DataFrames 2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"employees.csv\", parse_dates=[\"Start Date\", \"Last Login Time\"] )\n",
    "df[\"Senior Management\"] = df[\"Senior Management\"].astype(\"bool\")\n",
    "df[\"Gender\"] = df[\"Gender\"].astype(\"category\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df.head()\n",
    "output = None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "\n",
    "output = None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df[\"Start Date\"]\n",
    "outpput = None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df[\"Start Date\"] = pd.to_datetime(df[\"Start Date\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df[\"Last Login Time\"] = pd.to_datetime(df[\"Last Login Time\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df[\"Senior Management\"] = df[\"Senior Management\"].astype(\"bool\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df[\"Gender\"] = df[\"Gender\"].astype(\"category\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "\n",
    "output = None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>First Name</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Start Date</th>\n",
       "      <th>Last Login Time</th>\n",
       "      <th>Salary</th>\n",
       "      <th>Bonus %</th>\n",
       "      <th>Senior Management</th>\n",
       "      <th>Team</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Douglas</td>\n",
       "      <td>Male</td>\n",
       "      <td>1993-08-06</td>\n",
       "      <td>2018-01-11 12:42:00</td>\n",
       "      <td>97308</td>\n",
       "      <td>6.945</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Thomas</td>\n",
       "      <td>Male</td>\n",
       "      <td>1996-03-31</td>\n",
       "      <td>2018-01-11 06:53:00</td>\n",
       "      <td>61933</td>\n",
       "      <td>4.170</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Maria</td>\n",
       "      <td>Female</td>\n",
       "      <td>1993-04-23</td>\n",
       "      <td>2018-01-11 11:17:00</td>\n",
       "      <td>130590</td>\n",
       "      <td>11.858</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Jerry</td>\n",
       "      <td>Male</td>\n",
       "      <td>2005-03-04</td>\n",
       "      <td>2018-01-11 13:00:00</td>\n",
       "      <td>138705</td>\n",
       "      <td>9.340</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Larry</td>\n",
       "      <td>Male</td>\n",
       "      <td>1998-01-24</td>\n",
       "      <td>2018-01-11 16:47:00</td>\n",
       "      <td>101004</td>\n",
       "      <td>1.389</td>\n",
       "      <td>True</td>\n",
       "      <td>Client Services</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Dennis</td>\n",
       "      <td>Male</td>\n",
       "      <td>1987-04-18</td>\n",
       "      <td>2018-01-11 01:35:00</td>\n",
       "      <td>115163</td>\n",
       "      <td>10.125</td>\n",
       "      <td>False</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Ruby</td>\n",
       "      <td>Female</td>\n",
       "      <td>1987-08-17</td>\n",
       "      <td>2018-01-11 16:20:00</td>\n",
       "      <td>65476</td>\n",
       "      <td>10.012</td>\n",
       "      <td>True</td>\n",
       "      <td>Product</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Female</td>\n",
       "      <td>2015-07-20</td>\n",
       "      <td>2018-01-11 10:43:00</td>\n",
       "      <td>45906</td>\n",
       "      <td>11.598</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Angela</td>\n",
       "      <td>Female</td>\n",
       "      <td>2005-11-22</td>\n",
       "      <td>2018-01-11 06:29:00</td>\n",
       "      <td>95570</td>\n",
       "      <td>18.523</td>\n",
       "      <td>True</td>\n",
       "      <td>Engineering</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Frances</td>\n",
       "      <td>Female</td>\n",
       "      <td>2002-08-08</td>\n",
       "      <td>2018-01-11 06:51:00</td>\n",
       "      <td>139852</td>\n",
       "      <td>7.524</td>\n",
       "      <td>True</td>\n",
       "      <td>Business Development</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Louise</td>\n",
       "      <td>Female</td>\n",
       "      <td>1980-08-12</td>\n",
       "      <td>2018-01-11 09:01:00</td>\n",
       "      <td>63241</td>\n",
       "      <td>15.132</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Julie</td>\n",
       "      <td>Female</td>\n",
       "      <td>1997-10-26</td>\n",
       "      <td>2018-01-11 15:19:00</td>\n",
       "      <td>102508</td>\n",
       "      <td>12.637</td>\n",
       "      <td>True</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Brandon</td>\n",
       "      <td>Male</td>\n",
       "      <td>1980-12-01</td>\n",
       "      <td>2018-01-11 01:08:00</td>\n",
       "      <td>112807</td>\n",
       "      <td>17.492</td>\n",
       "      <td>True</td>\n",
       "      <td>Human Resources</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Gary</td>\n",
       "      <td>Male</td>\n",
       "      <td>2008-01-27</td>\n",
       "      <td>2018-01-11 23:40:00</td>\n",
       "      <td>109831</td>\n",
       "      <td>5.831</td>\n",
       "      <td>False</td>\n",
       "      <td>Sales</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Kimberly</td>\n",
       "      <td>Female</td>\n",
       "      <td>1999-01-14</td>\n",
       "      <td>2018-01-11 07:13:00</td>\n",
       "      <td>41426</td>\n",
       "      <td>14.543</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Lillian</td>\n",
       "      <td>Female</td>\n",
       "      <td>2016-06-05</td>\n",
       "      <td>2018-01-11 06:09:00</td>\n",
       "      <td>59414</td>\n",
       "      <td>1.256</td>\n",
       "      <td>False</td>\n",
       "      <td>Product</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Jeremy</td>\n",
       "      <td>Male</td>\n",
       "      <td>2010-09-21</td>\n",
       "      <td>2018-01-11 05:56:00</td>\n",
       "      <td>90370</td>\n",
       "      <td>7.369</td>\n",
       "      <td>False</td>\n",
       "      <td>Human Resources</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Shawn</td>\n",
       "      <td>Male</td>\n",
       "      <td>1986-12-07</td>\n",
       "      <td>2018-01-11 19:45:00</td>\n",
       "      <td>111737</td>\n",
       "      <td>6.414</td>\n",
       "      <td>False</td>\n",
       "      <td>Product</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Diana</td>\n",
       "      <td>Female</td>\n",
       "      <td>1981-10-23</td>\n",
       "      <td>2018-01-11 10:27:00</td>\n",
       "      <td>132940</td>\n",
       "      <td>19.082</td>\n",
       "      <td>False</td>\n",
       "      <td>Client Services</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Donna</td>\n",
       "      <td>Female</td>\n",
       "      <td>2010-07-22</td>\n",
       "      <td>2018-01-11 03:48:00</td>\n",
       "      <td>81014</td>\n",
       "      <td>1.894</td>\n",
       "      <td>False</td>\n",
       "      <td>Product</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Lois</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1995-04-22</td>\n",
       "      <td>2018-01-11 19:18:00</td>\n",
       "      <td>64714</td>\n",
       "      <td>4.934</td>\n",
       "      <td>True</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Matthew</td>\n",
       "      <td>Male</td>\n",
       "      <td>1995-09-05</td>\n",
       "      <td>2018-01-11 02:12:00</td>\n",
       "      <td>100612</td>\n",
       "      <td>13.645</td>\n",
       "      <td>False</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Joshua</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2012-03-08</td>\n",
       "      <td>2018-01-11 01:58:00</td>\n",
       "      <td>90816</td>\n",
       "      <td>18.816</td>\n",
       "      <td>True</td>\n",
       "      <td>Client Services</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Male</td>\n",
       "      <td>2012-06-14</td>\n",
       "      <td>2018-01-11 16:19:00</td>\n",
       "      <td>125792</td>\n",
       "      <td>5.042</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>John</td>\n",
       "      <td>Male</td>\n",
       "      <td>1992-07-01</td>\n",
       "      <td>2018-01-11 22:08:00</td>\n",
       "      <td>97950</td>\n",
       "      <td>13.873</td>\n",
       "      <td>False</td>\n",
       "      <td>Client Services</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Male</td>\n",
       "      <td>2012-10-08</td>\n",
       "      <td>2018-01-11 01:12:00</td>\n",
       "      <td>37076</td>\n",
       "      <td>18.576</td>\n",
       "      <td>True</td>\n",
       "      <td>Client Services</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Craig</td>\n",
       "      <td>Male</td>\n",
       "      <td>2000-02-27</td>\n",
       "      <td>2018-01-11 07:45:00</td>\n",
       "      <td>37598</td>\n",
       "      <td>7.757</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Scott</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1991-07-11</td>\n",
       "      <td>2018-01-11 18:58:00</td>\n",
       "      <td>122367</td>\n",
       "      <td>5.218</td>\n",
       "      <td>False</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Terry</td>\n",
       "      <td>Male</td>\n",
       "      <td>1981-11-27</td>\n",
       "      <td>2018-01-11 18:30:00</td>\n",
       "      <td>124008</td>\n",
       "      <td>13.464</td>\n",
       "      <td>True</td>\n",
       "      <td>Client Services</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Benjamin</td>\n",
       "      <td>Male</td>\n",
       "      <td>2005-01-26</td>\n",
       "      <td>2018-01-11 22:06:00</td>\n",
       "      <td>79529</td>\n",
       "      <td>7.008</td>\n",
       "      <td>True</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>970</th>\n",
       "      <td>Alice</td>\n",
       "      <td>Female</td>\n",
       "      <td>1988-09-03</td>\n",
       "      <td>2018-01-11 20:54:00</td>\n",
       "      <td>63571</td>\n",
       "      <td>15.397</td>\n",
       "      <td>True</td>\n",
       "      <td>Product</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>971</th>\n",
       "      <td>Patrick</td>\n",
       "      <td>Male</td>\n",
       "      <td>2002-12-30</td>\n",
       "      <td>2018-01-11 02:01:00</td>\n",
       "      <td>75423</td>\n",
       "      <td>5.368</td>\n",
       "      <td>True</td>\n",
       "      <td>Business Development</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>972</th>\n",
       "      <td>Victor</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2006-07-28</td>\n",
       "      <td>2018-01-11 14:49:00</td>\n",
       "      <td>76381</td>\n",
       "      <td>11.159</td>\n",
       "      <td>True</td>\n",
       "      <td>Sales</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>973</th>\n",
       "      <td>Russell</td>\n",
       "      <td>Male</td>\n",
       "      <td>2013-05-10</td>\n",
       "      <td>2018-01-11 23:08:00</td>\n",
       "      <td>137359</td>\n",
       "      <td>11.105</td>\n",
       "      <td>False</td>\n",
       "      <td>Business Development</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>974</th>\n",
       "      <td>Harry</td>\n",
       "      <td>Male</td>\n",
       "      <td>2011-08-30</td>\n",
       "      <td>2018-01-11 18:31:00</td>\n",
       "      <td>67656</td>\n",
       "      <td>16.455</td>\n",
       "      <td>True</td>\n",
       "      <td>Client Services</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>975</th>\n",
       "      <td>Susan</td>\n",
       "      <td>Female</td>\n",
       "      <td>1995-04-07</td>\n",
       "      <td>2018-01-11 22:05:00</td>\n",
       "      <td>92436</td>\n",
       "      <td>12.467</td>\n",
       "      <td>False</td>\n",
       "      <td>Sales</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>976</th>\n",
       "      <td>Denise</td>\n",
       "      <td>Female</td>\n",
       "      <td>1992-10-19</td>\n",
       "      <td>2018-01-11 05:42:00</td>\n",
       "      <td>137954</td>\n",
       "      <td>4.195</td>\n",
       "      <td>True</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>977</th>\n",
       "      <td>Sarah</td>\n",
       "      <td>Female</td>\n",
       "      <td>1995-12-04</td>\n",
       "      <td>2018-01-11 09:16:00</td>\n",
       "      <td>124566</td>\n",
       "      <td>5.949</td>\n",
       "      <td>False</td>\n",
       "      <td>Product</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>978</th>\n",
       "      <td>Sean</td>\n",
       "      <td>Male</td>\n",
       "      <td>1983-01-17</td>\n",
       "      <td>2018-01-11 14:23:00</td>\n",
       "      <td>66146</td>\n",
       "      <td>11.178</td>\n",
       "      <td>False</td>\n",
       "      <td>Human Resources</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>979</th>\n",
       "      <td>Ernest</td>\n",
       "      <td>Male</td>\n",
       "      <td>2013-07-20</td>\n",
       "      <td>2018-01-11 06:41:00</td>\n",
       "      <td>142935</td>\n",
       "      <td>13.198</td>\n",
       "      <td>True</td>\n",
       "      <td>Product</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>980</th>\n",
       "      <td>Kimberly</td>\n",
       "      <td>Female</td>\n",
       "      <td>2013-01-26</td>\n",
       "      <td>2018-01-11 00:57:00</td>\n",
       "      <td>46233</td>\n",
       "      <td>8.862</td>\n",
       "      <td>True</td>\n",
       "      <td>Engineering</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>981</th>\n",
       "      <td>James</td>\n",
       "      <td>Male</td>\n",
       "      <td>1993-01-15</td>\n",
       "      <td>2018-01-11 17:19:00</td>\n",
       "      <td>148985</td>\n",
       "      <td>19.280</td>\n",
       "      <td>False</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>982</th>\n",
       "      <td>Rose</td>\n",
       "      <td>Female</td>\n",
       "      <td>1982-04-06</td>\n",
       "      <td>2018-01-11 10:43:00</td>\n",
       "      <td>91411</td>\n",
       "      <td>8.639</td>\n",
       "      <td>True</td>\n",
       "      <td>Human Resources</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>983</th>\n",
       "      <td>John</td>\n",
       "      <td>Male</td>\n",
       "      <td>1982-12-23</td>\n",
       "      <td>2018-01-11 22:35:00</td>\n",
       "      <td>146907</td>\n",
       "      <td>11.738</td>\n",
       "      <td>False</td>\n",
       "      <td>Engineering</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>984</th>\n",
       "      <td>Maria</td>\n",
       "      <td>Female</td>\n",
       "      <td>2011-10-15</td>\n",
       "      <td>2018-01-11 16:53:00</td>\n",
       "      <td>43455</td>\n",
       "      <td>13.040</td>\n",
       "      <td>False</td>\n",
       "      <td>Engineering</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>985</th>\n",
       "      <td>Stephen</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1983-07-10</td>\n",
       "      <td>2018-01-11 20:10:00</td>\n",
       "      <td>85668</td>\n",
       "      <td>1.909</td>\n",
       "      <td>False</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>986</th>\n",
       "      <td>Donna</td>\n",
       "      <td>Female</td>\n",
       "      <td>1982-11-26</td>\n",
       "      <td>2018-01-11 07:04:00</td>\n",
       "      <td>82871</td>\n",
       "      <td>17.999</td>\n",
       "      <td>False</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>987</th>\n",
       "      <td>Gloria</td>\n",
       "      <td>Female</td>\n",
       "      <td>2014-12-08</td>\n",
       "      <td>2018-01-11 05:08:00</td>\n",
       "      <td>136709</td>\n",
       "      <td>10.331</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>988</th>\n",
       "      <td>Alice</td>\n",
       "      <td>Female</td>\n",
       "      <td>2004-10-05</td>\n",
       "      <td>2018-01-11 09:34:00</td>\n",
       "      <td>47638</td>\n",
       "      <td>11.209</td>\n",
       "      <td>False</td>\n",
       "      <td>Human Resources</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>989</th>\n",
       "      <td>Justin</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1991-02-10</td>\n",
       "      <td>2018-01-11 16:58:00</td>\n",
       "      <td>38344</td>\n",
       "      <td>3.794</td>\n",
       "      <td>False</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>990</th>\n",
       "      <td>Robin</td>\n",
       "      <td>Female</td>\n",
       "      <td>1987-07-24</td>\n",
       "      <td>2018-01-11 13:35:00</td>\n",
       "      <td>100765</td>\n",
       "      <td>10.982</td>\n",
       "      <td>True</td>\n",
       "      <td>Client Services</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>991</th>\n",
       "      <td>Rose</td>\n",
       "      <td>Female</td>\n",
       "      <td>2002-08-25</td>\n",
       "      <td>2018-01-11 05:12:00</td>\n",
       "      <td>134505</td>\n",
       "      <td>11.051</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>992</th>\n",
       "      <td>Anthony</td>\n",
       "      <td>Male</td>\n",
       "      <td>2011-10-16</td>\n",
       "      <td>2018-01-11 08:35:00</td>\n",
       "      <td>112769</td>\n",
       "      <td>11.625</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>993</th>\n",
       "      <td>Tina</td>\n",
       "      <td>Female</td>\n",
       "      <td>1997-05-15</td>\n",
       "      <td>2018-01-11 15:53:00</td>\n",
       "      <td>56450</td>\n",
       "      <td>19.040</td>\n",
       "      <td>True</td>\n",
       "      <td>Engineering</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>994</th>\n",
       "      <td>George</td>\n",
       "      <td>Male</td>\n",
       "      <td>2013-06-21</td>\n",
       "      <td>2018-01-11 17:47:00</td>\n",
       "      <td>98874</td>\n",
       "      <td>4.479</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>995</th>\n",
       "      <td>Henry</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2014-11-23</td>\n",
       "      <td>2018-01-11 06:09:00</td>\n",
       "      <td>132483</td>\n",
       "      <td>16.655</td>\n",
       "      <td>False</td>\n",
       "      <td>Distribution</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>Phillip</td>\n",
       "      <td>Male</td>\n",
       "      <td>1984-01-31</td>\n",
       "      <td>2018-01-11 06:30:00</td>\n",
       "      <td>42392</td>\n",
       "      <td>19.675</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997</th>\n",
       "      <td>Russell</td>\n",
       "      <td>Male</td>\n",
       "      <td>2013-05-20</td>\n",
       "      <td>2018-01-11 12:39:00</td>\n",
       "      <td>96914</td>\n",
       "      <td>1.421</td>\n",
       "      <td>False</td>\n",
       "      <td>Product</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>998</th>\n",
       "      <td>Larry</td>\n",
       "      <td>Male</td>\n",
       "      <td>2013-04-20</td>\n",
       "      <td>2018-01-11 16:45:00</td>\n",
       "      <td>60500</td>\n",
       "      <td>11.985</td>\n",
       "      <td>False</td>\n",
       "      <td>Business Development</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>Albert</td>\n",
       "      <td>Male</td>\n",
       "      <td>2012-05-15</td>\n",
       "      <td>2018-01-11 18:24:00</td>\n",
       "      <td>129949</td>\n",
       "      <td>10.169</td>\n",
       "      <td>True</td>\n",
       "      <td>Sales</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1000 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    First Name  Gender Start Date     Last Login Time  Salary  Bonus %  \\\n",
       "0      Douglas    Male 1993-08-06 2018-01-11 12:42:00   97308    6.945   \n",
       "1       Thomas    Male 1996-03-31 2018-01-11 06:53:00   61933    4.170   \n",
       "2        Maria  Female 1993-04-23 2018-01-11 11:17:00  130590   11.858   \n",
       "3        Jerry    Male 2005-03-04 2018-01-11 13:00:00  138705    9.340   \n",
       "4        Larry    Male 1998-01-24 2018-01-11 16:47:00  101004    1.389   \n",
       "5       Dennis    Male 1987-04-18 2018-01-11 01:35:00  115163   10.125   \n",
       "6         Ruby  Female 1987-08-17 2018-01-11 16:20:00   65476   10.012   \n",
       "7          NaN  Female 2015-07-20 2018-01-11 10:43:00   45906   11.598   \n",
       "8       Angela  Female 2005-11-22 2018-01-11 06:29:00   95570   18.523   \n",
       "9      Frances  Female 2002-08-08 2018-01-11 06:51:00  139852    7.524   \n",
       "10      Louise  Female 1980-08-12 2018-01-11 09:01:00   63241   15.132   \n",
       "11       Julie  Female 1997-10-26 2018-01-11 15:19:00  102508   12.637   \n",
       "12     Brandon    Male 1980-12-01 2018-01-11 01:08:00  112807   17.492   \n",
       "13        Gary    Male 2008-01-27 2018-01-11 23:40:00  109831    5.831   \n",
       "14    Kimberly  Female 1999-01-14 2018-01-11 07:13:00   41426   14.543   \n",
       "15     Lillian  Female 2016-06-05 2018-01-11 06:09:00   59414    1.256   \n",
       "16      Jeremy    Male 2010-09-21 2018-01-11 05:56:00   90370    7.369   \n",
       "17       Shawn    Male 1986-12-07 2018-01-11 19:45:00  111737    6.414   \n",
       "18       Diana  Female 1981-10-23 2018-01-11 10:27:00  132940   19.082   \n",
       "19       Donna  Female 2010-07-22 2018-01-11 03:48:00   81014    1.894   \n",
       "20        Lois     NaN 1995-04-22 2018-01-11 19:18:00   64714    4.934   \n",
       "21     Matthew    Male 1995-09-05 2018-01-11 02:12:00  100612   13.645   \n",
       "22      Joshua     NaN 2012-03-08 2018-01-11 01:58:00   90816   18.816   \n",
       "23         NaN    Male 2012-06-14 2018-01-11 16:19:00  125792    5.042   \n",
       "24        John    Male 1992-07-01 2018-01-11 22:08:00   97950   13.873   \n",
       "25         NaN    Male 2012-10-08 2018-01-11 01:12:00   37076   18.576   \n",
       "26       Craig    Male 2000-02-27 2018-01-11 07:45:00   37598    7.757   \n",
       "27       Scott     NaN 1991-07-11 2018-01-11 18:58:00  122367    5.218   \n",
       "28       Terry    Male 1981-11-27 2018-01-11 18:30:00  124008   13.464   \n",
       "29    Benjamin    Male 2005-01-26 2018-01-11 22:06:00   79529    7.008   \n",
       "..         ...     ...        ...                 ...     ...      ...   \n",
       "970      Alice  Female 1988-09-03 2018-01-11 20:54:00   63571   15.397   \n",
       "971    Patrick    Male 2002-12-30 2018-01-11 02:01:00   75423    5.368   \n",
       "972     Victor     NaN 2006-07-28 2018-01-11 14:49:00   76381   11.159   \n",
       "973    Russell    Male 2013-05-10 2018-01-11 23:08:00  137359   11.105   \n",
       "974      Harry    Male 2011-08-30 2018-01-11 18:31:00   67656   16.455   \n",
       "975      Susan  Female 1995-04-07 2018-01-11 22:05:00   92436   12.467   \n",
       "976     Denise  Female 1992-10-19 2018-01-11 05:42:00  137954    4.195   \n",
       "977      Sarah  Female 1995-12-04 2018-01-11 09:16:00  124566    5.949   \n",
       "978       Sean    Male 1983-01-17 2018-01-11 14:23:00   66146   11.178   \n",
       "979     Ernest    Male 2013-07-20 2018-01-11 06:41:00  142935   13.198   \n",
       "980   Kimberly  Female 2013-01-26 2018-01-11 00:57:00   46233    8.862   \n",
       "981      James    Male 1993-01-15 2018-01-11 17:19:00  148985   19.280   \n",
       "982       Rose  Female 1982-04-06 2018-01-11 10:43:00   91411    8.639   \n",
       "983       John    Male 1982-12-23 2018-01-11 22:35:00  146907   11.738   \n",
       "984      Maria  Female 2011-10-15 2018-01-11 16:53:00   43455   13.040   \n",
       "985    Stephen     NaN 1983-07-10 2018-01-11 20:10:00   85668    1.909   \n",
       "986      Donna  Female 1982-11-26 2018-01-11 07:04:00   82871   17.999   \n",
       "987     Gloria  Female 2014-12-08 2018-01-11 05:08:00  136709   10.331   \n",
       "988      Alice  Female 2004-10-05 2018-01-11 09:34:00   47638   11.209   \n",
       "989     Justin     NaN 1991-02-10 2018-01-11 16:58:00   38344    3.794   \n",
       "990      Robin  Female 1987-07-24 2018-01-11 13:35:00  100765   10.982   \n",
       "991       Rose  Female 2002-08-25 2018-01-11 05:12:00  134505   11.051   \n",
       "992    Anthony    Male 2011-10-16 2018-01-11 08:35:00  112769   11.625   \n",
       "993       Tina  Female 1997-05-15 2018-01-11 15:53:00   56450   19.040   \n",
       "994     George    Male 2013-06-21 2018-01-11 17:47:00   98874    4.479   \n",
       "995      Henry     NaN 2014-11-23 2018-01-11 06:09:00  132483   16.655   \n",
       "996    Phillip    Male 1984-01-31 2018-01-11 06:30:00   42392   19.675   \n",
       "997    Russell    Male 2013-05-20 2018-01-11 12:39:00   96914    1.421   \n",
       "998      Larry    Male 2013-04-20 2018-01-11 16:45:00   60500   11.985   \n",
       "999     Albert    Male 2012-05-15 2018-01-11 18:24:00  129949   10.169   \n",
       "\n",
       "     Senior Management                  Team  \n",
       "0                 True             Marketing  \n",
       "1                 True                   NaN  \n",
       "2                False               Finance  \n",
       "3                 True               Finance  \n",
       "4                 True       Client Services  \n",
       "5                False                 Legal  \n",
       "6                 True               Product  \n",
       "7                 True               Finance  \n",
       "8                 True           Engineering  \n",
       "9                 True  Business Development  \n",
       "10                True                   NaN  \n",
       "11                True                 Legal  \n",
       "12                True       Human Resources  \n",
       "13               False                 Sales  \n",
       "14                True               Finance  \n",
       "15               False               Product  \n",
       "16               False       Human Resources  \n",
       "17               False               Product  \n",
       "18               False       Client Services  \n",
       "19               False               Product  \n",
       "20                True                 Legal  \n",
       "21               False             Marketing  \n",
       "22                True       Client Services  \n",
       "23                True                   NaN  \n",
       "24               False       Client Services  \n",
       "25                True       Client Services  \n",
       "26                True             Marketing  \n",
       "27               False                 Legal  \n",
       "28                True       Client Services  \n",
       "29                True                 Legal  \n",
       "..                 ...                   ...  \n",
       "970               True               Product  \n",
       "971               True  Business Development  \n",
       "972               True                 Sales  \n",
       "973              False  Business Development  \n",
       "974               True       Client Services  \n",
       "975              False                 Sales  \n",
       "976               True                 Legal  \n",
       "977              False               Product  \n",
       "978              False       Human Resources  \n",
       "979               True               Product  \n",
       "980               True           Engineering  \n",
       "981              False                 Legal  \n",
       "982               True       Human Resources  \n",
       "983              False           Engineering  \n",
       "984              False           Engineering  \n",
       "985              False                 Legal  \n",
       "986              False             Marketing  \n",
       "987               True               Finance  \n",
       "988              False       Human Resources  \n",
       "989              False                 Legal  \n",
       "990               True       Client Services  \n",
       "991               True             Marketing  \n",
       "992               True               Finance  \n",
       "993               True           Engineering  \n",
       "994               True             Marketing  \n",
       "995              False          Distribution  \n",
       "996              False               Finance  \n",
       "997              False               Product  \n",
       "998              False  Business Development  \n",
       "999               True                 Sales  \n",
       "\n",
       "[1000 rows x 8 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
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       "    .dataframe thead th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>First Name</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Start Date</th>\n",
       "      <th>Last Login Time</th>\n",
       "      <th>Salary</th>\n",
       "      <th>Bonus %</th>\n",
       "      <th>Senior Management</th>\n",
       "      <th>Team</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Douglas</td>\n",
       "      <td>Male</td>\n",
       "      <td>1993-08-06</td>\n",
       "      <td>2018-01-11 12:42:00</td>\n",
       "      <td>97308</td>\n",
       "      <td>6.945</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Thomas</td>\n",
       "      <td>Male</td>\n",
       "      <td>1996-03-31</td>\n",
       "      <td>2018-01-11 06:53:00</td>\n",
       "      <td>61933</td>\n",
       "      <td>4.170</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Jerry</td>\n",
       "      <td>Male</td>\n",
       "      <td>2005-03-04</td>\n",
       "      <td>2018-01-11 13:00:00</td>\n",
       "      <td>138705</td>\n",
       "      <td>9.340</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Larry</td>\n",
       "      <td>Male</td>\n",
       "      <td>1998-01-24</td>\n",
       "      <td>2018-01-11 16:47:00</td>\n",
       "      <td>101004</td>\n",
       "      <td>1.389</td>\n",
       "      <td>True</td>\n",
       "      <td>Client Services</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Dennis</td>\n",
       "      <td>Male</td>\n",
       "      <td>1987-04-18</td>\n",
       "      <td>2018-01-11 01:35:00</td>\n",
       "      <td>115163</td>\n",
       "      <td>10.125</td>\n",
       "      <td>False</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Brandon</td>\n",
       "      <td>Male</td>\n",
       "      <td>1980-12-01</td>\n",
       "      <td>2018-01-11 01:08:00</td>\n",
       "      <td>112807</td>\n",
       "      <td>17.492</td>\n",
       "      <td>True</td>\n",
       "      <td>Human Resources</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Gary</td>\n",
       "      <td>Male</td>\n",
       "      <td>2008-01-27</td>\n",
       "      <td>2018-01-11 23:40:00</td>\n",
       "      <td>109831</td>\n",
       "      <td>5.831</td>\n",
       "      <td>False</td>\n",
       "      <td>Sales</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Jeremy</td>\n",
       "      <td>Male</td>\n",
       "      <td>2010-09-21</td>\n",
       "      <td>2018-01-11 05:56:00</td>\n",
       "      <td>90370</td>\n",
       "      <td>7.369</td>\n",
       "      <td>False</td>\n",
       "      <td>Human Resources</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Shawn</td>\n",
       "      <td>Male</td>\n",
       "      <td>1986-12-07</td>\n",
       "      <td>2018-01-11 19:45:00</td>\n",
       "      <td>111737</td>\n",
       "      <td>6.414</td>\n",
       "      <td>False</td>\n",
       "      <td>Product</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Matthew</td>\n",
       "      <td>Male</td>\n",
       "      <td>1995-09-05</td>\n",
       "      <td>2018-01-11 02:12:00</td>\n",
       "      <td>100612</td>\n",
       "      <td>13.645</td>\n",
       "      <td>False</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Male</td>\n",
       "      <td>2012-06-14</td>\n",
       "      <td>2018-01-11 16:19:00</td>\n",
       "      <td>125792</td>\n",
       "      <td>5.042</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>John</td>\n",
       "      <td>Male</td>\n",
       "      <td>1992-07-01</td>\n",
       "      <td>2018-01-11 22:08:00</td>\n",
       "      <td>97950</td>\n",
       "      <td>13.873</td>\n",
       "      <td>False</td>\n",
       "      <td>Client Services</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Male</td>\n",
       "      <td>2012-10-08</td>\n",
       "      <td>2018-01-11 01:12:00</td>\n",
       "      <td>37076</td>\n",
       "      <td>18.576</td>\n",
       "      <td>True</td>\n",
       "      <td>Client Services</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Craig</td>\n",
       "      <td>Male</td>\n",
       "      <td>2000-02-27</td>\n",
       "      <td>2018-01-11 07:45:00</td>\n",
       "      <td>37598</td>\n",
       "      <td>7.757</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Terry</td>\n",
       "      <td>Male</td>\n",
       "      <td>1981-11-27</td>\n",
       "      <td>2018-01-11 18:30:00</td>\n",
       "      <td>124008</td>\n",
       "      <td>13.464</td>\n",
       "      <td>True</td>\n",
       "      <td>Client Services</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Benjamin</td>\n",
       "      <td>Male</td>\n",
       "      <td>2005-01-26</td>\n",
       "      <td>2018-01-11 22:06:00</td>\n",
       "      <td>79529</td>\n",
       "      <td>7.008</td>\n",
       "      <td>True</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Male</td>\n",
       "      <td>1998-08-21</td>\n",
       "      <td>2018-01-11 14:27:00</td>\n",
       "      <td>122340</td>\n",
       "      <td>6.417</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Jerry</td>\n",
       "      <td>Male</td>\n",
       "      <td>2004-01-10</td>\n",
       "      <td>2018-01-11 12:56:00</td>\n",
       "      <td>95734</td>\n",
       "      <td>19.096</td>\n",
       "      <td>False</td>\n",
       "      <td>Client Services</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Male</td>\n",
       "      <td>2016-01-29</td>\n",
       "      <td>2018-01-11 02:33:00</td>\n",
       "      <td>122173</td>\n",
       "      <td>7.797</td>\n",
       "      <td>True</td>\n",
       "      <td>Client Services</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>Michael</td>\n",
       "      <td>Male</td>\n",
       "      <td>2008-10-10</td>\n",
       "      <td>2018-01-11 11:25:00</td>\n",
       "      <td>99283</td>\n",
       "      <td>2.665</td>\n",
       "      <td>True</td>\n",
       "      <td>Distribution</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>Roger</td>\n",
       "      <td>Male</td>\n",
       "      <td>1980-04-17</td>\n",
       "      <td>2018-01-11 11:32:00</td>\n",
       "      <td>88010</td>\n",
       "      <td>13.886</td>\n",
       "      <td>True</td>\n",
       "      <td>Sales</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>Bruce</td>\n",
       "      <td>Male</td>\n",
       "      <td>2009-11-28</td>\n",
       "      <td>2018-01-11 22:47:00</td>\n",
       "      <td>114796</td>\n",
       "      <td>6.796</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>Clarence</td>\n",
       "      <td>Male</td>\n",
       "      <td>1996-03-26</td>\n",
       "      <td>2018-01-11 05:57:00</td>\n",
       "      <td>93581</td>\n",
       "      <td>6.083</td>\n",
       "      <td>True</td>\n",
       "      <td>Business Development</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>Todd</td>\n",
       "      <td>Male</td>\n",
       "      <td>1990-02-18</td>\n",
       "      <td>2018-01-11 02:41:00</td>\n",
       "      <td>49339</td>\n",
       "      <td>1.695</td>\n",
       "      <td>True</td>\n",
       "      <td>Human Resources</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>Carl</td>\n",
       "      <td>Male</td>\n",
       "      <td>2006-05-03</td>\n",
       "      <td>2018-01-11 17:55:00</td>\n",
       "      <td>130276</td>\n",
       "      <td>16.084</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>Henry</td>\n",
       "      <td>Male</td>\n",
       "      <td>1996-06-26</td>\n",
       "      <td>2018-01-11 01:44:00</td>\n",
       "      <td>64715</td>\n",
       "      <td>15.107</td>\n",
       "      <td>True</td>\n",
       "      <td>Human Resources</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>Matthew</td>\n",
       "      <td>Male</td>\n",
       "      <td>2013-01-02</td>\n",
       "      <td>2018-01-11 22:33:00</td>\n",
       "      <td>35203</td>\n",
       "      <td>18.040</td>\n",
       "      <td>False</td>\n",
       "      <td>Human Resources</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>Steve</td>\n",
       "      <td>Male</td>\n",
       "      <td>2009-11-11</td>\n",
       "      <td>2018-01-11 23:44:00</td>\n",
       "      <td>61310</td>\n",
       "      <td>12.428</td>\n",
       "      <td>True</td>\n",
       "      <td>Distribution</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>Jose</td>\n",
       "      <td>Male</td>\n",
       "      <td>2004-10-30</td>\n",
       "      <td>2018-01-11 13:39:00</td>\n",
       "      <td>84834</td>\n",
       "      <td>14.330</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>Johnny</td>\n",
       "      <td>Male</td>\n",
       "      <td>2009-11-06</td>\n",
       "      <td>2018-01-11 16:23:00</td>\n",
       "      <td>118172</td>\n",
       "      <td>16.194</td>\n",
       "      <td>True</td>\n",
       "      <td>Sales</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>931</th>\n",
       "      <td>Harold</td>\n",
       "      <td>Male</td>\n",
       "      <td>2012-06-23</td>\n",
       "      <td>2018-01-11 12:40:00</td>\n",
       "      <td>140444</td>\n",
       "      <td>3.771</td>\n",
       "      <td>False</td>\n",
       "      <td>Distribution</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>934</th>\n",
       "      <td>Samuel</td>\n",
       "      <td>Male</td>\n",
       "      <td>1997-08-07</td>\n",
       "      <td>2018-01-11 12:40:00</td>\n",
       "      <td>43694</td>\n",
       "      <td>3.787</td>\n",
       "      <td>True</td>\n",
       "      <td>Engineering</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>940</th>\n",
       "      <td>Andrew</td>\n",
       "      <td>Male</td>\n",
       "      <td>1990-09-28</td>\n",
       "      <td>2018-01-11 09:38:00</td>\n",
       "      <td>137386</td>\n",
       "      <td>8.611</td>\n",
       "      <td>True</td>\n",
       "      <td>Distribution</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>941</th>\n",
       "      <td>William</td>\n",
       "      <td>Male</td>\n",
       "      <td>1997-06-26</td>\n",
       "      <td>2018-01-11 08:33:00</td>\n",
       "      <td>104840</td>\n",
       "      <td>15.653</td>\n",
       "      <td>True</td>\n",
       "      <td>Engineering</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>943</th>\n",
       "      <td>Wayne</td>\n",
       "      <td>Male</td>\n",
       "      <td>2006-09-08</td>\n",
       "      <td>2018-01-11 11:09:00</td>\n",
       "      <td>67471</td>\n",
       "      <td>2.728</td>\n",
       "      <td>False</td>\n",
       "      <td>Engineering</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>944</th>\n",
       "      <td>Kenneth</td>\n",
       "      <td>Male</td>\n",
       "      <td>2006-05-10</td>\n",
       "      <td>2018-01-11 08:24:00</td>\n",
       "      <td>101914</td>\n",
       "      <td>1.905</td>\n",
       "      <td>True</td>\n",
       "      <td>Distribution</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>947</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Male</td>\n",
       "      <td>2012-07-30</td>\n",
       "      <td>2018-01-11 15:07:00</td>\n",
       "      <td>107351</td>\n",
       "      <td>5.329</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>949</th>\n",
       "      <td>Scott</td>\n",
       "      <td>Male</td>\n",
       "      <td>2011-08-20</td>\n",
       "      <td>2018-01-11 08:08:00</td>\n",
       "      <td>37385</td>\n",
       "      <td>8.226</td>\n",
       "      <td>True</td>\n",
       "      <td>Business Development</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>953</th>\n",
       "      <td>Randy</td>\n",
       "      <td>Male</td>\n",
       "      <td>2012-02-25</td>\n",
       "      <td>2018-01-11 05:33:00</td>\n",
       "      <td>57266</td>\n",
       "      <td>14.077</td>\n",
       "      <td>False</td>\n",
       "      <td>Product</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>954</th>\n",
       "      <td>Joe</td>\n",
       "      <td>Male</td>\n",
       "      <td>1980-01-19</td>\n",
       "      <td>2018-01-11 16:06:00</td>\n",
       "      <td>119667</td>\n",
       "      <td>1.148</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>957</th>\n",
       "      <td>Jeffrey</td>\n",
       "      <td>Male</td>\n",
       "      <td>1984-02-03</td>\n",
       "      <td>2018-01-11 13:26:00</td>\n",
       "      <td>70990</td>\n",
       "      <td>15.901</td>\n",
       "      <td>True</td>\n",
       "      <td>Sales</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>959</th>\n",
       "      <td>Albert</td>\n",
       "      <td>Male</td>\n",
       "      <td>1992-09-19</td>\n",
       "      <td>2018-01-11 02:35:00</td>\n",
       "      <td>45094</td>\n",
       "      <td>5.850</td>\n",
       "      <td>True</td>\n",
       "      <td>Business Development</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>960</th>\n",
       "      <td>Stephen</td>\n",
       "      <td>Male</td>\n",
       "      <td>1989-10-29</td>\n",
       "      <td>2018-01-11 23:34:00</td>\n",
       "      <td>93997</td>\n",
       "      <td>18.093</td>\n",
       "      <td>True</td>\n",
       "      <td>Business Development</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>962</th>\n",
       "      <td>Jonathan</td>\n",
       "      <td>Male</td>\n",
       "      <td>2013-08-21</td>\n",
       "      <td>2018-01-11 00:45:00</td>\n",
       "      <td>121797</td>\n",
       "      <td>16.923</td>\n",
       "      <td>False</td>\n",
       "      <td>Product</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>964</th>\n",
       "      <td>Bruce</td>\n",
       "      <td>Male</td>\n",
       "      <td>1980-05-07</td>\n",
       "      <td>2018-01-11 20:00:00</td>\n",
       "      <td>35802</td>\n",
       "      <td>12.391</td>\n",
       "      <td>True</td>\n",
       "      <td>Sales</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>966</th>\n",
       "      <td>Louis</td>\n",
       "      <td>Male</td>\n",
       "      <td>2011-08-16</td>\n",
       "      <td>2018-01-11 17:19:00</td>\n",
       "      <td>93022</td>\n",
       "      <td>9.146</td>\n",
       "      <td>True</td>\n",
       "      <td>Human Resources</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>967</th>\n",
       "      <td>Thomas</td>\n",
       "      <td>Male</td>\n",
       "      <td>2016-03-12</td>\n",
       "      <td>2018-01-11 15:10:00</td>\n",
       "      <td>105681</td>\n",
       "      <td>19.572</td>\n",
       "      <td>False</td>\n",
       "      <td>Engineering</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>971</th>\n",
       "      <td>Patrick</td>\n",
       "      <td>Male</td>\n",
       "      <td>2002-12-30</td>\n",
       "      <td>2018-01-11 02:01:00</td>\n",
       "      <td>75423</td>\n",
       "      <td>5.368</td>\n",
       "      <td>True</td>\n",
       "      <td>Business Development</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>973</th>\n",
       "      <td>Russell</td>\n",
       "      <td>Male</td>\n",
       "      <td>2013-05-10</td>\n",
       "      <td>2018-01-11 23:08:00</td>\n",
       "      <td>137359</td>\n",
       "      <td>11.105</td>\n",
       "      <td>False</td>\n",
       "      <td>Business Development</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>974</th>\n",
       "      <td>Harry</td>\n",
       "      <td>Male</td>\n",
       "      <td>2011-08-30</td>\n",
       "      <td>2018-01-11 18:31:00</td>\n",
       "      <td>67656</td>\n",
       "      <td>16.455</td>\n",
       "      <td>True</td>\n",
       "      <td>Client Services</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>978</th>\n",
       "      <td>Sean</td>\n",
       "      <td>Male</td>\n",
       "      <td>1983-01-17</td>\n",
       "      <td>2018-01-11 14:23:00</td>\n",
       "      <td>66146</td>\n",
       "      <td>11.178</td>\n",
       "      <td>False</td>\n",
       "      <td>Human Resources</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>979</th>\n",
       "      <td>Ernest</td>\n",
       "      <td>Male</td>\n",
       "      <td>2013-07-20</td>\n",
       "      <td>2018-01-11 06:41:00</td>\n",
       "      <td>142935</td>\n",
       "      <td>13.198</td>\n",
       "      <td>True</td>\n",
       "      <td>Product</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>981</th>\n",
       "      <td>James</td>\n",
       "      <td>Male</td>\n",
       "      <td>1993-01-15</td>\n",
       "      <td>2018-01-11 17:19:00</td>\n",
       "      <td>148985</td>\n",
       "      <td>19.280</td>\n",
       "      <td>False</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>983</th>\n",
       "      <td>John</td>\n",
       "      <td>Male</td>\n",
       "      <td>1982-12-23</td>\n",
       "      <td>2018-01-11 22:35:00</td>\n",
       "      <td>146907</td>\n",
       "      <td>11.738</td>\n",
       "      <td>False</td>\n",
       "      <td>Engineering</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>992</th>\n",
       "      <td>Anthony</td>\n",
       "      <td>Male</td>\n",
       "      <td>2011-10-16</td>\n",
       "      <td>2018-01-11 08:35:00</td>\n",
       "      <td>112769</td>\n",
       "      <td>11.625</td>\n",
       "      <td>True</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>994</th>\n",
       "      <td>George</td>\n",
       "      <td>Male</td>\n",
       "      <td>2013-06-21</td>\n",
       "      <td>2018-01-11 17:47:00</td>\n",
       "      <td>98874</td>\n",
       "      <td>4.479</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>Phillip</td>\n",
       "      <td>Male</td>\n",
       "      <td>1984-01-31</td>\n",
       "      <td>2018-01-11 06:30:00</td>\n",
       "      <td>42392</td>\n",
       "      <td>19.675</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997</th>\n",
       "      <td>Russell</td>\n",
       "      <td>Male</td>\n",
       "      <td>2013-05-20</td>\n",
       "      <td>2018-01-11 12:39:00</td>\n",
       "      <td>96914</td>\n",
       "      <td>1.421</td>\n",
       "      <td>False</td>\n",
       "      <td>Product</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>998</th>\n",
       "      <td>Larry</td>\n",
       "      <td>Male</td>\n",
       "      <td>2013-04-20</td>\n",
       "      <td>2018-01-11 16:45:00</td>\n",
       "      <td>60500</td>\n",
       "      <td>11.985</td>\n",
       "      <td>False</td>\n",
       "      <td>Business Development</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>Albert</td>\n",
       "      <td>Male</td>\n",
       "      <td>2012-05-15</td>\n",
       "      <td>2018-01-11 18:24:00</td>\n",
       "      <td>129949</td>\n",
       "      <td>10.169</td>\n",
       "      <td>True</td>\n",
       "      <td>Sales</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>424 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    First Name Gender Start Date     Last Login Time  Salary  Bonus %  \\\n",
       "0      Douglas   Male 1993-08-06 2018-01-11 12:42:00   97308    6.945   \n",
       "1       Thomas   Male 1996-03-31 2018-01-11 06:53:00   61933    4.170   \n",
       "3        Jerry   Male 2005-03-04 2018-01-11 13:00:00  138705    9.340   \n",
       "4        Larry   Male 1998-01-24 2018-01-11 16:47:00  101004    1.389   \n",
       "5       Dennis   Male 1987-04-18 2018-01-11 01:35:00  115163   10.125   \n",
       "12     Brandon   Male 1980-12-01 2018-01-11 01:08:00  112807   17.492   \n",
       "13        Gary   Male 2008-01-27 2018-01-11 23:40:00  109831    5.831   \n",
       "16      Jeremy   Male 2010-09-21 2018-01-11 05:56:00   90370    7.369   \n",
       "17       Shawn   Male 1986-12-07 2018-01-11 19:45:00  111737    6.414   \n",
       "21     Matthew   Male 1995-09-05 2018-01-11 02:12:00  100612   13.645   \n",
       "23         NaN   Male 2012-06-14 2018-01-11 16:19:00  125792    5.042   \n",
       "24        John   Male 1992-07-01 2018-01-11 22:08:00   97950   13.873   \n",
       "25         NaN   Male 2012-10-08 2018-01-11 01:12:00   37076   18.576   \n",
       "26       Craig   Male 2000-02-27 2018-01-11 07:45:00   37598    7.757   \n",
       "28       Terry   Male 1981-11-27 2018-01-11 18:30:00  124008   13.464   \n",
       "29    Benjamin   Male 2005-01-26 2018-01-11 22:06:00   79529    7.008   \n",
       "32         NaN   Male 1998-08-21 2018-01-11 14:27:00  122340    6.417   \n",
       "34       Jerry   Male 2004-01-10 2018-01-11 12:56:00   95734   19.096   \n",
       "39         NaN   Male 2016-01-29 2018-01-11 02:33:00  122173    7.797   \n",
       "40     Michael   Male 2008-10-10 2018-01-11 11:25:00   99283    2.665   \n",
       "45       Roger   Male 1980-04-17 2018-01-11 11:32:00   88010   13.886   \n",
       "46       Bruce   Male 2009-11-28 2018-01-11 22:47:00  114796    6.796   \n",
       "48    Clarence   Male 1996-03-26 2018-01-11 05:57:00   93581    6.083   \n",
       "52        Todd   Male 1990-02-18 2018-01-11 02:41:00   49339    1.695   \n",
       "56        Carl   Male 2006-05-03 2018-01-11 17:55:00  130276   16.084   \n",
       "57       Henry   Male 1996-06-26 2018-01-11 01:44:00   64715   15.107   \n",
       "63     Matthew   Male 2013-01-02 2018-01-11 22:33:00   35203   18.040   \n",
       "65       Steve   Male 2009-11-11 2018-01-11 23:44:00   61310   12.428   \n",
       "68        Jose   Male 2004-10-30 2018-01-11 13:39:00   84834   14.330   \n",
       "71      Johnny   Male 2009-11-06 2018-01-11 16:23:00  118172   16.194   \n",
       "..         ...    ...        ...                 ...     ...      ...   \n",
       "931     Harold   Male 2012-06-23 2018-01-11 12:40:00  140444    3.771   \n",
       "934     Samuel   Male 1997-08-07 2018-01-11 12:40:00   43694    3.787   \n",
       "940     Andrew   Male 1990-09-28 2018-01-11 09:38:00  137386    8.611   \n",
       "941    William   Male 1997-06-26 2018-01-11 08:33:00  104840   15.653   \n",
       "943      Wayne   Male 2006-09-08 2018-01-11 11:09:00   67471    2.728   \n",
       "944    Kenneth   Male 2006-05-10 2018-01-11 08:24:00  101914    1.905   \n",
       "947        NaN   Male 2012-07-30 2018-01-11 15:07:00  107351    5.329   \n",
       "949      Scott   Male 2011-08-20 2018-01-11 08:08:00   37385    8.226   \n",
       "953      Randy   Male 2012-02-25 2018-01-11 05:33:00   57266   14.077   \n",
       "954        Joe   Male 1980-01-19 2018-01-11 16:06:00  119667    1.148   \n",
       "957    Jeffrey   Male 1984-02-03 2018-01-11 13:26:00   70990   15.901   \n",
       "959     Albert   Male 1992-09-19 2018-01-11 02:35:00   45094    5.850   \n",
       "960    Stephen   Male 1989-10-29 2018-01-11 23:34:00   93997   18.093   \n",
       "962   Jonathan   Male 2013-08-21 2018-01-11 00:45:00  121797   16.923   \n",
       "964      Bruce   Male 1980-05-07 2018-01-11 20:00:00   35802   12.391   \n",
       "966      Louis   Male 2011-08-16 2018-01-11 17:19:00   93022    9.146   \n",
       "967     Thomas   Male 2016-03-12 2018-01-11 15:10:00  105681   19.572   \n",
       "971    Patrick   Male 2002-12-30 2018-01-11 02:01:00   75423    5.368   \n",
       "973    Russell   Male 2013-05-10 2018-01-11 23:08:00  137359   11.105   \n",
       "974      Harry   Male 2011-08-30 2018-01-11 18:31:00   67656   16.455   \n",
       "978       Sean   Male 1983-01-17 2018-01-11 14:23:00   66146   11.178   \n",
       "979     Ernest   Male 2013-07-20 2018-01-11 06:41:00  142935   13.198   \n",
       "981      James   Male 1993-01-15 2018-01-11 17:19:00  148985   19.280   \n",
       "983       John   Male 1982-12-23 2018-01-11 22:35:00  146907   11.738   \n",
       "992    Anthony   Male 2011-10-16 2018-01-11 08:35:00  112769   11.625   \n",
       "994     George   Male 2013-06-21 2018-01-11 17:47:00   98874    4.479   \n",
       "996    Phillip   Male 1984-01-31 2018-01-11 06:30:00   42392   19.675   \n",
       "997    Russell   Male 2013-05-20 2018-01-11 12:39:00   96914    1.421   \n",
       "998      Larry   Male 2013-04-20 2018-01-11 16:45:00   60500   11.985   \n",
       "999     Albert   Male 2012-05-15 2018-01-11 18:24:00  129949   10.169   \n",
       "\n",
       "     Senior Management                  Team  \n",
       "0                 True             Marketing  \n",
       "1                 True                   NaN  \n",
       "3                 True               Finance  \n",
       "4                 True       Client Services  \n",
       "5                False                 Legal  \n",
       "12                True       Human Resources  \n",
       "13               False                 Sales  \n",
       "16               False       Human Resources  \n",
       "17               False               Product  \n",
       "21               False             Marketing  \n",
       "23                True                   NaN  \n",
       "24               False       Client Services  \n",
       "25                True       Client Services  \n",
       "26                True             Marketing  \n",
       "28                True       Client Services  \n",
       "29                True                 Legal  \n",
       "32                True                   NaN  \n",
       "34               False       Client Services  \n",
       "39                True       Client Services  \n",
       "40                True          Distribution  \n",
       "45                True                 Sales  \n",
       "46               False               Finance  \n",
       "48                True  Business Development  \n",
       "52                True       Human Resources  \n",
       "56                True               Finance  \n",
       "57                True       Human Resources  \n",
       "63               False       Human Resources  \n",
       "65                True          Distribution  \n",
       "68                True               Finance  \n",
       "71                True                 Sales  \n",
       "..                 ...                   ...  \n",
       "931              False          Distribution  \n",
       "934               True           Engineering  \n",
       "940               True          Distribution  \n",
       "941               True           Engineering  \n",
       "943              False           Engineering  \n",
       "944               True          Distribution  \n",
       "947               True             Marketing  \n",
       "949               True  Business Development  \n",
       "953              False               Product  \n",
       "954               True               Finance  \n",
       "957               True                 Sales  \n",
       "959               True  Business Development  \n",
       "960               True  Business Development  \n",
       "962              False               Product  \n",
       "964               True                 Sales  \n",
       "966               True       Human Resources  \n",
       "967              False           Engineering  \n",
       "971               True  Business Development  \n",
       "973              False  Business Development  \n",
       "974               True       Client Services  \n",
       "978              False       Human Resources  \n",
       "979               True               Product  \n",
       "981              False                 Legal  \n",
       "983              False           Engineering  \n",
       "992               True               Finance  \n",
       "994               True             Marketing  \n",
       "996              False               Finance  \n",
       "997              False               Product  \n",
       "998              False  Business Development  \n",
       "999               True                 Sales  \n",
       "\n",
       "[424 rows x 8 columns]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df[\"Gender\"] == \"Male\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyError",
     "evalue": "'team'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m   2441\u001b[0m             \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2442\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2443\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mKeyError\u001b[0m: 'team'",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-34-c55621c97461>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"team\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   1962\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_multilevel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1963\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1964\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_column\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1965\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1966\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_getitem_column\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m_getitem_column\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   1969\u001b[0m         \u001b[0;31m# get column\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1970\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_unique\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1971\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_item_cache\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1972\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1973\u001b[0m         \u001b[0;31m# duplicate columns & possible reduce dimensionality\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36m_get_item_cache\u001b[0;34m(self, item)\u001b[0m\n\u001b[1;32m   1643\u001b[0m         \u001b[0mres\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcache\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1644\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mres\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1645\u001b[0;31m             \u001b[0mvalues\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_data\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1646\u001b[0m             \u001b[0mres\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_box_item_values\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalues\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1647\u001b[0m             \u001b[0mcache\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mres\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/pandas/core/internals.py\u001b[0m in \u001b[0;36mget\u001b[0;34m(self, item, fastpath)\u001b[0m\n\u001b[1;32m   3588\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3589\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0misnull\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3590\u001b[0;31m                 \u001b[0mloc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   3591\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3592\u001b[0m                 \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0misnull\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m   2442\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2443\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2444\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_maybe_cast_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2445\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2446\u001b[0m         \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmethod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtolerance\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtolerance\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mKeyError\u001b[0m: 'team'"
     ]
    }
   ],
   "source": [
    "df[\"team\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\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>First Name</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Start Date</th>\n",
       "      <th>Last Login Time</th>\n",
       "      <th>Salary</th>\n",
       "      <th>Bonus %</th>\n",
       "      <th>Senior Management</th>\n",
       "      <th>Team</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Douglas</td>\n",
       "      <td>Male</td>\n",
       "      <td>1993-08-06</td>\n",
       "      <td>2018-01-11 12:42:00</td>\n",
       "      <td>97308</td>\n",
       "      <td>6.945</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Dennis</td>\n",
       "      <td>Male</td>\n",
       "      <td>1987-04-18</td>\n",
       "      <td>2018-01-11 01:35:00</td>\n",
       "      <td>115163</td>\n",
       "      <td>10.125</td>\n",
       "      <td>False</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Julie</td>\n",
       "      <td>Female</td>\n",
       "      <td>1997-10-26</td>\n",
       "      <td>2018-01-11 15:19:00</td>\n",
       "      <td>102508</td>\n",
       "      <td>12.637</td>\n",
       "      <td>True</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Lois</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1995-04-22</td>\n",
       "      <td>2018-01-11 19:18:00</td>\n",
       "      <td>64714</td>\n",
       "      <td>4.934</td>\n",
       "      <td>True</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Matthew</td>\n",
       "      <td>Male</td>\n",
       "      <td>1995-09-05</td>\n",
       "      <td>2018-01-11 02:12:00</td>\n",
       "      <td>100612</td>\n",
       "      <td>13.645</td>\n",
       "      <td>False</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Craig</td>\n",
       "      <td>Male</td>\n",
       "      <td>2000-02-27</td>\n",
       "      <td>2018-01-11 07:45:00</td>\n",
       "      <td>37598</td>\n",
       "      <td>7.757</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Scott</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1991-07-11</td>\n",
       "      <td>2018-01-11 18:58:00</td>\n",
       "      <td>122367</td>\n",
       "      <td>5.218</td>\n",
       "      <td>False</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Benjamin</td>\n",
       "      <td>Male</td>\n",
       "      <td>2005-01-26</td>\n",
       "      <td>2018-01-11 22:06:00</td>\n",
       "      <td>79529</td>\n",
       "      <td>7.008</td>\n",
       "      <td>True</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>Beverly</td>\n",
       "      <td>Female</td>\n",
       "      <td>1998-09-09</td>\n",
       "      <td>2018-01-11 20:26:00</td>\n",
       "      <td>121918</td>\n",
       "      <td>15.835</td>\n",
       "      <td>False</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>Marilyn</td>\n",
       "      <td>Female</td>\n",
       "      <td>1980-12-07</td>\n",
       "      <td>2018-01-11 03:16:00</td>\n",
       "      <td>73524</td>\n",
       "      <td>5.207</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Female</td>\n",
       "      <td>2007-06-12</td>\n",
       "      <td>2018-01-11 17:25:00</td>\n",
       "      <td>58112</td>\n",
       "      <td>19.414</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>Thomas</td>\n",
       "      <td>Male</td>\n",
       "      <td>1995-06-04</td>\n",
       "      <td>2018-01-11 14:24:00</td>\n",
       "      <td>62096</td>\n",
       "      <td>17.029</td>\n",
       "      <td>False</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>Charles</td>\n",
       "      <td>Male</td>\n",
       "      <td>2004-09-14</td>\n",
       "      <td>2018-01-11 20:13:00</td>\n",
       "      <td>107391</td>\n",
       "      <td>1.260</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>Christopher</td>\n",
       "      <td>Male</td>\n",
       "      <td>2008-03-30</td>\n",
       "      <td>2018-01-11 10:52:00</td>\n",
       "      <td>47369</td>\n",
       "      <td>14.822</td>\n",
       "      <td>False</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>Donna</td>\n",
       "      <td>Female</td>\n",
       "      <td>1991-11-27</td>\n",
       "      <td>2018-01-11 13:59:00</td>\n",
       "      <td>64088</td>\n",
       "      <td>6.155</td>\n",
       "      <td>True</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>Janice</td>\n",
       "      <td>Female</td>\n",
       "      <td>2016-03-12</td>\n",
       "      <td>2018-01-11 00:40:00</td>\n",
       "      <td>51082</td>\n",
       "      <td>11.955</td>\n",
       "      <td>False</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>Janice</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1997-08-21</td>\n",
       "      <td>2018-01-11 05:12:00</td>\n",
       "      <td>91719</td>\n",
       "      <td>11.583</td>\n",
       "      <td>True</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>Virginia</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1994-05-07</td>\n",
       "      <td>2018-01-11 17:58:00</td>\n",
       "      <td>111858</td>\n",
       "      <td>1.601</td>\n",
       "      <td>True</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>Harry</td>\n",
       "      <td>Male</td>\n",
       "      <td>1981-08-26</td>\n",
       "      <td>2018-01-11 15:16:00</td>\n",
       "      <td>130620</td>\n",
       "      <td>7.030</td>\n",
       "      <td>False</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>Laura</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2014-07-19</td>\n",
       "      <td>2018-01-11 21:23:00</td>\n",
       "      <td>140371</td>\n",
       "      <td>10.620</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>Tina</td>\n",
       "      <td>Female</td>\n",
       "      <td>2016-06-16</td>\n",
       "      <td>2018-01-11 19:47:00</td>\n",
       "      <td>100705</td>\n",
       "      <td>16.961</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>Aaron</td>\n",
       "      <td>Male</td>\n",
       "      <td>2012-02-17</td>\n",
       "      <td>2018-01-11 10:20:00</td>\n",
       "      <td>61602</td>\n",
       "      <td>11.849</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>John</td>\n",
       "      <td>Male</td>\n",
       "      <td>1989-12-23</td>\n",
       "      <td>2018-01-11 07:01:00</td>\n",
       "      <td>80740</td>\n",
       "      <td>19.305</td>\n",
       "      <td>False</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>Paul</td>\n",
       "      <td>Male</td>\n",
       "      <td>1993-08-04</td>\n",
       "      <td>2018-01-11 19:25:00</td>\n",
       "      <td>42146</td>\n",
       "      <td>3.046</td>\n",
       "      <td>False</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>Steven</td>\n",
       "      <td>Male</td>\n",
       "      <td>2013-04-23</td>\n",
       "      <td>2018-01-11 22:12:00</td>\n",
       "      <td>68680</td>\n",
       "      <td>16.565</td>\n",
       "      <td>False</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>Russell</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1988-05-05</td>\n",
       "      <td>2018-01-11 07:57:00</td>\n",
       "      <td>133980</td>\n",
       "      <td>12.396</td>\n",
       "      <td>True</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>Shirley</td>\n",
       "      <td>Female</td>\n",
       "      <td>2001-06-20</td>\n",
       "      <td>2018-01-11 22:39:00</td>\n",
       "      <td>147113</td>\n",
       "      <td>16.135</td>\n",
       "      <td>False</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>Willie</td>\n",
       "      <td>Male</td>\n",
       "      <td>2003-11-27</td>\n",
       "      <td>2018-01-11 06:21:00</td>\n",
       "      <td>64363</td>\n",
       "      <td>4.023</td>\n",
       "      <td>False</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Male</td>\n",
       "      <td>1991-06-22</td>\n",
       "      <td>2018-01-11 20:58:00</td>\n",
       "      <td>76189</td>\n",
       "      <td>18.988</td>\n",
       "      <td>True</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>Paul</td>\n",
       "      <td>Male</td>\n",
       "      <td>2008-06-03</td>\n",
       "      <td>2018-01-11 15:05:00</td>\n",
       "      <td>41054</td>\n",
       "      <td>12.299</td>\n",
       "      <td>False</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>824</th>\n",
       "      <td>Julia</td>\n",
       "      <td>Female</td>\n",
       "      <td>2014-08-18</td>\n",
       "      <td>2018-01-11 03:12:00</td>\n",
       "      <td>97566</td>\n",
       "      <td>2.147</td>\n",
       "      <td>False</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>827</th>\n",
       "      <td>Jesse</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2014-07-16</td>\n",
       "      <td>2018-01-11 02:24:00</td>\n",
       "      <td>98811</td>\n",
       "      <td>7.487</td>\n",
       "      <td>False</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>832</th>\n",
       "      <td>Keith</td>\n",
       "      <td>Male</td>\n",
       "      <td>2003-02-12</td>\n",
       "      <td>2018-01-11 15:02:00</td>\n",
       "      <td>120672</td>\n",
       "      <td>19.467</td>\n",
       "      <td>False</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>844</th>\n",
       "      <td>Maria</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1985-06-19</td>\n",
       "      <td>2018-01-11 01:48:00</td>\n",
       "      <td>148857</td>\n",
       "      <td>8.738</td>\n",
       "      <td>False</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>860</th>\n",
       "      <td>Phillip</td>\n",
       "      <td>Male</td>\n",
       "      <td>1984-10-07</td>\n",
       "      <td>2018-01-11 11:05:00</td>\n",
       "      <td>36837</td>\n",
       "      <td>14.660</td>\n",
       "      <td>False</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>865</th>\n",
       "      <td>Karen</td>\n",
       "      <td>Female</td>\n",
       "      <td>1997-08-29</td>\n",
       "      <td>2018-01-11 16:56:00</td>\n",
       "      <td>80633</td>\n",
       "      <td>16.306</td>\n",
       "      <td>False</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>867</th>\n",
       "      <td>Earl</td>\n",
       "      <td>Male</td>\n",
       "      <td>2013-06-15</td>\n",
       "      <td>2018-01-11 03:00:00</td>\n",
       "      <td>48046</td>\n",
       "      <td>7.737</td>\n",
       "      <td>False</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>870</th>\n",
       "      <td>Cynthia</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1996-11-19</td>\n",
       "      <td>2018-01-11 22:40:00</td>\n",
       "      <td>107816</td>\n",
       "      <td>18.751</td>\n",
       "      <td>False</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>876</th>\n",
       "      <td>Terry</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1992-09-11</td>\n",
       "      <td>2018-01-11 16:41:00</td>\n",
       "      <td>41238</td>\n",
       "      <td>8.219</td>\n",
       "      <td>False</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>881</th>\n",
       "      <td>Ruby</td>\n",
       "      <td>Female</td>\n",
       "      <td>1980-01-28</td>\n",
       "      <td>2018-01-11 23:08:00</td>\n",
       "      <td>142868</td>\n",
       "      <td>6.318</td>\n",
       "      <td>False</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>883</th>\n",
       "      <td>Kathryn</td>\n",
       "      <td>Female</td>\n",
       "      <td>1995-10-27</td>\n",
       "      <td>2018-01-11 15:39:00</td>\n",
       "      <td>57300</td>\n",
       "      <td>18.015</td>\n",
       "      <td>False</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>887</th>\n",
       "      <td>David</td>\n",
       "      <td>Male</td>\n",
       "      <td>2009-12-05</td>\n",
       "      <td>2018-01-11 08:48:00</td>\n",
       "      <td>92242</td>\n",
       "      <td>15.407</td>\n",
       "      <td>False</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>888</th>\n",
       "      <td>Marilyn</td>\n",
       "      <td>Female</td>\n",
       "      <td>2007-10-08</td>\n",
       "      <td>2018-01-11 00:32:00</td>\n",
       "      <td>115149</td>\n",
       "      <td>11.934</td>\n",
       "      <td>True</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>894</th>\n",
       "      <td>Betty</td>\n",
       "      <td>Female</td>\n",
       "      <td>2002-11-19</td>\n",
       "      <td>2018-01-11 10:40:00</td>\n",
       "      <td>37005</td>\n",
       "      <td>7.645</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>899</th>\n",
       "      <td>Walter</td>\n",
       "      <td>Male</td>\n",
       "      <td>1992-05-21</td>\n",
       "      <td>2018-01-11 00:39:00</td>\n",
       "      <td>144701</td>\n",
       "      <td>16.323</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>910</th>\n",
       "      <td>Melissa</td>\n",
       "      <td>Female</td>\n",
       "      <td>2002-10-22</td>\n",
       "      <td>2018-01-11 01:20:00</td>\n",
       "      <td>45223</td>\n",
       "      <td>8.879</td>\n",
       "      <td>True</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>913</th>\n",
       "      <td>Lois</td>\n",
       "      <td>Female</td>\n",
       "      <td>2015-12-11</td>\n",
       "      <td>2018-01-11 16:10:00</td>\n",
       "      <td>99747</td>\n",
       "      <td>6.168</td>\n",
       "      <td>False</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>929</th>\n",
       "      <td>Theresa</td>\n",
       "      <td>Female</td>\n",
       "      <td>2001-04-27</td>\n",
       "      <td>2018-01-11 21:17:00</td>\n",
       "      <td>75661</td>\n",
       "      <td>1.079</td>\n",
       "      <td>True</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>930</th>\n",
       "      <td>Nancy</td>\n",
       "      <td>Female</td>\n",
       "      <td>2001-09-10</td>\n",
       "      <td>2018-01-11 23:57:00</td>\n",
       "      <td>85213</td>\n",
       "      <td>2.386</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>942</th>\n",
       "      <td>Lori</td>\n",
       "      <td>Female</td>\n",
       "      <td>2015-11-20</td>\n",
       "      <td>2018-01-11 13:15:00</td>\n",
       "      <td>75498</td>\n",
       "      <td>6.537</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>947</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Male</td>\n",
       "      <td>2012-07-30</td>\n",
       "      <td>2018-01-11 15:07:00</td>\n",
       "      <td>107351</td>\n",
       "      <td>5.329</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>955</th>\n",
       "      <td>Sarah</td>\n",
       "      <td>Female</td>\n",
       "      <td>2014-08-17</td>\n",
       "      <td>2018-01-11 23:08:00</td>\n",
       "      <td>127118</td>\n",
       "      <td>11.176</td>\n",
       "      <td>False</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>961</th>\n",
       "      <td>Antonio</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1989-06-18</td>\n",
       "      <td>2018-01-11 21:37:00</td>\n",
       "      <td>103050</td>\n",
       "      <td>3.050</td>\n",
       "      <td>False</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>976</th>\n",
       "      <td>Denise</td>\n",
       "      <td>Female</td>\n",
       "      <td>1992-10-19</td>\n",
       "      <td>2018-01-11 05:42:00</td>\n",
       "      <td>137954</td>\n",
       "      <td>4.195</td>\n",
       "      <td>True</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>981</th>\n",
       "      <td>James</td>\n",
       "      <td>Male</td>\n",
       "      <td>1993-01-15</td>\n",
       "      <td>2018-01-11 17:19:00</td>\n",
       "      <td>148985</td>\n",
       "      <td>19.280</td>\n",
       "      <td>False</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>985</th>\n",
       "      <td>Stephen</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1983-07-10</td>\n",
       "      <td>2018-01-11 20:10:00</td>\n",
       "      <td>85668</td>\n",
       "      <td>1.909</td>\n",
       "      <td>False</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>986</th>\n",
       "      <td>Donna</td>\n",
       "      <td>Female</td>\n",
       "      <td>1982-11-26</td>\n",
       "      <td>2018-01-11 07:04:00</td>\n",
       "      <td>82871</td>\n",
       "      <td>17.999</td>\n",
       "      <td>False</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>989</th>\n",
       "      <td>Justin</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1991-02-10</td>\n",
       "      <td>2018-01-11 16:58:00</td>\n",
       "      <td>38344</td>\n",
       "      <td>3.794</td>\n",
       "      <td>False</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>991</th>\n",
       "      <td>Rose</td>\n",
       "      <td>Female</td>\n",
       "      <td>2002-08-25</td>\n",
       "      <td>2018-01-11 05:12:00</td>\n",
       "      <td>134505</td>\n",
       "      <td>11.051</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>994</th>\n",
       "      <td>George</td>\n",
       "      <td>Male</td>\n",
       "      <td>2013-06-21</td>\n",
       "      <td>2018-01-11 17:47:00</td>\n",
       "      <td>98874</td>\n",
       "      <td>4.479</td>\n",
       "      <td>True</td>\n",
       "      <td>Marketing</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>186 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      First Name  Gender Start Date     Last Login Time  Salary  Bonus %  \\\n",
       "0        Douglas    Male 1993-08-06 2018-01-11 12:42:00   97308    6.945   \n",
       "5         Dennis    Male 1987-04-18 2018-01-11 01:35:00  115163   10.125   \n",
       "11         Julie  Female 1997-10-26 2018-01-11 15:19:00  102508   12.637   \n",
       "20          Lois     NaN 1995-04-22 2018-01-11 19:18:00   64714    4.934   \n",
       "21       Matthew    Male 1995-09-05 2018-01-11 02:12:00  100612   13.645   \n",
       "26         Craig    Male 2000-02-27 2018-01-11 07:45:00   37598    7.757   \n",
       "27         Scott     NaN 1991-07-11 2018-01-11 18:58:00  122367    5.218   \n",
       "29      Benjamin    Male 2005-01-26 2018-01-11 22:06:00   79529    7.008   \n",
       "42       Beverly  Female 1998-09-09 2018-01-11 20:26:00  121918   15.835   \n",
       "43       Marilyn  Female 1980-12-07 2018-01-11 03:16:00   73524    5.207   \n",
       "62           NaN  Female 2007-06-12 2018-01-11 17:25:00   58112   19.414   \n",
       "74        Thomas    Male 1995-06-04 2018-01-11 14:24:00   62096   17.029   \n",
       "77       Charles    Male 2004-09-14 2018-01-11 20:13:00  107391    1.260   \n",
       "81   Christopher    Male 2008-03-30 2018-01-11 10:52:00   47369   14.822   \n",
       "88         Donna  Female 1991-11-27 2018-01-11 13:59:00   64088    6.155   \n",
       "89        Janice  Female 2016-03-12 2018-01-11 00:40:00   51082   11.955   \n",
       "90        Janice     NaN 1997-08-21 2018-01-11 05:12:00   91719   11.583   \n",
       "93      Virginia     NaN 1994-05-07 2018-01-11 17:58:00  111858    1.601   \n",
       "94         Harry    Male 1981-08-26 2018-01-11 15:16:00  130620    7.030   \n",
       "97         Laura     NaN 2014-07-19 2018-01-11 21:23:00  140371   10.620   \n",
       "98          Tina  Female 2016-06-16 2018-01-11 19:47:00  100705   16.961   \n",
       "101        Aaron    Male 2012-02-17 2018-01-11 10:20:00   61602   11.849   \n",
       "104         John    Male 1989-12-23 2018-01-11 07:01:00   80740   19.305   \n",
       "106         Paul    Male 1993-08-04 2018-01-11 19:25:00   42146    3.046   \n",
       "107       Steven    Male 2013-04-23 2018-01-11 22:12:00   68680   16.565   \n",
       "108      Russell     NaN 1988-05-05 2018-01-11 07:57:00  133980   12.396   \n",
       "110      Shirley  Female 2001-06-20 2018-01-11 22:39:00  147113   16.135   \n",
       "112       Willie    Male 2003-11-27 2018-01-11 06:21:00   64363    4.023   \n",
       "116          NaN    Male 1991-06-22 2018-01-11 20:58:00   76189   18.988   \n",
       "119         Paul    Male 2008-06-03 2018-01-11 15:05:00   41054   12.299   \n",
       "..           ...     ...        ...                 ...     ...      ...   \n",
       "824        Julia  Female 2014-08-18 2018-01-11 03:12:00   97566    2.147   \n",
       "827        Jesse     NaN 2014-07-16 2018-01-11 02:24:00   98811    7.487   \n",
       "832        Keith    Male 2003-02-12 2018-01-11 15:02:00  120672   19.467   \n",
       "844        Maria     NaN 1985-06-19 2018-01-11 01:48:00  148857    8.738   \n",
       "860      Phillip    Male 1984-10-07 2018-01-11 11:05:00   36837   14.660   \n",
       "865        Karen  Female 1997-08-29 2018-01-11 16:56:00   80633   16.306   \n",
       "867         Earl    Male 2013-06-15 2018-01-11 03:00:00   48046    7.737   \n",
       "870      Cynthia     NaN 1996-11-19 2018-01-11 22:40:00  107816   18.751   \n",
       "876        Terry     NaN 1992-09-11 2018-01-11 16:41:00   41238    8.219   \n",
       "881         Ruby  Female 1980-01-28 2018-01-11 23:08:00  142868    6.318   \n",
       "883      Kathryn  Female 1995-10-27 2018-01-11 15:39:00   57300   18.015   \n",
       "887        David    Male 2009-12-05 2018-01-11 08:48:00   92242   15.407   \n",
       "888      Marilyn  Female 2007-10-08 2018-01-11 00:32:00  115149   11.934   \n",
       "894        Betty  Female 2002-11-19 2018-01-11 10:40:00   37005    7.645   \n",
       "899       Walter    Male 1992-05-21 2018-01-11 00:39:00  144701   16.323   \n",
       "910      Melissa  Female 2002-10-22 2018-01-11 01:20:00   45223    8.879   \n",
       "913         Lois  Female 2015-12-11 2018-01-11 16:10:00   99747    6.168   \n",
       "929      Theresa  Female 2001-04-27 2018-01-11 21:17:00   75661    1.079   \n",
       "930        Nancy  Female 2001-09-10 2018-01-11 23:57:00   85213    2.386   \n",
       "942         Lori  Female 2015-11-20 2018-01-11 13:15:00   75498    6.537   \n",
       "947          NaN    Male 2012-07-30 2018-01-11 15:07:00  107351    5.329   \n",
       "955        Sarah  Female 2014-08-17 2018-01-11 23:08:00  127118   11.176   \n",
       "961      Antonio     NaN 1989-06-18 2018-01-11 21:37:00  103050    3.050   \n",
       "976       Denise  Female 1992-10-19 2018-01-11 05:42:00  137954    4.195   \n",
       "981        James    Male 1993-01-15 2018-01-11 17:19:00  148985   19.280   \n",
       "985      Stephen     NaN 1983-07-10 2018-01-11 20:10:00   85668    1.909   \n",
       "986        Donna  Female 1982-11-26 2018-01-11 07:04:00   82871   17.999   \n",
       "989       Justin     NaN 1991-02-10 2018-01-11 16:58:00   38344    3.794   \n",
       "991         Rose  Female 2002-08-25 2018-01-11 05:12:00  134505   11.051   \n",
       "994       George    Male 2013-06-21 2018-01-11 17:47:00   98874    4.479   \n",
       "\n",
       "     Senior Management       Team  \n",
       "0                 True  Marketing  \n",
       "5                False      Legal  \n",
       "11                True      Legal  \n",
       "20                True      Legal  \n",
       "21               False  Marketing  \n",
       "26                True  Marketing  \n",
       "27               False      Legal  \n",
       "29                True      Legal  \n",
       "42               False      Legal  \n",
       "43                True  Marketing  \n",
       "62                True  Marketing  \n",
       "74               False  Marketing  \n",
       "77                True  Marketing  \n",
       "81               False      Legal  \n",
       "88                True      Legal  \n",
       "89               False      Legal  \n",
       "90                True      Legal  \n",
       "93                True      Legal  \n",
       "94               False      Legal  \n",
       "97                True  Marketing  \n",
       "98                True  Marketing  \n",
       "101               True  Marketing  \n",
       "104              False  Marketing  \n",
       "106              False      Legal  \n",
       "107              False      Legal  \n",
       "108               True      Legal  \n",
       "110              False      Legal  \n",
       "112              False  Marketing  \n",
       "116               True      Legal  \n",
       "119              False  Marketing  \n",
       "..                 ...        ...  \n",
       "824              False  Marketing  \n",
       "827              False      Legal  \n",
       "832              False      Legal  \n",
       "844              False      Legal  \n",
       "860              False  Marketing  \n",
       "865              False      Legal  \n",
       "867              False  Marketing  \n",
       "870              False  Marketing  \n",
       "876              False  Marketing  \n",
       "881              False  Marketing  \n",
       "883              False  Marketing  \n",
       "887              False      Legal  \n",
       "888               True      Legal  \n",
       "894               True  Marketing  \n",
       "899               True  Marketing  \n",
       "910               True      Legal  \n",
       "913              False  Marketing  \n",
       "929               True      Legal  \n",
       "930               True  Marketing  \n",
       "942               True  Marketing  \n",
       "947               True  Marketing  \n",
       "955              False      Legal  \n",
       "961              False      Legal  \n",
       "976               True      Legal  \n",
       "981              False      Legal  \n",
       "985              False      Legal  \n",
       "986              False  Marketing  \n",
       "989              False      Legal  \n",
       "991               True  Marketing  \n",
       "994               True  Marketing  \n",
       "\n",
       "[186 rows x 8 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df[\"Team\"].isin([\"Marketing\",\"Legal\"])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df.sort_values(\"First Name\", inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "mask = ~df[\"First Name\"].duplicated(keep = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>First Name</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Start Date</th>\n",
       "      <th>Last Login Time</th>\n",
       "      <th>Salary</th>\n",
       "      <th>Bonus %</th>\n",
       "      <th>Senior Management</th>\n",
       "      <th>Team</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Angela</td>\n",
       "      <td>Female</td>\n",
       "      <td>2005-11-22</td>\n",
       "      <td>2018-01-11 06:29:00</td>\n",
       "      <td>95570</td>\n",
       "      <td>18.523</td>\n",
       "      <td>True</td>\n",
       "      <td>Engineering</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>688</th>\n",
       "      <td>Brian</td>\n",
       "      <td>Male</td>\n",
       "      <td>2007-04-07</td>\n",
       "      <td>2018-01-11 22:47:00</td>\n",
       "      <td>93901</td>\n",
       "      <td>17.821</td>\n",
       "      <td>True</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>Carol</td>\n",
       "      <td>Female</td>\n",
       "      <td>1996-03-19</td>\n",
       "      <td>2018-01-11 03:39:00</td>\n",
       "      <td>57783</td>\n",
       "      <td>9.129</td>\n",
       "      <td>False</td>\n",
       "      <td>Finance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>887</th>\n",
       "      <td>David</td>\n",
       "      <td>Male</td>\n",
       "      <td>2009-12-05</td>\n",
       "      <td>2018-01-11 08:48:00</td>\n",
       "      <td>92242</td>\n",
       "      <td>15.407</td>\n",
       "      <td>False</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Dennis</td>\n",
       "      <td>Male</td>\n",
       "      <td>1987-04-18</td>\n",
       "      <td>2018-01-11 01:35:00</td>\n",
       "      <td>115163</td>\n",
       "      <td>10.125</td>\n",
       "      <td>False</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>495</th>\n",
       "      <td>Eugene</td>\n",
       "      <td>Male</td>\n",
       "      <td>1984-05-24</td>\n",
       "      <td>2018-01-11 10:54:00</td>\n",
       "      <td>81077</td>\n",
       "      <td>2.117</td>\n",
       "      <td>False</td>\n",
       "      <td>Sales</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Jean</td>\n",
       "      <td>Female</td>\n",
       "      <td>1993-12-18</td>\n",
       "      <td>2018-01-11 09:07:00</td>\n",
       "      <td>119082</td>\n",
       "      <td>16.180</td>\n",
       "      <td>False</td>\n",
       "      <td>Business Development</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>832</th>\n",
       "      <td>Keith</td>\n",
       "      <td>Male</td>\n",
       "      <td>2003-02-12</td>\n",
       "      <td>2018-01-11 15:02:00</td>\n",
       "      <td>120672</td>\n",
       "      <td>19.467</td>\n",
       "      <td>False</td>\n",
       "      <td>Legal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>291</th>\n",
       "      <td>Tammy</td>\n",
       "      <td>Female</td>\n",
       "      <td>1984-11-11</td>\n",
       "      <td>2018-01-11 10:30:00</td>\n",
       "      <td>132839</td>\n",
       "      <td>17.463</td>\n",
       "      <td>True</td>\n",
       "      <td>Client Services</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    First Name  Gender Start Date     Last Login Time  Salary  Bonus %  \\\n",
       "8       Angela  Female 2005-11-22 2018-01-11 06:29:00   95570   18.523   \n",
       "688      Brian    Male 2007-04-07 2018-01-11 22:47:00   93901   17.821   \n",
       "190      Carol  Female 1996-03-19 2018-01-11 03:39:00   57783    9.129   \n",
       "887      David    Male 2009-12-05 2018-01-11 08:48:00   92242   15.407   \n",
       "5       Dennis    Male 1987-04-18 2018-01-11 01:35:00  115163   10.125   \n",
       "495     Eugene    Male 1984-05-24 2018-01-11 10:54:00   81077    2.117   \n",
       "33        Jean  Female 1993-12-18 2018-01-11 09:07:00  119082   16.180   \n",
       "832      Keith    Male 2003-02-12 2018-01-11 15:02:00  120672   19.467   \n",
       "291      Tammy  Female 1984-11-11 2018-01-11 10:30:00  132839   17.463   \n",
       "\n",
       "     Senior Management                  Team  \n",
       "8                 True           Engineering  \n",
       "688               True                 Legal  \n",
       "190              False               Finance  \n",
       "887              False                 Legal  \n",
       "5                False                 Legal  \n",
       "495              False                 Sales  \n",
       "33               False  Business Development  \n",
       "832              False                 Legal  \n",
       "291               True       Client Services  "
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[mask]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df.drop_duplicates(subset = \"First Name\", keep = False))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Male, NaN, Female]\n",
       "Categories (2, object): [Male, Female]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"Gender\"].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Marketing', 'Client Services', 'Distribution', 'Product',\n",
       "       'Human Resources', 'Engineering', 'Finance', 'Business Development',\n",
       "       'Sales', nan, 'Legal'], dtype=object)"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"Team\"].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"Team\"].nunique(dropna= False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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