PyDSWebinar.ipynb

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   "source": [
    "# XSEDE Webinar: Python Tools for Data Science\n",
    "\n",
    "<b>Chris Myers &nbsp;&nbsp; ( c.myers @ cornell.edu )<br />\n",
    "    <br />\n",
    "Center for Advanced Computing (CAC)&nbsp;&nbsp; & &nbsp;&nbsp;Department of Physics<br />\n",
    "    <br />\n",
    "Cornell University<br />\n",
    "</b>\n",
    "\n",
    "<hr />\n",
    "\n",
    "See the Cornell Virtual Workshop (CVW) tutorials on \"Python for Data Science\", by Chris Myers and Jeff Sale, at: https://cvw.cac.cornell.edu/PyDataSci1 and https://cvw.cac.cornell.edu/PyDataSci2 .  \n",
    "\n",
    "These slides are available as a Jupyter notebook in a github repository at https://github.com/CornellCAC/CVW_PyDataSci2 (in the file named PyDSWebinar.ipynb).\n",
    "\n",
    "<table style=\"float:left\"><tr>\n",
    "    <td><img src=\"images/cornell_seal_simple_b31b1b.png\" width=\"200\"/></td>\n",
    "    <td>                      </td>\n",
    "    <td><img src=\"images/XSEDE_Logo_Blue.png\" width=\"400\"/></td>\n",
    "    </tr></table>"
   ]
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   "source": [
    "## Code of Conduct\n",
    "\n",
    "XSEDE has an external code of conduct which represents our commitment to providing an inclusive and harassment-free environment in all interactions regardless of race, age, ethnicity, national origin, language, gender, gender identity, sexual orientation, disability, physical appearance, political views, military service, health status, or religion. The code of conduct extends to all XSEDE-sponsored events, services, and interactions.\n",
    "\n",
    "Code of Conduct: https://www.xsede.org/codeofconduct \n",
    "\n",
    "Contact:\n",
    "* Event organizer: Susan Mehringer, CAC (shm7@cornell.edu) \n",
    "* XSEDE ombudspersons:\n",
    "    * Linda Akli, Southeastern Universities Research Association (akli@sura.org)\n",
    "    * Lizanne Destefano, Georgia Tech (lizanne.destefano@ceismc.gatech.edu)\n",
    "    * Ken Hackworth, Pittsburgh Supercomputing Center (hackworth@psc.edu)\n",
    "    * Bryan Snead, Texas Advanced Computing Center (jbsnead@tacc.utexas.edu)\n",
    "* Anonymous reporting form available at https://www.xsede.org/codeofconduct"
   ]
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   "source": [
    "## Words Matter !\n",
    "\n",
    "In line with XSEDE’s Code of Conduct, XSEDE is committed to providing training events that foster inclusion and show respect for all. This commitment applies not only to how we interact during the event; it also applies to the training materials and presentation. It is not XSEDE’s position to use, condone, or promote offensive terminology. XSEDE has posted a [Terminology Statement](http://xsede.org/terminology) at http://xsede.org/terminology .\n",
    "\n",
    "XSEDE instructors strive to keep inclusive language at the forefront. In the event that we have included inappropriate materials, verbal or written, please let us know at terminology@xsede.org\n",
    "\n",
    "While XSEDE has no control over external third-party documentation, we are taking steps to effect change by contacting the relevant organizations; we hope this will be addressed by all third parties soon. \n",
    "\n",
    "If you see any terminology concerns in the following presentation or slides, we want to know!  \u000b",
    "Please contact the Terminology Task Force: terminology@xsede.org"
   ]
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  {
   "cell_type": "markdown",
   "metadata": {
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   "source": [
    "# XSEDE Webinar: Python Tools for Data Science\n",
    "\n",
    "<b>Chris Myers &nbsp;&nbsp; ( c.myers @ cornell.edu )<br />\n",
    "    <br />\n",
    "Center for Advanced Computing (CAC)&nbsp;&nbsp; & &nbsp;&nbsp;Department of Physics<br />\n",
    "    <br />\n",
    "Cornell University<br />\n",
    "</b>\n",
    "\n",
    "<hr />\n",
    "\n",
    "See the Cornell Virtual Workshop (CVW) tutorials on \"Python for Data Science\", by Chris Myers and Jeff Sale, at: https://cvw.cac.cornell.edu/PyDataSci1 and https://cvw.cac.cornell.edu/PyDataSci2 .  \n",
    "\n",
    "These slides are available as a Jupyter notebook in a github repository at https://github.com/CornellCAC/CVW_PyDataSci2 (in the file named PyDSWebinar.ipynb).  The talk is being recorded and will be posted on the [CAC YouTube Channel](https://www.youtube.com/channel/UCVPGMVWhp3sqWZFU5NntjTA).\n",
    "\n",
    "<table style=\"float:left\"><tr>\n",
    "    <td><img src=\"images/cornell_seal_simple_b31b1b.png\" width=\"200\"/></td>\n",
    "    <td>                      </td>\n",
    "    <td><img src=\"images/XSEDE_Logo_Blue.png\" width=\"400\"/></td>\n",
    "    </tr></table>"
   ]
  },
  {
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   "source": [
    "# Introduction\n",
    "\n",
    "* Data Science involves the amalgamation of tools and techniques from computational science, statistics, machine learning, and other fields, aimed at making sense of complex datasets and in building predictive models from those data\n",
    "    * Data access and import\n",
    "    * Data cleaning, processing, and filtering\n",
    "    * Data visualization\n",
    "    * Analysis, statistics, and modeling\n",
    "    * Machine Learning\n",
    "    * Construction of data processing pipelines to link these steps\n",
    "* Due to both its expressive language and rich ecosystem of tools and packages, Python has emerged as a central player in the world of Data Science\n"
   ]
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   "source": [
    "# Python the Language & Python the Ecosystem \n",
    "\n",
    "* <b>Python the Language</b>: interpreted, dynamically typed, object-oriented, and extensible with compiled code\n",
    "* <b>Python the Ecosystem</b>: packages, libraries and tools to support activities in a number of areas\n",
    "    * System administration\n",
    "    * Web programming\n",
    "    * Computational science, data science & machine learning\n",
    "* For numerically intensive tasks, many packages are partially written in compiled code (C/C++/Fortran) that is accessible from within Python\n",
    "    * for more details, see \"Python for High Performance\" at https://cvw.cac.cornell.edu/Python"
   ]
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   "source": [
    "# The Python Data Science Ecosystem\n",
    "\n",
    "* Most specific functionality for data science and scientific computing is provided by third-party libraries, which are typically a mix of Python code and compiled extension modules\n",
    "    * <b>NumPy</b>: multi-dimensional arrays, linear algebra, random numbers\n",
    "    * <b>SciPy</b>: routines for integration, optimization, root-finding, interpolation, etc.\n",
    "    * <b>Pandas</b>: Series and Dataframes for tabular data and statistics (e.g., from spreadsheets)\n",
    "    * <b>Scikit-learn, TensorFlow, Keras, PyTorch, Caffe</b>: machine learning\n",
    "    * <b>Matplotlib, Seaborn, Bokeh</b>: plotting & graphics\n",
    "    * <b>NetworkX</b>: networks\n",
    "    * <b>Statsmodels</b>: statistical modeling\n",
    "    * <b>SQLAlchemy</b>: interfacing to SQL databases\n",
    "    * <b>Jupyter / IPython</b>: notebooks and interactive analyses\n",
    "* Bundled distributions (e.g., Anaconda) and pip/PyPI provide support for managing packages and environments"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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    }
   },
   "source": [
    "<img src=\"images/PyDSEcosystem.png\" width=\"1000\"/>"
   ]
  },
  {
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   "metadata": {
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   },
   "source": [
    "# Datasets\n",
    "\n",
    "* <b>Baseball Databank</b>: compilation of Major League Baseball data maintained by the Chadwick Baseball Bureau\n",
    "    * consists of a set of interlinked CSV files for players, teams, etc.\n",
    "* <b>Twitter Search</b>: a set of tweets involving #ClimateChange during Nov-Dec 2018\n",
    "    * collected via the Twitter API\n",
    "* <b>California Wildfires</b>: historical data on wildfire size and duration dating back to 1895\n",
    "    * XLSX file originally provided on the Cal Fire website, derived from detailed GIS data on fire locations and extents"
   ]
  },
  {
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   "source": [
    "# Data come in many forms\n",
    "\n",
    "* Array data\n",
    "* Tabular data\n",
    "* Heterogeneous data\n",
    "* Relational data\n",
    "* Network data\n",
    "* \"Big\" data\n",
    "* Image data\n",
    "* Textual data\n",
    "* Streaming data\n",
    "* Hierarchical and aggregated data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "<img src=\"images/ArraysAndDataframes.png\"/>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Reading data tables with Pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import glob, os\n",
    "pd.set_option('max_columns', 30)\n",
    "\n",
    "def read_all_databank_core_csv(directory):\n",
    "    \"\"\"\n",
    "    read all csv files in the specified baseball databank directory and\n",
    "    populate a dictionary storing each of the tables keyed to its name\n",
    "    \"\"\"\n",
    "    dfs = {}\n",
    "    files = glob.glob('{}/*.csv'.format(directory))\n",
    "    for f in files:\n",
    "        d, name = os.path.split(f)\n",
    "        table = os.path.splitext(name)[0]\n",
    "        df = pd.read_csv(f)\n",
    "        dfs[table] = df\n",
    "    return dfs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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     "slide_type": "slide"
    }
   },
   "source": [
    "## Read in all the baseball dataframes (bbdfs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
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   },
   "outputs": [],
   "source": [
    "bbdfs = read_all_databank_core_csv('/Users/myers/repos/cvw_pydatasci1/data/baseballdatabank/core')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dict_keys(['AwardsManagers', 'Managers', 'AwardsPlayers', 'Fielding', 'Salaries', 'Parks', 'Schools', 'People', 'PitchingPost', 'Teams', 'Appearances', 'AwardsSharePlayers', 'TeamsFranchises', 'Batting', 'ManagersHalf', 'FieldingOF', 'Pitching', 'CollegePlaying', 'HomeGames', 'HallOfFame', 'AwardsShareManagers', 'BattingPost', 'TeamsHalf', 'SeriesPost', 'FieldingPost', 'AllstarFull', 'FieldingOFsplit'])\n"
     ]
    }
   ],
   "source": [
    "print(bbdfs.keys())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
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       "      <th>playerID</th>\n",
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       "      <td>abercda01</td>\n",
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       "      <th>1</th>\n",
       "      <td>addybo01</td>\n",
       "      <td>1871</td>\n",
       "      <td>1</td>\n",
       "      <td>RC1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25</td>\n",
       "      <td>118</td>\n",
       "      <td>30</td>\n",
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       "      <td>6</td>\n",
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       "      <td>allisar01</td>\n",
       "      <td>1871</td>\n",
       "      <td>1</td>\n",
       "      <td>CL1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29</td>\n",
       "      <td>137</td>\n",
       "      <td>28</td>\n",
       "      <td>40</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>allisdo01</td>\n",
       "      <td>1871</td>\n",
       "      <td>1</td>\n",
       "      <td>WS3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27</td>\n",
       "      <td>133</td>\n",
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       "      <th>4</th>\n",
       "      <td>ansonca01</td>\n",
       "      <td>1871</td>\n",
       "      <td>1</td>\n",
       "      <td>RC1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25</td>\n",
       "      <td>120</td>\n",
       "      <td>29</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
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       "    playerID  yearID  stint teamID lgID   G   AB   R   H  2B  3B  HR   RBI  \\\n",
       "0  abercda01    1871      1    TRO  NaN   1    4   0   0   0   0   0   0.0   \n",
       "1   addybo01    1871      1    RC1  NaN  25  118  30  32   6   0   0  13.0   \n",
       "2  allisar01    1871      1    CL1  NaN  29  137  28  40   4   5   0  19.0   \n",
       "3  allisdo01    1871      1    WS3  NaN  27  133  28  44  10   2   2  27.0   \n",
       "4  ansonca01    1871      1    RC1  NaN  25  120  29  39  11   3   0  16.0   \n",
       "\n",
       "    SB   CS  BB   SO  IBB  HBP  SH  SF  GIDP  \n",
       "0  0.0  0.0   0  0.0  NaN  NaN NaN NaN   0.0  \n",
       "1  8.0  1.0   4  0.0  NaN  NaN NaN NaN   0.0  \n",
       "2  3.0  1.0   2  5.0  NaN  NaN NaN NaN   1.0  \n",
       "3  1.0  1.0   0  2.0  NaN  NaN NaN NaN   0.0  \n",
       "4  6.0  2.0   2  1.0  NaN  NaN NaN NaN   0.0  "
      ]
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     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bbdfs['Batting'].head()   # note missing data - NaN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
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       "      <th>franchID</th>\n",
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       "      <th>WCWin</th>\n",
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       "      <th>WSWin</th>\n",
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       "      <th>attendance</th>\n",
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       "      <td>...</td>\n",
       "      <td>367</td>\n",
       "      <td>2</td>\n",
       "      <td>42</td>\n",
       "      <td>23</td>\n",
       "      <td>243</td>\n",
       "      <td>24</td>\n",
       "      <td>0.834</td>\n",
       "      <td>Boston Red Stockings</td>\n",
       "      <td>South End Grounds I</td>\n",
       "      <td>NaN</td>\n",
       "      <td>103</td>\n",
       "      <td>98</td>\n",
       "      <td>BOS</td>\n",
       "      <td>BS1</td>\n",
       "      <td>BS1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1871</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CH1</td>\n",
       "      <td>CNA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>28</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19</td>\n",
       "      <td>9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>NaN</td>\n",
       "      <td>302</td>\n",
       "      <td>...</td>\n",
       "      <td>308</td>\n",
       "      <td>6</td>\n",
       "      <td>28</td>\n",
       "      <td>22</td>\n",
       "      <td>229</td>\n",
       "      <td>16</td>\n",
       "      <td>0.829</td>\n",
       "      <td>Chicago White Stockings</td>\n",
       "      <td>Union Base-Ball Grounds</td>\n",
       "      <td>NaN</td>\n",
       "      <td>104</td>\n",
       "      <td>102</td>\n",
       "      <td>CHI</td>\n",
       "      <td>CH1</td>\n",
       "      <td>CH1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1871</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CL1</td>\n",
       "      <td>CFC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8</td>\n",
       "      <td>29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10</td>\n",
       "      <td>19</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>NaN</td>\n",
       "      <td>249</td>\n",
       "      <td>...</td>\n",
       "      <td>346</td>\n",
       "      <td>13</td>\n",
       "      <td>53</td>\n",
       "      <td>34</td>\n",
       "      <td>234</td>\n",
       "      <td>15</td>\n",
       "      <td>0.818</td>\n",
       "      <td>Cleveland Forest Citys</td>\n",
       "      <td>National Association Grounds</td>\n",
       "      <td>NaN</td>\n",
       "      <td>96</td>\n",
       "      <td>100</td>\n",
       "      <td>CLE</td>\n",
       "      <td>CL1</td>\n",
       "      <td>CL1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1871</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FW1</td>\n",
       "      <td>KEK</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7</td>\n",
       "      <td>19</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7</td>\n",
       "      <td>12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>NaN</td>\n",
       "      <td>137</td>\n",
       "      <td>...</td>\n",
       "      <td>261</td>\n",
       "      <td>5</td>\n",
       "      <td>21</td>\n",
       "      <td>17</td>\n",
       "      <td>163</td>\n",
       "      <td>8</td>\n",
       "      <td>0.803</td>\n",
       "      <td>Fort Wayne Kekiongas</td>\n",
       "      <td>Hamilton Field</td>\n",
       "      <td>NaN</td>\n",
       "      <td>101</td>\n",
       "      <td>107</td>\n",
       "      <td>KEK</td>\n",
       "      <td>FW1</td>\n",
       "      <td>FW1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1871</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NY2</td>\n",
       "      <td>NNA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5</td>\n",
       "      <td>33</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16</td>\n",
       "      <td>17</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>NaN</td>\n",
       "      <td>302</td>\n",
       "      <td>...</td>\n",
       "      <td>373</td>\n",
       "      <td>7</td>\n",
       "      <td>42</td>\n",
       "      <td>22</td>\n",
       "      <td>235</td>\n",
       "      <td>14</td>\n",
       "      <td>0.840</td>\n",
       "      <td>New York Mutuals</td>\n",
       "      <td>Union Grounds (Brooklyn)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>90</td>\n",
       "      <td>88</td>\n",
       "      <td>NYU</td>\n",
       "      <td>NY2</td>\n",
       "      <td>NY2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 48 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   yearID lgID teamID franchID divID  Rank   G  Ghome   W   L DivWin WCWin  \\\n",
       "0    1871  NaN    BS1      BNA   NaN     3  31    NaN  20  10    NaN   NaN   \n",
       "1    1871  NaN    CH1      CNA   NaN     2  28    NaN  19   9    NaN   NaN   \n",
       "2    1871  NaN    CL1      CFC   NaN     8  29    NaN  10  19    NaN   NaN   \n",
       "3    1871  NaN    FW1      KEK   NaN     7  19    NaN   7  12    NaN   NaN   \n",
       "4    1871  NaN    NY2      NNA   NaN     5  33    NaN  16  17    NaN   NaN   \n",
       "\n",
       "  LgWin WSWin    R  ...   HA  HRA  BBA  SOA    E  DP     FP  \\\n",
       "0     N   NaN  401  ...  367    2   42   23  243  24  0.834   \n",
       "1     N   NaN  302  ...  308    6   28   22  229  16  0.829   \n",
       "2     N   NaN  249  ...  346   13   53   34  234  15  0.818   \n",
       "3     N   NaN  137  ...  261    5   21   17  163   8  0.803   \n",
       "4     N   NaN  302  ...  373    7   42   22  235  14  0.840   \n",
       "\n",
       "                      name                          park  attendance  BPF  \\\n",
       "0     Boston Red Stockings           South End Grounds I         NaN  103   \n",
       "1  Chicago White Stockings       Union Base-Ball Grounds         NaN  104   \n",
       "2   Cleveland Forest Citys  National Association Grounds         NaN   96   \n",
       "3     Fort Wayne Kekiongas                Hamilton Field         NaN  101   \n",
       "4         New York Mutuals      Union Grounds (Brooklyn)         NaN   90   \n",
       "\n",
       "   PPF  teamIDBR  teamIDlahman45  teamIDretro  \n",
       "0   98       BOS             BS1          BS1  \n",
       "1  102       CHI             CH1          CH1  \n",
       "2  100       CLE             CL1          CL1  \n",
       "3  107       KEK             FW1          FW1  \n",
       "4   88       NYU             NY2          NY2  \n",
       "\n",
       "[5 rows x 48 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bbdfs['Teams'].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Adding derived data: calculating singles (1B) from H,2B,3B,HR\n",
    "   \n",
    "Sometimes, our dataset doesn't contain all the information that we might want, but perhaps we can augment it with additional data. For example, the baseball batting dataset does not contain information about the number of singles (i.e., one-base hits in which the batter reached first base safely and remained there until the next batter batted), but that information can be derived from other data. \n",
    "\n",
    "Since the dataset contains information about the total number of hits H, as well as the number of 2B, 3B and HR, we can define an additional column in both the batting and teams dataframes to compute the number of singles (1B). Note the 1B data has been added as the last column.           \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\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>playerID</th>\n",
       "      <th>yearID</th>\n",
       "      <th>stint</th>\n",
       "      <th>teamID</th>\n",
       "      <th>lgID</th>\n",
       "      <th>G</th>\n",
       "      <th>AB</th>\n",
       "      <th>R</th>\n",
       "      <th>H</th>\n",
       "      <th>2B</th>\n",
       "      <th>3B</th>\n",
       "      <th>HR</th>\n",
       "      <th>RBI</th>\n",
       "      <th>SB</th>\n",
       "      <th>CS</th>\n",
       "      <th>BB</th>\n",
       "      <th>SO</th>\n",
       "      <th>IBB</th>\n",
       "      <th>HBP</th>\n",
       "      <th>SH</th>\n",
       "      <th>SF</th>\n",
       "      <th>GIDP</th>\n",
       "      <th>1B</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>abercda01</td>\n",
       "      <td>1871</td>\n",
       "      <td>1</td>\n",
       "      <td>TRO</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>addybo01</td>\n",
       "      <td>1871</td>\n",
       "      <td>1</td>\n",
       "      <td>RC1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25</td>\n",
       "      <td>118</td>\n",
       "      <td>30</td>\n",
       "      <td>32</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>allisar01</td>\n",
       "      <td>1871</td>\n",
       "      <td>1</td>\n",
       "      <td>CL1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29</td>\n",
       "      <td>137</td>\n",
       "      <td>28</td>\n",
       "      <td>40</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>allisdo01</td>\n",
       "      <td>1871</td>\n",
       "      <td>1</td>\n",
       "      <td>WS3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27</td>\n",
       "      <td>133</td>\n",
       "      <td>28</td>\n",
       "      <td>44</td>\n",
       "      <td>10</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>27.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ansonca01</td>\n",
       "      <td>1871</td>\n",
       "      <td>1</td>\n",
       "      <td>RC1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25</td>\n",
       "      <td>120</td>\n",
       "      <td>29</td>\n",
       "      <td>39</td>\n",
       "      <td>11</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    playerID  yearID  stint teamID lgID   G   AB   R   H  2B  3B  HR   RBI  \\\n",
       "0  abercda01    1871      1    TRO  NaN   1    4   0   0   0   0   0   0.0   \n",
       "1   addybo01    1871      1    RC1  NaN  25  118  30  32   6   0   0  13.0   \n",
       "2  allisar01    1871      1    CL1  NaN  29  137  28  40   4   5   0  19.0   \n",
       "3  allisdo01    1871      1    WS3  NaN  27  133  28  44  10   2   2  27.0   \n",
       "4  ansonca01    1871      1    RC1  NaN  25  120  29  39  11   3   0  16.0   \n",
       "\n",
       "    SB   CS  BB   SO  IBB  HBP  SH  SF  GIDP  1B  \n",
       "0  0.0  0.0   0  0.0  NaN  NaN NaN NaN   0.0   0  \n",
       "1  8.0  1.0   4  0.0  NaN  NaN NaN NaN   0.0  26  \n",
       "2  3.0  1.0   2  5.0  NaN  NaN NaN NaN   1.0  31  \n",
       "3  1.0  1.0   0  2.0  NaN  NaN NaN NaN   0.0  30  \n",
       "4  6.0  2.0   2  1.0  NaN  NaN NaN NaN   0.0  25  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# let's extract a few dataframes for further processing\n",
    "batting = bbdfs['Batting']\n",
    "pitching = bbdfs['Pitching']\n",
    "teams = bbdfs['Teams']\n",
    "\n",
    "batting['1B'] = batting['H'] - batting['2B'] - batting['3B'] - batting['HR']\n",
    "teams['1B'] = teams['H'] - teams['2B'] - teams['3B'] - teams['HR']\n",
    "batting.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Descriptive statistics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>yearID</th>\n",
       "      <th>lgID</th>\n",
       "      <th>teamID</th>\n",
       "      <th>franchID</th>\n",
       "      <th>divID</th>\n",
       "      <th>Rank</th>\n",
       "      <th>G</th>\n",
       "      <th>Ghome</th>\n",
       "      <th>W</th>\n",
       "      <th>L</th>\n",
       "      <th>DivWin</th>\n",
       "      <th>WCWin</th>\n",
       "      <th>LgWin</th>\n",
       "      <th>WSWin</th>\n",
       "      <th>R</th>\n",
       "      <th>...</th>\n",
       "      <th>HRA</th>\n",
       "      <th>BBA</th>\n",
       "      <th>SOA</th>\n",
       "      <th>E</th>\n",
       "      <th>DP</th>\n",
       "      <th>FP</th>\n",
       "      <th>name</th>\n",
       "      <th>park</th>\n",
       "      <th>attendance</th>\n",
       "      <th>BPF</th>\n",
       "      <th>PPF</th>\n",
       "      <th>teamIDBR</th>\n",
       "      <th>teamIDlahman45</th>\n",
       "      <th>teamIDretro</th>\n",
       "      <th>1B</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1871</td>\n",
       "      <td>NaN</td>\n",
       "      <td>BS1</td>\n",
       "      <td>BNA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>31</td>\n",
       "      <td>NaN</td>\n",
       "      <td>20</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>NaN</td>\n",
       "      <td>401</td>\n",
       "      <td>...</td>\n",
       "      <td>2</td>\n",
       "      <td>42</td>\n",
       "      <td>23</td>\n",
       "      <td>243</td>\n",
       "      <td>24</td>\n",
       "      <td>0.834</td>\n",
       "      <td>Boston Red Stockings</td>\n",
       "      <td>South End Grounds I</td>\n",
       "      <td>NaN</td>\n",
       "      <td>103</td>\n",
       "      <td>98</td>\n",
       "      <td>BOS</td>\n",
       "      <td>BS1</td>\n",
       "      <td>BS1</td>\n",
       "      <td>316</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1871</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CH1</td>\n",
       "      <td>CNA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "      <td>28</td>\n",
       "      <td>NaN</td>\n",
       "      <td>19</td>\n",
       "      <td>9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>NaN</td>\n",
       "      <td>302</td>\n",
       "      <td>...</td>\n",
       "      <td>6</td>\n",
       "      <td>28</td>\n",
       "      <td>22</td>\n",
       "      <td>229</td>\n",
       "      <td>16</td>\n",
       "      <td>0.829</td>\n",
       "      <td>Chicago White Stockings</td>\n",
       "      <td>Union Base-Ball Grounds</td>\n",
       "      <td>NaN</td>\n",
       "      <td>104</td>\n",
       "      <td>102</td>\n",
       "      <td>CHI</td>\n",
       "      <td>CH1</td>\n",
       "      <td>CH1</td>\n",
       "      <td>240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1871</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CL1</td>\n",
       "      <td>CFC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8</td>\n",
       "      <td>29</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10</td>\n",
       "      <td>19</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>NaN</td>\n",
       "      <td>249</td>\n",
       "      <td>...</td>\n",
       "      <td>13</td>\n",
       "      <td>53</td>\n",
       "      <td>34</td>\n",
       "      <td>234</td>\n",
       "      <td>15</td>\n",
       "      <td>0.818</td>\n",
       "      <td>Cleveland Forest Citys</td>\n",
       "      <td>National Association Grounds</td>\n",
       "      <td>NaN</td>\n",
       "      <td>96</td>\n",
       "      <td>100</td>\n",
       "      <td>CLE</td>\n",
       "      <td>CL1</td>\n",
       "      <td>CL1</td>\n",
       "      <td>246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1871</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FW1</td>\n",
       "      <td>KEK</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7</td>\n",
       "      <td>19</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7</td>\n",
       "      <td>12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>NaN</td>\n",
       "      <td>137</td>\n",
       "      <td>...</td>\n",
       "      <td>5</td>\n",
       "      <td>21</td>\n",
       "      <td>17</td>\n",
       "      <td>163</td>\n",
       "      <td>8</td>\n",
       "      <td>0.803</td>\n",
       "      <td>Fort Wayne Kekiongas</td>\n",
       "      <td>Hamilton Field</td>\n",
       "      <td>NaN</td>\n",
       "      <td>101</td>\n",
       "      <td>107</td>\n",
       "      <td>KEK</td>\n",
       "      <td>FW1</td>\n",
       "      <td>FW1</td>\n",
       "      <td>149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1871</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NY2</td>\n",
       "      <td>NNA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5</td>\n",
       "      <td>33</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16</td>\n",
       "      <td>17</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>N</td>\n",
       "      <td>NaN</td>\n",
       "      <td>302</td>\n",
       "      <td>...</td>\n",
       "      <td>7</td>\n",
       "      <td>42</td>\n",
       "      <td>22</td>\n",
       "      <td>235</td>\n",
       "      <td>14</td>\n",
       "      <td>0.840</td>\n",
       "      <td>New York Mutuals</td>\n",
       "      <td>Union Grounds (Brooklyn)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>90</td>\n",
       "      <td>88</td>\n",
       "      <td>NYU</td>\n",
       "      <td>NY2</td>\n",
       "      <td>NY2</td>\n",
       "      <td>338</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 49 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   yearID lgID teamID franchID divID  Rank   G  Ghome   W   L DivWin WCWin  \\\n",
       "0    1871  NaN    BS1      BNA   NaN     3  31    NaN  20  10    NaN   NaN   \n",
       "1    1871  NaN    CH1      CNA   NaN     2  28    NaN  19   9    NaN   NaN   \n",
       "2    1871  NaN    CL1      CFC   NaN     8  29    NaN  10  19    NaN   NaN   \n",
       "3    1871  NaN    FW1      KEK   NaN     7  19    NaN   7  12    NaN   NaN   \n",
       "4    1871  NaN    NY2      NNA   NaN     5  33    NaN  16  17    NaN   NaN   \n",
       "\n",
       "  LgWin WSWin    R  ...  HRA  BBA  SOA    E  DP     FP  \\\n",
       "0     N   NaN  401  ...    2   42   23  243  24  0.834   \n",
       "1     N   NaN  302  ...    6   28   22  229  16  0.829   \n",
       "2     N   NaN  249  ...   13   53   34  234  15  0.818   \n",
       "3     N   NaN  137  ...    5   21   17  163   8  0.803   \n",
       "4     N   NaN  302  ...    7   42   22  235  14  0.840   \n",
       "\n",
       "                      name                          park  attendance  BPF  \\\n",
       "0     Boston Red Stockings           South End Grounds I         NaN  103   \n",
       "1  Chicago White Stockings       Union Base-Ball Grounds         NaN  104   \n",
       "2   Cleveland Forest Citys  National Association Grounds         NaN   96   \n",
       "3     Fort Wayne Kekiongas                Hamilton Field         NaN  101   \n",
       "4         New York Mutuals      Union Grounds (Brooklyn)         NaN   90   \n",
       "\n",
       "   PPF  teamIDBR  teamIDlahman45  teamIDretro   1B  \n",
       "0   98       BOS             BS1          BS1  316  \n",
       "1  102       CHI             CH1          CH1  240  \n",
       "2  100       CLE             CL1          CL1  246  \n",
       "3  107       KEK             FW1          FW1  149  \n",
       "4   88       NYU             NY2          NY2  338  \n",
       "\n",
       "[5 rows x 49 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "teams.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>yearID</th>\n",
       "      <th>Rank</th>\n",
       "      <th>G</th>\n",
       "      <th>Ghome</th>\n",
       "      <th>W</th>\n",
       "      <th>L</th>\n",
       "      <th>R</th>\n",
       "      <th>AB</th>\n",
       "      <th>H</th>\n",
       "      <th>2B</th>\n",
       "      <th>3B</th>\n",
       "      <th>HR</th>\n",
       "      <th>BB</th>\n",
       "      <th>SO</th>\n",
       "      <th>SB</th>\n",
       "      <th>...</th>\n",
       "      <th>CG</th>\n",
       "      <th>SHO</th>\n",
       "      <th>SV</th>\n",
       "      <th>IPouts</th>\n",
       "      <th>HA</th>\n",
       "      <th>HRA</th>\n",
       "      <th>BBA</th>\n",
       "      <th>SOA</th>\n",
       "      <th>E</th>\n",
       "      <th>DP</th>\n",
       "      <th>FP</th>\n",
       "      <th>attendance</th>\n",
       "      <th>BPF</th>\n",
       "      <th>PPF</th>\n",
       "      <th>1B</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>2895.000000</td>\n",
       "      <td>2895.000000</td>\n",
       "      <td>2895.000000</td>\n",
       "      <td>2496.000000</td>\n",
       "      <td>2895.000000</td>\n",
       "      <td>2895.000000</td>\n",
       "      <td>2895.000000</td>\n",
       "      <td>2895.000000</td>\n",
       "      <td>2895.000000</td>\n",
       "      <td>2895.000000</td>\n",
       "      <td>2895.000000</td>\n",
       "      <td>2895.000000</td>\n",
       "      <td>2894.000000</td>\n",
       "      <td>2879.000000</td>\n",
       "      <td>2769.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>2895.000000</td>\n",
       "      <td>2895.000000</td>\n",
       "      <td>2895.000000</td>\n",
       "      <td>2895.000000</td>\n",
       "      <td>2895.000000</td>\n",
       "      <td>2895.000000</td>\n",
       "      <td>2895.000000</td>\n",
       "      <td>2895.000000</td>\n",
       "      <td>2895.000000</td>\n",
       "      <td>2895.000000</td>\n",
       "      <td>2895.000000</td>\n",
       "      <td>2.616000e+03</td>\n",
       "      <td>2895.000000</td>\n",
       "      <td>2895.000000</td>\n",
       "      <td>2895.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1956.963040</td>\n",
       "      <td>4.072539</td>\n",
       "      <td>150.692919</td>\n",
       "      <td>78.556891</td>\n",
       "      <td>74.942314</td>\n",
       "      <td>74.942314</td>\n",
       "      <td>683.611744</td>\n",
       "      <td>5154.547496</td>\n",
       "      <td>1347.913644</td>\n",
       "      <td>229.140933</td>\n",
       "      <td>46.506736</td>\n",
       "      <td>103.967530</td>\n",
       "      <td>475.229440</td>\n",
       "      <td>751.031956</td>\n",
       "      <td>111.022391</td>\n",
       "      <td>...</td>\n",
       "      <td>48.980656</td>\n",
       "      <td>9.685665</td>\n",
       "      <td>24.216235</td>\n",
       "      <td>4032.811744</td>\n",
       "      <td>1347.686356</td>\n",
       "      <td>103.967530</td>\n",
       "      <td>475.424870</td>\n",
       "      <td>750.522971</td>\n",
       "      <td>184.138860</td>\n",
       "      <td>133.539551</td>\n",
       "      <td>0.965802</td>\n",
       "      <td>1.380458e+06</td>\n",
       "      <td>100.194128</td>\n",
       "      <td>100.217271</td>\n",
       "      <td>968.298446</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>42.260337</td>\n",
       "      <td>2.308810</td>\n",
       "      <td>22.968790</td>\n",
       "      <td>4.638081</td>\n",
       "      <td>17.530459</td>\n",
       "      <td>17.274056</td>\n",
       "      <td>134.572259</td>\n",
       "      <td>741.546183</td>\n",
       "      <td>216.989317</td>\n",
       "      <td>58.673209</td>\n",
       "      <td>22.260486</td>\n",
       "      <td>62.781245</td>\n",
       "      <td>130.915516</td>\n",
       "      <td>308.694949</td>\n",
       "      <td>70.055574</td>\n",
       "      <td>...</td>\n",
       "      <td>39.056428</td>\n",
       "      <td>5.032649</td>\n",
       "      <td>16.351810</td>\n",
       "      <td>623.227983</td>\n",
       "      <td>216.955229</td>\n",
       "      <td>59.625974</td>\n",
       "      <td>130.396145</td>\n",
       "      <td>309.842690</td>\n",
       "      <td>108.208599</td>\n",
       "      <td>35.302549</td>\n",
       "      <td>0.029347</td>\n",
       "      <td>9.578068e+05</td>\n",
       "      <td>4.919002</td>\n",
       "      <td>4.846016</td>\n",
       "      <td>147.071761</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1871.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>44.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>211.000000</td>\n",
       "      <td>33.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>162.000000</td>\n",
       "      <td>49.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>47.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.761000</td>\n",
       "      <td>6.088000e+03</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>32.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1921.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>154.000000</td>\n",
       "      <td>77.000000</td>\n",
       "      <td>66.000000</td>\n",
       "      <td>66.000000</td>\n",
       "      <td>615.000000</td>\n",
       "      <td>5142.000000</td>\n",
       "      <td>1303.000000</td>\n",
       "      <td>195.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>43.000000</td>\n",
       "      <td>427.000000</td>\n",
       "      <td>513.500000</td>\n",
       "      <td>64.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>4080.000000</td>\n",
       "      <td>1290.500000</td>\n",
       "      <td>49.000000</td>\n",
       "      <td>430.000000</td>\n",
       "      <td>506.500000</td>\n",
       "      <td>114.000000</td>\n",
       "      <td>117.000000</td>\n",
       "      <td>0.965000</td>\n",
       "      <td>5.447818e+05</td>\n",
       "      <td>97.000000</td>\n",
       "      <td>97.000000</td>\n",
       "      <td>929.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1965.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>158.000000</td>\n",
       "      <td>81.000000</td>\n",
       "      <td>77.000000</td>\n",
       "      <td>76.000000</td>\n",
       "      <td>691.000000</td>\n",
       "      <td>5404.000000</td>\n",
       "      <td>1393.000000</td>\n",
       "      <td>233.000000</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>109.000000</td>\n",
       "      <td>494.000000</td>\n",
       "      <td>755.000000</td>\n",
       "      <td>94.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>43.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>4251.000000</td>\n",
       "      <td>1392.000000</td>\n",
       "      <td>112.000000</td>\n",
       "      <td>496.000000</td>\n",
       "      <td>754.000000</td>\n",
       "      <td>143.000000</td>\n",
       "      <td>141.000000</td>\n",
       "      <td>0.977000</td>\n",
       "      <td>1.185781e+06</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>990.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1994.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>162.000000</td>\n",
       "      <td>81.000000</td>\n",
       "      <td>87.000000</td>\n",
       "      <td>87.000000</td>\n",
       "      <td>764.000000</td>\n",
       "      <td>5520.500000</td>\n",
       "      <td>1466.000000</td>\n",
       "      <td>272.000000</td>\n",
       "      <td>59.000000</td>\n",
       "      <td>153.000000</td>\n",
       "      <td>554.000000</td>\n",
       "      <td>980.500000</td>\n",
       "      <td>139.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>77.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>38.000000</td>\n",
       "      <td>4342.000000</td>\n",
       "      <td>1470.000000</td>\n",
       "      <td>152.000000</td>\n",
       "      <td>554.000000</td>\n",
       "      <td>985.500000</td>\n",
       "      <td>212.000000</td>\n",
       "      <td>157.000000</td>\n",
       "      <td>0.981000</td>\n",
       "      <td>2.065338e+06</td>\n",
       "      <td>103.000000</td>\n",
       "      <td>103.000000</td>\n",
       "      <td>1046.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2018.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>165.000000</td>\n",
       "      <td>84.000000</td>\n",
       "      <td>116.000000</td>\n",
       "      <td>134.000000</td>\n",
       "      <td>1220.000000</td>\n",
       "      <td>5781.000000</td>\n",
       "      <td>1783.000000</td>\n",
       "      <td>376.000000</td>\n",
       "      <td>150.000000</td>\n",
       "      <td>267.000000</td>\n",
       "      <td>835.000000</td>\n",
       "      <td>1594.000000</td>\n",
       "      <td>581.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>148.000000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>68.000000</td>\n",
       "      <td>4518.000000</td>\n",
       "      <td>1993.000000</td>\n",
       "      <td>258.000000</td>\n",
       "      <td>827.000000</td>\n",
       "      <td>1687.000000</td>\n",
       "      <td>639.000000</td>\n",
       "      <td>217.000000</td>\n",
       "      <td>0.991000</td>\n",
       "      <td>4.483350e+06</td>\n",
       "      <td>129.000000</td>\n",
       "      <td>141.000000</td>\n",
       "      <td>1345.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 36 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            yearID         Rank            G        Ghome            W  \\\n",
       "count  2895.000000  2895.000000  2895.000000  2496.000000  2895.000000   \n",
       "mean   1956.963040     4.072539   150.692919    78.556891    74.942314   \n",
       "std      42.260337     2.308810    22.968790     4.638081    17.530459   \n",
       "min    1871.000000     1.000000     6.000000    44.000000     0.000000   \n",
       "25%    1921.000000     2.000000   154.000000    77.000000    66.000000   \n",
       "50%    1965.000000     4.000000   158.000000    81.000000    77.000000   \n",
       "75%    1994.000000     6.000000   162.000000    81.000000    87.000000   \n",
       "max    2018.000000    13.000000   165.000000    84.000000   116.000000   \n",
       "\n",
       "                 L            R           AB            H           2B  \\\n",
       "count  2895.000000  2895.000000  2895.000000  2895.000000  2895.000000   \n",
       "mean     74.942314   683.611744  5154.547496  1347.913644   229.140933   \n",
       "std      17.274056   134.572259   741.546183   216.989317    58.673209   \n",
       "min       4.000000    24.000000   211.000000    33.000000     1.000000   \n",
       "25%      66.000000   615.000000  5142.000000  1303.000000   195.000000   \n",
       "50%      76.000000   691.000000  5404.000000  1393.000000   233.000000   \n",
       "75%      87.000000   764.000000  5520.500000  1466.000000   272.000000   \n",
       "max     134.000000  1220.000000  5781.000000  1783.000000   376.000000   \n",
       "\n",
       "                3B           HR           BB           SO           SB  ...  \\\n",
       "count  2895.000000  2895.000000  2894.000000  2879.000000  2769.000000  ...   \n",
       "mean     46.506736   103.967530   475.229440   751.031956   111.022391  ...   \n",
       "std      22.260486    62.781245   130.915516   308.694949    70.055574  ...   \n",
       "min       0.000000     0.000000     1.000000     3.000000     1.000000  ...   \n",
       "25%      30.000000    43.000000   427.000000   513.500000    64.000000  ...   \n",
       "50%      41.000000   109.000000   494.000000   755.000000    94.000000  ...   \n",
       "75%      59.000000   153.000000   554.000000   980.500000   139.000000  ...   \n",
       "max     150.000000   267.000000   835.000000  1594.000000   581.000000  ...   \n",
       "\n",
       "                CG          SHO           SV       IPouts           HA  \\\n",
       "count  2895.000000  2895.000000  2895.000000  2895.000000  2895.000000   \n",
       "mean     48.980656     9.685665    24.216235  4032.811744  1347.686356   \n",
       "std      39.056428     5.032649    16.351810   623.227983   216.955229   \n",
       "min       0.000000     0.000000     0.000000   162.000000    49.000000   \n",
       "25%      11.000000     6.000000     9.000000  4080.000000  1290.500000   \n",
       "50%      43.000000     9.000000    25.000000  4251.000000  1392.000000   \n",
       "75%      77.000000    13.000000    38.000000  4342.000000  1470.000000   \n",
       "max     148.000000    32.000000    68.000000  4518.000000  1993.000000   \n",
       "\n",
       "               HRA          BBA          SOA            E           DP  \\\n",
       "count  2895.000000  2895.000000  2895.000000  2895.000000  2895.000000   \n",
       "mean    103.967530   475.424870   750.522971   184.138860   133.539551   \n",
       "std      59.625974   130.396145   309.842690   108.208599    35.302549   \n",
       "min       0.000000     1.000000     0.000000    47.000000     0.000000   \n",
       "25%      49.000000   430.000000   506.500000   114.000000   117.000000   \n",
       "50%     112.000000   496.000000   754.000000   143.000000   141.000000   \n",
       "75%     152.000000   554.000000   985.500000   212.000000   157.000000   \n",
       "max     258.000000   827.000000  1687.000000   639.000000   217.000000   \n",
       "\n",
       "                FP    attendance          BPF          PPF           1B  \n",
       "count  2895.000000  2.616000e+03  2895.000000  2895.000000  2895.000000  \n",
       "mean      0.965802  1.380458e+06   100.194128   100.217271   968.298446  \n",
       "std       0.029347  9.578068e+05     4.919002     4.846016   147.071761  \n",
       "min       0.761000  6.088000e+03    60.000000    60.000000    32.000000  \n",
       "25%       0.965000  5.447818e+05    97.000000    97.000000   929.000000  \n",
       "50%       0.977000  1.185781e+06   100.000000   100.000000   990.000000  \n",
       "75%       0.981000  2.065338e+06   103.000000   103.000000  1046.000000  \n",
       "max       0.991000  4.483350e+06   129.000000   141.000000  1345.000000  \n",
       "\n",
       "[8 rows x 36 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "teams.describe()     # note the result is a new dataframe"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Groupby operations\n",
    "\n",
    "An extremely powerful set of capabilities is provided by the <code>groupby</code> method on dataframes, which provides support for <i>split-apply-combine</i> operations.  This means, for example, that we can:\n",
    "<ul>\n",
    "    <li><i>split</i> a dataframe into groups based on identity of a specified key or some other criterion\n",
    "            <li><i>apply</i> an aggregating function across each of the subgroups, and then <li> <i>combine</i> the aggregated information back in a single dataframe  \n",
    "    </ul>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "Each row in the <code>batting</code> dataframe contains information about a single player in a single year.  What if we wanted to know the totals of all of those statistics, on a year-by-year basis.  We can create a new dataframe by grouping by the <code>'yearID'</code> and then summing each of those year-by-year groups."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>playerID</th>\n",
       "      <th>yearID</th>\n",
       "      <th>stint</th>\n",
       "      <th>teamID</th>\n",
       "      <th>lgID</th>\n",
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       "      <th>IBB</th>\n",
       "      <th>HBP</th>\n",
       "      <th>SH</th>\n",
       "      <th>SF</th>\n",
       "      <th>GIDP</th>\n",
       "      <th>1B</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>abercda01</td>\n",
       "      <td>1871</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>addybo01</td>\n",
       "      <td>1871</td>\n",
       "      <td>1</td>\n",
       "      <td>RC1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25</td>\n",
       "      <td>118</td>\n",
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       "      <td>6</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>allisar01</td>\n",
       "      <td>1871</td>\n",
       "      <td>1</td>\n",
       "      <td>CL1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>29</td>\n",
       "      <td>137</td>\n",
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       "      <td>40</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>allisdo01</td>\n",
       "      <td>1871</td>\n",
       "      <td>1</td>\n",
       "      <td>WS3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ansonca01</td>\n",
       "      <td>1871</td>\n",
       "      <td>1</td>\n",
       "      <td>RC1</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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       "</div>"
      ],
      "text/plain": [
       "    playerID  yearID  stint teamID lgID   G   AB   R   H  2B  3B  HR   RBI  \\\n",
       "0  abercda01    1871      1    TRO  NaN   1    4   0   0   0   0   0   0.0   \n",
       "1   addybo01    1871      1    RC1  NaN  25  118  30  32   6   0   0  13.0   \n",
       "2  allisar01    1871      1    CL1  NaN  29  137  28  40   4   5   0  19.0   \n",
       "3  allisdo01    1871      1    WS3  NaN  27  133  28  44  10   2   2  27.0   \n",
       "4  ansonca01    1871      1    RC1  NaN  25  120  29  39  11   3   0  16.0   \n",
       "\n",
       "    SB   CS  BB   SO  IBB  HBP  SH  SF  GIDP  1B  \n",
       "0  0.0  0.0   0  0.0  NaN  NaN NaN NaN   0.0   0  \n",
       "1  8.0  1.0   4  0.0  NaN  NaN NaN NaN   0.0  26  \n",
       "2  3.0  1.0   2  5.0  NaN  NaN NaN NaN   1.0  31  \n",
       "3  1.0  1.0   0  2.0  NaN  NaN NaN NaN   0.0  30  \n",
       "4  6.0  2.0   2  1.0  NaN  NaN NaN NaN   0.0  25  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "batting.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1871</th>\n",
       "      <td>115</td>\n",
       "      <td>2296</td>\n",
       "      <td>10822</td>\n",
       "      <td>2659</td>\n",
       "      <td>3101</td>\n",
       "      <td>434</td>\n",
       "      <td>239</td>\n",
       "      <td>47</td>\n",
       "      <td>1783.0</td>\n",
       "      <td>441.0</td>\n",
       "      <td>123.0</td>\n",
       "      <td>393</td>\n",
       "      <td>175.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>74.0</td>\n",
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       "    <tr>\n",
       "      <th>1872</th>\n",
       "      <td>172</td>\n",
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       "      <td>15663</td>\n",
       "      <td>3390</td>\n",
       "      <td>4467</td>\n",
       "      <td>581</td>\n",
       "      <td>145</td>\n",
       "      <td>37</td>\n",
       "      <td>2132.0</td>\n",
       "      <td>269.0</td>\n",
       "      <td>134.0</td>\n",
       "      <td>263</td>\n",
       "      <td>264.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>3704</td>\n",
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       "    <tr>\n",
       "      <th>1873</th>\n",
       "      <td>128</td>\n",
       "      <td>3604</td>\n",
       "      <td>16959</td>\n",
       "      <td>3580</td>\n",
       "      <td>4926</td>\n",
       "      <td>570</td>\n",
       "      <td>211</td>\n",
       "      <td>47</td>\n",
       "      <td>2331.0</td>\n",
       "      <td>314.0</td>\n",
       "      <td>131.0</td>\n",
       "      <td>335</td>\n",
       "      <td>278.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>122.0</td>\n",
       "      <td>4098</td>\n",
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       "    <tr>\n",
       "      <th>1874</th>\n",
       "      <td>126</td>\n",
       "      <td>4199</td>\n",
       "      <td>19104</td>\n",
       "      <td>3470</td>\n",
       "      <td>5224</td>\n",
       "      <td>634</td>\n",
       "      <td>194</td>\n",
       "      <td>40</td>\n",
       "      <td>2252.0</td>\n",
       "      <td>242.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>238</td>\n",
       "      <td>357.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>107.0</td>\n",
       "      <td>4356</td>\n",
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       "    <tr>\n",
       "      <th>1875</th>\n",
       "      <td>248</td>\n",
       "      <td>6248</td>\n",
       "      <td>26833</td>\n",
       "      <td>4234</td>\n",
       "      <td>6812</td>\n",
       "      <td>839</td>\n",
       "      <td>273</td>\n",
       "      <td>40</td>\n",
       "      <td>2710.0</td>\n",
       "      <td>629.0</td>\n",
       "      <td>320.0</td>\n",
       "      <td>249</td>\n",
       "      <td>675.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>142.0</td>\n",
       "      <td>5660</td>\n",
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       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "        stint     G     AB     R     H   2B   3B  HR     RBI     SB     CS  \\\n",
       "yearID                                                                       \n",
       "1871      115  2296  10822  2659  3101  434  239  47  1783.0  441.0  123.0   \n",
       "1872      172  3305  15663  3390  4467  581  145  37  2132.0  269.0  134.0   \n",
       "1873      128  3604  16959  3580  4926  570  211  47  2331.0  314.0  131.0   \n",
       "1874      126  4199  19104  3470  5224  634  194  40  2252.0  242.0   97.0   \n",
       "1875      248  6248  26833  4234  6812  839  273  40  2710.0  629.0  320.0   \n",
       "\n",
       "         BB     SO  IBB  HBP   SH   SF   GIDP    1B  \n",
       "yearID                                               \n",
       "1871    393  175.0  0.0  0.0  0.0  0.0   74.0  2381  \n",
       "1872    263  264.0  0.0  0.0  0.0  0.0   97.0  3704  \n",
       "1873    335  278.0  0.0  0.0  0.0  0.0  122.0  4098  \n",
       "1874    238  357.0  0.0  0.0  0.0  0.0  107.0  4356  \n",
       "1875    249  675.0  0.0  0.0  0.0  0.0  142.0  5660  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "batting_by_year = batting.groupby('yearID').sum()   #.reset_index()\n",
    "batting_by_year.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "If we group and sum instead by the <code>'playerID'</code> column, we get each player's career batting statistics."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>playerID</th>\n",
       "      <th>yearID</th>\n",
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       "      <th>G</th>\n",
       "      <th>AB</th>\n",
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       "      <th>BB</th>\n",
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       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>aardsda01</td>\n",
       "      <td>18084</td>\n",
       "      <td>9</td>\n",
       "      <td>331</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>aaronha01</td>\n",
       "      <td>45195</td>\n",
       "      <td>23</td>\n",
       "      <td>3298</td>\n",
       "      <td>12364</td>\n",
       "      <td>2174</td>\n",
       "      <td>3771</td>\n",
       "      <td>624</td>\n",
       "      <td>98</td>\n",
       "      <td>755</td>\n",
       "      <td>2297.0</td>\n",
       "      <td>240.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>1402</td>\n",
       "      <td>1383.0</td>\n",
       "      <td>293.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>121.0</td>\n",
       "      <td>328.0</td>\n",
       "      <td>2294</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>aaronto01</td>\n",
       "      <td>13768</td>\n",
       "      <td>7</td>\n",
       "      <td>437</td>\n",
       "      <td>944</td>\n",
       "      <td>102</td>\n",
       "      <td>216</td>\n",
       "      <td>42</td>\n",
       "      <td>6</td>\n",
       "      <td>13</td>\n",
       "      <td>94.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>86</td>\n",
       "      <td>145.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>155</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>aasedo01</td>\n",
       "      <td>25786</td>\n",
       "      <td>13</td>\n",
       "      <td>448</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>abadan01</td>\n",
       "      <td>6010</td>\n",
       "      <td>3</td>\n",
       "      <td>15</td>\n",
       "      <td>21</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>abadfe01</td>\n",
       "      <td>18124</td>\n",
       "      <td>10</td>\n",
       "      <td>363</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>abadijo01</td>\n",
       "      <td>3750</td>\n",
       "      <td>3</td>\n",
       "      <td>12</td>\n",
       "      <td>49</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>abbated01</td>\n",
       "      <td>19051</td>\n",
       "      <td>11</td>\n",
       "      <td>855</td>\n",
       "      <td>3044</td>\n",
       "      <td>355</td>\n",
       "      <td>772</td>\n",
       "      <td>99</td>\n",
       "      <td>43</td>\n",
       "      <td>11</td>\n",
       "      <td>324.0</td>\n",
       "      <td>142.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>289</td>\n",
       "      <td>283.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>93.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>619</td>\n",
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       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>abbeybe01</td>\n",
       "      <td>11365</td>\n",
       "      <td>7</td>\n",
       "      <td>79</td>\n",
       "      <td>225</td>\n",
       "      <td>21</td>\n",
       "      <td>38</td>\n",
       "      <td>3</td>\n",
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       "      <td>0</td>\n",
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       "      <td>21</td>\n",
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       "      <td>6.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>32</td>\n",
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       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>abbeych01</td>\n",
       "      <td>9475</td>\n",
       "      <td>5</td>\n",
       "      <td>452</td>\n",
       "      <td>1756</td>\n",
       "      <td>307</td>\n",
       "      <td>493</td>\n",
       "      <td>67</td>\n",
       "      <td>46</td>\n",
       "      <td>19</td>\n",
       "      <td>280.0</td>\n",
       "      <td>93.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>167</td>\n",
       "      <td>122.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>361</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    playerID  yearID  stint     G     AB     R     H   2B  3B   HR     RBI  \\\n",
       "0  aardsda01   18084      9   331      4     0     0    0   0    0     0.0   \n",
       "1  aaronha01   45195     23  3298  12364  2174  3771  624  98  755  2297.0   \n",
       "2  aaronto01   13768      7   437    944   102   216   42   6   13    94.0   \n",
       "3   aasedo01   25786     13   448      5     0     0    0   0    0     0.0   \n",
       "4   abadan01    6010      3    15     21     1     2    0   0    0     0.0   \n",
       "5   abadfe01   18124     10   363      9     0     1    0   0    0     0.0   \n",
       "6  abadijo01    3750      3    12     49     4    11    0   0    0     5.0   \n",
       "7  abbated01   19051     11   855   3044   355   772   99  43   11   324.0   \n",
       "8  abbeybe01   11365      7    79    225    21    38    3   3    0    17.0   \n",
       "9  abbeych01    9475      5   452   1756   307   493   67  46   19   280.0   \n",
       "\n",
       "      SB    CS    BB      SO    IBB   HBP    SH     SF   GIDP    1B  \n",
       "0    0.0   0.0     0     2.0    0.0   0.0   1.0    0.0    0.0     0  \n",
       "1  240.0  73.0  1402  1383.0  293.0  32.0  21.0  121.0  328.0  2294  \n",
       "2    9.0   8.0    86   145.0    3.0   0.0   9.0    6.0   36.0   155  \n",
       "3    0.0   0.0     0     3.0    0.0   0.0   0.0    0.0    0.0     0  \n",
       "4    0.0   1.0     4     5.0    0.0   0.0   0.0    0.0    1.0     2  \n",
       "5    0.0   0.0     0     5.0    0.0   0.0   0.0    0.0    1.0     1  \n",
       "6    1.0   0.0     0     3.0    0.0   0.0   0.0    0.0    0.0    11  \n",
       "7  142.0   0.0   289   283.0    0.0  33.0  93.0    0.0    0.0   619  \n",
       "8    3.0   0.0    21    54.0    0.0   0.0   6.0    0.0    0.0    32  \n",
       "9   93.0   0.0   167   122.0    0.0  23.0  19.0    0.0    0.0   361  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pl_bat = batting.groupby('playerID').sum().reset_index()    # could apply other aggregating functions\n",
    "pl_bat.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## SQL databases: the interoperation of SQLAlchemy and Pandas\n",
    "\n",
    "<b>Relational database</b>: a set of data tables connected through shared data\n",
    "\n",
    "Note: running the code cell below will generate a file in the code directory named 'bbdb.sqlite', which will be approximately 34 MB in size."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sqlalchemy import create_engine\n",
    "\n",
    "def write_all_tables_to_sqlite(dfs, sql_filename):\n",
    "    engine = create_engine('sqlite:///{}'.format(sql_filename))\n",
    "    for table, df in dfs.items():\n",
    "        df.to_sql(table, con=engine, index=False)\n",
    "    engine.dispose()\n",
    "    \n",
    "sqlite_filename = 'bbdb.sqlite'\n",
    "try:\n",
    "    os.remove(sqlite_filename)\n",
    "except FileNotFoundError:\n",
    "    pass\n",
    "\n",
    "write_all_tables_to_sqlite(bbdfs, sqlite_filename)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Making a SQL query to Baseball DB\n",
    "\n",
    "With all the data in a SQLite database, we can connect to it and issue SQL queries to extract data of interest, such as which players had the most hits in a season."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>playerID</th>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>suzukic01</td>\n",
       "      <td>2004</td>\n",
       "      <td>1</td>\n",
       "      <td>SEA</td>\n",
       "      <td>AL</td>\n",
       "      <td>161</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>sislege01</td>\n",
       "      <td>1920</td>\n",
       "      <td>1</td>\n",
       "      <td>SLA</td>\n",
       "      <td>AL</td>\n",
       "      <td>154</td>\n",
       "      <td>631</td>\n",
       "      <td>137</td>\n",
       "      <td>257</td>\n",
       "      <td>49</td>\n",
       "      <td>18</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>171</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>odoulle01</td>\n",
       "      <td>1929</td>\n",
       "      <td>1</td>\n",
       "      <td>PHI</td>\n",
       "      <td>NL</td>\n",
       "      <td>154</td>\n",
       "      <td>638</td>\n",
       "      <td>152</td>\n",
       "      <td>254</td>\n",
       "      <td>35</td>\n",
       "      <td>6</td>\n",
       "      <td>32</td>\n",
       "      <td>122.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>76</td>\n",
       "      <td>19.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>181</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>terrybi01</td>\n",
       "      <td>1930</td>\n",
       "      <td>1</td>\n",
       "      <td>NY1</td>\n",
       "      <td>NL</td>\n",
       "      <td>154</td>\n",
       "      <td>633</td>\n",
       "      <td>139</td>\n",
       "      <td>254</td>\n",
       "      <td>39</td>\n",
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       "      <td>129.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>57</td>\n",
       "      <td>33.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>19.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>simmoal01</td>\n",
       "      <td>1925</td>\n",
       "      <td>1</td>\n",
       "      <td>PHA</td>\n",
       "      <td>AL</td>\n",
       "      <td>153</td>\n",
       "      <td>654</td>\n",
       "      <td>122</td>\n",
       "      <td>253</td>\n",
       "      <td>43</td>\n",
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       "      <td>24</td>\n",
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       "      <td>7.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>35</td>\n",
       "      <td>41.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>174</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>hornsro01</td>\n",
       "      <td>1922</td>\n",
       "      <td>1</td>\n",
       "      <td>SLN</td>\n",
       "      <td>NL</td>\n",
       "      <td>154</td>\n",
       "      <td>623</td>\n",
       "      <td>141</td>\n",
       "      <td>250</td>\n",
       "      <td>46</td>\n",
       "      <td>14</td>\n",
       "      <td>42</td>\n",
       "      <td>152.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>65</td>\n",
       "      <td>50.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>kleinch01</td>\n",
       "      <td>1930</td>\n",
       "      <td>1</td>\n",
       "      <td>PHI</td>\n",
       "      <td>NL</td>\n",
       "      <td>156</td>\n",
       "      <td>648</td>\n",
       "      <td>158</td>\n",
       "      <td>250</td>\n",
       "      <td>59</td>\n",
       "      <td>8</td>\n",
       "      <td>40</td>\n",
       "      <td>170.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>54</td>\n",
       "      <td>50.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>cobbty01</td>\n",
       "      <td>1911</td>\n",
       "      <td>1</td>\n",
       "      <td>DET</td>\n",
       "      <td>AL</td>\n",
       "      <td>146</td>\n",
       "      <td>591</td>\n",
       "      <td>147</td>\n",
       "      <td>248</td>\n",
       "      <td>47</td>\n",
       "      <td>24</td>\n",
       "      <td>8</td>\n",
       "      <td>127.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>44</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>169</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>sislege01</td>\n",
       "      <td>1922</td>\n",
       "      <td>1</td>\n",
       "      <td>SLA</td>\n",
       "      <td>AL</td>\n",
       "      <td>142</td>\n",
       "      <td>586</td>\n",
       "      <td>134</td>\n",
       "      <td>246</td>\n",
       "      <td>42</td>\n",
       "      <td>18</td>\n",
       "      <td>8</td>\n",
       "      <td>105.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>49</td>\n",
       "      <td>14.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>suzukic01</td>\n",
       "      <td>2001</td>\n",
       "      <td>1</td>\n",
       "      <td>SEA</td>\n",
       "      <td>AL</td>\n",
       "      <td>157</td>\n",
       "      <td>692</td>\n",
       "      <td>127</td>\n",
       "      <td>242</td>\n",
       "      <td>34</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>69.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>30</td>\n",
       "      <td>53.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    playerID  yearID  stint teamID lgID    G   AB    R    H  2B  3B  HR  \\\n",
       "0  suzukic01    2004      1    SEA   AL  161  704  101  262  24   5   8   \n",
       "1  sislege01    1920      1    SLA   AL  154  631  137  257  49  18  19   \n",
       "2  odoulle01    1929      1    PHI   NL  154  638  152  254  35   6  32   \n",
       "3  terrybi01    1930      1    NY1   NL  154  633  139  254  39  15  23   \n",
       "4  simmoal01    1925      1    PHA   AL  153  654  122  253  43  12  24   \n",
       "5  hornsro01    1922      1    SLN   NL  154  623  141  250  46  14  42   \n",
       "6  kleinch01    1930      1    PHI   NL  156  648  158  250  59   8  40   \n",
       "7   cobbty01    1911      1    DET   AL  146  591  147  248  47  24   8   \n",
       "8  sislege01    1922      1    SLA   AL  142  586  134  246  42  18   8   \n",
       "9  suzukic01    2001      1    SEA   AL  157  692  127  242  34   8   8   \n",
       "\n",
       "     RBI    SB    CS  BB    SO   IBB  HBP    SH   SF  GIDP   1B  \n",
       "0   60.0  36.0  11.0  49  63.0  19.0  4.0   2.0  3.0   6.0  225  \n",
       "1  122.0  42.0  17.0  46  19.0   NaN  2.0  13.0  NaN   NaN  171  \n",
       "2  122.0   2.0   NaN  76  19.0   NaN  4.0  13.0  NaN   NaN  181  \n",
       "3  129.0   8.0   NaN  57  33.0   NaN  1.0  19.0  NaN   NaN  177  \n",
       "4  129.0   7.0  14.0  35  41.0   NaN  1.0   6.0  NaN   NaN  174  \n",
       "5  152.0  17.0  12.0  65  50.0   NaN  1.0  15.0  NaN   NaN  148  \n",
       "6  170.0   4.0   NaN  54  50.0   NaN  4.0  13.0  NaN   NaN  143  \n",
       "7  127.0  83.0   NaN  44   NaN   NaN  8.0  11.0  NaN   NaN  169  \n",
       "8  105.0  51.0  19.0  49  14.0   NaN  3.0  16.0  NaN   NaN  178  \n",
       "9   69.0  56.0  14.0  30  53.0  10.0  8.0   4.0  4.0   3.0  192  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "engine = create_engine('sqlite:///bbdb.sqlite')\n",
    "most_hits_in_a_year = \\\n",
    "    pd.read_sql_query('select * from batting order by H desc limit 10', engine)\n",
    "most_hits_in_a_year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "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>nameFirst</th>\n",
       "      <th>nameLast</th>\n",
       "      <th>playerID</th>\n",
       "      <th>yearID</th>\n",
       "      <th>H</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Ichiro</td>\n",
       "      <td>Suzuki</td>\n",
       "      <td>suzukic01</td>\n",
       "      <td>2004</td>\n",
       "      <td>262</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>George</td>\n",
       "      <td>Sisler</td>\n",
       "      <td>sislege01</td>\n",
       "      <td>1920</td>\n",
       "      <td>257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Lefty</td>\n",
       "      <td>O'Doul</td>\n",
       "      <td>odoulle01</td>\n",
       "      <td>1929</td>\n",
       "      <td>254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Bill</td>\n",
       "      <td>Terry</td>\n",
       "      <td>terrybi01</td>\n",
       "      <td>1930</td>\n",
       "      <td>254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Al</td>\n",
       "      <td>Simmons</td>\n",
       "      <td>simmoal01</td>\n",
       "      <td>1925</td>\n",
       "      <td>253</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Rogers</td>\n",
       "      <td>Hornsby</td>\n",
       "      <td>hornsro01</td>\n",
       "      <td>1922</td>\n",
       "      <td>250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Chuck</td>\n",
       "      <td>Klein</td>\n",
       "      <td>kleinch01</td>\n",
       "      <td>1930</td>\n",
       "      <td>250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Ty</td>\n",
       "      <td>Cobb</td>\n",
       "      <td>cobbty01</td>\n",
       "      <td>1911</td>\n",
       "      <td>248</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>George</td>\n",
       "      <td>Sisler</td>\n",
       "      <td>sislege01</td>\n",
       "      <td>1922</td>\n",
       "      <td>246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Ichiro</td>\n",
       "      <td>Suzuki</td>\n",
       "      <td>suzukic01</td>\n",
       "      <td>2001</td>\n",
       "      <td>242</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  nameFirst nameLast   playerID  yearID    H\n",
       "0    Ichiro   Suzuki  suzukic01    2004  262\n",
       "1    George   Sisler  sislege01    1920  257\n",
       "2     Lefty   O'Doul  odoulle01    1929  254\n",
       "3      Bill    Terry  terrybi01    1930  254\n",
       "4        Al  Simmons  simmoal01    1925  253\n",
       "5    Rogers  Hornsby  hornsro01    1922  250\n",
       "6     Chuck    Klein  kleinch01    1930  250\n",
       "7        Ty     Cobb   cobbty01    1911  248\n",
       "8    George   Sisler  sislege01    1922  246\n",
       "9    Ichiro   Suzuki  suzukic01    2001  242"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_sql_query(\"\"\"select people.nameFirst, people.nameLast, batting.playerID, batting.yearID, batting.H\n",
    "from people join batting on people.playerID=batting.playerID order by batting.H desc limit 10\"\"\", engine) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Any quick questions about Pandas and DataFrames?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Data Visualization\n",
    "\n",
    "* Matplotlib & friends\n",
    "    * matplotlib: low-level, comprehensive plotting API\n",
    "    * pandas: uses matplotlib for plotting from DataFrames and Series\n",
    "    * seaborn: uses matplotlib for plotting, with emphasis on statistical distributions\n",
    "    * statsmodels: uses matplotlib for plotting statistical models alongside data\n",
    "* Bokeh: interactive, web-based visualization (Python interfacing to Javascript)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "batting_by_year.plot.scatter('HR', 'SO');\n",
    "plt.title('Homeruns and Strikeouts')\n",
    "plt.savefig('batting_HR_SO_scatter.png');\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": false,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1501.38x1440 with 72 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "\n",
    "batting_by_year = batting.groupby('yearID').sum().reset_index()\n",
    "\n",
    "batting_per_AB_by_year = batting_by_year.copy()\n",
    "for col in batting_per_AB_by_year.columns:\n",
    "    if col in ['yearID', 'stint', 'G', 'AB']:\n",
    "        continue\n",
    "    batting_per_AB_by_year[col] = batting_per_AB_by_year[col]/batting_per_AB_by_year['AB']\n",
    "\n",
    "batting_per_AB_by_year['decade'] = np.floor_divide(batting_per_AB_by_year['yearID'],10)*10\n",
    "\n",
    "hit_vars = ('1B', '2B', '3B', 'HR', 'SO', 'BB', 'R', 'RBI')\n",
    "\n",
    "pg = sns.pairplot(batting_per_AB_by_year, vars=hit_vars, hue='decade', palette='Blues')\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Statistics with statsmodels\n",
    "\n",
    "* Provides support for the estimation of many different statistical models, conducting statistical tests, and statistical data exploration\n",
    "* Provides functionality similar to that offered by other widely used statistical modeling environments, such as R, SAS, and Minitab  \n",
    "* Linear regression models, generalized linear models, time series analysis, and state space models\n",
    "* Consider here Ordinary Least Squares (OLS) analysis of Homerun and Strikeout data\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                            OLS Regression Results                            \n",
      "==============================================================================\n",
      "Dep. Variable:                     SO   R-squared:                       0.923\n",
      "Model:                            OLS   Adj. R-squared:                  0.922\n",
      "Method:                 Least Squares   F-statistic:                     1744.\n",
      "Date:                Wed, 28 Jul 2021   Prob (F-statistic):           4.49e-83\n",
      "Time:                        10:03:30   Log-Likelihood:                -1392.9\n",
      "No. Observations:                 148   AIC:                             2790.\n",
      "Df Residuals:                     146   BIC:                             2796.\n",
      "Df Model:                           1                                         \n",
      "Covariance Type:            nonrobust                                         \n",
      "==============================================================================\n",
      "                 coef    std err          t      P>|t|      [0.025      0.975]\n",
      "------------------------------------------------------------------------------\n",
      "const       2318.1553    379.549      6.108      0.000    1568.036    3068.274\n",
      "HR             5.9538      0.143     41.761      0.000       5.672       6.236\n",
      "==============================================================================\n",
      "Omnibus:                       17.182   Durbin-Watson:                   0.392\n",
      "Prob(Omnibus):                  0.000   Jarque-Bera (JB):               19.497\n",
      "Skew:                           0.865   Prob(JB):                     5.84e-05\n",
      "Kurtosis:                       3.409   Cond. No.                     4.13e+03\n",
      "==============================================================================\n",
      "\n",
      "Warnings:\n",
      "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
      "[2] The condition number is large, 4.13e+03. This might indicate that there are\n",
      "strong multicollinearity or other numerical problems.\n"
     ]
    }
   ],
   "source": [
    "import statsmodels.api as sm\n",
    "X = batting_by_year['HR']\n",
    "y = batting_by_year['SO']\n",
    "X = sm.add_constant(X)\n",
    "results = sm.OLS(y, X).fit()\n",
    "print(results.summary())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Statsmodels provides a plotting API that also uses matplotlib\n",
    "fig = sm.graphics.abline_plot(model_results=results, c='r')\n",
    "ax = fig.axes[0]\n",
    "ax.scatter(X['HR'], y, s=10)\n",
    "plt.xlabel('HR');\n",
    "plt.ylabel('SO');\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Modeling data\n",
    "\n",
    "#### Sabermetrics and the \"Pythagorean\" theorem of baseball\n",
    "\n",
    "<a href=\"https://en.wikipedia.org/wiki/Pythagorean_expectation\">\"Pythonagorean winning percentage\" (Bill James)</a>: What fraction of games (G) should we expect a team to win (W) based upon the number of runs it scores (R) and the number it allows (RA)?\n",
    "\n",
    "$W/G = \\frac{R^2}{R^2 + RA^2} = \\frac{1}{1 + (RA/R)^2}$\n",
    "\n",
    "James originally formulated this with exponent 2.  Later analyses estimated different exponents based on the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "teams00 = teams[teams.yearID >= 1900].copy()\n",
    "teams00['W/G'] = teams00.W/teams00.G\n",
    "teams00['RA/R'] = teams00.RA / teams00.R\n",
    "teams00.plot.scatter('RA/R', 'W/G', figsize=(12,8))\n",
    "plt.xlabel('RA/R');\n",
    "plt.ylabel('W/G');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Parameter estimation using scipy\n",
    "\n",
    "$W/G = \\frac{R^2}{R^2 + RA^2} = \\frac{1}{1 + (RA/R)^2}$\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1.83891722]\n"
     ]
    }
   ],
   "source": [
    "from scipy.optimize import curve_fit\n",
    "\n",
    "def pythag(x, exponent):\n",
    "    return 1 / (1 + x**exponent)\n",
    "\n",
    "xdata = teams00.RA/teams00.R\n",
    "ydata = teams00['W/G']\n",
    "\n",
    "popt, pcov = curve_fit(pythag, xdata, ydata, [2.0])\n",
    "print(popt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "xs = np.linspace(teams00['RA/R'].min(), teams00['RA/R'].max(), 100)\n",
    "expected_wins_2 = pythag(xs, exponent=2)\n",
    "expected_wins_popt = pythag(xs, exponent=popt[0])\n",
    "\n",
    "teams00.plot.scatter('RA/R', 'W/G', figsize=(12,8))\n",
    "plt.plot(xs, expected_wins_2, color='k', linewidth=2, label='2')\n",
    "plt.plot(xs, expected_wins_popt, color='r', linewidth=2, label=str(popt[0]))\n",
    "plt.legend();\n",
    "plt.savefig('pythagorean_curve_fit.png');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Any quick questions about Data Visualization, Modeling and Parameter Estimation?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Networks from Data\n",
    "\n",
    "* network (or graph): data structure with nodes (or vertices) connected by edges (or links)\n",
    "    * edges can be undirected, directed, weighted, etc.\n",
    "* NetworkX: Python package for construction and analysis of complex networks\n",
    "* Some common network analyses\n",
    "    * computing shortest paths between pairs of nodes\n",
    "    * identifying the set of connected components within a network\n",
    "    * computing various centrality measures characterizing nodes and edges (e.g., degree, closeness, betweenness, etc.)\n",
    "    * identifying modules or communities within networks based upon patterns of connectivity\n",
    "    * creating random graphs consistent with prescribed statistical properties\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Co-Player Network in Baseball\n",
    "\n",
    "## Something like the co-actor network used to play the Kevin Bacon game\n",
    "\n",
    "![](images/coactor.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "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>yearID</th>\n",
       "      <th>teamID</th>\n",
       "      <th>lgID</th>\n",
       "      <th>playerID</th>\n",
       "      <th>G_all</th>\n",
       "      <th>GS</th>\n",
       "      <th>G_batting</th>\n",
       "      <th>G_defense</th>\n",
       "      <th>G_p</th>\n",
       "      <th>G_c</th>\n",
       "      <th>G_1b</th>\n",
       "      <th>G_2b</th>\n",
       "      <th>G_3b</th>\n",
       "      <th>G_ss</th>\n",
       "      <th>G_lf</th>\n",
       "      <th>G_cf</th>\n",
       "      <th>G_rf</th>\n",
       "      <th>G_of</th>\n",
       "      <th>G_dh</th>\n",
       "      <th>G_ph</th>\n",
       "      <th>G_pr</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>105784</th>\n",
       "      <td>2018</td>\n",
       "      <td>CLE</td>\n",
       "      <td>AL</td>\n",
       "      <td>zimmebr01</td>\n",
       "      <td>34</td>\n",
       "      <td>29.0</td>\n",
       "      <td>34</td>\n",
       "      <td>34.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>34</td>\n",
       "      <td>0</td>\n",
       "      <td>34</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105785</th>\n",
       "      <td>2018</td>\n",
       "      <td>DET</td>\n",
       "      <td>AL</td>\n",
       "      <td>zimmejo02</td>\n",
       "      <td>25</td>\n",
       "      <td>25.0</td>\n",
       "      <td>2</td>\n",
       "      <td>25.0</td>\n",
       "      <td>25</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105786</th>\n",
       "      <td>2018</td>\n",
       "      <td>WAS</td>\n",
       "      <td>NL</td>\n",
       "      <td>zimmery01</td>\n",
       "      <td>85</td>\n",
       "      <td>72.0</td>\n",
       "      <td>85</td>\n",
       "      <td>73.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>73</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105787</th>\n",
       "      <td>2018</td>\n",
       "      <td>CHN</td>\n",
       "      <td>NL</td>\n",
       "      <td>zobribe01</td>\n",
       "      <td>139</td>\n",
       "      <td>108.0</td>\n",
       "      <td>139</td>\n",
       "      <td>125.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>63</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>43</td>\n",
       "      <td>0</td>\n",
       "      <td>61</td>\n",
       "      <td>84</td>\n",
       "      <td>1.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105788</th>\n",
       "      <td>2018</td>\n",
       "      <td>SEA</td>\n",
       "      <td>AL</td>\n",
       "      <td>zuninmi01</td>\n",
       "      <td>113</td>\n",
       "      <td>102.0</td>\n",
       "      <td>113</td>\n",
       "      <td>111.0</td>\n",
       "      <td>0</td>\n",
       "      <td>111</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        yearID teamID lgID   playerID  G_all     GS  G_batting  G_defense  \\\n",
       "105784    2018    CLE   AL  zimmebr01     34   29.0         34       34.0   \n",
       "105785    2018    DET   AL  zimmejo02     25   25.0          2       25.0   \n",
       "105786    2018    WAS   NL  zimmery01     85   72.0         85       73.0   \n",
       "105787    2018    CHN   NL  zobribe01    139  108.0        139      125.0   \n",
       "105788    2018    SEA   AL  zuninmi01    113  102.0        113      111.0   \n",
       "\n",
       "        G_p  G_c  G_1b  G_2b  G_3b  G_ss  G_lf  G_cf  G_rf  G_of  G_dh  G_ph  \\\n",
       "105784    0    0     0     0     0     0     0    34     0    34   0.0   2.0   \n",
       "105785   25    0     0     0     0     0     0     0     0     0   0.0   0.0   \n",
       "105786    0    0    73     0     0     0     0     0     0     0   0.0  13.0   \n",
       "105787    0    0     4    63     0     0    43     0    61    84   1.0  22.0   \n",
       "105788    0  111     0     0     0     0     0     0     0     0   1.0   7.0   \n",
       "\n",
       "        G_pr  \n",
       "105784   0.0  \n",
       "105785   0.0  \n",
       "105786   0.0  \n",
       "105787   0.0  \n",
       "105788   0.0  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "appearances = bbdfs['Appearances']\n",
    "appearances.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(2006, 'TBA'),\n",
       " (2007, 'TBA'),\n",
       " (2008, 'TBA'),\n",
       " (2009, 'TBA'),\n",
       " (2010, 'TBA'),\n",
       " (2011, 'TBA'),\n",
       " (2012, 'TBA'),\n",
       " (2013, 'TBA'),\n",
       " (2014, 'TBA'),\n",
       " (2015, 'KCA'),\n",
       " (2015, 'OAK'),\n",
       " (2016, 'CHN'),\n",
       " (2017, 'CHN'),\n",
       " (2018, 'CHN')]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import networkx as nx\n",
    "\n",
    "def make_coplayer_network(appearances):\n",
    "    dfyt = appearances.groupby(['yearID', 'teamID'])['playerID'].\\\n",
    "        apply(np.unique).reset_index()\n",
    "    g = nx.Graph()\n",
    "    for idx, entry in dfyt.iterrows():\n",
    "        yearID, teamID, playerIDs = entry\n",
    "        for pid in playerIDs:\n",
    "            g.add_edge((yearID, teamID), pid)\n",
    "    return g\n",
    "\n",
    "coplayer = make_coplayer_network(bbdfs['Appearances'])\n",
    "list(coplayer.neighbors('zobribe01'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['almoral01',\n",
       " 'arrieja01',\n",
       " 'baezja01',\n",
       " 'bryankr01',\n",
       " 'buchaja01',\n",
       " 'cahiltr01',\n",
       " 'candeje01',\n",
       " 'chapmar01',\n",
       " 'coghlch01',\n",
       " 'concege01',\n",
       " 'contrwi01',\n",
       " 'edwarca01',\n",
       " 'federti01',\n",
       " 'fowlede01',\n",
       " 'grimmju01',\n",
       " 'hammeja01',\n",
       " 'hendrky01',\n",
       " 'heywaja01',\n",
       " 'kalisry01',\n",
       " 'kawasmu01',\n",
       " 'lackejo01',\n",
       " 'lasteto01',\n",
       " 'lestejo01',\n",
       " 'matusbr01',\n",
       " 'montemi01',\n",
       " 'montgmi01',\n",
       " 'nathajo01',\n",
       " 'pattosp01',\n",
       " 'penafe01',\n",
       " 'peraljo01',\n",
       " 'ramirne01',\n",
       " 'richacl01',\n",
       " 'rizzoan01',\n",
       " 'rondohe01',\n",
       " 'rossda01',\n",
       " 'russead02',\n",
       " 'schwaky01',\n",
       " 'smithjo05',\n",
       " 'solerjo01',\n",
       " 'stroppe01',\n",
       " 'szczuma01',\n",
       " 'warread01',\n",
       " 'woodtr01',\n",
       " 'zastrro01',\n",
       " 'zobribe01']"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(coplayer.neighbors((2016, 'CHN')))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "scrolled": false,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['ruthba01',\n",
       " (1919, 'BOS'),\n",
       " 'hoytwa01',\n",
       " (1937, 'BRO'),\n",
       " 'haasbe01',\n",
       " (1951, 'CHA'),\n",
       " 'minosmi01',\n",
       " (1980, 'CHA'),\n",
       " 'baineha01',\n",
       " (1999, 'CLE'),\n",
       " 'branyru01',\n",
       " (2006, 'TBA'),\n",
       " 'zobribe01']"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nx.shortest_path(coplayer, 'ruthba01', 'zobribe01')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Babe Ruth',\n",
       " (1919, 'BOS'),\n",
       " 'Waite Hoyt',\n",
       " (1937, 'BRO'),\n",
       " 'Bert Haas',\n",
       " (1951, 'CHA'),\n",
       " 'Minnie Minoso',\n",
       " (1980, 'CHA'),\n",
       " 'Harold Baines',\n",
       " (1999, 'CLE'),\n",
       " 'Russell Branyan',\n",
       " (2006, 'TBA'),\n",
       " 'Ben Zobrist']"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def get_player_name(pid, people):\n",
    "    try:\n",
    "        return people[people.playerID==pid][['nameFirst', 'nameLast']].\\\n",
    "            apply(lambda x: ' '.join(x), axis=1).iloc[0]\n",
    "    except IndexError:\n",
    "        return None\n",
    "    except TypeError:\n",
    "        return people[people.playerID==pid]['nameLast'].iloc[0]\n",
    "\n",
    "def get_shortest_coplayer_path(coplayer, people, node1, node2):\n",
    "    spath = nx.shortest_path(coplayer, node1, node2)\n",
    "    spathn = []\n",
    "    for elem in spath:\n",
    "        pname = get_player_name(elem, people)\n",
    "        if pname is not None:\n",
    "            spathn.append(pname)\n",
    "        else:\n",
    "            spathn.append(elem)\n",
    "    return spathn\n",
    "\n",
    "\n",
    "\n",
    "people = bbdfs['People']\n",
    "\n",
    "get_shortest_coplayer_path(coplayer, people, 'ruthba01', 'zobribe01')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Who is the \"center\" of the baseball universe?\n",
    "\n",
    "### Closeness centrality"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.1155177677846028\n",
      "0.131967721911856\n",
      "0.16586297339267536\n"
     ]
    }
   ],
   "source": [
    "print(nx.closeness_centrality(coplayer, 'zobribe01'))\n",
    "print(nx.closeness_centrality(coplayer, 'ruthba01'))\n",
    "print(nx.closeness_centrality(coplayer, 'minosmi01'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Retweet Networks\n",
    "\n",
    "![](images/climatechange_graph.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Any quick questions about Networks?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Machine Learning\n",
    "\n",
    "* \"Classical\" machine learning (Ridge/Lasso, Decision Trees/Random Forests, Support Vector Machines, etc.)\n",
    "    * Scikit-learn (sklearn): scikit-learn.org\n",
    "* \"Deep Learning\" with Neural Networks &#8594; tensors with automatic differentiation for backpropagation\n",
    "    * TensorFlow/Keras\n",
    "    * PyTorch\n",
    "    * Caffe\n",
    "* Scikit-learn supports\n",
    "    * Supervised Learning - Classification, Regression\n",
    "    * Unsupervised Learning - Clustering, Dimensionality Reduction, Feature Selection\n",
    "    * Model selection, cross-validation, hyperparameter optimization, etc."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Scikit-learn: Choosing the right estimator\n",
    "\n",
    "![](https://scikit-learn.org/stable/_static/ml_map.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## K-Means clustering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [],
   "source": [
    "batting = bbdfs['Batting']\n",
    "pl_bat = batting.groupby('playerID').sum().reset_index()\n",
    "\n",
    "pl_bat_with_ab = pl_bat[pl_bat.AB>0]\n",
    "\n",
    "pl_bat_per_ab = pl_bat_with_ab[['R', 'H', '2B', '3B', 'HR','RBI', 'SB', 'CS', 'BB', 'SO', 'IBB', 'HBP', 'SH', 'SF', 'GIDP']].div(pl_bat_with_ab.AB, axis=0)\n",
    "pl_bat_per_ab['playerID'] = pl_bat['playerID']\n",
    "pl_bat_per_ab.set_index('playerID', inplace=True)\n",
    "\n",
    "from sklearn.cluster import KMeans\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "X = pl_bat_per_ab.values\n",
    "scaler = StandardScaler().fit(X)\n",
    "Xsc = scaler.fit_transform(X)\n",
    "\n",
    "k = 10\n",
    "kcluster = KMeans(n_clusters=k)\n",
    "kcluster.fit(Xsc)\n",
    "\n",
    "labels = list(kcluster.labels_)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## K-Means clustering\n",
    "\n",
    "![](https://scikit-learn.org/stable/_images/sphx_glr_plot_kmeans_digits_001.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "scrolled": false,
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 10 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(5,2,sharex=True, figsize=(12,8))\n",
    "n = 0\n",
    "for i in range(5):\n",
    "    for j in range(2):\n",
    "        axes[i,j].plot(kcluster.cluster_centers_[n])\n",
    "        n += 1\n",
    "plt.xticks(range(len(pl_bat_per_ab.columns)), pl_bat_per_ab.columns);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Dimensionality Reduction using T-SNE\n",
    "\n",
    "#### Compressing our 15-dimensional batting feature space to 2 dimensions for visualization\n",
    " * an example of \"manifold learning\"\n",
    "\n",
    "#### NOTE: We won't run this during the webinar since it takes a little while to complete..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [],
   "source": [
    "from sklearn.manifold import TSNE\n",
    "\n",
    "X = pl_bat_per_ab.values\n",
    "scaler = StandardScaler().fit(X)\n",
    "Xsc = scaler.fit_transform(X)\n",
    "\n",
    "def run_tsne(Xsc, index):\n",
    "    X_e = TSNE(n_components=2).fit_transform(Xsc)\n",
    "    dfe = pd.DataFrame(X_e, index=index)\n",
    "    dfe.reset_index()\n",
    "    return dfe\n",
    "\n",
    "dfe = run_tsne(Xsc, pl_bat_per_ab.index)\n",
    "\n",
    "dfe.reset_index(inplace=True)\n",
    "dfe.rename(columns={0: 'X', 1:'Y'}, inplace=True)\n",
    "dfe.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Add some additional information to the tsne-embedded dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [],
   "source": [
    "HOF = bbdfs['HallOfFame']\n",
    "inHOF = set(HOF[HOF.inducted=='Y'].playerID)\n",
    "\n",
    "# add HOF (Hall of Fame) column to dfe if person has been inducted in the HOF\n",
    "dfe['HOF'] = dfe.playerID.apply(lambda x: x in inHOF)\n",
    "\n",
    "# add Pitcher column to dfe if person is in pitching dataframe and has pitched in at least 10 games in their career\n",
    "pl_pitch = pitching.groupby('playerID').sum()\n",
    "dfe['Pitcher'] = dfe.playerID.apply(lambda x: x in pitching.playerID.values and pl_pitch.loc[x].G >= 10)\n",
    "\n",
    "# add Name column by looking up their playerID in the people dataframe\n",
    "people = bbdfs['People']\n",
    "dfe['Name'] = dfe.playerID.apply(lambda x: get_player_name(x, people))\n",
    "\n",
    "# let's have a peek\n",
    "dfe.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Interactive visualization using Bokeh\n",
    "\n",
    "* Python library for plotting glyphs in figures\n",
    "* Python-generated Javascript for visualization in web browser\n",
    "* Can generate standalone HTML pages (as done here)\n",
    "* Can be run in \"server\" mode with Python callbacks to change visualizations in response to user interactions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "from bokeh.plotting import figure, show, output_file\n",
    "from bokeh.models import ColumnDataSource, HoverTool, Legend, LegendItem\n",
    "\n",
    "colors = dfe.Pitcher.apply(lambda x: {True:'#3333dd', False: '#dd3333'}[x])\n",
    "radii = 12*dfe.HOF + 3\n",
    "status = list(zip(1*dfe.HOF, 1*dfe.Pitcher))\n",
    "labelmap = {(0,0): 'Player', (0,1): 'Pitcher', (1,0): 'HOF Player', (1,1): 'HOF Pitcher'}\n",
    "labels = list(map(lambda x: labelmap[x], status))\n",
    "\n",
    "R = pl_bat_per_ab['R']\n",
    "H = pl_bat_per_ab['H']\n",
    "TwoB = pl_bat_per_ab['2B']\n",
    "ThreeB = pl_bat_per_ab['3B']\n",
    "HR = pl_bat_per_ab['HR']\n",
    "RBI = pl_bat_per_ab['RBI']\n",
    "SO = pl_bat_per_ab['SO']\n",
    "BB = pl_bat_per_ab['BB']\n",
    "\n",
    "source = ColumnDataSource(data=dict(\n",
    "    x = dfe.X,\n",
    "    y = dfe.Y,\n",
    "    playerID = dfe.playerID,\n",
    "    name = dfe.Name,\n",
    "    radii = radii,\n",
    "    hof = dfe.HOF,\n",
    "    pitcher = dfe.Pitcher,\n",
    "    color = colors,\n",
    "    label = labels,\n",
    "    R = R,\n",
    "    H = H,\n",
    "    TwoB = TwoB,\n",
    "    ThreeB = ThreeB,\n",
    "    HR = HR,\n",
    "    RBI = RBI,\n",
    "    SO = SO,\n",
    "    BB = BB\n",
    "))\n",
    "    \n",
    "TOOLS=\"crosshair,pan,wheel_zoom,zoom_in,zoom_out,box_zoom,undo,redo,reset,save\"\n",
    "\n",
    "p = figure(tools=TOOLS, plot_width=1000, plot_height=1000)\n",
    "scatter = p.scatter(source=source, x='x', y='y', size='radii', color='color', fill_alpha=0.50)\n",
    "p.add_tools(HoverTool(tooltips=[('Name:', '@name'), ('HOF', '@hof'), \n",
    "                                ('R', '@R'), ('H', '@H'), ('2B', '@TwoB'), ('3B', '@ThreeB'),\n",
    "                                   ('HR', '@HR'), ('SO', '@SO'), ('BB', '@BB')]))\n",
    "\n",
    "output_file(\"batting_TSNE.html\", title='batting')  # see also https://cvw.cac.cornell.edu/pydatasci2/images/batting_TSNE.html\n",
    "show(p)"
   ]
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   "source": [
    "## Summary\n",
    "\n",
    "* The Python Ecosystem provides many useful tools and packages for Data Science\n",
    "* A layered ecosystem: \n",
    "    * NumPy &#8594; ( SciPy / Pandas ) &#8594; ( Scikit-learn / TensorFlow / PyTorch / Statsmodels )\n",
    "    * Matplotlib &#8594; ( Pandas / Seaborn / Statsmodels / NetworkX )\n",
    "* The Python Language provides support for the creation of custom pipelines not handled by default methods\n",
    "\n",
    "For more detail, see the Cornell Virtual Workshop (CVW) tutorials:\n",
    "* Python for Data Science - Part 1: Data Processing & Visualization: https://cvw.cac.cornell.edu/PyDS1\n",
    "* Python for Data Science - Part 2: Data Modeling & Machine Learning: https://cvw.cac.cornell.edu/PyDS2\n",
    "\n",
    "These slides are available as a Jupyter notebook named PyDSWebinar.ipynb in the repository at: https://github.com/CornellCAC/CVW_PyDataSci2\n"
   ]
  }
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