pyEmdat_usage.ipynb

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   "source": [
    "## Example queries with pyEmdat\n",
    "This notebook shows a set of example queries using an EMDAT dataset of disaster events since 1960 for the world:\n",
    "* number of events for selected countries/dates/hazards\n",
    "* disaster stats for selected countries/dates/hazards (grouped by hazard or country)\n",
    "* breakdown of disaster impacts for a single period (grouped by hazard or country)\n",
    "* annual average loss (CPI rebased)\n",
    "\n",
    "pyEmdat makes these queries easy: just load the data as an *emdat* object then use the built-in methods which filter, group and aggregate the individual disaster records to produce the required outputs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "developing-damage",
   "metadata": {
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   "outputs": [],
   "source": [
    "# imports\n",
    "import pandas as pd\n",
    "import pylab as plt\n",
    "\n",
    "# pyEmdat\n",
    "from pyEmdat.emdat_df import emdat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "functional-needle",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "# additional imports\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "import matplotlib.ticker as ticker\n",
    "%pylab inline\n",
    "\n",
    "# config\n",
    "import os\n",
    "data = os.getenv('data')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "under-control",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## 1. Load downloaded Excel file as a PyEmdat object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "veterinary-professor",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "ED = emdat((data + '/emdat_1960.xlsx'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "criminal-princeton",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>dis_no</th>\n",
       "      <th>year</th>\n",
       "      <th>Seq</th>\n",
       "      <th>disaster_group</th>\n",
       "      <th>disaster_subgroup</th>\n",
       "      <th>disaster_type</th>\n",
       "      <th>disaster_subtype</th>\n",
       "      <th>Disaster Subsubtype</th>\n",
       "      <th>event_name</th>\n",
       "      <th>Entry Criteria</th>\n",
       "      <th>...</th>\n",
       "      <th>End Day</th>\n",
       "      <th>deaths</th>\n",
       "      <th>injured</th>\n",
       "      <th>affected</th>\n",
       "      <th>homeless</th>\n",
       "      <th>total_affected</th>\n",
       "      <th>reconstruction_costs</th>\n",
       "      <th>insured_damages</th>\n",
       "      <th>total_damages</th>\n",
       "      <th>CPI</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1960-0013-CHL</td>\n",
       "      <td>1960</td>\n",
       "      <td>13</td>\n",
       "      <td>Natural</td>\n",
       "      <td>Geophysical</td>\n",
       "      <td>Earthquake</td>\n",
       "      <td>Tsunami</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Kill</td>\n",
       "      <td>...</td>\n",
       "      <td>22.0</td>\n",
       "      <td>6000.0</td>\n",
       "      <td>3000.0</td>\n",
       "      <td>2000000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2003000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>550000.0</td>\n",
       "      <td>11.568216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1960-0026-AIA</td>\n",
       "      <td>1960</td>\n",
       "      <td>26</td>\n",
       "      <td>Natural</td>\n",
       "      <td>Meteorological</td>\n",
       "      <td>Storm</td>\n",
       "      <td>Tropical cyclone</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Donna</td>\n",
       "      <td>Affect</td>\n",
       "      <td>...</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1250.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35000.0</td>\n",
       "      <td>11.568216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1960-0025-ANT</td>\n",
       "      <td>1960</td>\n",
       "      <td>25</td>\n",
       "      <td>Natural</td>\n",
       "      <td>Meteorological</td>\n",
       "      <td>Storm</td>\n",
       "      <td>Tropical cyclone</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Donna</td>\n",
       "      <td>OFDA</td>\n",
       "      <td>...</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.568216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1960-0024-ATG</td>\n",
       "      <td>1960</td>\n",
       "      <td>24</td>\n",
       "      <td>Natural</td>\n",
       "      <td>Meteorological</td>\n",
       "      <td>Storm</td>\n",
       "      <td>Tropical cyclone</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Donna</td>\n",
       "      <td>OFDA</td>\n",
       "      <td>...</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.568216</td>\n",
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       "      <th>4</th>\n",
       "      <td>1960-0030-BGD</td>\n",
       "      <td>1960</td>\n",
       "      <td>30</td>\n",
       "      <td>Natural</td>\n",
       "      <td>Meteorological</td>\n",
       "      <td>Storm</td>\n",
       "      <td>Tropical cyclone</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Kill</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>3000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.568216</td>\n",
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       "<p>5 rows × 43 columns</p>\n",
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      "text/plain": [
       "          dis_no  year  Seq disaster_group disaster_subgroup disaster_type  \\\n",
       "0  1960-0013-CHL  1960   13        Natural       Geophysical    Earthquake   \n",
       "1  1960-0026-AIA  1960   26        Natural    Meteorological         Storm   \n",
       "2  1960-0025-ANT  1960   25        Natural    Meteorological         Storm   \n",
       "3  1960-0024-ATG  1960   24        Natural    Meteorological         Storm   \n",
       "4  1960-0030-BGD  1960   30        Natural    Meteorological         Storm   \n",
       "\n",
       "   disaster_subtype Disaster Subsubtype event_name Entry Criteria  ...  \\\n",
       "0           Tsunami                 NaN        NaN           Kill  ...   \n",
       "1  Tropical cyclone                 NaN      Donna         Affect  ...   \n",
       "2  Tropical cyclone                 NaN      Donna           OFDA  ...   \n",
       "3  Tropical cyclone                 NaN      Donna           OFDA  ...   \n",
       "4  Tropical cyclone                 NaN        NaN           Kill  ...   \n",
       "\n",
       "  End Day  deaths injured   affected homeless total_affected  \\\n",
       "0    22.0  6000.0  3000.0  2000000.0      NaN      2003000.0   \n",
       "1     4.0     5.0   250.0        NaN   1000.0         1250.0   \n",
       "2     4.0     NaN     NaN        NaN      NaN            NaN   \n",
       "3     4.0     2.0     NaN        NaN      NaN            NaN   \n",
       "4     9.0  3000.0     NaN        NaN      NaN            NaN   \n",
       "\n",
       "  reconstruction_costs insured_damages total_damages        CPI  \n",
       "0                  NaN             NaN      550000.0  11.568216  \n",
       "1                  NaN             NaN       35000.0  11.568216  \n",
       "2                  NaN             NaN           NaN  11.568216  \n",
       "3                  NaN             NaN           NaN  11.568216  \n",
       "4                  NaN             NaN           NaN  11.568216  \n",
       "\n",
       "[5 rows x 43 columns]"
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     "execution_count": 98,
     "metadata": {},
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   ],
   "source": [
    "ED.data.head()"
   ]
  },
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   "cell_type": "markdown",
   "id": "worst-activity",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## 2. Time series: number of events\n",
    "The emdat_df object provides a method disaster_count_timeseries. This returns number of events by year for the parameters supplied (min_year, max_year, countries, disastertype)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "sharp-inside",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "df = ED.disaster_count_timeseries(1960, 2000, countries = 'all',\n",
    "        disastertype = ['Storm','Flood', 'Earthquake','Volcanic activity','Landslide'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "saved-theater",
   "metadata": {
    "slideshow": {
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    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>disaster_type</th>\n",
       "      <th>Earthquake</th>\n",
       "      <th>Flood</th>\n",
       "      <th>Landslide</th>\n",
       "      <th>Storm</th>\n",
       "      <th>Volcanic activity</th>\n",
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       "      <th>year</th>\n",
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       "      <th>1961</th>\n",
       "      <td>3.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1962</th>\n",
       "      <td>4.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>1963</th>\n",
       "      <td>3.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>3.0</td>\n",
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       "    <tr>\n",
       "      <th>1964</th>\n",
       "      <td>7.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1.0</td>\n",
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       "    <tr>\n",
       "      <th>1965</th>\n",
       "      <td>8.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>1.0</td>\n",
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      "text/plain": [
       "disaster_type  Earthquake  Flood  Landslide  Storm  Volcanic activity\n",
       "year                                                                 \n",
       "1961                  3.0    8.0        2.0   14.0                0.0\n",
       "1962                  4.0    8.0        2.0   13.0                0.0\n",
       "1963                  3.0    8.0        2.0   21.0                3.0\n",
       "1964                  7.0   22.0        1.0   22.0                1.0\n",
       "1965                  8.0   19.0        6.0   19.0                1.0"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
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   "execution_count": 101,
   "id": "failing-return",
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot(title = 'World: Number of events by year');"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "structural-comparative",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## 3. Time series grouped by hazard (for selected countries & dates)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "suspended-glance",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "df = ED.disaster_stats_timeseries(1960, 2020, 'Mexico','all','deaths')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "basic-samba",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "cols_over_1000 = [column for column in df.columns if df[column].sum() > 1000]\n",
    "df = df[cols_over_1000]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "gross-border",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot(title = 'Mexico: deaths by hazard type since 1980');"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "applicable-prison",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## 4. Time series grouped by country (for selected dates & hazard)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "remarkable-singing",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = ED.country_stats_timeseries(1980, 2020, ['Georgia','Armenia','Azerbaijan'],'all','total_damages')\n",
    "ax = df.plot.area(title = \"South Caucasus: Total damages 1980 - present (all hazards, current USD '000)\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "greenhouse-cameroon",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## 5. Annual average loss grouped by hazard\n",
    "* Note: EMDAT records losses in nominal USD (ie. current dollar values of a given year). The nominal figures over-represent recent disasters vs those several decades ago.\n",
    "* The method below provides annual average loss (sum of loss / n_years) adjusted into real USD for the given year, using the Bureau of Labor Statistics CPI index."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "economic-cancellation",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "df = ED.aal_by_disaster_type(1960, 2020, 'Peru', 'all',base_year=2010)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "current-browser",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "df = df[df>0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "matched-citizenship",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "disaster_type\n",
       "Earthquake                75964\n",
       "Flood                     54028\n",
       "Landslide                 39772\n",
       "Mass movement (dry)       25292\n",
       "Drought                    8912\n",
       "Extreme temperature        1517\n",
       "Transport accident         1505\n",
       "Miscellaneous accident      589\n",
       "Storm                       285\n",
       "Industrial accident          56\n",
       "dtype: int64"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "different-adelaide",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = df.plot(kind = 'bar')\n",
    "plt.title('Indonesia: average annual loss by hazard (1960-2020), real 2010 USD');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "secondary-shareware",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "country = 'Indonesia'\n",
    "df_decades=pd.DataFrame({'1970s': ED.aal_by_disaster_type(1970, 1980, country, 'all',base_year=2010),\n",
    "                        '1980s':ED.aal_by_disaster_type(1980, 1990, country, 'all',base_year=2010),\n",
    "                        '1990s':ED.aal_by_disaster_type(1990, 2000, country, 'all',base_year=2010),\n",
    "                        '2000s':ED.aal_by_disaster_type(2000, 2010, country, 'all',base_year=2010),\n",
    "                        '2010s':ED.aal_by_disaster_type(2010, 2020, country, 'all',base_year=2010)})\n",
    "df_decades = df_decades.fillna(0)\n",
    "df_decades['mean'] = df_decades.mean(axis=1)\n",
    "df_decades.sort_values(ascending=False, by='mean')\n",
    "df_decades=df_decades[:4]\n",
    "df_decades.drop(columns='mean',inplace=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "proved-eagle",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "def thousands(x, pos):\n",
    "    return('{:,.0f}'.format(x*1e-3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "id": "quality-destination",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = df_decades.T.plot(kind='barh',stacked=True)\n",
    "plt.title('Indonesia: annual average loss by hazard, real 2010 USD (thousand)')\n",
    "x_labels = ax.get_xticks()\n",
    "ax.xaxis.set_major_formatter(ticker.FuncFormatter(thousands));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "republican-humor",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "GPD3",
   "language": "python",
   "name": "gpd3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}