pandas_1.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Библиотека Pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "frame = pd.DataFrame({\n",
    "    'numbers':range(10),\n",
    "    'chars': ['a']*10\n",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>chars</th>\n",
       "      <th>numbers</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>a</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>a</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>a</td>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>a</td>\n",
       "      <td>3</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>a</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>a</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>a</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>a</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>a</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>a</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "  chars  numbers\n",
       "0     a        0\n",
       "1     a        1\n",
       "2     a        2\n",
       "3     a        3\n",
       "4     a        4\n",
       "5     a        5\n",
       "6     a        6\n",
       "7     a        7\n",
       "8     a        8\n",
       "9     a        9"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "frame = pd.read_csv('pandas_explain.csv', header= 0, sep= '\\t')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index([u'Name', u'Birth', u'City', u'Position'], dtype='object')"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frame.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(6, 4)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frame.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Birth</th>\n",
       "      <th>City</th>\n",
       "      <th>Position</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Иванов А.А.</td>\n",
       "      <td>22.03.1980</td>\n",
       "      <td>Москва</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Сорокин И.В.</td>\n",
       "      <td>07.08.1965</td>\n",
       "      <td>Волгоград</td>\n",
       "      <td>инженер</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Белов М.М.</td>\n",
       "      <td>13.02.1980</td>\n",
       "      <td>Ростов</td>\n",
       "      <td>менеджер</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Мельникова Д.С.</td>\n",
       "      <td>15.04.1985</td>\n",
       "      <td>Ростов</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Рыбина Е.П.</td>\n",
       "      <td>19.11.1985</td>\n",
       "      <td>Москва</td>\n",
       "      <td>инженер</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Костров С.О.</td>\n",
       "      <td>31.05.1985</td>\n",
       "      <td>Москва</td>\n",
       "      <td>стажер</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Petrov</td>\n",
       "      <td>22.03.1990</td>\n",
       "      <td>Penza</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Name       Birth       City  Position\n",
       "0      Иванов А.А.  22.03.1980     Москва       NaN\n",
       "1     Сорокин И.В.  07.08.1965  Волгоград   инженер\n",
       "2       Белов М.М.  13.02.1980     Ростов  менеджер\n",
       "3  Мельникова Д.С.  15.04.1985     Ростов       NaN\n",
       "4      Рыбина Е.П.  19.11.1985     Москва   инженер\n",
       "5     Костров С.О.  31.05.1985     Москва    стажер\n",
       "6           Petrov  22.03.1990      Penza       NaN"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_line = {'Name': 'Petrov', 'Birth': '22.03.1990', 'City':'Penza'}\n",
    "frame.append(new_line, ignore_index= True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
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       "      <td>Иванов А.А.</td>\n",
       "      <td>22.03.1980</td>\n",
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       "      <th>1</th>\n",
       "      <td>Сорокин И.В.</td>\n",
       "      <td>07.08.1965</td>\n",
       "      <td>Волгоград</td>\n",
       "      <td>инженер</td>\n",
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       "      <th>2</th>\n",
       "      <td>Белов М.М.</td>\n",
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       "      <td>менеджер</td>\n",
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       "      <th>3</th>\n",
       "      <td>Мельникова Д.С.</td>\n",
       "      <td>15.04.1985</td>\n",
       "      <td>Ростов</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Рыбина Е.П.</td>\n",
       "      <td>19.11.1985</td>\n",
       "      <td>Москва</td>\n",
       "      <td>инженер</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Костров С.О.</td>\n",
       "      <td>31.05.1985</td>\n",
       "      <td>Москва</td>\n",
       "      <td>стажер</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Petrov</td>\n",
       "      <td>22.03.1990</td>\n",
       "      <td>Penza</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Petrov</td>\n",
       "      <td>22.03.1990</td>\n",
       "      <td>Penza</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "              Name       Birth       City  Position\n",
       "0      Иванов А.А.  22.03.1980     Москва       NaN\n",
       "1     Сорокин И.В.  07.08.1965  Волгоград   инженер\n",
       "2       Белов М.М.  13.02.1980     Ростов  менеджер\n",
       "3  Мельникова Д.С.  15.04.1985     Ростов       NaN\n",
       "4      Рыбина Е.П.  19.11.1985     Москва   инженер\n",
       "5     Костров С.О.  31.05.1985     Москва    стажер\n",
       "6           Petrov  22.03.1990      Penza       NaN\n",
       "7           Petrov  22.03.1990      Penza       NaN"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frame = frame.append(new_line, ignore_index= True)\n",
    "frame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>22.03.1980</td>\n",
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       "      <th>1</th>\n",
       "      <td>Сорокин И.В.</td>\n",
       "      <td>07.08.1965</td>\n",
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       "      <td>Белов М.М.</td>\n",
       "      <td>13.02.1980</td>\n",
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       "      <td>15.04.1985</td>\n",
       "      <td>Ростов</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>4</th>\n",
       "      <td>Рыбина Е.П.</td>\n",
       "      <td>19.11.1985</td>\n",
       "      <td>Москва</td>\n",
       "      <td>инженер</td>\n",
       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Костров С.О.</td>\n",
       "      <td>31.05.1985</td>\n",
       "      <td>Москва</td>\n",
       "      <td>стажер</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Petrov</td>\n",
       "      <td>22.03.1990</td>\n",
       "      <td>Penza</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Petrov</td>\n",
       "      <td>22.03.1990</td>\n",
       "      <td>Penza</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
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      "text/plain": [
       "              Name       Birth       City  Position  IsStudent\n",
       "0      Иванов А.А.  22.03.1980     Москва       NaN      False\n",
       "1     Сорокин И.В.  07.08.1965  Волгоград   инженер      False\n",
       "2       Белов М.М.  13.02.1980     Ростов  менеджер      False\n",
       "3  Мельникова Д.С.  15.04.1985     Ростов       NaN      False\n",
       "4      Рыбина Е.П.  19.11.1985     Москва   инженер      False\n",
       "5     Костров С.О.  31.05.1985     Москва    стажер       True\n",
       "6           Petrov  22.03.1990      Penza       NaN       True\n",
       "7           Petrov  22.03.1990      Penza       NaN       True"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frame['IsStudent'] = [False]*5 + [True]*3\n",
    "frame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "ename": "KeyError",
     "evalue": "'[5 6 7] not found in axis'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-39-57086a56054c>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mframe\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdrop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m6\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m7\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minplace\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m/home/sasha/anaconda2/lib/python2.7/site-packages/pandas/core/frame.pyc\u001b[0m in \u001b[0;36mdrop\u001b[0;34m(self, labels, axis, index, columns, level, inplace, errors)\u001b[0m\n\u001b[1;32m   3695\u001b[0m                                            \u001b[0mindex\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcolumns\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3696\u001b[0m                                            \u001b[0mlevel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlevel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minplace\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0minplace\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3697\u001b[0;31m                                            errors=errors)\n\u001b[0m\u001b[1;32m   3698\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3699\u001b[0m     @rewrite_axis_style_signature('mapper', [('copy', True),\n",
      "\u001b[0;32m/home/sasha/anaconda2/lib/python2.7/site-packages/pandas/core/generic.pyc\u001b[0m in \u001b[0;36mdrop\u001b[0;34m(self, labels, axis, index, columns, level, inplace, errors)\u001b[0m\n\u001b[1;32m   3109\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabels\u001b[0m \u001b[0;32min\u001b[0m \u001b[0maxes\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[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3110\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mlabels\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3111\u001b[0;31m                 \u001b[0mobj\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_drop_axis\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabels\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlevel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlevel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0merrors\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0merrors\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   3112\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3113\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0minplace\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/home/sasha/anaconda2/lib/python2.7/site-packages/pandas/core/generic.pyc\u001b[0m in \u001b[0;36m_drop_axis\u001b[0;34m(self, labels, axis, level, errors)\u001b[0m\n\u001b[1;32m   3141\u001b[0m                 \u001b[0mnew_axis\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdrop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabels\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlevel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlevel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0merrors\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0merrors\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3142\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3143\u001b[0;31m                 \u001b[0mnew_axis\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdrop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabels\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0merrors\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0merrors\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   3144\u001b[0m             \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreindex\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0maxis_name\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mnew_axis\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3145\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/home/sasha/anaconda2/lib/python2.7/site-packages/pandas/core/indexes/base.pyc\u001b[0m in \u001b[0;36mdrop\u001b[0;34m(self, labels, errors)\u001b[0m\n\u001b[1;32m   4402\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0merrors\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0;34m'ignore'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4403\u001b[0m                 raise KeyError(\n\u001b[0;32m-> 4404\u001b[0;31m                     '{} not found in axis'.format(labels[mask]))\n\u001b[0m\u001b[1;32m   4405\u001b[0m             \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m~\u001b[0m\u001b[0mmask\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4406\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdelete\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyError\u001b[0m: '[5 6 7] not found in axis'"
     ]
    }
   ],
   "source": [
    "frame.drop([5, 6, 7], axis= 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyError",
     "evalue": "\"['IsStudent'] not found in axis\"",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-44-6a1a3149efe1>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mframe\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdrop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'IsStudent'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minplace\u001b[0m\u001b[0;34m=\u001b[0m \u001b[0mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m/home/sasha/anaconda2/lib/python2.7/site-packages/pandas/core/frame.pyc\u001b[0m in \u001b[0;36mdrop\u001b[0;34m(self, labels, axis, index, columns, level, inplace, errors)\u001b[0m\n\u001b[1;32m   3695\u001b[0m                                            \u001b[0mindex\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcolumns\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3696\u001b[0m                                            \u001b[0mlevel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlevel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minplace\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0minplace\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3697\u001b[0;31m                                            errors=errors)\n\u001b[0m\u001b[1;32m   3698\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3699\u001b[0m     @rewrite_axis_style_signature('mapper', [('copy', True),\n",
      "\u001b[0;32m/home/sasha/anaconda2/lib/python2.7/site-packages/pandas/core/generic.pyc\u001b[0m in \u001b[0;36mdrop\u001b[0;34m(self, labels, axis, index, columns, level, inplace, errors)\u001b[0m\n\u001b[1;32m   3109\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabels\u001b[0m \u001b[0;32min\u001b[0m \u001b[0maxes\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[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3110\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mlabels\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3111\u001b[0;31m                 \u001b[0mobj\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_drop_axis\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabels\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlevel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlevel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0merrors\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0merrors\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   3112\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3113\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0minplace\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/home/sasha/anaconda2/lib/python2.7/site-packages/pandas/core/generic.pyc\u001b[0m in \u001b[0;36m_drop_axis\u001b[0;34m(self, labels, axis, level, errors)\u001b[0m\n\u001b[1;32m   3141\u001b[0m                 \u001b[0mnew_axis\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdrop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabels\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlevel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlevel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0merrors\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0merrors\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3142\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3143\u001b[0;31m                 \u001b[0mnew_axis\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdrop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabels\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0merrors\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0merrors\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   3144\u001b[0m             \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreindex\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0maxis_name\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mnew_axis\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3145\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/home/sasha/anaconda2/lib/python2.7/site-packages/pandas/core/indexes/base.pyc\u001b[0m in \u001b[0;36mdrop\u001b[0;34m(self, labels, errors)\u001b[0m\n\u001b[1;32m   4402\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0merrors\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0;34m'ignore'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4403\u001b[0m                 raise KeyError(\n\u001b[0;32m-> 4404\u001b[0;31m                     '{} not found in axis'.format(labels[mask]))\n\u001b[0m\u001b[1;32m   4405\u001b[0m             \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mindexer\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m~\u001b[0m\u001b[0mmask\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4406\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdelete\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyError\u001b[0m: \"['IsStudent'] not found in axis\""
     ]
    }
   ],
   "source": [
    "frame.drop('IsStudent', axis= 1, inplace= True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Birth</th>\n",
       "      <th>City</th>\n",
       "      <th>Position</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Иванов А.А.</td>\n",
       "      <td>22.03.1980</td>\n",
       "      <td>Москва</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Сорокин И.В.</td>\n",
       "      <td>07.08.1965</td>\n",
       "      <td>Волгоград</td>\n",
       "      <td>инженер</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Белов М.М.</td>\n",
       "      <td>13.02.1980</td>\n",
       "      <td>Ростов</td>\n",
       "      <td>менеджер</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Мельникова Д.С.</td>\n",
       "      <td>15.04.1985</td>\n",
       "      <td>Ростов</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Рыбина Е.П.</td>\n",
       "      <td>19.11.1985</td>\n",
       "      <td>Москва</td>\n",
       "      <td>инженер</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Name       Birth       City  Position\n",
       "0      Иванов А.А.  22.03.1980     Москва       NaN\n",
       "1     Сорокин И.В.  07.08.1965  Волгоград   инженер\n",
       "2       Белов М.М.  13.02.1980     Ростов  менеджер\n",
       "3  Мельникова Д.С.  15.04.1985     Ростов       NaN\n",
       "4      Рыбина Е.П.  19.11.1985     Москва   инженер"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "frame.to_csv('updated_dataset.csv', sep = ',', header= True, index= None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Name,Birth,City,Position\r\n",
      "Иванов А.А.,22.03.1980,Москва,\r\n",
      "Сорокин И.В.,07.08.1965,Волгоград,инженер\r\n",
      "Белов М.М.,13.02.1980,Ростов,менеджер\r\n",
      "Мельникова Д.С.,15.04.1985,Ростов,\r\n",
      "Рыбина Е.П.,19.11.1985,Москва,инженер\r\n"
     ]
    }
   ],
   "source": [
    "!cat updated_dataset.csv"
   ]
  }
 ],
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