{
    "cells": [
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "# Earthquakes"
            ]
        },
        {
            "attachments": {},
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "For this problem, we will be using the earthquakes dataset from the last lesson."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 1,
            "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>id</th>\n",
                            "      <th>year</th>\n",
                            "      <th>month</th>\n",
                            "      <th>day</th>\n",
                            "      <th>latitude</th>\n",
                            "      <th>longitude</th>\n",
                            "      <th>name</th>\n",
                            "      <th>magnitude</th>\n",
                            "    </tr>\n",
                            "  </thead>\n",
                            "  <tbody>\n",
                            "    <tr>\n",
                            "      <th>0</th>\n",
                            "      <td>nc72666881</td>\n",
                            "      <td>2016</td>\n",
                            "      <td>7</td>\n",
                            "      <td>27</td>\n",
                            "      <td>37.672333</td>\n",
                            "      <td>-121.619000</td>\n",
                            "      <td>California</td>\n",
                            "      <td>1.43</td>\n",
                            "    </tr>\n",
                            "    <tr>\n",
                            "      <th>1</th>\n",
                            "      <td>us20006i0y</td>\n",
                            "      <td>2016</td>\n",
                            "      <td>7</td>\n",
                            "      <td>27</td>\n",
                            "      <td>21.514600</td>\n",
                            "      <td>94.572100</td>\n",
                            "      <td>Burma</td>\n",
                            "      <td>4.90</td>\n",
                            "    </tr>\n",
                            "    <tr>\n",
                            "      <th>2</th>\n",
                            "      <td>nc72666891</td>\n",
                            "      <td>2016</td>\n",
                            "      <td>7</td>\n",
                            "      <td>27</td>\n",
                            "      <td>37.576500</td>\n",
                            "      <td>-118.859167</td>\n",
                            "      <td>California</td>\n",
                            "      <td>0.06</td>\n",
                            "    </tr>\n",
                            "    <tr>\n",
                            "      <th>3</th>\n",
                            "      <td>nc72666896</td>\n",
                            "      <td>2016</td>\n",
                            "      <td>7</td>\n",
                            "      <td>27</td>\n",
                            "      <td>37.595833</td>\n",
                            "      <td>-118.994833</td>\n",
                            "      <td>California</td>\n",
                            "      <td>0.40</td>\n",
                            "    </tr>\n",
                            "    <tr>\n",
                            "      <th>4</th>\n",
                            "      <td>nn00553447</td>\n",
                            "      <td>2016</td>\n",
                            "      <td>7</td>\n",
                            "      <td>27</td>\n",
                            "      <td>39.377500</td>\n",
                            "      <td>-119.845000</td>\n",
                            "      <td>Nevada</td>\n",
                            "      <td>0.30</td>\n",
                            "    </tr>\n",
                            "  </tbody>\n",
                            "</table>\n",
                            "</div>"
                        ],
                        "text/plain": [
                            "           id  year  month  day   latitude   longitude        name  magnitude\n",
                            "0  nc72666881  2016      7   27  37.672333 -121.619000  California       1.43\n",
                            "1  us20006i0y  2016      7   27  21.514600   94.572100       Burma       4.90\n",
                            "2  nc72666891  2016      7   27  37.576500 -118.859167  California       0.06\n",
                            "3  nc72666896  2016      7   27  37.595833 -118.994833  California       0.40\n",
                            "4  nn00553447  2016      7   27  39.377500 -119.845000      Nevada       0.30"
                        ]
                    },
                    "execution_count": 1,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "import pandas as pd\n",
                "\n",
                "# Make sure to update this to the correct file path!\n",
                "df = pd.read_csv('earthquakes.csv')\n",
                "df.head() # Method to only display the first few rows"
            ]
        },
        {
            "attachments": {},
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "# Problem 1\n",
                "Compute the average magnitude of all the earthquakes in the dataset. Your result should be a `float`."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 4,
            "metadata": {},
            "outputs": [
                {
                    "data": {
                        "text/plain": [
                            "np.float64(1.512941386704789)"
                        ]
                    },
                    "execution_count": 4,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "# Your answer here!"
            ]
        },
        {
            "attachments": {},
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "# Problem 2\n",
                "Compute the number of earthquakes that have a magnitude greater than or equal to the average magnitude earthquake. `DataFrames` also support the `len` function to tell you the number of rows in it. Your result should be an `int`.\n"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 0,
            "metadata": {},
            "outputs": [],
            "source": [
                "# Your answer here!"
            ]
        },
        {
            "attachments": {},
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "# Problem 3\n",
                "Find the subset of all the earthquakes that happened on the 8th day of the month in either Tonga or Papua New Guinea. Your result should be a `DataFrame`."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 5,
            "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>id</th>\n",
                            "      <th>year</th>\n",
                            "      <th>month</th>\n",
                            "      <th>day</th>\n",
                            "      <th>latitude</th>\n",
                            "      <th>longitude</th>\n",
                            "      <th>name</th>\n",
                            "      <th>magnitude</th>\n",
                            "    </tr>\n",
                            "  </thead>\n",
                            "  <tbody>\n",
                            "    <tr>\n",
                            "      <th>3877</th>\n",
                            "      <td>us10006cwy</td>\n",
                            "      <td>2016</td>\n",
                            "      <td>8</td>\n",
                            "      <td>8</td>\n",
                            "      <td>-4.6796</td>\n",
                            "      <td>155.2703</td>\n",
                            "      <td>Papua New Guinea</td>\n",
                            "      <td>4.3</td>\n",
                            "    </tr>\n",
                            "    <tr>\n",
                            "      <th>3897</th>\n",
                            "      <td>us10006cx0</td>\n",
                            "      <td>2016</td>\n",
                            "      <td>8</td>\n",
                            "      <td>8</td>\n",
                            "      <td>-4.2667</td>\n",
                            "      <td>153.6873</td>\n",
                            "      <td>Papua New Guinea</td>\n",
                            "      <td>4.1</td>\n",
                            "    </tr>\n",
                            "    <tr>\n",
                            "      <th>4012</th>\n",
                            "      <td>us10006cxc</td>\n",
                            "      <td>2016</td>\n",
                            "      <td>8</td>\n",
                            "      <td>8</td>\n",
                            "      <td>-23.3895</td>\n",
                            "      <td>-175.0769</td>\n",
                            "      <td>Tonga</td>\n",
                            "      <td>4.6</td>\n",
                            "    </tr>\n",
                            "    <tr>\n",
                            "      <th>4036</th>\n",
                            "      <td>us10006cxf</td>\n",
                            "      <td>2016</td>\n",
                            "      <td>8</td>\n",
                            "      <td>8</td>\n",
                            "      <td>-4.4296</td>\n",
                            "      <td>151.9396</td>\n",
                            "      <td>Papua New Guinea</td>\n",
                            "      <td>4.4</td>\n",
                            "    </tr>\n",
                            "  </tbody>\n",
                            "</table>\n",
                            "</div>"
                        ],
                        "text/plain": [
                            "              id  year  month  day  latitude  longitude              name  \\\n",
                            "3877  us10006cwy  2016      8    8   -4.6796   155.2703  Papua New Guinea   \n",
                            "3897  us10006cx0  2016      8    8   -4.2667   153.6873  Papua New Guinea   \n",
                            "4012  us10006cxc  2016      8    8  -23.3895  -175.0769             Tonga   \n",
                            "4036  us10006cxf  2016      8    8   -4.4296   151.9396  Papua New Guinea   \n",
                            "\n",
                            "      magnitude  \n",
                            "3877        4.3  \n",
                            "3897        4.1  \n",
                            "4012        4.6  \n",
                            "4036        4.4  "
                        ]
                    },
                    "execution_count": 5,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "# Your answer here!"
            ]
        },
        {
            "attachments": {},
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "# Problem 4\n",
                "Find the row that corresponds to the location that has the largest earthquake on record. Your result should be a `Series` that represents that row. If there are multiple locations with the largest earthquake, you should return the first row.\n",
                "\n",
                "*Hint: It probably won't work to try to mask this by comparing magnitudes to the largest earthquake (since a mask won't necessarily only have a single value `True`). Is there a method that tells you the index of the largest value of a `Series`?*"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 0,
            "metadata": {},
            "outputs": [],
            "source": [
                "# Your answer here!"
            ]
        }
    ],
    "metadata": {
        "kernelspec": {
            "display_name": "Python 3 (ipykernel)",
            "language": "python",
            "name": "python3"
        }
    },
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    "nbformat_minor": 2
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