{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h1>14. Introduction to Pandas</h1>\n",
    "<h2>11/01/2023</h2>\n",
    "\n",
    "<h2>14.0 Last Time...</h2>\n",
    "<ul>\n",
    "    <li>The <b>operator</b> package enables us to use a function called <b>attrgetter()</b> to grab attribute information from various classes.</li>\n",
    "    <li>The <b>sorted()</b> function lets us sort data alphabetically or numerically as needed.</li>\n",
    "    <li>NumPy's <b>meshgrid()</b> module lets us create a grid from lat/lon vectors.</li> \n",
    "</ul>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2>14.1 Why Pandas?</h2>\n",
    "\n",
    "Python's standard library has some tools for working with CSV files, but Pandas makes life a whole lot easier! It handles missing data well and also allows for quick calculations and plotting (which we'll be talking about in a couple weeks). A Pandas <b>dataframe</b> is a lot like an Excel spreadsheet, but it's a lot faster and more flexible."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Here's the new library we'll want for today:\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's begin by using a tool we're familiar with that should work pretty well for this kind of data: dictionaries!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[23, 45, 12]\n"
     ]
    }
   ],
   "source": [
    "data = {\"name\":[\"john\",\"bob\",\"dan\"], \"age\":[23,45,12],\"salary\":[23333,43555,90000],\"title\":[\"CFO\",\"VP\",\"CTO\"]}\n",
    "print(data[\"age\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So far so good, but if we want to get the designation for the employee Sam, that can get a little complex. Pandas will make this endeavor easier and more intuitive.\n",
    "\n",
    "Pandas features two data structures:\n",
    "<ul>\n",
    "    <li><b>Series:</b> 1-D labeled arrays that resemble dictionaries</li>\n",
    "    <li><b>DataFrame:</b> (most common) 2-D like a spreadsheet</li>\n",
    "</ul>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   name  age  salary title\n",
      "0  john   23   23333   CFO\n",
      "1   bob   45   43555    VP\n",
      "2   dan   12   90000   CTO\n"
     ]
    }
   ],
   "source": [
    "employees = pd.DataFrame(data)\n",
    "print(employees)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Remember from our object-oriented programming lectures: a DataFrame is just an object! We can list its attributes and methods using dir()."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
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       " 'to_latex',\n",
       " 'to_markdown',\n",
       " 'to_numpy',\n",
       " 'to_orc',\n",
       " 'to_parquet',\n",
       " 'to_period',\n",
       " 'to_pickle',\n",
       " 'to_records',\n",
       " 'to_sql',\n",
       " 'to_stata',\n",
       " 'to_string',\n",
       " 'to_timestamp',\n",
       " 'to_xarray',\n",
       " 'to_xml',\n",
       " 'transform',\n",
       " 'transpose',\n",
       " 'truediv',\n",
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       " 'tz_localize',\n",
       " 'unstack',\n",
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       " 'values',\n",
       " 'var',\n",
       " 'where',\n",
       " 'xs']"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dir(employees)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   name  age  salary title\n",
      "0  john   23   23333   CFO\n",
      "1   bob   45   43555    VP\n",
      "2   dan   12   90000   CTO\n"
     ]
    }
   ],
   "source": [
    "print(employees)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Just like Excel spreadsheets, dataframes are made up of <b>rows</b> and <b>columns</b>. Each column will have the same data type (all ints, all floats, all strings, etc.).\n",
    "\n",
    "We can then set a column (or multiple columns) as an <b>index</b> that we can use as a shorthand."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      age  salary title\n",
      "name                   \n",
      "john   23   23333   CFO\n",
      "bob    45   43555    VP\n",
      "dan    12   90000   CTO\n"
     ]
    }
   ],
   "source": [
    "employees.set_index(\"name\",inplace=True)\n",
    "# The inplace argument above means we're replacing\n",
    "# our 'default' index with our new index.\n",
    "\n",
    "print(employees)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['john', 'bob', 'dan'], dtype='object', name='name')\n",
      "Index(['age', 'salary', 'title'], dtype='object')\n"
     ]
    }
   ],
   "source": [
    "print(employees.index)\n",
    "print(employees.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can then use the <b>loc[]</b> function to access a group of rows and columns by a particular label."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "age          23\n",
       "salary    23333\n",
       "title       CFO\n",
       "Name: john, dtype: object"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "employees.loc[\"john\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "age          12\n",
       "salary    90000\n",
       "title       CTO\n",
       "Name: dan, dtype: object"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Similarly, we can use 'iloc[]' to refer to a particular index.\n",
    "employees.iloc[2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It's also possible to create subsets of dataframes based on their values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      age  salary title\n",
      "name                   \n",
      "bob    45   43555    VP\n"
     ]
    }
   ],
   "source": [
    "# Let's only look at employees older than 30.\n",
    "print(employees[employees.age>30])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "name\n",
      "john    False\n",
      "bob      True\n",
      "dan     False\n",
      "Name: title, dtype: bool\n"
     ]
    }
   ],
   "source": [
    "# Let's look at who's a VP and who isn't.\n",
    "print(employees['title'] == 'VP')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      age  salary title\n",
      "name                   \n",
      "john   22   23333   CFO\n",
      "bob    45   43555    VP\n",
      "dan    12   90000   CTO\n"
     ]
    }
   ],
   "source": [
    "# We can also easily set values or add new columns.\n",
    "employees.loc['john','age'] = 22\n",
    "print(employees)\n",
    "# Change John's age to 22.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      age  salary title      city\n",
      "name                             \n",
      "john   22   23333   CFO  montreal\n",
      "bob    45   43555    VP  montreal\n",
      "dan    12   90000   CTO  montreal\n"
     ]
    }
   ],
   "source": [
    "# Let's say we now have information about what city\n",
    "# everyone's in and we want to add that where we have it.\n",
    "employees['city'] = 'montreal'\n",
    "print(employees)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      age  salary title      city\n",
      "name                             \n",
      "john   22   23333   CFO   toronto\n",
      "bob    45   43555    VP  montreal\n",
      "dan    12   90000   CTO  montreal\n"
     ]
    }
   ],
   "source": [
    "# Whoops, Diane's moved to Toronto!\n",
    "employees.loc['john','city'] = 'toronto'\n",
    "print(employees)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The <b>describe()</b> function is a helpful summary of statistics."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count        3.000000\n",
       "mean     52296.000000\n",
       "std      34182.247337\n",
       "min      23333.000000\n",
       "25%      33444.000000\n",
       "50%      43555.000000\n",
       "75%      66777.500000\n",
       "max      90000.000000\n",
       "Name: salary, dtype: float64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# employees.age.describe()\n",
    "employees.salary.describe()\n",
    "# WHAT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      age  salary title      city\n",
      "name                             \n",
      "john   22   24333   CFO   toronto\n",
      "bob    45   44555    VP  montreal\n",
      "dan    12   91000   CTO  montreal\n"
     ]
    }
   ],
   "source": [
    "# We can also easily do mathematical operations.\n",
    "\n",
    "employees.salary = employees.salary + 1000\n",
    "print(employees)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "title\n",
       "CFO    1\n",
       "VP     1\n",
       "CTO    1\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Or use things like value counts!\n",
    "\n",
    "employees.title.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2021-01-01', '2021-01-02', '2021-01-03', '2021-01-04',\n",
       "               '2021-01-05', '2021-01-06', '2021-01-07', '2021-01-08',\n",
       "               '2021-01-09', '2021-01-10', '2021-01-11', '2021-01-12'],\n",
       "              dtype='datetime64[ns]', freq='D')"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Pandas can also be used to create some useful date ranges!\n",
    "pd.date_range('1/1/2021','1/12/2021')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2>14.2 Pandas Examples</h2>\n",
    "\n",
    "You'll need to re-run these lines of code to clear out all the changes\n",
    "we made above..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'my_dict' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m/Users/nik/data/python/notebooks/Week 06 W.ipynb Cell 30\u001b[0m line \u001b[0;36m1\n\u001b[0;32m----> <a href='vscode-notebook-cell:/Users/nik/data/python/notebooks/Week%2006%20W.ipynb#X41sZmlsZQ%3D%3D?line=0'>1</a>\u001b[0m employees \u001b[39m=\u001b[39m pd\u001b[39m.\u001b[39mDataFrame(my_dict)\n\u001b[1;32m      <a href='vscode-notebook-cell:/Users/nik/data/python/notebooks/Week%2006%20W.ipynb#X41sZmlsZQ%3D%3D?line=1'>2</a>\u001b[0m employees\u001b[39m.\u001b[39mset_index(\u001b[39m'\u001b[39m\u001b[39mname\u001b[39m\u001b[39m'\u001b[39m, inplace\u001b[39m=\u001b[39m\u001b[39mTrue\u001b[39;00m)\n",
      "\u001b[0;31mNameError\u001b[0m: name 'my_dict' is not defined"
     ]
    }
   ],
   "source": [
    "employees = pd.DataFrame(my_dict)\n",
    "employees.set_index('name', inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b>1. Promote Ashley to CEO.</b>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b>2. Using methods you learned in this lecture, find the mean and standard deviation of salaries.</b>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b>3. A year has passed! Increase everyone's ages by 1.</b>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2>14.3 Pandas With Atmospheric Data</h2>\n",
    "\n",
    "Let's use a real-life example! This is information from Chris McCray at McGill: Daily weather data for Montreal from 1871-2019. Pandas has a <b>read_csv()</b> function that will come in handy here."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/0x/8vc0k5b97mq8hxcghjr_nb300000gn/T/ipykernel_61695/2319455187.py:3: DtypeWarning: Columns (24,25,26) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  mtl_weather = pd.read_csv('http://www.cdmccray.com/python_tutorial/pandas/montreal_daily_weather.csv')\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "mtl_weather = pd.read_csv('http://www.cdmccray.com/python_tutorial/pandas/montreal_daily_weather.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['Date/Time', 'Year', 'Month', 'Day', 'Data Quality', 'Max Temp (°C)',\n",
      "       'Max Temp Flag', 'Min Temp (°C)', 'Min Temp Flag', 'Mean Temp (°C)',\n",
      "       'Mean Temp Flag', 'Heat Deg Days (°C)', 'Heat Deg Days Flag',\n",
      "       'Cool Deg Days (°C)', 'Cool Deg Days Flag', 'Total Rain (mm)',\n",
      "       'Total Rain Flag', 'Total Snow (cm)', 'Total Snow Flag',\n",
      "       'Total Precip (mm)', 'Total Precip Flag', 'Snow on Grnd (cm)',\n",
      "       'Snow on Grnd Flag', 'Dir of Max Gust (10s deg)',\n",
      "       'Dir of Max Gust Flag', 'Spd of Max Gust (km/h)',\n",
      "       'Spd of Max Gust Flag', 'Date', 'season'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "print(mtl_weather.columns)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's set the index to the date of observation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "mtl_weather.set_index('Date/Time',inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b>Grouping</b> is a useful feature within Pandas that lets us do the following:\n",
    "<ul>\n",
    "    <li>Split the data into groups based on some criteria.</li>\n",
    "    <li>Apply a function to each group independently.</li>\n",
    "    <li>Combine the results into a data structure.</li>\n",
    "</ul>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Year\n",
      "1871    184\n",
      "1872    366\n",
      "1873    334\n",
      "1874    365\n",
      "1875    365\n",
      "       ... \n",
      "2015    358\n",
      "2016    360\n",
      "2017    351\n",
      "2018    357\n",
      "2019     74\n",
      "Name: Max Temp (°C), Length: 149, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "# As an example, let's count how much temperature data is available for each year.\n",
    "\n",
    "a = mtl_weather.groupby('Year').count()['Max Temp (°C)']\n",
    "print(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Year'>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "a.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Okay, so there's a lot of missing data in the 90s! We can actually remove all rows with missing data by using <b>dropna()</b>. Since there's probably a lot of data missing, let's specify that we're only removing the rows that have missing temperature data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(54421, 28)\n",
      "(52456, 28)\n"
     ]
    }
   ],
   "source": [
    "print(mtl_weather.shape)\n",
    "mtl_weather.dropna(subset=['Max Temp (°C)'], inplace=True)\n",
    "print(mtl_weather.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also use <b>groupby()</b> to calculate the average temperature for each year!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Year'>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mtl_weather.groupby('Year')['Mean Temp (°C)'].mean().plot(figsize=(25,5))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Okay, well, there's obviously something suspicious going on here - it's not that cold, even in Montreal! Note that these are years where a lot of data is missing - it looks like most of that data's from the warm season.\n",
    "\n",
    "How would you handle this kind of problem?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Year'>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "yearlycounts = mtl_weather.groupby('Year').count()['Mean Temp (°C)']\n",
    "yearlycounts.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's set our threshold to about 350 days."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index([1872, 1874, 1875, 1876, 1877, 1878, 1879, 1880, 1881, 1882,\n",
      "       ...\n",
      "       2008, 2009, 2010, 2011, 2012, 2013, 2015, 2016, 2017, 2018],\n",
      "      dtype='int64', name='Year', length=135)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Year'>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "goodyears = yearlycounts[yearlycounts>350].index\n",
    "print(goodyears)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can now subset the dataframe to only include data from our good years using the <b>isin()</b> function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Year'>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mtl_weather = mtl_weather[mtl_weather.Year.isin(goodyears)]\n",
    "mtl_weather.groupby('Year')['Mean Temp (°C)'].mean().plot(figsize=(25,5))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It's also very easy to get extreme values from the dataset. The <b>nsmallest()</b> function will list the smallest values, and the <b>nlargest()</b> function will list the largest."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Date/Time\n",
      "1933-12-29   -33.9\n",
      "1981-01-04   -33.5\n",
      "1943-02-15   -33.3\n",
      "1914-01-13   -32.8\n",
      "1914-02-11   -32.8\n",
      "Name: Min Temp (°C), dtype: float64\n"
     ]
    }
   ],
   "source": [
    "print(mtl_weather['Min Temp (°C)'].nsmallest())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>Day</th>\n",
       "      <th>Data Quality</th>\n",
       "      <th>Max Temp (°C)</th>\n",
       "      <th>Min Temp (°C)</th>\n",
       "      <th>Mean Temp (°C)</th>\n",
       "      <th>Heat Deg Days (°C)</th>\n",
       "      <th>Cool Deg Days (°C)</th>\n",
       "      <th>Total Rain (mm)</th>\n",
       "      <th>Total Snow (cm)</th>\n",
       "      <th>Total Precip (mm)</th>\n",
       "      <th>Snow on Grnd (cm)</th>\n",
       "      <th>Dir of Max Gust (10s deg)</th>\n",
       "      <th>season</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>49226.000000</td>\n",
       "      <td>49226.000000</td>\n",
       "      <td>49226.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>49226.000000</td>\n",
       "      <td>49215.000000</td>\n",
       "      <td>49215.000000</td>\n",
       "      <td>49215.000000</td>\n",
       "      <td>49215.000000</td>\n",
       "      <td>41958.000000</td>\n",
       "      <td>41949.000000</td>\n",
       "      <td>48913.000000</td>\n",
       "      <td>12384.000000</td>\n",
       "      <td>1992.000000</td>\n",
       "      <td>49226.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1941.422480</td>\n",
       "      <td>6.522468</td>\n",
       "      <td>15.725287</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.807128</td>\n",
       "      <td>2.680293</td>\n",
       "      <td>6.753986</td>\n",
       "      <td>12.040049</td>\n",
       "      <td>0.794034</td>\n",
       "      <td>2.111869</td>\n",
       "      <td>0.736919</td>\n",
       "      <td>2.901108</td>\n",
       "      <td>10.154797</td>\n",
       "      <td>20.743474</td>\n",
       "      <td>1941.841385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>41.283202</td>\n",
       "      <td>3.448537</td>\n",
       "      <td>8.799889</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.444379</td>\n",
       "      <td>11.722607</td>\n",
       "      <td>11.986670</td>\n",
       "      <td>11.006062</td>\n",
       "      <td>1.850957</td>\n",
       "      <td>5.781769</td>\n",
       "      <td>2.854098</td>\n",
       "      <td>6.503921</td>\n",
       "      <td>19.577769</td>\n",
       "      <td>11.753323</td>\n",
       "      <td>41.286312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1872.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-28.900000</td>\n",
       "      <td>-33.900000</td>\n",
       "      <td>-31.400000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1872.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1906.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.100000</td>\n",
       "      <td>-6.100000</td>\n",
       "      <td>-2.500000</td>\n",
       "      <td>0.700000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>14.000000</td>\n",
       "      <td>1907.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1940.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.700000</td>\n",
       "      <td>3.800000</td>\n",
       "      <td>7.700000</td>\n",
       "      <td>10.300000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>21.500000</td>\n",
       "      <td>1940.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1974.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21.700000</td>\n",
       "      <td>12.800000</td>\n",
       "      <td>17.300000</td>\n",
       "      <td>20.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.800000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.500000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>33.000000</td>\n",
       "      <td>1974.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2018.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36.600000</td>\n",
       "      <td>26.100000</td>\n",
       "      <td>30.300000</td>\n",
       "      <td>49.400000</td>\n",
       "      <td>12.300000</td>\n",
       "      <td>90.400000</td>\n",
       "      <td>46.500000</td>\n",
       "      <td>94.700000</td>\n",
       "      <td>145.000000</td>\n",
       "      <td>36.000000</td>\n",
       "      <td>2019.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Year         Month           Day  Data Quality  Max Temp (°C)  \\\n",
       "count  49226.000000  49226.000000  49226.000000           0.0   49226.000000   \n",
       "mean    1941.422480      6.522468     15.725287           NaN      10.807128   \n",
       "std       41.283202      3.448537      8.799889           NaN      12.444379   \n",
       "min     1872.000000      1.000000      1.000000           NaN     -28.900000   \n",
       "25%     1906.000000      4.000000      8.000000           NaN       1.100000   \n",
       "50%     1940.000000      7.000000     16.000000           NaN      11.700000   \n",
       "75%     1974.000000     10.000000     23.000000           NaN      21.700000   \n",
       "max     2018.000000     12.000000     31.000000           NaN      36.600000   \n",
       "\n",
       "       Min Temp (°C)  Mean Temp (°C)  Heat Deg Days (°C)  Cool Deg Days (°C)  \\\n",
       "count   49215.000000    49215.000000        49215.000000        49215.000000   \n",
       "mean        2.680293        6.753986           12.040049            0.794034   \n",
       "std        11.722607       11.986670           11.006062            1.850957   \n",
       "min       -33.900000      -31.400000            0.000000            0.000000   \n",
       "25%        -6.100000       -2.500000            0.700000            0.000000   \n",
       "50%         3.800000        7.700000           10.300000            0.000000   \n",
       "75%        12.800000       17.300000           20.500000            0.000000   \n",
       "max        26.100000       30.300000           49.400000           12.300000   \n",
       "\n",
       "       Total Rain (mm)  Total Snow (cm)  Total Precip (mm)  Snow on Grnd (cm)  \\\n",
       "count     41958.000000     41949.000000       48913.000000       12384.000000   \n",
       "mean          2.111869         0.736919           2.901108          10.154797   \n",
       "std           5.781769         2.854098           6.503921          19.577769   \n",
       "min           0.000000         0.000000           0.000000           0.000000   \n",
       "25%           0.000000         0.000000           0.000000           0.000000   \n",
       "50%           0.000000         0.000000           0.000000           0.000000   \n",
       "75%           0.800000         0.000000           2.500000          10.000000   \n",
       "max          90.400000        46.500000          94.700000         145.000000   \n",
       "\n",
       "       Dir of Max Gust (10s deg)        season  \n",
       "count                1992.000000  49226.000000  \n",
       "mean                   20.743474   1941.841385  \n",
       "std                    11.753323     41.286312  \n",
       "min                     1.000000   1872.000000  \n",
       "25%                    14.000000   1907.000000  \n",
       "50%                    21.500000   1940.000000  \n",
       "75%                    33.000000   1974.000000  \n",
       "max                    36.000000   2019.000000  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mtl_weather.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2>14.4 Take-Home Points</h2>\n",
    "<ul>\n",
    "    <li><b>Pandas</b> is a useful way of working with CSV data!</li>\n",
    "    <li>A <b>dataframe</b> is an object that contains rows and columns, much like an Excel spreadsheet.</li>\n",
    "    <li><b>loc()</b> will let you identify individual rows, columns, or values.</li>\n",
    "    <li><b>describe()</b> summarizes statistics for a specified section of a dataframe.</li>\n",
    "    <li><b>read_csv()</b> will read in a CSV file specified by a file location.</li>\n",
    "    <li><b>groupby()</b> carries out specific operations on groupings within a dataframe.</li>\n",
    "</ul>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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