{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Tabular Data with Pandas"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[Pandas](https://pandas.pydata.org/docs/getting_started/intro_tutorials/index.html) is the most popular Python tool for data analysis. It handles tabular data and has tons of nice features for manipulating text, grouping data by attributes, formatting dates, the list goes on... Even if you do not use tabular or csv data, you will likely end up using Pandas tools for some of their nice data-wrangling features. In general, if you have data that could be organized in an Excel spreadsheet or a table, you should use Pandas. This is particularly useful for data downloaded from places like NOAA and USGS where observations from individual meaurement stations are usually concatenated into a table of some kind. Pandas can be used to open data in CSV, HTML, JSON, XLS, Parquet, SQL, GBQ formats and more. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Earthquake Data Tutorial\n",
    "\n",
    "For this tutorial we have grabbed the last 30 days of global earthquake activity from [USGS](https://earthquake.usgs.gov/earthquakes/search/) (downloaded August 11th, 2025). The data only includes earthquakes of magnitude greater than or equal to 2.5. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd #import the pandas library\n",
    "\n",
    "# open our csv file, this assumes it is in the top level of your VSCode workspace\n",
    "df = pd.read_csv('global_30day_earthquakes.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When we open a dataset, Pandas reads the data into an object called a 'DataFrame' which looks like a table."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "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>time</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>depth</th>\n",
       "      <th>mag</th>\n",
       "      <th>magType</th>\n",
       "      <th>nst</th>\n",
       "      <th>gap</th>\n",
       "      <th>dmin</th>\n",
       "      <th>rms</th>\n",
       "      <th>...</th>\n",
       "      <th>updated</th>\n",
       "      <th>place</th>\n",
       "      <th>type</th>\n",
       "      <th>horizontalError</th>\n",
       "      <th>depthError</th>\n",
       "      <th>magError</th>\n",
       "      <th>magNst</th>\n",
       "      <th>status</th>\n",
       "      <th>locationSource</th>\n",
       "      <th>magSource</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2025-08-12T00:30:58.784Z</td>\n",
       "      <td>62.008000</td>\n",
       "      <td>-145.533400</td>\n",
       "      <td>9.800</td>\n",
       "      <td>2.60</td>\n",
       "      <td>ml</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.8700</td>\n",
       "      <td>...</td>\n",
       "      <td>2025-08-12T00:37:39.629Z</td>\n",
       "      <td>7 km SW of Copperville, Alaska</td>\n",
       "      <td>earthquake</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.300</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>automatic</td>\n",
       "      <td>ak</td>\n",
       "      <td>ak</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2025-08-12T00:30:53.834Z</td>\n",
       "      <td>61.740900</td>\n",
       "      <td>-146.097200</td>\n",
       "      <td>42.400</td>\n",
       "      <td>2.60</td>\n",
       "      <td>ml</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.5700</td>\n",
       "      <td>...</td>\n",
       "      <td>2025-08-12T00:35:35.397Z</td>\n",
       "      <td>38 km S of Tolsona, Alaska</td>\n",
       "      <td>earthquake</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.200</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>automatic</td>\n",
       "      <td>ak</td>\n",
       "      <td>ak</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2025-08-11T23:45:41.896Z</td>\n",
       "      <td>51.193700</td>\n",
       "      <td>160.859900</td>\n",
       "      <td>10.000</td>\n",
       "      <td>4.50</td>\n",
       "      <td>mb</td>\n",
       "      <td>25.0</td>\n",
       "      <td>135.00</td>\n",
       "      <td>2.2830</td>\n",
       "      <td>0.4400</td>\n",
       "      <td>...</td>\n",
       "      <td>2025-08-12T00:10:36.040Z</td>\n",
       "      <td>256 km SE of Vilyuchinsk, Russia</td>\n",
       "      <td>earthquake</td>\n",
       "      <td>7.30</td>\n",
       "      <td>1.883</td>\n",
       "      <td>0.069</td>\n",
       "      <td>61.0</td>\n",
       "      <td>reviewed</td>\n",
       "      <td>us</td>\n",
       "      <td>us</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2025-08-11T21:24:31.503Z</td>\n",
       "      <td>41.242100</td>\n",
       "      <td>-116.714900</td>\n",
       "      <td>6.300</td>\n",
       "      <td>2.90</td>\n",
       "      <td>ml</td>\n",
       "      <td>14.0</td>\n",
       "      <td>144.57</td>\n",
       "      <td>0.3420</td>\n",
       "      <td>0.1627</td>\n",
       "      <td>...</td>\n",
       "      <td>2025-08-11T22:14:22.638Z</td>\n",
       "      <td>60 km NE of Valmy, Nevada</td>\n",
       "      <td>earthquake</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.300</td>\n",
       "      <td>0.260</td>\n",
       "      <td>12.0</td>\n",
       "      <td>reviewed</td>\n",
       "      <td>nn</td>\n",
       "      <td>nn</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2025-08-11T21:02:42.456Z</td>\n",
       "      <td>51.651500</td>\n",
       "      <td>159.778700</td>\n",
       "      <td>35.000</td>\n",
       "      <td>5.00</td>\n",
       "      <td>mb</td>\n",
       "      <td>61.0</td>\n",
       "      <td>106.00</td>\n",
       "      <td>1.5390</td>\n",
       "      <td>0.6000</td>\n",
       "      <td>...</td>\n",
       "      <td>2025-08-12T00:35:51.040Z</td>\n",
       "      <td>170 km SSE of Vilyuchinsk, Russia</td>\n",
       "      <td>earthquake</td>\n",
       "      <td>6.76</td>\n",
       "      <td>1.859</td>\n",
       "      <td>0.043</td>\n",
       "      <td>175.0</td>\n",
       "      <td>reviewed</td>\n",
       "      <td>us</td>\n",
       "      <td>us</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2658</th>\n",
       "      <td>2025-07-13T03:02:17.889Z</td>\n",
       "      <td>-22.593300</td>\n",
       "      <td>-68.014400</td>\n",
       "      <td>153.524</td>\n",
       "      <td>4.40</td>\n",
       "      <td>mb</td>\n",
       "      <td>29.0</td>\n",
       "      <td>89.00</td>\n",
       "      <td>0.3880</td>\n",
       "      <td>0.8700</td>\n",
       "      <td>...</td>\n",
       "      <td>2025-08-02T22:30:27.040Z</td>\n",
       "      <td>40 km NNE of San Pedro de Atacama, Chile</td>\n",
       "      <td>earthquake</td>\n",
       "      <td>7.46</td>\n",
       "      <td>5.557</td>\n",
       "      <td>0.138</td>\n",
       "      <td>15.0</td>\n",
       "      <td>reviewed</td>\n",
       "      <td>us</td>\n",
       "      <td>us</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2659</th>\n",
       "      <td>2025-07-13T02:32:49.570Z</td>\n",
       "      <td>32.791833</td>\n",
       "      <td>-115.829333</td>\n",
       "      <td>4.810</td>\n",
       "      <td>2.62</td>\n",
       "      <td>ml</td>\n",
       "      <td>67.0</td>\n",
       "      <td>28.00</td>\n",
       "      <td>0.1032</td>\n",
       "      <td>0.2600</td>\n",
       "      <td>...</td>\n",
       "      <td>2025-08-02T22:22:55.040Z</td>\n",
       "      <td>17 km ENE of Ocotillo, CA</td>\n",
       "      <td>earthquake</td>\n",
       "      <td>0.20</td>\n",
       "      <td>0.640</td>\n",
       "      <td>0.121</td>\n",
       "      <td>131.0</td>\n",
       "      <td>reviewed</td>\n",
       "      <td>ci</td>\n",
       "      <td>ci</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2660</th>\n",
       "      <td>2025-07-13T00:49:42.340Z</td>\n",
       "      <td>-9.885400</td>\n",
       "      <td>116.631100</td>\n",
       "      <td>54.034</td>\n",
       "      <td>4.10</td>\n",
       "      <td>mb</td>\n",
       "      <td>17.0</td>\n",
       "      <td>104.00</td>\n",
       "      <td>1.5440</td>\n",
       "      <td>0.4500</td>\n",
       "      <td>...</td>\n",
       "      <td>2025-07-25T02:12:15.040Z</td>\n",
       "      <td>128 km S of Taliwang, Indonesia</td>\n",
       "      <td>earthquake</td>\n",
       "      <td>8.08</td>\n",
       "      <td>5.198</td>\n",
       "      <td>0.174</td>\n",
       "      <td>9.0</td>\n",
       "      <td>reviewed</td>\n",
       "      <td>us</td>\n",
       "      <td>us</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2661</th>\n",
       "      <td>2025-07-13T00:30:59.994Z</td>\n",
       "      <td>50.336900</td>\n",
       "      <td>-175.400000</td>\n",
       "      <td>10.000</td>\n",
       "      <td>2.80</td>\n",
       "      <td>ml</td>\n",
       "      <td>19.0</td>\n",
       "      <td>235.00</td>\n",
       "      <td>1.6530</td>\n",
       "      <td>0.7300</td>\n",
       "      <td>...</td>\n",
       "      <td>2025-07-22T21:41:02.040Z</td>\n",
       "      <td>191 km SSE of Adak, Alaska</td>\n",
       "      <td>earthquake</td>\n",
       "      <td>3.57</td>\n",
       "      <td>2.019</td>\n",
       "      <td>0.105</td>\n",
       "      <td>12.0</td>\n",
       "      <td>reviewed</td>\n",
       "      <td>us</td>\n",
       "      <td>us</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2662</th>\n",
       "      <td>2025-07-13T00:11:12.440Z</td>\n",
       "      <td>-49.427300</td>\n",
       "      <td>-8.066900</td>\n",
       "      <td>10.000</td>\n",
       "      <td>4.50</td>\n",
       "      <td>mb</td>\n",
       "      <td>14.0</td>\n",
       "      <td>106.00</td>\n",
       "      <td>22.4470</td>\n",
       "      <td>0.6600</td>\n",
       "      <td>...</td>\n",
       "      <td>2025-07-25T01:58:47.040Z</td>\n",
       "      <td>southern Mid-Atlantic Ridge</td>\n",
       "      <td>earthquake</td>\n",
       "      <td>8.85</td>\n",
       "      <td>1.934</td>\n",
       "      <td>0.145</td>\n",
       "      <td>14.0</td>\n",
       "      <td>reviewed</td>\n",
       "      <td>us</td>\n",
       "      <td>us</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2663 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                          time   latitude   longitude    depth   mag magType  \\\n",
       "0     2025-08-12T00:30:58.784Z  62.008000 -145.533400    9.800  2.60      ml   \n",
       "1     2025-08-12T00:30:53.834Z  61.740900 -146.097200   42.400  2.60      ml   \n",
       "2     2025-08-11T23:45:41.896Z  51.193700  160.859900   10.000  4.50      mb   \n",
       "3     2025-08-11T21:24:31.503Z  41.242100 -116.714900    6.300  2.90      ml   \n",
       "4     2025-08-11T21:02:42.456Z  51.651500  159.778700   35.000  5.00      mb   \n",
       "...                        ...        ...         ...      ...   ...     ...   \n",
       "2658  2025-07-13T03:02:17.889Z -22.593300  -68.014400  153.524  4.40      mb   \n",
       "2659  2025-07-13T02:32:49.570Z  32.791833 -115.829333    4.810  2.62      ml   \n",
       "2660  2025-07-13T00:49:42.340Z  -9.885400  116.631100   54.034  4.10      mb   \n",
       "2661  2025-07-13T00:30:59.994Z  50.336900 -175.400000   10.000  2.80      ml   \n",
       "2662  2025-07-13T00:11:12.440Z -49.427300   -8.066900   10.000  4.50      mb   \n",
       "\n",
       "       nst     gap     dmin     rms  ...                   updated  \\\n",
       "0      NaN     NaN      NaN  0.8700  ...  2025-08-12T00:37:39.629Z   \n",
       "1      NaN     NaN      NaN  0.5700  ...  2025-08-12T00:35:35.397Z   \n",
       "2     25.0  135.00   2.2830  0.4400  ...  2025-08-12T00:10:36.040Z   \n",
       "3     14.0  144.57   0.3420  0.1627  ...  2025-08-11T22:14:22.638Z   \n",
       "4     61.0  106.00   1.5390  0.6000  ...  2025-08-12T00:35:51.040Z   \n",
       "...    ...     ...      ...     ...  ...                       ...   \n",
       "2658  29.0   89.00   0.3880  0.8700  ...  2025-08-02T22:30:27.040Z   \n",
       "2659  67.0   28.00   0.1032  0.2600  ...  2025-08-02T22:22:55.040Z   \n",
       "2660  17.0  104.00   1.5440  0.4500  ...  2025-07-25T02:12:15.040Z   \n",
       "2661  19.0  235.00   1.6530  0.7300  ...  2025-07-22T21:41:02.040Z   \n",
       "2662  14.0  106.00  22.4470  0.6600  ...  2025-07-25T01:58:47.040Z   \n",
       "\n",
       "                                         place        type horizontalError  \\\n",
       "0               7 km SW of Copperville, Alaska  earthquake             NaN   \n",
       "1                   38 km S of Tolsona, Alaska  earthquake             NaN   \n",
       "2             256 km SE of Vilyuchinsk, Russia  earthquake            7.30   \n",
       "3                    60 km NE of Valmy, Nevada  earthquake             NaN   \n",
       "4            170 km SSE of Vilyuchinsk, Russia  earthquake            6.76   \n",
       "...                                        ...         ...             ...   \n",
       "2658  40 km NNE of San Pedro de Atacama, Chile  earthquake            7.46   \n",
       "2659                 17 km ENE of Ocotillo, CA  earthquake            0.20   \n",
       "2660           128 km S of Taliwang, Indonesia  earthquake            8.08   \n",
       "2661                191 km SSE of Adak, Alaska  earthquake            3.57   \n",
       "2662               southern Mid-Atlantic Ridge  earthquake            8.85   \n",
       "\n",
       "     depthError  magError  magNst     status  locationSource magSource  \n",
       "0         0.300       NaN     NaN  automatic              ak        ak  \n",
       "1         3.200       NaN     NaN  automatic              ak        ak  \n",
       "2         1.883     0.069    61.0   reviewed              us        us  \n",
       "3         3.300     0.260    12.0   reviewed              nn        nn  \n",
       "4         1.859     0.043   175.0   reviewed              us        us  \n",
       "...         ...       ...     ...        ...             ...       ...  \n",
       "2658      5.557     0.138    15.0   reviewed              us        us  \n",
       "2659      0.640     0.121   131.0   reviewed              ci        ci  \n",
       "2660      5.198     0.174     9.0   reviewed              us        us  \n",
       "2661      2.019     0.105    12.0   reviewed              us        us  \n",
       "2662      1.934     0.145    14.0   reviewed              us        us  \n",
       "\n",
       "[2663 rows x 22 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# inspect our dataframe\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2663 entries, 0 to 2662\n",
      "Data columns (total 22 columns):\n",
      " #   Column           Non-Null Count  Dtype  \n",
      "---  ------           --------------  -----  \n",
      " 0   time             2663 non-null   object \n",
      " 1   latitude         2663 non-null   float64\n",
      " 2   longitude        2663 non-null   float64\n",
      " 3   depth            2663 non-null   float64\n",
      " 4   mag              2663 non-null   float64\n",
      " 5   magType          2663 non-null   object \n",
      " 6   nst              2498 non-null   float64\n",
      " 7   gap              2496 non-null   float64\n",
      " 8   dmin             2496 non-null   float64\n",
      " 9   rms              2662 non-null   float64\n",
      " 10  net              2663 non-null   object \n",
      " 11  id               2663 non-null   object \n",
      " 12  updated          2663 non-null   object \n",
      " 13  place            2663 non-null   object \n",
      " 14  type             2663 non-null   object \n",
      " 15  horizontalError  2481 non-null   float64\n",
      " 16  depthError       2662 non-null   float64\n",
      " 17  magError         2470 non-null   float64\n",
      " 18  magNst           2478 non-null   float64\n",
      " 19  status           2663 non-null   object \n",
      " 20  locationSource   2663 non-null   object \n",
      " 21  magSource        2663 non-null   object \n",
      "dtypes: float64(12), object(10)\n",
      "memory usage: 457.8+ KB\n"
     ]
    }
   ],
   "source": [
    "# instead of looking at the whole table, lets see an overview of the information we have \n",
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see that the column 'time' has been recognized as a generic object, instead of a date. Let's fix that by telling Pandas which column to interpret as a date type. The list above tells us that the date is the 0th column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('global_30day_earthquakes.csv', parse_dates=[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When we run `df.info()` again, we can see that time is now a datetime64 type. We can also see that the datetime units are nanoseconds, and that it is UTC time. One of the best features of Pandas is the ease with which it can handle and interpret dates."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2663 entries, 0 to 2662\n",
      "Data columns (total 22 columns):\n",
      " #   Column           Non-Null Count  Dtype              \n",
      "---  ------           --------------  -----              \n",
      " 0   time             2663 non-null   datetime64[ns, UTC]\n",
      " 1   latitude         2663 non-null   float64            \n",
      " 2   longitude        2663 non-null   float64            \n",
      " 3   depth            2663 non-null   float64            \n",
      " 4   mag              2663 non-null   float64            \n",
      " 5   magType          2663 non-null   object             \n",
      " 6   nst              2498 non-null   float64            \n",
      " 7   gap              2496 non-null   float64            \n",
      " 8   dmin             2496 non-null   float64            \n",
      " 9   rms              2662 non-null   float64            \n",
      " 10  net              2663 non-null   object             \n",
      " 11  id               2663 non-null   object             \n",
      " 12  updated          2663 non-null   object             \n",
      " 13  place            2663 non-null   object             \n",
      " 14  type             2663 non-null   object             \n",
      " 15  horizontalError  2481 non-null   float64            \n",
      " 16  depthError       2662 non-null   float64            \n",
      " 17  magError         2470 non-null   float64            \n",
      " 18  magNst           2478 non-null   float64            \n",
      " 19  status           2663 non-null   object             \n",
      " 20  locationSource   2663 non-null   object             \n",
      " 21  magSource        2663 non-null   object             \n",
      "dtypes: datetime64[ns, UTC](1), float64(12), object(9)\n",
      "memory usage: 457.8+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can inspect the first few entries with `df.head()`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>time</th>\n",
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       "      <th>type</th>\n",
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       "      <th>depthError</th>\n",
       "      <th>magError</th>\n",
       "      <th>magNst</th>\n",
       "      <th>status</th>\n",
       "      <th>locationSource</th>\n",
       "      <th>magSource</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2025-08-12 00:30:58.784000+00:00</td>\n",
       "      <td>62.0080</td>\n",
       "      <td>-145.5334</td>\n",
       "      <td>9.8</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.8700</td>\n",
       "      <td>...</td>\n",
       "      <td>2025-08-12T00:37:39.629Z</td>\n",
       "      <td>7 km SW of Copperville, Alaska</td>\n",
       "      <td>earthquake</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.300</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>1</th>\n",
       "      <td>2025-08-12 00:30:53.834000+00:00</td>\n",
       "      <td>61.7409</td>\n",
       "      <td>-146.0972</td>\n",
       "      <td>42.4</td>\n",
       "      <td>2.6</td>\n",
       "      <td>ml</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.5700</td>\n",
       "      <td>...</td>\n",
       "      <td>2025-08-12T00:35:35.397Z</td>\n",
       "      <td>38 km S of Tolsona, Alaska</td>\n",
       "      <td>earthquake</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.200</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>2</th>\n",
       "      <td>2025-08-11 23:45:41.896000+00:00</td>\n",
       "      <td>51.1937</td>\n",
       "      <td>160.8599</td>\n",
       "      <td>10.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>mb</td>\n",
       "      <td>25.0</td>\n",
       "      <td>135.00</td>\n",
       "      <td>2.283</td>\n",
       "      <td>0.4400</td>\n",
       "      <td>...</td>\n",
       "      <td>2025-08-12T00:10:36.040Z</td>\n",
       "      <td>256 km SE of Vilyuchinsk, Russia</td>\n",
       "      <td>earthquake</td>\n",
       "      <td>7.30</td>\n",
       "      <td>1.883</td>\n",
       "      <td>0.069</td>\n",
       "      <td>61.0</td>\n",
       "      <td>reviewed</td>\n",
       "      <td>us</td>\n",
       "      <td>us</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2025-08-11 21:24:31.503000+00:00</td>\n",
       "      <td>41.2421</td>\n",
       "      <td>-116.7149</td>\n",
       "      <td>6.3</td>\n",
       "      <td>2.9</td>\n",
       "      <td>ml</td>\n",
       "      <td>14.0</td>\n",
       "      <td>144.57</td>\n",
       "      <td>0.342</td>\n",
       "      <td>0.1627</td>\n",
       "      <td>...</td>\n",
       "      <td>2025-08-11T22:14:22.638Z</td>\n",
       "      <td>60 km NE of Valmy, Nevada</td>\n",
       "      <td>earthquake</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.300</td>\n",
       "      <td>0.260</td>\n",
       "      <td>12.0</td>\n",
       "      <td>reviewed</td>\n",
       "      <td>nn</td>\n",
       "      <td>nn</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2025-08-11 21:02:42.456000+00:00</td>\n",
       "      <td>51.6515</td>\n",
       "      <td>159.7787</td>\n",
       "      <td>35.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>mb</td>\n",
       "      <td>61.0</td>\n",
       "      <td>106.00</td>\n",
       "      <td>1.539</td>\n",
       "      <td>0.6000</td>\n",
       "      <td>...</td>\n",
       "      <td>2025-08-12T00:35:51.040Z</td>\n",
       "      <td>170 km SSE of Vilyuchinsk, Russia</td>\n",
       "      <td>earthquake</td>\n",
       "      <td>6.76</td>\n",
       "      <td>1.859</td>\n",
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       "<p>5 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                              time  latitude  longitude  depth  mag magType  \\\n",
       "0 2025-08-12 00:30:58.784000+00:00   62.0080  -145.5334    9.8  2.6      ml   \n",
       "1 2025-08-12 00:30:53.834000+00:00   61.7409  -146.0972   42.4  2.6      ml   \n",
       "2 2025-08-11 23:45:41.896000+00:00   51.1937   160.8599   10.0  4.5      mb   \n",
       "3 2025-08-11 21:24:31.503000+00:00   41.2421  -116.7149    6.3  2.9      ml   \n",
       "4 2025-08-11 21:02:42.456000+00:00   51.6515   159.7787   35.0  5.0      mb   \n",
       "\n",
       "    nst     gap   dmin     rms  ...                   updated  \\\n",
       "0   NaN     NaN    NaN  0.8700  ...  2025-08-12T00:37:39.629Z   \n",
       "1   NaN     NaN    NaN  0.5700  ...  2025-08-12T00:35:35.397Z   \n",
       "2  25.0  135.00  2.283  0.4400  ...  2025-08-12T00:10:36.040Z   \n",
       "3  14.0  144.57  0.342  0.1627  ...  2025-08-11T22:14:22.638Z   \n",
       "4  61.0  106.00  1.539  0.6000  ...  2025-08-12T00:35:51.040Z   \n",
       "\n",
       "                               place        type horizontalError depthError  \\\n",
       "0     7 km SW of Copperville, Alaska  earthquake             NaN      0.300   \n",
       "1         38 km S of Tolsona, Alaska  earthquake             NaN      3.200   \n",
       "2   256 km SE of Vilyuchinsk, Russia  earthquake            7.30      1.883   \n",
       "3          60 km NE of Valmy, Nevada  earthquake             NaN      3.300   \n",
       "4  170 km SSE of Vilyuchinsk, Russia  earthquake            6.76      1.859   \n",
       "\n",
       "   magError  magNst     status  locationSource magSource  \n",
       "0       NaN     NaN  automatic              ak        ak  \n",
       "1       NaN     NaN  automatic              ak        ak  \n",
       "2     0.069    61.0   reviewed              us        us  \n",
       "3     0.260    12.0   reviewed              nn        nn  \n",
       "4     0.043   175.0   reviewed              us        us  \n",
       "\n",
       "[5 rows x 22 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see above that each entry gets a generic row index of 0, 1, 2,... That isn't particularly useful for our analysis since the indices don't mean anything physical. Let's change that by telling Pandas which column to use as the index. In this case we will use the earthquake ID. These are unique alphanumeric strings assigned by USGS to each earthquake."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr>\n",
       "      <th>ak025aagkam9</th>\n",
       "      <td>2025-08-12 00:30:58.784000+00:00</td>\n",
       "      <td>62.0080</td>\n",
       "      <td>-145.5334</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>2025-08-12T00:37:39.629Z</td>\n",
       "      <td>7 km SW of Copperville, Alaska</td>\n",
       "      <td>earthquake</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.300</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>61.7409</td>\n",
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       "      <td>2025-08-12T00:35:35.397Z</td>\n",
       "      <td>38 km S of Tolsona, Alaska</td>\n",
       "      <td>earthquake</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.200</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>ak</td>\n",
       "      <td>ak</td>\n",
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       "    <tr>\n",
       "      <th>us6000qzzz</th>\n",
       "      <td>2025-08-11 23:45:41.896000+00:00</td>\n",
       "      <td>51.1937</td>\n",
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       "      <td>2025-08-12T00:10:36.040Z</td>\n",
       "      <td>256 km SE of Vilyuchinsk, Russia</td>\n",
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       "      <td>1.883</td>\n",
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       "      <th>nn00902440</th>\n",
       "      <td>2025-08-11 21:24:31.503000+00:00</td>\n",
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       "      <td>0.342</td>\n",
       "      <td>0.1627</td>\n",
       "      <td>...</td>\n",
       "      <td>2025-08-11T22:14:22.638Z</td>\n",
       "      <td>60 km NE of Valmy, Nevada</td>\n",
       "      <td>earthquake</td>\n",
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       "      <td>...</td>\n",
       "      <td>2025-08-12T00:35:51.040Z</td>\n",
       "      <td>170 km SSE of Vilyuchinsk, Russia</td>\n",
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       "      <td>6.76</td>\n",
       "      <td>1.859</td>\n",
       "      <td>0.043</td>\n",
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      ],
      "text/plain": [
       "                                         time  latitude  longitude  depth  \\\n",
       "id                                                                          \n",
       "ak025aagkam9 2025-08-12 00:30:58.784000+00:00   62.0080  -145.5334    9.8   \n",
       "ak025aagka93 2025-08-12 00:30:53.834000+00:00   61.7409  -146.0972   42.4   \n",
       "us6000qzzz   2025-08-11 23:45:41.896000+00:00   51.1937   160.8599   10.0   \n",
       "nn00902440   2025-08-11 21:24:31.503000+00:00   41.2421  -116.7149    6.3   \n",
       "us6000qzz1   2025-08-11 21:02:42.456000+00:00   51.6515   159.7787   35.0   \n",
       "\n",
       "              mag magType   nst     gap   dmin     rms  ...  \\\n",
       "id                                                      ...   \n",
       "ak025aagkam9  2.6      ml   NaN     NaN    NaN  0.8700  ...   \n",
       "ak025aagka93  2.6      ml   NaN     NaN    NaN  0.5700  ...   \n",
       "us6000qzzz    4.5      mb  25.0  135.00  2.283  0.4400  ...   \n",
       "nn00902440    2.9      ml  14.0  144.57  0.342  0.1627  ...   \n",
       "us6000qzz1    5.0      mb  61.0  106.00  1.539  0.6000  ...   \n",
       "\n",
       "                               updated                              place  \\\n",
       "id                                                                          \n",
       "ak025aagkam9  2025-08-12T00:37:39.629Z     7 km SW of Copperville, Alaska   \n",
       "ak025aagka93  2025-08-12T00:35:35.397Z         38 km S of Tolsona, Alaska   \n",
       "us6000qzzz    2025-08-12T00:10:36.040Z   256 km SE of Vilyuchinsk, Russia   \n",
       "nn00902440    2025-08-11T22:14:22.638Z          60 km NE of Valmy, Nevada   \n",
       "us6000qzz1    2025-08-12T00:35:51.040Z  170 km SSE of Vilyuchinsk, Russia   \n",
       "\n",
       "                    type horizontalError  depthError  magError  magNst  \\\n",
       "id                                                                       \n",
       "ak025aagkam9  earthquake             NaN       0.300       NaN     NaN   \n",
       "ak025aagka93  earthquake             NaN       3.200       NaN     NaN   \n",
       "us6000qzzz    earthquake            7.30       1.883     0.069    61.0   \n",
       "nn00902440    earthquake             NaN       3.300     0.260    12.0   \n",
       "us6000qzz1    earthquake            6.76       1.859     0.043   175.0   \n",
       "\n",
       "                 status locationSource magSource  \n",
       "id                                                \n",
       "ak025aagkam9  automatic             ak        ak  \n",
       "ak025aagka93  automatic             ak        ak  \n",
       "us6000qzzz     reviewed             us        us  \n",
       "nn00902440     reviewed             nn        nn  \n",
       "us6000qzz1     reviewed             us        us  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df.set_index('id')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can investigate specific columns of the first 10 entries with the following syntax:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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>place</th>\n",
       "      <th>mag</th>\n",
       "      <th>depth</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ak025aagkam9</th>\n",
       "      <td>7 km SW of Copperville, Alaska</td>\n",
       "      <td>2.6</td>\n",
       "      <td>9.800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ak025aagka93</th>\n",
       "      <td>38 km S of Tolsona, Alaska</td>\n",
       "      <td>2.6</td>\n",
       "      <td>42.400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>us6000qzzz</th>\n",
       "      <td>256 km SE of Vilyuchinsk, Russia</td>\n",
       "      <td>4.5</td>\n",
       "      <td>10.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nn00902440</th>\n",
       "      <td>60 km NE of Valmy, Nevada</td>\n",
       "      <td>2.9</td>\n",
       "      <td>6.300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>us6000qzz1</th>\n",
       "      <td>170 km SSE of Vilyuchinsk, Russia</td>\n",
       "      <td>5.0</td>\n",
       "      <td>35.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>us6000qzyh</th>\n",
       "      <td>195 km SE of Vilyuchinsk, Russia</td>\n",
       "      <td>4.8</td>\n",
       "      <td>10.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>us6000qzvz</th>\n",
       "      <td>94 km NW of Copiapó, Chile</td>\n",
       "      <td>4.8</td>\n",
       "      <td>23.635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>us6000qzv1</th>\n",
       "      <td>southeast of the Loyalty Islands</td>\n",
       "      <td>4.8</td>\n",
       "      <td>10.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>us6000qzux</th>\n",
       "      <td>115 km SE of Attu Station, Alaska</td>\n",
       "      <td>4.2</td>\n",
       "      <td>35.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>nn00902450</th>\n",
       "      <td>55 km NE of Valmy, Nevada</td>\n",
       "      <td>2.5</td>\n",
       "      <td>11.300</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          place  mag   depth\n",
       "id                                                          \n",
       "ak025aagkam9     7 km SW of Copperville, Alaska  2.6   9.800\n",
       "ak025aagka93         38 km S of Tolsona, Alaska  2.6  42.400\n",
       "us6000qzzz     256 km SE of Vilyuchinsk, Russia  4.5  10.000\n",
       "nn00902440            60 km NE of Valmy, Nevada  2.9   6.300\n",
       "us6000qzz1    170 km SSE of Vilyuchinsk, Russia  5.0  35.000\n",
       "us6000qzyh     195 km SE of Vilyuchinsk, Russia  4.8  10.000\n",
       "us6000qzvz           94 km NW of Copiapó, Chile  4.8  23.635\n",
       "us6000qzv1     southeast of the Loyalty Islands  4.8  10.000\n",
       "us6000qzux    115 km SE of Attu Station, Alaska  4.2  35.000\n",
       "nn00902450            55 km NE of Valmy, Nevada  2.5  11.300"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[['place', 'mag','depth']].head(n=10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can grab summary statistics of our entire DataFrame using `df.describe()`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>depth</th>\n",
       "      <th>mag</th>\n",
       "      <th>nst</th>\n",
       "      <th>gap</th>\n",
       "      <th>dmin</th>\n",
       "      <th>rms</th>\n",
       "      <th>horizontalError</th>\n",
       "      <th>depthError</th>\n",
       "      <th>magError</th>\n",
       "      <th>magNst</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>2663.000000</td>\n",
       "      <td>2663.000000</td>\n",
       "      <td>2663.000000</td>\n",
       "      <td>2663.000000</td>\n",
       "      <td>2498.000000</td>\n",
       "      <td>2496.000000</td>\n",
       "      <td>2496.000000</td>\n",
       "      <td>2662.000000</td>\n",
       "      <td>2481.000000</td>\n",
       "      <td>2662.000000</td>\n",
       "      <td>2470.000000</td>\n",
       "      <td>2478.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>35.686975</td>\n",
       "      <td>24.620066</td>\n",
       "      <td>44.237501</td>\n",
       "      <td>4.140421</td>\n",
       "      <td>51.969976</td>\n",
       "      <td>138.648778</td>\n",
       "      <td>1.958450</td>\n",
       "      <td>0.735855</td>\n",
       "      <td>7.573879</td>\n",
       "      <td>4.463947</td>\n",
       "      <td>0.093915</td>\n",
       "      <td>86.439871</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>28.067148</td>\n",
       "      <td>142.590874</td>\n",
       "      <td>83.846288</td>\n",
       "      <td>0.893920</td>\n",
       "      <td>39.714453</td>\n",
       "      <td>59.363062</td>\n",
       "      <td>2.873961</td>\n",
       "      <td>0.294644</td>\n",
       "      <td>3.474638</td>\n",
       "      <td>17.009364</td>\n",
       "      <td>0.050587</td>\n",
       "      <td>141.302986</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-63.245700</td>\n",
       "      <td>-179.983200</td>\n",
       "      <td>-2.360000</td>\n",
       "      <td>2.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.050000</td>\n",
       "      <td>0.080000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001186</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>19.406700</td>\n",
       "      <td>-149.969300</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>3.300000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>101.000000</td>\n",
       "      <td>0.527750</td>\n",
       "      <td>0.560000</td>\n",
       "      <td>5.440000</td>\n",
       "      <td>1.869000</td>\n",
       "      <td>0.056000</td>\n",
       "      <td>15.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>51.341200</td>\n",
       "      <td>120.729800</td>\n",
       "      <td>17.413000</td>\n",
       "      <td>4.400000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>131.000000</td>\n",
       "      <td>1.351000</td>\n",
       "      <td>0.730000</td>\n",
       "      <td>7.970000</td>\n",
       "      <td>1.961000</td>\n",
       "      <td>0.088000</td>\n",
       "      <td>30.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>52.897450</td>\n",
       "      <td>159.673300</td>\n",
       "      <td>35.000000</td>\n",
       "      <td>4.700000</td>\n",
       "      <td>68.000000</td>\n",
       "      <td>184.000000</td>\n",
       "      <td>2.246000</td>\n",
       "      <td>0.930000</td>\n",
       "      <td>9.850000</td>\n",
       "      <td>6.337750</td>\n",
       "      <td>0.121000</td>\n",
       "      <td>88.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>83.270300</td>\n",
       "      <td>179.909500</td>\n",
       "      <td>638.859000</td>\n",
       "      <td>8.800000</td>\n",
       "      <td>338.000000</td>\n",
       "      <td>352.000000</td>\n",
       "      <td>33.879000</td>\n",
       "      <td>2.340000</td>\n",
       "      <td>22.620000</td>\n",
       "      <td>850.600000</td>\n",
       "      <td>0.371000</td>\n",
       "      <td>1144.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          latitude    longitude        depth          mag          nst  \\\n",
       "count  2663.000000  2663.000000  2663.000000  2663.000000  2498.000000   \n",
       "mean     35.686975    24.620066    44.237501     4.140421    51.969976   \n",
       "std      28.067148   142.590874    83.846288     0.893920    39.714453   \n",
       "min     -63.245700  -179.983200    -2.360000     2.500000     0.000000   \n",
       "25%      19.406700  -149.969300    10.000000     3.300000    24.000000   \n",
       "50%      51.341200   120.729800    17.413000     4.400000    40.000000   \n",
       "75%      52.897450   159.673300    35.000000     4.700000    68.000000   \n",
       "max      83.270300   179.909500   638.859000     8.800000   338.000000   \n",
       "\n",
       "               gap         dmin          rms  horizontalError   depthError  \\\n",
       "count  2496.000000  2496.000000  2662.000000      2481.000000  2662.000000   \n",
       "mean    138.648778     1.958450     0.735855         7.573879     4.463947   \n",
       "std      59.363062     2.873961     0.294644         3.474638    17.009364   \n",
       "min      12.000000     0.000000     0.050000         0.080000     0.000000   \n",
       "25%     101.000000     0.527750     0.560000         5.440000     1.869000   \n",
       "50%     131.000000     1.351000     0.730000         7.970000     1.961000   \n",
       "75%     184.000000     2.246000     0.930000         9.850000     6.337750   \n",
       "max     352.000000    33.879000     2.340000        22.620000   850.600000   \n",
       "\n",
       "          magError       magNst  \n",
       "count  2470.000000  2478.000000  \n",
       "mean      0.093915    86.439871  \n",
       "std       0.050587   141.302986  \n",
       "min       0.001186     2.000000  \n",
       "25%       0.056000    15.000000  \n",
       "50%       0.088000    30.000000  \n",
       "75%       0.121000    88.000000  \n",
       "max       0.371000  1144.000000  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Looks like the largeset earthquake in the last 30 days was an 8.8 (see column `mag`, row `max`), and the average earthquake size was 4.1 with a standard deviation of 0.89. We can use features like `nlargest` to quickly sort through our data. If we use `nlargest` on `mag` we can find the n largest earthquakes. Let's do 20."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id\n",
       "us6000qw60    8.8\n",
       "us7000qdyl    7.4\n",
       "us7000qd1y    7.3\n",
       "us6000qvsf    7.0\n",
       "us6000qw6q    6.9\n",
       "us6000qxt4    6.8\n",
       "us7000qcik    6.7\n",
       "us6000qw1a    6.6\n",
       "us6000quy1    6.6\n",
       "us7000qdz2    6.6\n",
       "us7000qdyw    6.6\n",
       "us7000qdye    6.6\n",
       "us6000qvpp    6.5\n",
       "us6000qxsv    6.4\n",
       "us6000qwiq    6.4\n",
       "us6000qugg    6.3\n",
       "us6000qxzw    6.2\n",
       "us6000qwuh    6.2\n",
       "us6000qw6s    6.2\n",
       "us6000qvbw    6.2\n",
       "Name: mag, dtype: float64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.mag.nlargest(n=20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's look at some of the more interesting details, like where are these earthquakes happening? We can see there is a column called `place`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id\n",
       "ak025aagkam9       7 km SW of Copperville, Alaska\n",
       "ak025aagka93           38 km S of Tolsona, Alaska\n",
       "us6000qzzz       256 km SE of Vilyuchinsk, Russia\n",
       "nn00902440              60 km NE of Valmy, Nevada\n",
       "us6000qzz1      170 km SSE of Vilyuchinsk, Russia\n",
       "Name: place, dtype: object"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['place'].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It looks like the `place` descriptor has lots of extra text. We want something more concise so that we can categorize the earthquakes by larger areas (e.g., Alaska). Let's create a new column, called `loc` where we take just the last phrase in the `place` descriptor. \n",
    "\n",
    "The next step is a little nuanced, because you have to use a regex (regular expression) pattern to find what we are looking for. [Regex](https://www.w3schools.com/python/python_regex.asp) is a powerful tool for parsing text and matching strings of various formats. We won't teach it here, because ChatGPT is very good at generating regex patterns to find exactly what you need. The pattern used here will isolate the text after the comma in the `place` descriptor. If there isn't a comma, then we will take the whole string."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                          place     loc\n",
      "id                                                     \n",
      "ak025aagkam9     7 km SW of Copperville, Alaska  Alaska\n",
      "ak025aagka93         38 km S of Tolsona, Alaska  Alaska\n",
      "us6000qzzz     256 km SE of Vilyuchinsk, Russia  Russia\n",
      "nn00902440            60 km NE of Valmy, Nevada  Nevada\n",
      "us6000qzz1    170 km SSE of Vilyuchinsk, Russia  Russia\n"
     ]
    }
   ],
   "source": [
    "# We'll try to get the last comma-separated part of the `place`, or the whole string if there is no comma\n",
    "df['loc'] = df['place'].str.extract(r'(?:,\\s*)([^,]+)$')\n",
    "\n",
    "# If there are entires without a comma (like \"Fiji region\"), fill them with the original value\n",
    "df['loc'] = df['loc'].fillna(df['place'])\n",
    "\n",
    "# compare what we had in 'place' with what we have in 'loc'\n",
    "print(df[['place', 'loc']].head())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There could be many earthquakes in the same country, and none in another. Let's look at a list of the unique values in the `loc` column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Alaska', 'Russia', 'Nevada', 'Chile',\n",
       "       'southeast of the Loyalty Islands', 'Mexico', 'Turkey',\n",
       "       'New Zealand', 'Vanuatu', 'Peru', 'CA', 'Tonga',\n",
       "       'south of the Kermadec Islands', 'Philippines', 'Indonesia',\n",
       "       'Timor Leste', 'Colombia', 'Sea of Okhotsk', 'Guam', 'Guatemala',\n",
       "       'Washington', 'south of the Fiji Islands', 'Wyoming',\n",
       "       'Dominican Republic', 'Taiwan', 'Canada', 'Puerto Rico',\n",
       "       'western Indian-Antarctic Ridge', 'central Mid-Atlantic Ridge',\n",
       "       'Burma (Myanmar)', 'Arizona', 'Macquarie Island region',\n",
       "       'Azerbaijan', 'Indiana', 'Ethiopia', 'Chagos Archipelago region',\n",
       "       'Argentina', 'Japan', 'Papua New Guinea', 'Tanzania',\n",
       "       'Japan region', 'Uzbekistan', 'Oregon', 'Hawaii', 'Afghanistan',\n",
       "       'Fiji', 'Tajikistan', 'California', 'U.S. Virgin Islands', 'Texas',\n",
       "       'Greece', 'Solomon Islands', 'Reykjanes Ridge', 'West Chile Rise',\n",
       "       'southern Mid-Atlantic Ridge', 'New Mexico', 'Banda Sea',\n",
       "       'New Jersey', 'Kansas', 'Kyrgyzstan', 'Saint Eustatius and Saba ',\n",
       "       'east of the Kuril Islands', 'Iran', 'Bouvet Island region', 'MX',\n",
       "       'Haiti', 'Fiji region', 'Nicaragua', 'El Salvador', 'Brazil',\n",
       "       'Pacific-Antarctic Ridge', 'China', 'Pakistan', 'Portugal',\n",
       "       'Venezuela', 'Costa Rica', 'Arkansas', 'Gulf of Alaska',\n",
       "       'northern Mid-Atlantic Ridge', 'South Sandwich Islands region',\n",
       "       'Montana', 'Saudi Arabia', 'Russia Earthquake', 'India',\n",
       "       'Mariana Islands region', 'Mauritius - Reunion region', 'Idaho',\n",
       "       'Burundi', 'Ecuador', 'Djibouti', 'Iceland', 'India region',\n",
       "       'Northern Mariana Islands', 'east of the South Sandwich Islands',\n",
       "       'Kermadec Islands region', 'Bolivia', 'west of Macquarie Island',\n",
       "       'Antigua and Barbuda', 'New Caledonia',\n",
       "       'Azores-Cape St. Vincent Ridge', 'Wallis and Futuna', 'Oklahoma',\n",
       "       'Scotia Sea', 'Kazakhstan', 'Yemen', 'Madagascar',\n",
       "       'Easter Island region', 'Falkland Islands region',\n",
       "       'Balleny Islands region', 'southeast of Easter Island',\n",
       "       'North Pacific Ocean', 'north of Ascension Island',\n",
       "       'Iceland region', 'Anguilla', 'Malaysia', 'New Zealand region',\n",
       "       'northern East Pacific Rise', 'off the coast of Oregon',\n",
       "       'Owen Fracture Zone region', 'Carlsberg Ridge',\n",
       "       'east of the North Island of New Zealand', 'south of Tonga',\n",
       "       'Alaska Earthquake', 'Kuril Islands',\n",
       "       'near the north coast of Greenland', 'Mauritius', 'Panama',\n",
       "       'central East Pacific Rise', 'Spain'], dtype=object)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['loc'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Maybe we are only interested in larger earthquakes that are more likely to be felt. We can create a new DataFrame that only contains earthquakes larger than 4.0."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_mag4 = df[df['mag'] >= 4.0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we can start plotting. Pandas and matplotlib work well together to naturally generate plots that have nicely labeled axes. You will have to define the details of the plots, but Pandas makes it very easy to subset/select data by different columns, date ranges, etc. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **Plot Top 5 Most Earthquakes by Location**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt \n",
    "\n",
    "# count how many earthquakes per country\n",
    "counts = df_mag4['loc'].value_counts()\n",
    "\n",
    "# take the top 5\n",
    "top5 = counts.head(n=5)\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(8,5))\n",
    "top5.plot(kind='bar',color='skyblue')\n",
    "ax.set_title('Top 5 locations with most earthquakes')\n",
    "ax.set_xlabel('Location')\n",
    "ax.set_ylabel('Number of Earthquakes')\n",
    "ax.tick_params(axis=\"x\", rotation=45)\n",
    "\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **Plot a Histogram of Earthquake Magnitudes**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(8,5))\n",
    "ax.hist(df_mag4['mag'],bins=20,color='orange',edgecolor='black')\n",
    "ax.set_title('Distribution of earthquakes >= 4.0')\n",
    "ax.set_xlabel('Magnitude')\n",
    "ax.set_ylabel('Count')\n",
    "ax.grid(axis='y',linestyle='--')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **Plot a Histogram From Both Datasets with Log Axis**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1,2,figsize=(10,5))\n",
    "\n",
    "ax[0].hist(df['mag'],bins=20,color='skyblue',edgecolor='black')\n",
    "ax[0].set_title('Distribution of earthquakes')\n",
    "ax[0].set_xlabel('Magnitude')\n",
    "ax[0].set_ylabel('Count')\n",
    "ax[0].grid(axis='y',linestyle='--')\n",
    "ax[0].set_yscale('log')\n",
    "\n",
    "ax[1].hist(df_mag4['mag'],bins=20,color='orange',edgecolor='black')\n",
    "ax[1].set_title('Distribution of earthquakes >= 4.0')\n",
    "ax[1].set_xlabel('Magnitude')\n",
    "ax[1].set_ylabel('Count')\n",
    "ax[1].grid(axis='y',linestyle='--')\n",
    "ax[1].set_yscale('log')\n",
    "\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **Scatter Plot of Earthquake Locations**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(8,5))\n",
    "\n",
    "ax.scatter(df['longitude'],df['latitude'],s=10, alpha=0.6,c='red',edgecolors='black')\n",
    "ax.set_xlabel('longitude')\n",
    "ax.set_ylabel('latitude')\n",
    "ax.grid(True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **Add a Map to Scatter with Cartopy**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import cartopy.crs as ccrs\n",
    "import cartopy.feature as cfeature\n",
    "\n",
    "# Create a GeoAxes with PlateCarree projection (standard lat/lon)\n",
    "fig = plt.figure(figsize=(12,10))\n",
    "ax = plt.axes(projection=ccrs.PlateCarree())\n",
    "\n",
    "# Add coastlines and land features\n",
    "ax.coastlines(resolution='110m')\n",
    "ax.add_feature(cfeature.LAND, facecolor='lightgray')\n",
    "ax.add_feature(cfeature.OCEAN, facecolor='lightblue')\n",
    "\n",
    "# Scatter earthquake points\n",
    "ax.scatter(df['longitude'], df['latitude'], s=10, c='red', alpha=0.6,\n",
    "           edgecolors='k', linewidth=0.3, transform=ccrs.PlateCarree())\n",
    "\n",
    "# Add gridlines with labels\n",
    "gl = ax.gridlines(draw_labels=True, linewidth=0.5, color='gray', alpha=0.5, linestyle='--')\n",
    "gl.top_labels = False\n",
    "gl.right_labels = False\n",
    "\n",
    "ax.set_title('Earthquake Locations with Coastlines')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exercises\n",
    "\n",
    "1) Update the scatter plot, such that the color of each dot reflects the magnitude of the earthquake.\n",
    "\n",
    "2) Same idea as option (1), but make the size of each dot reflect the magnitude of the earthquake.\n",
    "\n",
    "3) Create a new table that only contains earthquakes from Russia. Investigate the distribution of earthquake magnitudes in Russia in the last 30 days. Plot just the relevant region, and include some coloring or sizing of the scatter to highlight the biggest earthquakes."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Content for this tutorial was inspired by following an assignment from the Earth and Environmental Science Databook. The assignment can be found [here](https://earth-env-data-science.github.io/assignments/basic_pandas.html)."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "sio_software",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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