <th>occ_type</th>\n",
       "      <th>...</th>\n",
       "      <th>archetype</th>\n",
       "      <th>appr_land</th>\n",
       "      <th>appr_tot</th>\n",
       "      <th>ffe_elev</th>\n",
       "      <th>g_elev</th>\n",
       "      <th>lhsm_elev</th>\n",
       "      <th>lon</th>\n",
       "      <th>lat</th>\n",
       "      <th>guid</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
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       "      <th>0</th>\n",
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       "      <td>6062</td>\n",
       "      <td>6062</td>\n",
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       "      <td>...</td>\n",
       "      <td>12</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>-90.02585</td>\n",
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       "      <td>1925</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>COMMERCIAL BSMT</td>\n",
       "      <td>19468</td>\n",
       "      <td>4867</td>\n",
       "      <td>COM6</td>\n",
       "      <td>...</td>\n",
       "      <td>12</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
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       "      <td>14</td>\n",
       "      <td>13</td>\n",
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       "      <td>COMMERCIAL BSMT</td>\n",
       "      <td>910583</td>\n",
       "      <td>65042</td>\n",
       "      <td>COM6</td>\n",
       "      <td>...</td>\n",
       "      <td>12</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>-90.01928</td>\n",
       "      <td>35.13640</td>\n",
       "      <td>9f9b11f8-c25c-4760-b1d2-a63bbeec8e72</td>\n",
       "      <td>POINT (-90.01928 35.13640)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>012008  00012</td>\n",
       "      <td>URM</td>\n",
       "      <td>1910</td>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>COMMERCIAL BSMT</td>\n",
       "      <td>65112</td>\n",
       "      <td>13022</td>\n",
       "      <td>COM6</td>\n",
       "      <td>...</td>\n",
       "      <td>12</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
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       "      <td>POINT (-90.07377 35.12344)</td>\n",
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       "      <td>S1</td>\n",
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       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
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       "      <td>32094</td>\n",
       "      <td>16047</td>\n",
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       "      <td>12</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>-90.04349</td>\n",
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       "      <td>b5069250-7a2b-47b1-9754-290528a6d72d</td>\n",
       "      <td>POINT (-90.04349 35.15360)</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 34 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            parid struct_typ  year_built  no_stories  a_stories  b_stories  \\\n",
       "0   018060  00010         C1        1978           1          1          0   \n",
       "1   018060  00010         C1        1925           4          3          1   \n",
       "2  016001  00001C         S1        1924          14         13          1   \n",
       "3   012008  00012        URM        1910           5          3          2   \n",
       "4  001041  00001C         S1        1991           2          2          0   \n",
       "\n",
       "         bsmt_type  sq_foot  gsq_foot occ_type  ... archetype appr_land  \\\n",
       "0             NONE     6062      6062     COM6  ...        12      None   \n",
       "1  COMMERCIAL BSMT    19468      4867     COM6  ...        12      None   \n",
       "2  COMMERCIAL BSMT   910583     65042     COM6  ...        12      None   \n",
       "3  COMMERCIAL BSMT    65112     13022     COM6  ...        12      None   \n",
       "4             NONE    32094     16047     COM6  ...        12      None   \n",
       "\n",
       "  appr_tot  ffe_elev  g_elev  lhsm_elev       lon       lat  \\\n",
       "0     None      None    None       None -90.02585  35.14020   \n",
       "1     None      None    None       None -90.02585  35.14020   \n",
       "2     None      None    None       None -90.01928  35.13640   \n",
       "3     None      None    None       None -90.07377  35.12344   \n",
       "4     None      None    None       None -90.04349  35.15360   \n",
       "\n",
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       "\n",
       "[5 rows x 34 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Exercise 1: \n",
    "# TODO: create a local dataset for building inventory with shapefiles (\"sample_bldgs_w_guid.shp\") \n",
    "#       and dataset inventory IN-CORE type: \"ergo:buildingInventoryVer7\"\n",
    "# TODO: acquire GeoDataFrame object from the dataset\n",
    "\n",
    "\n",
    "# Answer: \n",
    "# There is a shape file in your local directory. Sample building inventory has 4 files defining \n",
    "# the projection, attributes and other parts of a shape file (cpg, dbf, prj, shp, shx)\n",
    "\n",
    "# use class method Dataset.from_file with path, filename and corresponding data type.\n",
    "# Dataset.from_file(path, data_type)\n",
    "bldgs = Dataset.from_file(\"sample_bldgs_w_guid.shp\", data_type=\"ergo:buildingInventoryVer7\")\n",
    "\n",
    "# Object bldgs is now in pyincore object type. BTW pyIncore uses Fiona package to open shapefiles. \n",
    "print(type(bldgs))\n",
    "\n",
    "# Construct GeoPanda's GeoDataFrame from a pyincore type.\n",
    "# getting geodataframe of building dataset \n",
    "bldgs_gdf = bldgs.get_dataframe_from_shapefile()\n",
    "print(type(bldgs_gdf))\n",
    "\n",
    "# show first five rows only\n",
    "bldgs_gdf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "4df61c82",
   "metadata": {},
   "outputs": [
    {
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     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n"
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       "                                   guid      LS_0      LS_1          LS_2  \\\n",
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       "\n",
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   ],
   "source": [
    "# Exercise 2: \n",
    "# TODO: create a local dataset for building damage output with CSV (\"memphis_eq_bldg_dmg_result.csv\") - \n",
    "#       it should be in your browser if you ran session 4 notebook (dataset inventory IN-CORE type: \"ergo:buildingDamageVer5\")\n",
    "# TODO: acquire DataFrame object from the dataset\n",
    "\n",
    "# Answer: \n",
    "# A CSV file with guid, limit states and damage states is one of two resulting files of Infrastructure Damage Analyses \n",
    "# (building, pipeline etc.). The second, json file contains fragility ids, hazard values and other metadata \n",
    "# Locate CSV file in Jupyter browser directory\n",
    "\n",
    "# Retrieve result dataset. If there is no csv file you need to run Building Damage Analyses from session 4 notebook.\n",
    "bldgs = Dataset.from_file(\"memphis_eq_bldg_dmg_result.csv\", data_type=\"ergo:buildingDamageVer5\")\n",
    "\n",
    "# Convert dataset to Pandas DataFrame\n",
    "bldgs_df = bldgs.get_dataframe_from_csv()\n",
    "\n",
    "print(type(bldgs_df))\n",
    "\n",
    "# show first five rows only\n",
    "bldgs_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "ef8a52a5",
   "metadata": {},
   "outputs": [
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       "      <td>0.103226</td>\n",
       "      <td>0.415849</td>\n",
       "      <td>0.393358</td>\n",
       "      <td>8.756720e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>28321416-e473-473b-ad0a-c3c38248acc7</td>\n",
       "      <td>URM</td>\n",
       "      <td>POINT (-90.07377 35.12344)</td>\n",
       "      <td>367311</td>\n",
       "      <td>0.828098</td>\n",
       "      <td>0.293753</td>\n",
       "      <td>2.738378e-02</td>\n",
       "      <td>0.171902</td>\n",
       "      <td>0.534345</td>\n",
       "      <td>0.266369</td>\n",
       "      <td>2.738378e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>b5069250-7a2b-47b1-9754-290528a6d72d</td>\n",
       "      <td>S1</td>\n",
       "      <td>POINT (-90.04349 35.15360)</td>\n",
       "      <td>1027399</td>\n",
       "      <td>0.970343</td>\n",
       "      <td>0.154677</td>\n",
       "      <td>1.000000e-10</td>\n",
       "      <td>0.029657</td>\n",
       "      <td>0.815666</td>\n",
       "      <td>0.154677</td>\n",
       "      <td>1.000000e-10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   guid struct_typ  \\\n",
       "0  ac8b0b44-ae82-4c48-afb8-076e2d16c7e5         C1   \n",
       "1  154b0a62-cae6-456d-8d90-635e3e1c2dcb         C1   \n",
       "2  9f9b11f8-c25c-4760-b1d2-a63bbeec8e72         S1   \n",
       "3  28321416-e473-473b-ad0a-c3c38248acc7        URM   \n",
       "4  b5069250-7a2b-47b1-9754-290528a6d72d         S1   \n",
       "\n",
       "                     geometry  appr_bldg      LS_0      LS_1          LS_2  \\\n",
       "0  POINT (-90.02585 35.14020)     163315  0.848149  0.327322  2.722964e-02   \n",
       "1  POINT (-90.02585 35.14020)     524485  0.844343  0.328299  2.860543e-02   \n",
       "2  POINT (-90.01928 35.13640)   49457042  0.896774  0.480925  8.756720e-02   \n",
       "3  POINT (-90.07377 35.12344)     367311  0.828098  0.293753  2.738378e-02   \n",
       "4  POINT (-90.04349 35.15360)    1027399  0.970343  0.154677  1.000000e-10   \n",
       "\n",
       "       DS_0      DS_1      DS_2          DS_3  \n",
       "0  0.151851  0.520827  0.300092  2.722964e-02  \n",
       "1  0.155657  0.516043  0.299694  2.860543e-02  \n",
       "2  0.103226  0.415849  0.393358  8.756720e-02  \n",
       "3  0.171902  0.534345  0.266369  2.738378e-02  \n",
       "4  0.029657  0.815666  0.154677  1.000000e-10  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Exercise 3: \n",
    "# TODO: Join/merge building inventory GeoDataframe and damage output Dataframe using results of Excercise 1 and 2.\n",
    "\n",
    "# Answer: \n",
    "# We now have two objects, Geopanda's GeoDataFrame with buildings attributes and coordinates \n",
    "# and Panda's DataFrame with  Damage states. Both objects have GUID referencing buildings.\n",
    "\n",
    "# Merge/join two dataframe using GUID. We can also specify first three columns, guid, struct_typ and geometry, \n",
    "# and their order.\n",
    "bldgs_joined_gdf = bldgs_gdf[['guid', 'struct_typ', 'geometry', 'appr_bldg']].merge(bldgs_df, on='guid')\n",
    "bldgs_joined_gdf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "3bcd19f4",
   "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>guid</th>\n",
       "      <th>geometry</th>\n",
       "      <th>struct_typ</th>\n",
       "      <th>appr_bldg</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ac8b0b44-ae82-4c48-afb8-076e2d16c7e5</td>\n",
       "      <td>POINT (-90.02585 35.14020)</td>\n",
       "      <td>C1</td>\n",
       "      <td>163315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>154b0a62-cae6-456d-8d90-635e3e1c2dcb</td>\n",
       "      <td>POINT (-90.02585 35.14020)</td>\n",
       "      <td>C1</td>\n",
       "      <td>524485</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>9f9b11f8-c25c-4760-b1d2-a63bbeec8e72</td>\n",
       "      <td>POINT (-90.01928 35.13640)</td>\n",
       "      <td>S1</td>\n",
       "      <td>49457042</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>28321416-e473-473b-ad0a-c3c38248acc7</td>\n",
       "      <td>POINT (-90.07377 35.12344)</td>\n",
       "      <td>URM</td>\n",
       "      <td>367311</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>b5069250-7a2b-47b1-9754-290528a6d72d</td>\n",
       "      <td>POINT (-90.04349 35.15360)</td>\n",
       "      <td>S1</td>\n",
       "      <td>1027399</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   guid                    geometry  \\\n",
       "0  ac8b0b44-ae82-4c48-afb8-076e2d16c7e5  POINT (-90.02585 35.14020)   \n",
       "1  154b0a62-cae6-456d-8d90-635e3e1c2dcb  POINT (-90.02585 35.14020)   \n",
       "2  9f9b11f8-c25c-4760-b1d2-a63bbeec8e72  POINT (-90.01928 35.13640)   \n",
       "3  28321416-e473-473b-ad0a-c3c38248acc7  POINT (-90.07377 35.12344)   \n",
       "4  b5069250-7a2b-47b1-9754-290528a6d72d  POINT (-90.04349 35.15360)   \n",
       "\n",
       "  struct_typ  appr_bldg  \n",
       "0         C1     163315  \n",
       "1         C1     524485  \n",
       "2         S1   49457042  \n",
       "3        URM     367311  \n",
       "4         S1    1027399  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Exercise 4: \n",
    "# TODO: Using joined GeoDataFrame, display the table grouped by \"struct_type\" and show a sum of apprasial \n",
    "#       value of buildings \"appr_bldg\" \n",
    "\n",
    "# Answer: \n",
    "# We have a joined object, GeoDataFrame bldgs_joined_gdf with all attributes (columns). We can show only guid\n",
    "# and struct_type and appr_bldg columns. Dont forget to keep geometry column or new dataframe \n",
    "# will not be georeferenced\n",
    "\n",
    "bldgs_new = bldgs_joined_gdf[['guid', 'geometry', 'struct_typ', 'appr_bldg']]\n",
    "bldgs_new.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "db8670e9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "270160346\n"
     ]
    }
   ],
   "source": [
    "# Exercise 4 cont.:\n",
    "\n",
    "# Run stastics on a column.\n",
    "# Sum of all rows = 270,160,346\n",
    "total = bldgs_new[\"appr_bldg\"].sum()\n",
    "print(total)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "3a34b50d-3202-4758-b345-7c7166d9316d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    5.000000e+00\n",
       "mean     1.030791e+07\n",
       "std      2.188736e+07\n",
       "min      1.633150e+05\n",
       "25%      3.673110e+05\n",
       "50%      5.244850e+05\n",
       "75%      1.027399e+06\n",
       "max      4.945704e+07\n",
       "Name: appr_bldg, dtype: float64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Exercise 4 cont.:\n",
    "\n",
    "# Run stastics on a column (first five rows).\n",
    "# Sum of 5 rows = 51,539,552 with mean value of 10,307,910\n",
    "bldgs_new[\"appr_bldg\"].head().describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "279a61fb-ba96-475b-ae77-facd4f3d2d8e",
   "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>guid</th>\n",
       "      <th>DS_0</th>\n",
       "      <th>DS_1</th>\n",
       "      <th>DS_2</th>\n",
       "      <th>DS_3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ac8b0b44-ae82-4c48-afb8-076e2d16c7e5</td>\n",
       "      <td>0.151851</td>\n",
       "      <td>0.520827</td>\n",
       "      <td>0.300092</td>\n",
       "      <td>2.722964e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>154b0a62-cae6-456d-8d90-635e3e1c2dcb</td>\n",
       "      <td>0.155657</td>\n",
       "      <td>0.516043</td>\n",
       "      <td>0.299694</td>\n",
       "      <td>2.860543e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>9f9b11f8-c25c-4760-b1d2-a63bbeec8e72</td>\n",
       "      <td>0.103226</td>\n",
       "      <td>0.415849</td>\n",
       "      <td>0.393358</td>\n",
       "      <td>8.756720e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>28321416-e473-473b-ad0a-c3c38248acc7</td>\n",
       "      <td>0.171902</td>\n",
       "      <td>0.534345</td>\n",
       "      <td>0.266369</td>\n",
       "      <td>2.738378e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>b5069250-7a2b-47b1-9754-290528a6d72d</td>\n",
       "      <td>0.029657</td>\n",
       "      <td>0.815666</td>\n",
       "      <td>0.154677</td>\n",
       "      <td>1.000000e-10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   guid      DS_0      DS_1      DS_2  \\\n",
       "0  ac8b0b44-ae82-4c48-afb8-076e2d16c7e5  0.151851  0.520827  0.300092   \n",
       "1  154b0a62-cae6-456d-8d90-635e3e1c2dcb  0.155657  0.516043  0.299694   \n",
       "2  9f9b11f8-c25c-4760-b1d2-a63bbeec8e72  0.103226  0.415849  0.393358   \n",
       "3  28321416-e473-473b-ad0a-c3c38248acc7  0.171902  0.534345  0.266369   \n",
       "4  b5069250-7a2b-47b1-9754-290528a6d72d  0.029657  0.815666  0.154677   \n",
       "\n",
       "           DS_3  \n",
       "0  2.722964e-02  \n",
       "1  2.860543e-02  \n",
       "2  8.756720e-02  \n",
       "3  2.738378e-02  \n",
       "4  1.000000e-10  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Exercise 5: \n",
    "# TODO: Using joined GeoDataFrame, plot a pie chart of (DS_0, DS_1, DS_2, DS_3) with a building with highest \n",
    "#       value of DS_3\n",
    "\n",
    "# Answer: \n",
    "# We have a joined object, GeoDataFrame bldgs_joined_gdf with all attributes (columns). We can create a new one\n",
    "# only with guid and damage states probability values.\n",
    "df_ds = bldgs_joined_gdf[['guid', 'DS_0', 'DS_1', 'DS_2', 'DS_3']]\n",
    "df_ds.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "80ab20bd-5330-4893-a3dc-014040a931ac",
   "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>guid</th>\n",
       "      <th>DS_0</th>\n",
       "      <th>DS_1</th>\n",
       "      <th>DS_2</th>\n",
       "      <th>DS_3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>6dd342ef-498c-43a9-85cd-35ad76e4c279</td>\n",
       "      <td>0.143819</td>\n",
       "      <td>0.409244</td>\n",
       "      <td>0.352468</td>\n",
       "      <td>0.094468</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    guid      DS_0      DS_1      DS_2  \\\n",
       "14  6dd342ef-498c-43a9-85cd-35ad76e4c279  0.143819  0.409244  0.352468   \n",
       "\n",
       "        DS_3  \n",
       "14  0.094468  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Exercise 5 cont: \n",
    "# Return the entire row with max value of DS_3 column\n",
    "df = df_ds[df_ds['DS_3']==df_ds['DS_3'].max()]\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "a63d9f93",
   "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>probability</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>DS_0</th>\n",
       "      <td>0.143819</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DS_1</th>\n",
       "      <td>0.409244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DS_2</th>\n",
       "      <td>0.352468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DS_3</th>\n",
       "      <td>0.094468</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      probability\n",
       "DS_0     0.143819\n",
       "DS_1     0.409244\n",
       "DS_2     0.352468\n",
       "DS_3     0.094468"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Exercise 5 cont: \n",
    "\n",
    "# We use Panda's plot method for pie chart visualization of our four DS probabilities.\n",
    "# First, the dataframe must be transposed to get rows of DS\n",
    "df_pie = df[['DS_0', 'DS_1', 'DS_2', 'DS_3']].transpose()\n",
    "# Rename the column for proper legend\n",
    "df_pie.columns = ['probability']\n",
    "df_pie.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "411249ce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Exercise 5 cont: \n",
    "\n",
    "# Create pie chart\n",
    "plot = df_pie.plot.pie(subplots=True, figsize=(5, 5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "65cd1ed8-976d-473a-8dae-7de7485d5808",
   "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>guid</th>\n",
       "      <th>DS_0</th>\n",
       "      <th>DS_1</th>\n",
       "      <th>DS_2</th>\n",
       "      <th>DS_3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>11395729-3727-449d-9848-778d68edd7d8</td>\n",
       "      <td>0.076171</td>\n",
       "      <td>0.432794</td>\n",
       "      <td>0.420815</td>\n",
       "      <td>0.070220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>d7603d04-6917-478c-8bb7-50cf9118f973</td>\n",
       "      <td>0.119953</td>\n",
       "      <td>0.434135</td>\n",
       "      <td>0.371550</td>\n",
       "      <td>0.074362</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>9f9b11f8-c25c-4760-b1d2-a63bbeec8e72</td>\n",
       "      <td>0.103226</td>\n",
       "      <td>0.415849</td>\n",
       "      <td>0.393358</td>\n",
       "      <td>0.087567</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>6dd342ef-498c-43a9-85cd-35ad76e4c279</td>\n",
       "      <td>0.143819</td>\n",
       "      <td>0.409244</td>\n",
       "      <td>0.352468</td>\n",
       "      <td>0.094468</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    guid      DS_0      DS_1      DS_2  \\\n",
       "6   11395729-3727-449d-9848-778d68edd7d8  0.076171  0.432794  0.420815   \n",
       "11  d7603d04-6917-478c-8bb7-50cf9118f973  0.119953  0.434135  0.371550   \n",
       "2   9f9b11f8-c25c-4760-b1d2-a63bbeec8e72  0.103226  0.415849  0.393358   \n",
       "14  6dd342ef-498c-43a9-85cd-35ad76e4c279  0.143819  0.409244  0.352468   \n",
       "\n",
       "        DS_3  \n",
       "6   0.070220  \n",
       "11  0.074362  \n",
       "2   0.087567  \n",
       "14  0.094468  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Exercise 6: \n",
    "# TODO: Using joined GeoDataFrame, display a table of buidings with DS_3 >= 0.05 and sorted by DS_3\n",
    "\n",
    "# Answer: \n",
    "# We have our joined object, GeoDataFrame bldgs_joined_gdf with all attributes (columns). We can create \n",
    "# a new one only with guid and damage states probability values:\n",
    "# df_ds = bldgs_joined_gdf[['guid', 'DS_0', 'DS_1', 'DS_2', 'DS_3']]\n",
    "# or re-use df_ds object from Exercise 5\n",
    "\n",
    "df_ds3 = df_ds[df_ds['DS_3']>=0.05]\n",
    "df_ds3.sort_values(by=['DS_3'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "41981e2f-b166-457b-92b4-7f1460f42f24",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>guid</th>\n",
       "      <th>geometry</th>\n",
       "      <th>DS_3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ac8b0b44-ae82-4c48-afb8-076e2d16c7e5</td>\n",
       "      <td>POINT (-90.02585 35.14020)</td>\n",
       "      <td>2.722964e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>154b0a62-cae6-456d-8d90-635e3e1c2dcb</td>\n",
       "      <td>POINT (-90.02585 35.14020)</td>\n",
       "      <td>2.860543e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>9f9b11f8-c25c-4760-b1d2-a63bbeec8e72</td>\n",
       "      <td>POINT (-90.01928 35.13640)</td>\n",
       "      <td>8.756720e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>28321416-e473-473b-ad0a-c3c38248acc7</td>\n",
       "      <td>POINT (-90.07377 35.12344)</td>\n",
       "      <td>2.738378e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>b5069250-7a2b-47b1-9754-290528a6d72d</td>\n",
       "      <td>POINT (-90.04349 35.15360)</td>\n",
       "      <td>1.000000e-10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   guid                    geometry  \\\n",
       "0  ac8b0b44-ae82-4c48-afb8-076e2d16c7e5  POINT (-90.02585 35.14020)   \n",
       "1  154b0a62-cae6-456d-8d90-635e3e1c2dcb  POINT (-90.02585 35.14020)   \n",
       "2  9f9b11f8-c25c-4760-b1d2-a63bbeec8e72  POINT (-90.01928 35.13640)   \n",
       "3  28321416-e473-473b-ad0a-c3c38248acc7  POINT (-90.07377 35.12344)   \n",
       "4  b5069250-7a2b-47b1-9754-290528a6d72d  POINT (-90.04349 35.15360)   \n",
       "\n",
       "           DS_3  \n",
       "0  2.722964e-02  \n",
       "1  2.860543e-02  \n",
       "2  8.756720e-02  \n",
       "3  2.738378e-02  \n",
       "4  1.000000e-10  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Exercise 7: \n",
    "# TODO: Using joined GeoDataFrame, plot a map of buidings with DS_3 >= 0.05 and sorted by DS_3\n",
    "\n",
    "# Answer: \n",
    "# We have sorted object, df_ds3 from Exercise 6 however we removed the geometry. We need to go back and use \n",
    "# georeferenced object bldgs_joined_gdf with guid, geometry and DS_3.\n",
    "\n",
    "bldgs_ds3 = bldgs_joined_gdf[['guid', 'geometry', 'DS_3']]\n",
    "bldgs_ds3.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "4a75d81d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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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>guid</th>\n",
       "      <th>geometry</th>\n",
       "      <th>DS_3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>11395729-3727-449d-9848-778d68edd7d8</td>\n",
       "      <td>POINT (-90.04349 35.15360)</td>\n",
       "      <td>0.070220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>d7603d04-6917-478c-8bb7-50cf9118f973</td>\n",
       "      <td>POINT (-89.86438 35.09755)</td>\n",
       "      <td>0.074362</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>9f9b11f8-c25c-4760-b1d2-a63bbeec8e72</td>\n",
       "      <td>POINT (-90.01928 35.13640)</td>\n",
       "      <td>0.087567</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>6dd342ef-498c-43a9-85cd-35ad76e4c279</td>\n",
       "      <td>POINT (-89.77456 35.20624)</td>\n",
       "      <td>0.094468</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    guid                    geometry      DS_3\n",
       "6   11395729-3727-449d-9848-778d68edd7d8  POINT (-90.04349 35.15360)  0.070220\n",
       "11  d7603d04-6917-478c-8bb7-50cf9118f973  POINT (-89.86438 35.09755)  0.074362\n",
       "2   9f9b11f8-c25c-4760-b1d2-a63bbeec8e72  POINT (-90.01928 35.13640)  0.087567\n",
       "14  6dd342ef-498c-43a9-85cd-35ad76e4c279  POINT (-89.77456 35.20624)  0.094468"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Exercise 7 cont: \n",
    "\n",
    "# We filter buildings by DS_3 value and sort them:\n",
    "ds3 = bldgs_ds3[bldgs_ds3['DS_3']>=0.05]\n",
    "ds3_sorted = ds3.sort_values(by=['DS_3'])\n",
    "ds3_sorted.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "3a0822ad",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Exercise 7 cont: \n",
    "\n",
    "# Plot a map of ds3_sorted GeoPandasDataset with pyincore_viz\n",
    "geoviz.plot_gdf_map(ds3_sorted, 'DS_3', basemap=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f23d777b",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.7.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}