{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Visualizing Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "> To find signals in data, we must learn to reduce the noise - not just the noise that resides in the data, but also the noise that resides in us. It is nearly impossible for noisy minds to perceive anything but noise in data.\n",
    ">\n",
    "> \\- Stephen Few, Data Visualization Consultant and Author"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Applied Review"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Joining Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "- *Joining* is the process of combining two DataFrames to form a new DataFrame that incorporates data from both of the combined tables."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "- The most common type of join is an *inner join*, but full-outer, left-outer, and right-outer joins are all useful as well."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "- Joins are done in Pandas with the `pd.merge` function."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Exporting Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "- Most types of data in Python, including DataFrames and trained models, can be saved in files."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "- The most common types of files for this are CSVs, JSON, and pickle files."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Matplotlib and Seaborn"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Matplotlib"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "The most tried-and-true, mature plotting library in Python is called [Matplotlib](https://matplotlib.org/).\n",
    "It began with a mission of replicating Matlab's plotting functionality in Python, so if you're familiar with Matlab you may notice some syntactic similiaries."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Matplotlib is traditionally imported like this:\n",
    "```python\n",
    "import matplotlib.pyplot as plt\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "This means *import matplotlib's pyplot submodule under the name `plt`*."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Seaborn"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "While matplotlib is powerful and stable, the rise of Python's use within data science led to the development of a more data scientist-friendly library, called [Seaborn](https://seaborn.pydata.org/).\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Seaborn allows the user to describe graphics using clearer and less verbose function calls, but uses Matplotlib to generate the plots."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "This approach has the added benefit of allowing the user to \"drop down\" to Matplotlib to make fine adjustments to his/her plots if needed."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "Seaborn is traditionally imported like this:\n",
    "```python\n",
    "import seaborn as sns\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "<div class=\"admonition note alert alert-info\">\n",
    "    <b><p class=\"first admonition-title\" style=\"font-weight: bold\">Fun Fact!</p></b>\n",
    "    <p>Seaborn is allegedly named after West Wing character Sam Seaborn, whose full name is Samuel Norman Seaborn (S.N.S. -- the package import nickname).</p>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "So, altogether between Matplotlib and Seaborn, your importing code will usually look something like:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "```python\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "In practice, a good strategy is to try to make your plots with Seaborn and switch to Matplotlib only when you discover you need more flexibility than Seaborn provides.\n",
    "Today we'll strictly be using Seaborn, but it's important to understand Seaborn's relationship with Matplotlib to make sense of advice and code you find on the internet (e.g. Stack Overflow answers)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Examples"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "The first things we need to do is import our libraries."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# DataFrame capabilities\n",
    "import pandas as pd\n",
    "\n",
    "# Visualization capabilities\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "Now let's import some data for plotting."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "planes = pd.read_csv('../data/planes.csv')\n",
    "flights = pd.read_csv('../data/flights.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Distribution Plots"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "A very common need in data science is being able to see the distribution of a variable.\n",
    "Histograms, density plots, box plots, and violin plots are the most popular ways to do so."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "Seaborn can create histograms and density plots using the `histplot` function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='seats', ylabel='Count'>"
      ]
     },
     "execution_count": 3,
     "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": [
    "sns.histplot(data=planes, x='seats')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    },
    "tags": []
   },
   "source": [
    "<div class=\"admonition note alert alert-info\">\n",
    "    <b><p class=\"first admonition-title\" style=\"font-weight: bold\">Note</p></b>\n",
    "    <p>Note the annoying <tt class=\\\"docutils literal\\\">&lt;AxesSubplot:xlabel='seats', ylabel='Count'&gt</tt> at the top of the previous plot. We can remove this output by adding a <tt class=\\\"docutils literal\\\">;</tt> after the plotting function call.</p>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.histplot(data=planes, x='seats');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "By adding an argument, `kde=True`, you can overlay a *density estimate* on the histogram – this is very useful for visualizing continuous distributions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.histplot(data=planes, x='seats', kde=True);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "<div class=\"admonition note alert alert-info\">\n",
    "    <b><p class=\"first admonition-title\" style=\"font-weight: bold\">Note</p></b>\n",
    "    <p><tt class=\\\"docutils literal\\\">histplot</tt>, like all Seaborn plotting functions, supports a wide variety of customizations using various arguments. We won't cover those, but refer to the <a href=\"https://seaborn.pydata.org\">Seaborn docs</a> to learn more.\n",
    "    </p>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "Should you prefer a boxplot, use the `boxplot` function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(data=planes, x='seats');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "Or a violin plot:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.violinplot(data=planes, x='seats');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Scatter Plots"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "Scatter plots are used to see the relationship between two variables.\n",
    "They plot one variable on the x-axis and another on the y-axis, and use points to show where the records of the data occur."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "Seaborn provides the `scatterplot` function for making scatterplots.\n",
    "Simply pass in two columns of data –- the first will be your x-axis and the second your y-axis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot(data=flights, x='dep_delay', y='arr_delay');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "Adding a `hue` argument allows you to color points differently based on a categorical variable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/anaconda3/envs/uc-python/lib/python3.11/site-packages/IPython/core/events.py:89: UserWarning: Creating legend with loc=\"best\" can be slow with large amounts of data.\n",
      "  func(*args, **kwargs)\n",
      "/usr/local/anaconda3/envs/uc-python/lib/python3.11/site-packages/IPython/core/pylabtools.py:152: UserWarning: Creating legend with loc=\"best\" can be slow with large amounts of data.\n",
      "  fig.canvas.print_figure(bytes_io, **kw)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot(data=flights, x='dep_delay', y='arr_delay', hue='carrier');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "<div class=\"admonition note alert alert-info\">\n",
    "    <b><p class=\"first admonition-title\" style=\"font-weight: bold\">Note</p></b>\n",
    "    <p>This plot may take a while to render when you run it -- there are a <i>lot</i> of flights in our data, and it takes Python a while to assign them all coordinates and colors.\n",
    "    </p>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Line Plots"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "Line plot are useful for observing the change in a value over time.\n",
    "We can use Seaborn's `lineplot` function to see how departure delay changes throughout the day."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": []
   },
   "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>dep_time</th>\n",
       "      <th>dep_delay</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>517.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>533.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>542.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>544.0</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>554.0</td>\n",
       "      <td>-5.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   dep_time  dep_delay\n",
       "0     517.0        2.0\n",
       "1     533.0        4.0\n",
       "2     542.0        2.0\n",
       "3     544.0       -1.0\n",
       "4     554.0       -5.0"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## You can ignore this wrangling if you want.\n",
    "\n",
    "# Subset our data to just one day.\n",
    "cond = (flights['year'] == 2013) & (flights['month'] == 1) & (flights['day'] == 1)\n",
    "jan1_flights = flights[cond]\n",
    "\n",
    "# Group by time and get the mean delay.\n",
    "jan1_flights = jan1_flights.groupby('dep_time', as_index=False)['dep_delay'].mean()\n",
    "jan1_flights.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Make a line plot with dep_time on the x-axis and dep_delay on the y-axis.\n",
    "sns.lineplot(data=jan1_flights, x='dep_time', y='dep_delay');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Bar Plots"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "Bar plots are often used to display values across several groups.\n",
    "Seaborn supports them with the `barplot` function."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "Let's plot the number of flights from each origin airport."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": []
   },
   "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>origin</th>\n",
       "      <th>n_flights</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>EWR</td>\n",
       "      <td>120835</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>JFK</td>\n",
       "      <td>111279</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>LGA</td>\n",
       "      <td>104662</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  origin  n_flights\n",
       "0    EWR     120835\n",
       "1    JFK     111279\n",
       "2    LGA     104662"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get the number of flights from each origin\n",
    "flight_counts = flights.groupby('origin', as_index=False)['flight'].count()\n",
    "flight_counts = flight_counts.rename(columns={'flight': 'n_flights'})\n",
    "flight_counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(data=flight_counts, x='origin', y='n_flights');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "If the `hue` argument is also specified, you get a grouped bar chart -- the second argument is the groups and the `hue` argument is the bars within each group."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    },
    "tags": []
   },
   "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>origin</th>\n",
       "      <th>carrier</th>\n",
       "      <th>n_flights</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>EWR</td>\n",
       "      <td>9E</td>\n",
       "      <td>1268</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>EWR</td>\n",
       "      <td>AA</td>\n",
       "      <td>3487</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>EWR</td>\n",
       "      <td>B6</td>\n",
       "      <td>6557</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>JFK</td>\n",
       "      <td>9E</td>\n",
       "      <td>14651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>JFK</td>\n",
       "      <td>AA</td>\n",
       "      <td>13783</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>JFK</td>\n",
       "      <td>B6</td>\n",
       "      <td>42076</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>LGA</td>\n",
       "      <td>9E</td>\n",
       "      <td>2541</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>LGA</td>\n",
       "      <td>AA</td>\n",
       "      <td>15459</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>LGA</td>\n",
       "      <td>B6</td>\n",
       "      <td>6002</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   origin carrier  n_flights\n",
       "0     EWR      9E       1268\n",
       "1     EWR      AA       3487\n",
       "3     EWR      B6       6557\n",
       "12    JFK      9E      14651\n",
       "13    JFK      AA      13783\n",
       "14    JFK      B6      42076\n",
       "22    LGA      9E       2541\n",
       "23    LGA      AA      15459\n",
       "24    LGA      B6       6002"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# This time, get flights by origin and carrier\n",
    "flight_counts = flights.groupby(['origin', 'carrier'], as_index=False)['flight'].count()\n",
    "flight_counts = flight_counts.rename(columns={'flight': 'n_flights'})\n",
    "\n",
    "# For simplicity, let's narrow down to just a few carriers.\n",
    "flight_counts = flight_counts[flight_counts['carrier'].isin(['AA', 'B6', '9E'])]\n",
    "flight_counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(data=flight_counts, x='origin', y='n_flights', hue='carrier');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Seaborn Syntax\n",
    "\n",
    "Do you see a pattern in the functions to create seaborn plots?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Single variable plots:\n",
    "\n",
    "```python\n",
    "sns.plot_type(data=my_data, x=variable)\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Multi-variable plots:\n",
    "\n",
    "```python\n",
    "sns.plot_type(data=my_data, x=x_variable, y=y_variable)\n",
    "sns.plot_type(data=my_data, x=x_variable, y=y_variable, hue=hue_variable)\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Titles and Axis Labels"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "The plots we've created above are functional but lack the nice touches we'd want in a graphic we were planning to share."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Seaborn allows users to add a custom title and override the default axis labels with the `.set` method."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(data=flight_counts, x='origin', y='n_flights').set(title='Number of Flights by Origin');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    },
    "tags": []
   },
   "source": [
    "<div class=\"admonition note alert alert-info\">\n",
    "    <b><p class=\"first admonition-title\" style=\"font-weight: bold\">Note</p></b>\n",
    "    <p>It's common to break up the line when it becomes so long -- purely for readability.\n",
    "    </p>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(\n",
    "    data=flight_counts,\n",
    "    x='origin',\n",
    "    y='n_flights'\n",
    ").set(\n",
    "    title='Number of Flights by Origin',\n",
    "    xlabel='Flight Origin',\n",
    "    ylabel='Number of Flights'\n",
    ");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Your Turn\n",
    "\n",
    "You've now seen many types of plots.\n",
    "Using the flights data, make 3 different graphics to explore relationships or distributions that you think might be interesting.\n",
    "\n",
    "If you have extra time, you can try to customize your plot with axis labels, titles, and more –- take a look at the documentation using the question mark syntax we saw at the beginning of the day (e.g. `sns.barplot?`)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Other Plotting Libraries\n",
    "Unfortunately we don't have time to venture further into the Python data visualization ecosystem, but we want to provide you some background on other tools you are likely to hear about."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "- [**Altair**](https://altair-viz.github.io/) - A library with syntax focused on the famous \"Grammar of Graphics\", much like R's ggplot2. Converts the user's Python code into JavaScript, so adding interactivity is easy and it can be viewed in any browser. Ethan's favorite plotting package."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "- [**plotnine**](https://plotnine.readthedocs.io/en/stable/) - A library built to replicate the famous ggplot2 from R. Unfortunately, the differences between R and Python mean that its syntax can't be quite as elegant as ggplot2's, but it's close! Brad's favorite plotting package."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "- [**Bokeh**](https://bokeh.org/) - Similar to Altair in that it also creates graphs using JavaScript. More flexible than Altair, but at a cost of being less intuitive and more verbose."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "- [**Plotly**](https://plotly.com/python/) - A library that makes interactive, dashboard-like graphics easy. Created and maintained by a company of the same name. Does require a license for some features."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "- [**NetworkX**](https://networkx.org/) - A plotting library specifically for graphs (graphs in the nodes and edges sense). Built on top of Matplotlib, much like Seaborn."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Questions\n",
    "\n",
    "Are there questions before we move on?"
   ]
  }
 ],
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