demo.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "48cc002a-ab39-4390-8e14-2d5e91dc78b1",
   "metadata": {},
   "source": [
    "# Demo of Data Analysis in Python\n",
    "\n",
    "This is a \"notebook\", which is a kind of file that includes code (in our case, Python) along with helpful notes written in human language, to help people understand the data analysis steps.  We create \"cells\" which can hold text like this which is meant for people (these are called \"markdown\" cells) or can hold code meant for the computer (these are called \"code\" cells).  We can add, move, or delete cells, and we can run the code in just one cell, or choose to run all the cells in order.  There are lots of ways to build notebooks and work with them!\n",
    "\n",
    "## Load Packages\n",
    "\n",
    "The first thing we have to do is load some \"packages\" or \"libraries\" (you'll hear people call them different things).  Packages are optional extras that expand what Python can do.  There are thousands of packages, and you only want to load the handful you'll actually use during an analysis.  In our case, we want to use \"pandas\" (it's traditionally abbreviated \"pd\") to work with data and the \"seaborn\" package to visualize (graph) data.  Seaborn is based on a package called \"matplotlib\", and sometimes we need to get into the guts of matplotlib to change up the appearance of our graphs, so we'll load it as well."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "bf76a6af-daf6-43cd-ae82-65df1fea5996",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "755adfa3-983b-4699-bc6f-92d323387df2",
   "metadata": {},
   "source": [
    "# Import Data\n",
    "\n",
    "We need to work with data!  In our case, we're going to work with a very common kind of data called \"csv\".  A csv file, or \"comma separated values\" file, contains information organized in rows and columns.  If you try to open a csv file by double clicking on it from your computer, it will probably open in Microsoft Excel, if you have that installed.  But there are lots of other ways to work with csv files and other data that is stored in rows and columns.  In Python, the pandas package is very good at working with data that is organized in rows and columns.\n",
    "\n",
    "I got a link to my data by using the \"API\" button on this page: https://data.cityofnewyork.us/Health/New-York-City-Leading-Causes-of-Death/jb7j-dtam.  The website I'm getting this data from is set up to only deliver 1000 rows of data by default, so I'm going to add an extra bit of text to the link (\"$limit\") to say \"give me up to ten thousand rows of data\".\n",
    "\n",
    "I'm going to use that link and ingest the data there (ingest means \"go get something and bring it into my current work\", and call that data \"nyc_death_data\", because that's a short and memorable name that describes the data.  I could also just call it \"my_data\", but that's not a good descriptor!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "226623fa-0bc1-48b5-ab5e-1830b662bf21",
   "metadata": {},
   "outputs": [],
   "source": [
    "nyc_death_data = pd.read_csv(\"https://data.cityofnewyork.us/resource/jb7j-dtam.csv?$limit=10000\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9fcefa01-60d9-43e0-8c61-e09376d26ecc",
   "metadata": {},
   "source": [
    "# Look at the Data\n",
    "\n",
    "The first thing I want to do is look around at the data, and get an idea for what it looks like.  I'll use commands from the \"pandas\" library (which we're abbreviating as \"pd\") to look at the first few rows, then the last few rows."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "72e6771b-8078-4552-b36c-690570576be2",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>leading_cause</th>\n",
       "      <th>sex</th>\n",
       "      <th>race_ethnicity</th>\n",
       "      <th>deaths</th>\n",
       "      <th>death_rate</th>\n",
       "      <th>age_adjusted_death_rate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2014</td>\n",
       "      <td>Diseases of Heart (I00-I09, I11, I13, I20-I51)</td>\n",
       "      <td>M</td>\n",
       "      <td>Other Race/ Ethnicity</td>\n",
       "      <td>63</td>\n",
       "      <td>.</td>\n",
       "      <td>.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2014</td>\n",
       "      <td>Cerebrovascular Disease (Stroke: I60-I69)</td>\n",
       "      <td>M</td>\n",
       "      <td>Hispanic</td>\n",
       "      <td>165</td>\n",
       "      <td>13.8</td>\n",
       "      <td>20.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2014</td>\n",
       "      <td>Cerebrovascular Disease (Stroke: I60-I69)</td>\n",
       "      <td>M</td>\n",
       "      <td>Other Race/ Ethnicity</td>\n",
       "      <td>7</td>\n",
       "      <td>.</td>\n",
       "      <td>.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2014</td>\n",
       "      <td>Diseases of Heart (I00-I09, I11, I13, I20-I51)</td>\n",
       "      <td>M</td>\n",
       "      <td>Hispanic</td>\n",
       "      <td>1281</td>\n",
       "      <td>107.3</td>\n",
       "      <td>170.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2014</td>\n",
       "      <td>Diseases of Heart (I00-I09, I11, I13, I20-I51)</td>\n",
       "      <td>F</td>\n",
       "      <td>Other Race/ Ethnicity</td>\n",
       "      <td>68</td>\n",
       "      <td>.</td>\n",
       "      <td>.</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   year                                   leading_cause sex  \\\n",
       "0  2014  Diseases of Heart (I00-I09, I11, I13, I20-I51)   M   \n",
       "1  2014       Cerebrovascular Disease (Stroke: I60-I69)   M   \n",
       "2  2014       Cerebrovascular Disease (Stroke: I60-I69)   M   \n",
       "3  2014  Diseases of Heart (I00-I09, I11, I13, I20-I51)   M   \n",
       "4  2014  Diseases of Heart (I00-I09, I11, I13, I20-I51)   F   \n",
       "\n",
       "          race_ethnicity deaths death_rate age_adjusted_death_rate  \n",
       "0  Other Race/ Ethnicity     63          .                       .  \n",
       "1               Hispanic    165       13.8                    20.4  \n",
       "2  Other Race/ Ethnicity      7          .                       .  \n",
       "3               Hispanic   1281      107.3                   170.5  \n",
       "4  Other Race/ Ethnicity     68          .                       .  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nyc_death_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "b9962b72-c525-41e9-8e39-37d01564f9fd",
   "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",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>leading_cause</th>\n",
       "      <th>sex</th>\n",
       "      <th>race_ethnicity</th>\n",
       "      <th>deaths</th>\n",
       "      <th>death_rate</th>\n",
       "      <th>age_adjusted_death_rate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1089</th>\n",
       "      <td>2007</td>\n",
       "      <td>Diabetes Mellitus (E10-E14)</td>\n",
       "      <td>F</td>\n",
       "      <td>Hispanic</td>\n",
       "      <td>205</td>\n",
       "      <td>17.6</td>\n",
       "      <td>22.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1090</th>\n",
       "      <td>2007</td>\n",
       "      <td>Chronic Lower Respiratory Diseases (J40-J47)</td>\n",
       "      <td>F</td>\n",
       "      <td>White Non-Hispanic</td>\n",
       "      <td>472</td>\n",
       "      <td>32.9</td>\n",
       "      <td>19.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1091</th>\n",
       "      <td>2007</td>\n",
       "      <td>Human Immunodeficiency Virus Disease (HIV: B20...</td>\n",
       "      <td>M</td>\n",
       "      <td>Hispanic</td>\n",
       "      <td>218</td>\n",
       "      <td>20</td>\n",
       "      <td>23.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1092</th>\n",
       "      <td>2007</td>\n",
       "      <td>All Other Causes</td>\n",
       "      <td>F</td>\n",
       "      <td>Not Stated/Unknown</td>\n",
       "      <td>27</td>\n",
       "      <td>.</td>\n",
       "      <td>.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1093</th>\n",
       "      <td>2007</td>\n",
       "      <td>Assault (Homicide: Y87.1, X85-Y09)</td>\n",
       "      <td>M</td>\n",
       "      <td>Other Race/ Ethnicity</td>\n",
       "      <td>.</td>\n",
       "      <td>.</td>\n",
       "      <td>.</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      year                                      leading_cause sex  \\\n",
       "1089  2007                        Diabetes Mellitus (E10-E14)   F   \n",
       "1090  2007       Chronic Lower Respiratory Diseases (J40-J47)   F   \n",
       "1091  2007  Human Immunodeficiency Virus Disease (HIV: B20...   M   \n",
       "1092  2007                                   All Other Causes   F   \n",
       "1093  2007                 Assault (Homicide: Y87.1, X85-Y09)   M   \n",
       "\n",
       "             race_ethnicity deaths death_rate age_adjusted_death_rate  \n",
       "1089               Hispanic    205       17.6                    22.6  \n",
       "1090     White Non-Hispanic    472       32.9                    19.6  \n",
       "1091               Hispanic    218         20                    23.1  \n",
       "1092     Not Stated/Unknown     27          .                       .  \n",
       "1093  Other Race/ Ethnicity      .          .                       .  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nyc_death_data.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "53607724-ac1e-49f7-ba2d-3ed54986c934",
   "metadata": {},
   "source": [
    "I can also get an idea for what values are represented in my data using the \"value_counts\" command and passing along the name of a column:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "fa84d248-0dae-4996-ba83-d83c66654fae",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "year\n",
       "2007    141\n",
       "2011    141\n",
       "2010    138\n",
       "2008    136\n",
       "2014    136\n",
       "2009    135\n",
       "2012    134\n",
       "2013    133\n",
       "dtype: int64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nyc_death_data.value_counts(\"year\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "49eaedb3-f740-479a-b927-b8a71fab7da1",
   "metadata": {},
   "source": [
    "It can be important to know what the type of data is for each column.  For example, is the \"deaths\" column an integer?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "2c5d9bd9-d64b-48a3-9d58-a03fb27ab2dc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1094 entries, 0 to 1093\n",
      "Data columns (total 7 columns):\n",
      " #   Column                   Non-Null Count  Dtype \n",
      "---  ------                   --------------  ----- \n",
      " 0   year                     1094 non-null   int64 \n",
      " 1   leading_cause            1094 non-null   object\n",
      " 2   sex                      1094 non-null   object\n",
      " 3   race_ethnicity           1094 non-null   object\n",
      " 4   deaths                   1094 non-null   object\n",
      " 5   death_rate               1094 non-null   object\n",
      " 6   age_adjusted_death_rate  1094 non-null   object\n",
      "dtypes: int64(1), object(6)\n",
      "memory usage: 60.0+ KB\n"
     ]
    }
   ],
   "source": [
    "nyc_death_data.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "374dd50f-eb33-4d37-a76e-c681af0e3059",
   "metadata": {},
   "source": [
    "Oh no!  Everything except for year is listed as an \"object\", which means it's \"string\" data (alphanumeric text).  We need to make sure that columns that contain numbers are of a data type that's numeric.  Let's do some conversion.\n",
    "\n",
    "# Clean and Prepare Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "532e4f67-f244-4934-90a2-8c8e43470a10",
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "Unable to parse string \".\" at position 20",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32mpandas/_libs/lib.pyx\u001b[0m in \u001b[0;36mpandas._libs.lib.maybe_convert_numeric\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: Unable to parse string \".\"",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-21-19ee840afabe>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mnyc_death_data\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'deaths'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mto_numeric\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnyc_death_data\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'deaths'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m~/opt/anaconda3/lib/python3.8/site-packages/pandas/core/tools/numeric.py\u001b[0m in \u001b[0;36mto_numeric\u001b[0;34m(arg, errors, downcast)\u001b[0m\n\u001b[1;32m    152\u001b[0m         \u001b[0mcoerce_numeric\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0merrors\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32min\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;34m\"ignore\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"raise\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    153\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 154\u001b[0;31m             values = lib.maybe_convert_numeric(\n\u001b[0m\u001b[1;32m    155\u001b[0m                 \u001b[0mvalues\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcoerce_numeric\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcoerce_numeric\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    156\u001b[0m             )\n",
      "\u001b[0;32mpandas/_libs/lib.pyx\u001b[0m in \u001b[0;36mpandas._libs.lib.maybe_convert_numeric\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: Unable to parse string \".\" at position 20"
     ]
    }
   ],
   "source": [
    "nyc_death_data['deaths'] = pd.to_numeric(nyc_death_data['deaths'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0ab0a441-94f1-4f21-bb58-2a5f28cf5d7b",
   "metadata": {},
   "source": [
    "Whoops, we got our first error code.  If we look at the error, it looks like maybe one of our rows has just the value \".\" in it, to mean nothing?  Or zero?  It says it's at \"position 20\".  Maybe that means row 20?  Let's peek at the \"index location\" (\"iloc\") 20!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "5b762ba9-d03d-48a0-bc7a-888f4b832573",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "year                                                                 2014\n",
       "leading_cause              Chronic Liver Disease and Cirrhosis (K70, K73)\n",
       "sex                                                                     F\n",
       "race_ethnicity                                         Not Stated/Unknown\n",
       "deaths                                                                  .\n",
       "death_rate                                                              .\n",
       "age_adjusted_death_rate                                                 .\n",
       "Name: 20, dtype: object"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nyc_death_data.iloc[20]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "539867a5-a637-48e8-82b6-873db9f3f690",
   "metadata": {},
   "source": [
    "It sure seems like \".\" is supposed to just be \"nothing\"... zero, or absent data.  Let's replace \".\" with \"NA\", which stands for \"not a number\" or \"not applicable\", which is Python-speak for a missing or null value."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "f69ae502-e732-49ee-9748-b8715c5b032b",
   "metadata": {},
   "outputs": [],
   "source": [
    "nyc_death_data = nyc_death_data.replace('.',pd.NA)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "be1fcdb6-0ee5-4f2d-961e-0471960c7aae",
   "metadata": {},
   "source": [
    "Let's try again, and see if we can convert \"deaths\" to being numeric!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "34001e25-d017-4c16-a489-8ec467a2d873",
   "metadata": {},
   "outputs": [],
   "source": [
    "nyc_death_data['deaths'] = pd.to_numeric(nyc_death_data['deaths'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a33a41b8-5d93-4711-a187-a8519fcbe122",
   "metadata": {},
   "source": [
    "No error this time!  Let's look at our data types now:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "44d62f26-d44c-487e-bcdc-ba358fef47e8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1094 entries, 0 to 1093\n",
      "Data columns (total 7 columns):\n",
      " #   Column                   Non-Null Count  Dtype  \n",
      "---  ------                   --------------  -----  \n",
      " 0   year                     1094 non-null   int64  \n",
      " 1   leading_cause            1094 non-null   object \n",
      " 2   sex                      1094 non-null   object \n",
      " 3   race_ethnicity           1094 non-null   object \n",
      " 4   deaths                   956 non-null    float64\n",
      " 5   death_rate               708 non-null    object \n",
      " 6   age_adjusted_death_rate  708 non-null    object \n",
      "dtypes: float64(1), int64(1), object(5)\n",
      "memory usage: 60.0+ KB\n"
     ]
    }
   ],
   "source": [
    "nyc_death_data.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "858010a7-e771-4826-88dc-d0b202f31a48",
   "metadata": {},
   "source": [
    "OK, great, this is a \"float\", or decimal type.  That's good enough.  We should also do a conversion to numeric type for the death rate columns."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "adedf300-8092-4ebe-b0ff-b3dbfa1337fa",
   "metadata": {},
   "outputs": [],
   "source": [
    "nyc_death_data['death_rate'] = pd.to_numeric(nyc_death_data['death_rate'])\n",
    "nyc_death_data['age_adjusted_death_rate'] = pd.to_numeric(nyc_death_data['age_adjusted_death_rate'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7d603e4f-40f8-42ed-9618-8b9f6b61ca40",
   "metadata": {},
   "source": [
    "Let's check the data type again!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "a158a6d8-fa04-42c6-a89e-753d432cf701",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1094 entries, 0 to 1093\n",
      "Data columns (total 7 columns):\n",
      " #   Column                   Non-Null Count  Dtype  \n",
      "---  ------                   --------------  -----  \n",
      " 0   year                     1094 non-null   int64  \n",
      " 1   leading_cause            1094 non-null   object \n",
      " 2   sex                      1094 non-null   object \n",
      " 3   race_ethnicity           1094 non-null   object \n",
      " 4   deaths                   956 non-null    float64\n",
      " 5   death_rate               708 non-null    float64\n",
      " 6   age_adjusted_death_rate  708 non-null    float64\n",
      "dtypes: float64(3), int64(1), object(3)\n",
      "memory usage: 60.0+ KB\n"
     ]
    },
    {
     "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>year</th>\n",
       "      <th>leading_cause</th>\n",
       "      <th>sex</th>\n",
       "      <th>race_ethnicity</th>\n",
       "      <th>deaths</th>\n",
       "      <th>death_rate</th>\n",
       "      <th>age_adjusted_death_rate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2014</td>\n",
       "      <td>Diseases of Heart (I00-I09, I11, I13, I20-I51)</td>\n",
       "      <td>M</td>\n",
       "      <td>Other Race/ Ethnicity</td>\n",
       "      <td>63.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2014</td>\n",
       "      <td>Cerebrovascular Disease (Stroke: I60-I69)</td>\n",
       "      <td>M</td>\n",
       "      <td>Hispanic</td>\n",
       "      <td>165.0</td>\n",
       "      <td>13.8</td>\n",
       "      <td>20.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2014</td>\n",
       "      <td>Cerebrovascular Disease (Stroke: I60-I69)</td>\n",
       "      <td>M</td>\n",
       "      <td>Other Race/ Ethnicity</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2014</td>\n",
       "      <td>Diseases of Heart (I00-I09, I11, I13, I20-I51)</td>\n",
       "      <td>M</td>\n",
       "      <td>Hispanic</td>\n",
       "      <td>1281.0</td>\n",
       "      <td>107.3</td>\n",
       "      <td>170.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2014</td>\n",
       "      <td>Diseases of Heart (I00-I09, I11, I13, I20-I51)</td>\n",
       "      <td>F</td>\n",
       "      <td>Other Race/ Ethnicity</td>\n",
       "      <td>68.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1089</th>\n",
       "      <td>2007</td>\n",
       "      <td>Diabetes Mellitus (E10-E14)</td>\n",
       "      <td>F</td>\n",
       "      <td>Hispanic</td>\n",
       "      <td>205.0</td>\n",
       "      <td>17.6</td>\n",
       "      <td>22.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1090</th>\n",
       "      <td>2007</td>\n",
       "      <td>Chronic Lower Respiratory Diseases (J40-J47)</td>\n",
       "      <td>F</td>\n",
       "      <td>White Non-Hispanic</td>\n",
       "      <td>472.0</td>\n",
       "      <td>32.9</td>\n",
       "      <td>19.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1091</th>\n",
       "      <td>2007</td>\n",
       "      <td>Human Immunodeficiency Virus Disease (HIV: B20...</td>\n",
       "      <td>M</td>\n",
       "      <td>Hispanic</td>\n",
       "      <td>218.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>23.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1092</th>\n",
       "      <td>2007</td>\n",
       "      <td>All Other Causes</td>\n",
       "      <td>F</td>\n",
       "      <td>Not Stated/Unknown</td>\n",
       "      <td>27.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1093</th>\n",
       "      <td>2007</td>\n",
       "      <td>Assault (Homicide: Y87.1, X85-Y09)</td>\n",
       "      <td>M</td>\n",
       "      <td>Other Race/ Ethnicity</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1094 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      year                                      leading_cause sex  \\\n",
       "0     2014     Diseases of Heart (I00-I09, I11, I13, I20-I51)   M   \n",
       "1     2014          Cerebrovascular Disease (Stroke: I60-I69)   M   \n",
       "2     2014          Cerebrovascular Disease (Stroke: I60-I69)   M   \n",
       "3     2014     Diseases of Heart (I00-I09, I11, I13, I20-I51)   M   \n",
       "4     2014     Diseases of Heart (I00-I09, I11, I13, I20-I51)   F   \n",
       "...    ...                                                ...  ..   \n",
       "1089  2007                        Diabetes Mellitus (E10-E14)   F   \n",
       "1090  2007       Chronic Lower Respiratory Diseases (J40-J47)   F   \n",
       "1091  2007  Human Immunodeficiency Virus Disease (HIV: B20...   M   \n",
       "1092  2007                                   All Other Causes   F   \n",
       "1093  2007                 Assault (Homicide: Y87.1, X85-Y09)   M   \n",
       "\n",
       "             race_ethnicity  deaths  death_rate  age_adjusted_death_rate  \n",
       "0     Other Race/ Ethnicity    63.0         NaN                      NaN  \n",
       "1                  Hispanic   165.0        13.8                     20.4  \n",
       "2     Other Race/ Ethnicity     7.0         NaN                      NaN  \n",
       "3                  Hispanic  1281.0       107.3                    170.5  \n",
       "4     Other Race/ Ethnicity    68.0         NaN                      NaN  \n",
       "...                     ...     ...         ...                      ...  \n",
       "1089               Hispanic   205.0        17.6                     22.6  \n",
       "1090     White Non-Hispanic   472.0        32.9                     19.6  \n",
       "1091               Hispanic   218.0        20.0                     23.1  \n",
       "1092     Not Stated/Unknown    27.0         NaN                      NaN  \n",
       "1093  Other Race/ Ethnicity     NaN         NaN                      NaN  \n",
       "\n",
       "[1094 rows x 7 columns]"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nyc_death_data.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9b6b4585-24bb-44f8-92f7-14d6f17b3b11",
   "metadata": {},
   "source": [
    "# Visualize The Data\n",
    "\n",
    "There are 1094 rows of data and that's a lot to consider!  Sometimes data is easier to understand if we make graphs to show the data.  There are lots of ways to create exploratory data visualizations in Python.  In this case I'm going to make a series of bar charts using the seaborn package.\n",
    "\n",
    "This is just going to be an exploratory graph.  It's not perfect, and it's not intended for publication.  It's meant for us to get a quick overview of the data in order to generate new questions!  We want to look at death rate within race/sex (presumably, per thousand people in the race/sex category) to look for disparities."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "05441235-da66-4f00-825c-5fa1641723bd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x7fe49519b760>"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x9360 with 52 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot(x = \"year\",             # x variable: year\n",
    "            y = \"death_rate\",       # y variable: death rate within sex/race\n",
    "            hue = \"race_ethnicity\", # grouped bar variable: race\n",
    "            data = nyc_death_data,  # dataframe to plot\n",
    "            row = \"leading_cause\",  # make a plot for each leading cause\n",
    "            col = \"sex\",            # and split it out by M/F\n",
    "            kind = \"bar\",           # make it a bar plot\n",
    "            legend_out = False,     # optional: show legend at the top instead of \n",
    "                                    #           way down in the middle\n",
    "            sharex = False,         # make the x axis independent (show labels!)\n",
    "            sharey = False)         # make the y axis independent (show labels!)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c55b8405-f619-4d3b-865f-a732e20271d4",
   "metadata": {},
   "source": [
    "So, this is a clunky visualization, but it gives us interesting questions.  For example, we see:\n",
    "\n",
    "* Higher rates in white people caused by heart disease and respiratory illness.\n",
    "* Higher death rates in Black people caused by renal disease and diabetes.\n",
    "* Higher death rates in males caused by homicide and suicide.\n",
    "* Decreasing death rates from septicemia over time.\n",
    "* Increasing death rates from Alzheimer's over time.\n",
    "\n",
    "There are a number of missing death rates. If we wanted to, we could use census data to estimate the population of each group for each year and create our own death rates... but for now let's not worry about the missing death rates (which may be missing because they are effectively zero).\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ad7fd8a7-6ca9-4600-8fa9-bfae6baf3a20",
   "metadata": {},
   "source": [
    "# Subsetting Data\n",
    "\n",
    "Let's say we want to work with data relating to Septicemia.  We can get just the data related to that cause of death.  First, let's remind ourselves of the various causes of death in our data by using the \"unique\" method to show us all the unique values in the \"leading_cause\" column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "12797cbc-9206-4ef1-9117-f0bbf8699935",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Diseases of Heart (I00-I09, I11, I13, I20-I51)',\n",
       "       'Cerebrovascular Disease (Stroke: I60-I69)',\n",
       "       'Malignant Neoplasms (Cancer: C00-C97)', 'All Other Causes',\n",
       "       'Chronic Liver Disease and Cirrhosis (K70, K73)',\n",
       "       'Accidents Except Drug Posioning (V01-X39, X43, X45-X59, Y85-Y86)',\n",
       "       'Chronic Lower Respiratory Diseases (J40-J47)',\n",
       "       'Nephritis, Nephrotic Syndrome and Nephrisis (N00-N07, N17-N19, N25-N27)',\n",
       "       'Influenza (Flu) and Pneumonia (J09-J18)',\n",
       "       'Certain Conditions originating in the Perinatal Period (P00-P96)',\n",
       "       'Diabetes Mellitus (E10-E14)',\n",
       "       'Essential Hypertension and Renal Diseases (I10, I12)',\n",
       "       'Mental and Behavioral Disorders due to Accidental Poisoning and Other Psychoactive Substance Use (F11-F16, F18-F19, X40-X42, X44)',\n",
       "       'Intentional Self-Harm (Suicide: X60-X84, Y87.0)',\n",
       "       'Assault (Homicide: Y87.1, X85-Y09)',\n",
       "       'Human Immunodeficiency Virus Disease (HIV: B20-B24)',\n",
       "       'Septicemia (A40-A41)', \"Alzheimer's Disease (G30)\",\n",
       "       'Congenital Malformations, Deformations, and Chromosomal Abnormalities (Q00-Q99)',\n",
       "       'Viral Hepatitis (B15-B19)',\n",
       "       'Aortic Aneurysm and Dissection (I71)', 'Tuberculosis (A16-A19)',\n",
       "       \"Parkinson's Disease (G20)\",\n",
       "       'Mental and Behavioral Disorders due to Use of Alcohol (F10)',\n",
       "       'Insitu or Benign / Uncertain Neoplasms (D00-D48)',\n",
       "       'Atherosclerosis (I70)'], dtype=object)"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nyc_death_data[\"leading_cause\"].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8ced56e5-5dad-4b2a-a893-4e5c94c393bf",
   "metadata": {},
   "source": [
    "We can subset our data by saying \"just give me the rows of nyc_death_data where the leading_cause is 'Septicemia (A40-A41)'.\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "38181c87-0c61-4c56-94c0-f87aab06dcb9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\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>year</th>\n",
       "      <th>leading_cause</th>\n",
       "      <th>sex</th>\n",
       "      <th>race_ethnicity</th>\n",
       "      <th>deaths</th>\n",
       "      <th>death_rate</th>\n",
       "      <th>age_adjusted_death_rate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>2014</td>\n",
       "      <td>Septicemia (A40-A41)</td>\n",
       "      <td>M</td>\n",
       "      <td>Not Stated/Unknown</td>\n",
       "      <td>8.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>2014</td>\n",
       "      <td>Septicemia (A40-A41)</td>\n",
       "      <td>F</td>\n",
       "      <td>White Non-Hispanic</td>\n",
       "      <td>118.0</td>\n",
       "      <td>8.3</td>\n",
       "      <td>4.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>2013</td>\n",
       "      <td>Septicemia (A40-A41)</td>\n",
       "      <td>F</td>\n",
       "      <td>White Non-Hispanic</td>\n",
       "      <td>135.0</td>\n",
       "      <td>9.5</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>2013</td>\n",
       "      <td>Septicemia (A40-A41)</td>\n",
       "      <td>F</td>\n",
       "      <td>Asian and Pacific Islander</td>\n",
       "      <td>16.0</td>\n",
       "      <td>2.7</td>\n",
       "      <td>2.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>283</th>\n",
       "      <td>2012</td>\n",
       "      <td>Septicemia (A40-A41)</td>\n",
       "      <td>F</td>\n",
       "      <td>Other Race/ Ethnicity</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>328</th>\n",
       "      <td>2012</td>\n",
       "      <td>Septicemia (A40-A41)</td>\n",
       "      <td>M</td>\n",
       "      <td>Other Race/ Ethnicity</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>386</th>\n",
       "      <td>2012</td>\n",
       "      <td>Septicemia (A40-A41)</td>\n",
       "      <td>F</td>\n",
       "      <td>White Non-Hispanic</td>\n",
       "      <td>113.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>4.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>457</th>\n",
       "      <td>2011</td>\n",
       "      <td>Septicemia (A40-A41)</td>\n",
       "      <td>F</td>\n",
       "      <td>Not Stated/Unknown</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>572</th>\n",
       "      <td>2010</td>\n",
       "      <td>Septicemia (A40-A41)</td>\n",
       "      <td>F</td>\n",
       "      <td>White Non-Hispanic</td>\n",
       "      <td>107.0</td>\n",
       "      <td>7.5</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>675</th>\n",
       "      <td>2010</td>\n",
       "      <td>Septicemia (A40-A41)</td>\n",
       "      <td>F</td>\n",
       "      <td>Not Stated/Unknown</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>772</th>\n",
       "      <td>2009</td>\n",
       "      <td>Septicemia (A40-A41)</td>\n",
       "      <td>F</td>\n",
       "      <td>Not Stated/Unknown</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>970</th>\n",
       "      <td>2007</td>\n",
       "      <td>Septicemia (A40-A41)</td>\n",
       "      <td>F</td>\n",
       "      <td>Hispanic</td>\n",
       "      <td>49.0</td>\n",
       "      <td>4.2</td>\n",
       "      <td>5.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>971</th>\n",
       "      <td>2007</td>\n",
       "      <td>Septicemia (A40-A41)</td>\n",
       "      <td>F</td>\n",
       "      <td>Black Non-Hispanic</td>\n",
       "      <td>89.0</td>\n",
       "      <td>8.5</td>\n",
       "      <td>8.1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     year         leading_cause sex              race_ethnicity  deaths  \\\n",
       "52   2014  Septicemia (A40-A41)   M          Not Stated/Unknown     8.0   \n",
       "130  2014  Septicemia (A40-A41)   F          White Non-Hispanic   118.0   \n",
       "136  2013  Septicemia (A40-A41)   F          White Non-Hispanic   135.0   \n",
       "138  2013  Septicemia (A40-A41)   F  Asian and Pacific Islander    16.0   \n",
       "283  2012  Septicemia (A40-A41)   F       Other Race/ Ethnicity     NaN   \n",
       "328  2012  Septicemia (A40-A41)   M       Other Race/ Ethnicity     6.0   \n",
       "386  2012  Septicemia (A40-A41)   F          White Non-Hispanic   113.0   \n",
       "457  2011  Septicemia (A40-A41)   F          Not Stated/Unknown     NaN   \n",
       "572  2010  Septicemia (A40-A41)   F          White Non-Hispanic   107.0   \n",
       "675  2010  Septicemia (A40-A41)   F          Not Stated/Unknown     NaN   \n",
       "772  2009  Septicemia (A40-A41)   F          Not Stated/Unknown     NaN   \n",
       "970  2007  Septicemia (A40-A41)   F                    Hispanic    49.0   \n",
       "971  2007  Septicemia (A40-A41)   F          Black Non-Hispanic    89.0   \n",
       "\n",
       "     death_rate  age_adjusted_death_rate  \n",
       "52          NaN                      NaN  \n",
       "130         8.3                      4.7  \n",
       "136         9.5                      5.0  \n",
       "138         2.7                      2.9  \n",
       "283         NaN                      NaN  \n",
       "328         NaN                      NaN  \n",
       "386         8.0                      4.2  \n",
       "457         NaN                      NaN  \n",
       "572         7.5                      4.3  \n",
       "675         NaN                      NaN  \n",
       "772         NaN                      NaN  \n",
       "970         4.2                      5.5  \n",
       "971         8.5                      8.1  "
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "septicemia_deaths = nyc_death_data[nyc_death_data[\"leading_cause\"] == \"Septicemia (A40-A41)\"]\n",
    "septicemia_deaths"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8a34f2b3-8762-4334-9bfb-71dc99f13c05",
   "metadata": {},
   "source": [
    "And we might want to get a total of *all* deaths by all causes so we can compare relative rates... that brings us to using \"groupby\" and \"aggregation\" functions in pandas:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "1c8cf0af-8167-4392-a2ce-49c65d7303df",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th rowspan=\"6\" valign=\"top\">M</th>\n",
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       "      <td>14564.0</td>\n",
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       "      <th>Black Non-Hispanic</th>\n",
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      ],
      "text/plain": [
       "                                total_deaths\n",
       "sex race_ethnicity                          \n",
       "F   Asian and Pacific Islander       11791.0\n",
       "    Black Non-Hispanic               58812.0\n",
       "    Hispanic                         35908.0\n",
       "    Not Stated/Unknown                1708.0\n",
       "    Other Race/ Ethnicity              993.0\n",
       "    White Non-Hispanic              107859.0\n",
       "M   Asian and Pacific Islander       14564.0\n",
       "    Black Non-Hispanic               52304.0\n",
       "    Hispanic                         38894.0\n",
       "    Not Stated/Unknown                2391.0\n",
       "    Other Race/ Ethnicity             1146.0\n",
       "    White Non-Hispanic               98628.0"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_causes = nyc_death_data.groupby([\"sex\", \"race_ethnicity\"]).agg(total_deaths=('deaths', 'sum'))\n",
    "all_causes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9ac20e88-7b86-4e0f-ab74-af7d173603a3",
   "metadata": {},
   "source": [
    "This layout of our data isn't what we're used to, because it's a grouped data frame.  We can flatten it down to what we're used to seeing using \"reset_index\"."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "3f6d9569-07a5-43cf-b9ed-091c88152786",
   "metadata": {},
   "outputs": [
    {
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       "      <th>8</th>\n",
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       "      <td>Hispanic</td>\n",
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       "      <td>Not Stated/Unknown</td>\n",
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       "      <th>10</th>\n",
       "      <td>M</td>\n",
       "      <td>Other Race/ Ethnicity</td>\n",
       "      <td>1146.0</td>\n",
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       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>M</td>\n",
       "      <td>White Non-Hispanic</td>\n",
       "      <td>98628.0</td>\n",
       "    </tr>\n",
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      ],
      "text/plain": [
       "   sex              race_ethnicity  total_deaths\n",
       "0    F  Asian and Pacific Islander       11791.0\n",
       "1    F          Black Non-Hispanic       58812.0\n",
       "2    F                    Hispanic       35908.0\n",
       "3    F          Not Stated/Unknown        1708.0\n",
       "4    F       Other Race/ Ethnicity         993.0\n",
       "5    F          White Non-Hispanic      107859.0\n",
       "6    M  Asian and Pacific Islander       14564.0\n",
       "7    M          Black Non-Hispanic       52304.0\n",
       "8    M                    Hispanic       38894.0\n",
       "9    M          Not Stated/Unknown        2391.0\n",
       "10   M       Other Race/ Ethnicity        1146.0\n",
       "11   M          White Non-Hispanic       98628.0"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_causes = all_causes.reset_index()\n",
    "all_causes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f3216f59-67cb-464d-a1e9-4fae3c8d3157",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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