diff --git a/task_1-7.ipynb b/task_1-7.ipynb
new file mode 100644
index 0000000..56e024f
--- /dev/null
+++ b/task_1-7.ipynb
@@ -0,0 +1,1256 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "431b73df",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "d89e36d1",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>salary</th>\n",
+       "      <th>educationType</th>\n",
+       "      <th>jobTitle</th>\n",
+       "      <th>qualification</th>\n",
+       "      <th>gender</th>\n",
+       "      <th>dateModify</th>\n",
+       "      <th>skills</th>\n",
+       "      <th>otherInfo</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>60000</td>\n",
+       "      <td>Высшее</td>\n",
+       "      <td>Специалист пресс-службы</td>\n",
+       "      <td>Магистр</td>\n",
+       "      <td>Мужской</td>\n",
+       "      <td>2021-04-01</td>\n",
+       "      <td>&lt;p&gt;Аналитическое&amp;nbsp;мышление,&amp;nbsp;&lt;span cla...</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>85000</td>\n",
+       "      <td>Высшее</td>\n",
+       "      <td>менеджер проектов</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Мужской</td>\n",
+       "      <td>2021-04-01</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>15000</td>\n",
+       "      <td>Среднее профессиональное</td>\n",
+       "      <td>....</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Женский</td>\n",
+       "      <td>2021-06-01</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>30000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Женский</td>\n",
+       "      <td>2021-04-03</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>45000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Мужской</td>\n",
+       "      <td>2021-06-28</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</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>32678</th>\n",
+       "      <td>15000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Женский</td>\n",
+       "      <td>2021-06-23</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32679</th>\n",
+       "      <td>13000</td>\n",
+       "      <td>Среднее</td>\n",
+       "      <td>уборщица</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Женский</td>\n",
+       "      <td>2021-07-29</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32680</th>\n",
+       "      <td>16000</td>\n",
+       "      <td>Среднее профессиональное</td>\n",
+       "      <td>кочегар машинист котельной</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Мужской</td>\n",
+       "      <td>2021-11-11</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32681</th>\n",
+       "      <td>35000</td>\n",
+       "      <td>Высшее</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Мужской</td>\n",
+       "      <td>2020-04-21</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32682</th>\n",
+       "      <td>30000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Мужской</td>\n",
+       "      <td>2021-06-20</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>32683 rows × 8 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       salary             educationType                    jobTitle  \\\n",
+       "0       60000                    Высшее     Специалист пресс-службы   \n",
+       "1       85000                    Высшее           менеджер проектов   \n",
+       "2       15000  Среднее профессиональное                        ....   \n",
+       "3       30000                       NaN                         NaN   \n",
+       "4       45000                       NaN                         NaN   \n",
+       "...       ...                       ...                         ...   \n",
+       "32678   15000                       NaN                         NaN   \n",
+       "32679   13000                   Среднее                    уборщица   \n",
+       "32680   16000  Среднее профессиональное  кочегар машинист котельной   \n",
+       "32681   35000                    Высшее                         NaN   \n",
+       "32682   30000                       NaN                         NaN   \n",
+       "\n",
+       "      qualification   gender  dateModify  \\\n",
+       "0           Магистр  Мужской  2021-04-01   \n",
+       "1               NaN  Мужской  2021-04-01   \n",
+       "2               NaN  Женский  2021-06-01   \n",
+       "3               NaN  Женский  2021-04-03   \n",
+       "4               NaN  Мужской  2021-06-28   \n",
+       "...             ...      ...         ...   \n",
+       "32678           NaN  Женский  2021-06-23   \n",
+       "32679           NaN  Женский  2021-07-29   \n",
+       "32680           NaN  Мужской  2021-11-11   \n",
+       "32681           NaN  Мужской  2020-04-21   \n",
+       "32682           NaN  Мужской  2021-06-20   \n",
+       "\n",
+       "                                                  skills otherInfo  \n",
+       "0      <p>Аналитическое&nbsp;мышление,&nbsp;<span cla...       NaN  \n",
+       "1                                                    NaN       NaN  \n",
+       "2                                                    NaN       NaN  \n",
+       "3                                                    NaN       NaN  \n",
+       "4                                                    NaN       NaN  \n",
+       "...                                                  ...       ...  \n",
+       "32678                                                NaN       NaN  \n",
+       "32679                                                NaN       NaN  \n",
+       "32680                                                NaN       NaN  \n",
+       "32681                                                NaN       NaN  \n",
+       "32682                                                NaN       NaN  \n",
+       "\n",
+       "[32683 rows x 8 columns]"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "works = pd.read_csv(\"works.csv\")\n",
+    "works"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f7c75647",
+   "metadata": {},
+   "source": [
+    "### 1.Узнать общее количество записей в датасете"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "e752d434",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(32683, 8)"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "works.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "2be3c542",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "32683"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "works['salary'].count()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "b98dcfd1",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "32683"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(works.index)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8c120d74",
+   "metadata": {},
+   "source": [
+    "### 2.Узнать количество мужчин и женщин в датасете"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "1b82f99c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "13386"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "works[works['gender'] == 'Мужской'].shape[0]\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "4dba6382",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "17910"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "(works['gender'] == 'Женский').values.sum()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "e70ed371",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Женский    17910\n",
+       "Мужской    13386\n",
+       "Name: gender, dtype: int64"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "works['gender'].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ff1cb14b",
+   "metadata": {},
+   "source": [
+    "### 3.Узнать сколько значений в столбце skills не NAN"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "196b5286",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "8972"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "works['skills'].notnull().values.sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "36ee77c1",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "8972"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "works['skills'].notna().values.sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "85410ba8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "8972"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "works['skills'].dropna().shape[0]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2ff24d07",
+   "metadata": {},
+   "source": [
+    "### 4.Получить все заполненные скиллы"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "b41a3b96",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0        <p>Аналитическое&nbsp;мышление,&nbsp;<span cla...\n",
+       "5        Ответственная,пунктуальная,дисциплинированная ...\n",
+       "10                         <p>Коммуникабельность&nbsp;</p>\n",
+       "13                         <p>Ответственность в работе</p>\n",
+       "21       <p>Усидчивость, умение удерживать в памяти нуж...\n",
+       "                               ...                        \n",
+       "32665    <p>Отвественность</p><p>Исполнительность</p><p...\n",
+       "32668    <p>Высокая работоспособность, нацеленность на ...\n",
+       "32672                                <p>исполнительный</p>\n",
+       "32674    <p>Нацелен на результат. Считаю себя командным...\n",
+       "32675                                 <p>трудоспособен</p>\n",
+       "Name: skills, Length: 8972, dtype: object"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "works['skills'].dropna()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "58a3bc5d",
+   "metadata": {},
+   "source": [
+    "### 5.Вывести зарплату только у тех, у которых в скиллах есть Python (Питон)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "b93d618d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "230      35000\n",
+       "334      20000\n",
+       "2394     35000\n",
+       "8096     15000\n",
+       "9014     25000\n",
+       "9667     90000\n",
+       "20930    30000\n",
+       "22530    50000\n",
+       "28286    23000\n",
+       "30430    23000\n",
+       "Name: salary, dtype: int64"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df = works.skills.dropna().str.lower().str.contains('python|питон')\n",
+    "works[works.skills.notna()][df]['salary']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cc98d1b7",
+   "metadata": {},
+   "source": [
+    "### 6.Построить перцентили по заработной плате у мужчин и женщин"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "92355509",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1. ])"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "percentiles = np.linspace(.1, 1, 10)\n",
+    "percentiles"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "4772a178",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>salary</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0.1</th>\n",
+       "      <td>15000.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>0.2</th>\n",
+       "      <td>20000.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>0.3</th>\n",
+       "      <td>25000.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>0.4</th>\n",
+       "      <td>30000.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>0.5</th>\n",
+       "      <td>30000.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>0.6</th>\n",
+       "      <td>35000.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>0.7</th>\n",
+       "      <td>40000.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>0.8</th>\n",
+       "      <td>50000.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>0.9</th>\n",
+       "      <td>60000.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1.0</th>\n",
+       "      <td>1000000.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        salary\n",
+       "0.1    15000.0\n",
+       "0.2    20000.0\n",
+       "0.3    25000.0\n",
+       "0.4    30000.0\n",
+       "0.5    30000.0\n",
+       "0.6    35000.0\n",
+       "0.7    40000.0\n",
+       "0.8    50000.0\n",
+       "0.9    60000.0\n",
+       "1.0  1000000.0"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "men_salary = works.query('gender == \"Мужской\"').quantile(percentiles)\n",
+    "men_salary"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "a88da054",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 504x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(7, 5)) \n",
+    "plt.title('Перцентили по заработной плате у мужчин') \n",
+    "plt.xlabel('Перцентили') \n",
+    "plt.ylabel('Зарплата мужчин') \n",
+    "plt.grid() \n",
+    "\n",
+    "plt.plot(men_salary)  \n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "e90846e5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>salary</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0.1</th>\n",
+       "      <td>15000.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>0.2</th>\n",
+       "      <td>18000.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>0.3</th>\n",
+       "      <td>20000.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>0.4</th>\n",
+       "      <td>22000.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>0.5</th>\n",
+       "      <td>25000.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>0.6</th>\n",
+       "      <td>30000.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>0.7</th>\n",
+       "      <td>30000.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>0.8</th>\n",
+       "      <td>35000.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>0.9</th>\n",
+       "      <td>47000.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1.0</th>\n",
+       "      <td>900000.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       salary\n",
+       "0.1   15000.0\n",
+       "0.2   18000.0\n",
+       "0.3   20000.0\n",
+       "0.4   22000.0\n",
+       "0.5   25000.0\n",
+       "0.6   30000.0\n",
+       "0.7   30000.0\n",
+       "0.8   35000.0\n",
+       "0.9   47000.0\n",
+       "1.0  900000.0"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "women_salary = works.query('gender == \"Женский\"').quantile(percentiles)\n",
+    "women_salary"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "fd01445d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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/PiLG0+5eB1wEzAe+kx4AXwAukdRP1vI8M+1rm6T3Azem9d4XEdvq9V7NzKwxCoNDDRlABHVMoAARcR7Z5SSVhslaoxOt/0HggxOU3wQcN0H5blICnmDZhcCFBxiymZm1iPII3P/9tKOmXrkOPBORmZm1pPse2sXOkXHWNeD8JziBmplZi+pPU/itn+E5cMucQM3MrCUVBocA3AI1MzM7EH0DRVYsmsviQ2Z+BC44gZqZWYsqDBZZ16DuW3ACNTOzFhQR9A8MNaz7FpxAzcysBd3/8G52jIy7BWpmZnYgCgONHUAETqBmZtaCCmkO3HUNuA9omROomZm1nMLgEMsXzmXJgjkNi8EJ1MzMWk7fQLFhEyiUOYGamVlLicjmwG1k9y04gZqZWYv5zSO7KQ6PsbZBd2EpcwI1M7OWUr6J9nq3QM3MzPLbcwmLW6BmZmb5FQaKLF84h6UNHIELTqBmZtZiCoNDrG1w9y04gZqZWQuJCAoDxYbOQFTmBGpmZi1j4JFhhobHGn4NKDiBmplZCynfRHutW6BmZmb57bmExS1QMzOz/PoHh1i6YA7LFs5tdChOoGZm1jr6BopNMQIXnEDNzKxFZCNwh5qi+xacQM3MrEVsGRrmkd1jTXEJCziBmplZiygPIFrnFqiZmVl+5UtY3AI1MzM7AH0DRQ47pJvlCxs7B26ZE6iZmbWE/sEh1q9YhKRGhwI4gZqZWQuIiOwSliY5/wlOoGZm1gK2FId5eNdow2+iXckJ1MzMml7/nhG4zTGACJxAzcysBfQNpBG47sI1MzPLrzBYZPH8bg5vgjlwy5xAzcys6WU30V7YNCNwwQnUzMyaXETQNzjUVOc/wQnUzMya3NYdIzy0c5R1TTQCF5xAzcysyZUHEK13C9TMzCy//sHmmkS+zAnUzMyaWt/AEIvmdbFiUfOMwAUnUDMza3KFgSLrVzbPHLhlTqBmZtbU+geLTTeACJxAzcysiW0tDrN1x0jTXcIC0DXVCpKOnqg8Iu6d/nDMzMz2KpQHEDVhC3TKBAp8K/18HPArQEAAx9crKDMzM4BCE86BWzZlAo2IJwNI+mlE/Hb9QzIzM8sUBossmtvFYw6d1+hQHuVAzoHGge5c0mGSLpf0S0l3SHqGpKWSNkoqpJ9LKtZ/h6R+SXdKOq2i/ERJt6Zl5ysNxZI0V9KlqfwGSWsqtjk7HaMg6ewDjd3MzBqvb2CItSubaw7csikTqKSXSnopcFj5eXqdxz8C/xURTwBOAO4A3g5cHRHrgKvTayQdC5wJPAk4HfiMpM60n88C5wLr0uP0VH4OsD0i1gKfBD6a9rUUOA94OnAScF5lojYzs9bQP1hk/YrmG0AE+VqgL0yP71c8f8FUG0k6FHg28AWAiBiJiIeAM4CL02oXAy9Oz88AvhoRwxFxN9APnCTpCODQiLguIgL4YtU25X1dDpySWqenARsjYltEbAc2sjfpmplZC9i2Y4QHiyNNef4T8p0DfXWN+34csAX4N0knADcDbwZWRsQDad8PSFqR1l8FXF+x/eZUNpqeV5eXt9mU9jUm6WFgWWX5BNuYmVkLKA8gWtuEI3Ah32Us509UHhFvyrHvpwJvjIgbJP0jqbt2skNNdJj9lNe6zd4DSueSdQ2zcuVKent79xNeeygWi7PifdaD6642rrfazfa6u+beUQC23vULeh84sGkLZqLu8lzG8gLgEbLzkLsPYN+bgc0RcUN6fTlZAh2QdERqfR4BDFasf1TF9quB+1P56gnKK7fZLKkLWAxsS+U9Vdv0VgcYERcAFwBs2LAhenp6qldpO729vcyG91kPrrvauN5qN9vr7ntX/IKFc+/jpac/54AHEc1E3eVJ6euBfwVeA3QDl0TExfvfBCLiN8AmSb+Vik4BbgeuBMqjYs8GrkjPrwTOTCNrjyEbLPTj1N07JOnkdH7zrKptyvt6GXBNOk96FXCqpCVp8NCpqczMzFpEYbDI2hXNOQIX8p0DHQP+WdKFwFuAH0n6eERcnmP/bwS+LGkOcBfwarKkfZmkc4B7gZen49wm6TKyJDsGvD4ixtN+XgdcBMwHvpMekA1QukRSP1nL88y0r22S3g/cmNZ7X0RsyxGvmZk1icJgkZ71hzc6jEnlOQd6K/uec1wMXAp0TrpREhE/AzZMsOiUSdb/IPDBCcpvAo6boHw3KQFPsOxC4MKpYjQzs+bz0M4RtgwNN+0IXMh/DtTMzGzG7JkDtwknkS/L04V7T3WZpFelSeaviYhr6xKZmZnNWn3lOXCb9BIWyNeF+z32vQREwFPIJjHwHVnMzGzaFQaKLJjTyarD5jc6lEnl6cJ9a9VrAf8aET+oQzxmZmb0N/kIXMjXhXtzdZmkofqEY2ZmlnXhPruJR+BCvi7c91QXARPeZNvMzOxgPbxzlMGh4aY+/wn5unB3TFA2PkGZmZnZQSsMNu9NtCvl6cL9h+oySWfUJxwzM5vt9lzC0qS3MSvL04U70b0/l9UhFjMzM/oGhpjf3dwjcCFfF+4LJyj78XQHYmZmBtkI3HUrF9LR0bwjcKG+9wM1MzM7YIWBIs9c2/wdnXm6cP+NCe6lGRF/WpeIzMxs1np41yi/eWR305//hHxduN9MP/8e+Js6xmJmZrNcfxpAtL7JR+BCvi7crwFIenf5uZmZWT0U9syB2/wt0Dw31C57VDeumZnZdCoMFpnX3cHqJc09AhcO7H6gayXdQjYTUUTE8fUOzszMZpdCmgO32Ufggu8HamZmTaQwMMTJj2v+EbiQows33Q/0KOC56fnOPNuZmZkdiKHdozzw8O6mn8KvbMpEKOk84G3AO1JRN/ClegZlZmazT6tM4VeWpyX5EuBFpEnlI+J+oDXenZmZtYz+gda5hAXyJdCRiAjSKFxJC+obkpmZzUZ9A0PM7epg9ZJDGh1KLnkS6GWSPgccJum1wH8Dn69vWGZmNtsUBos8/vCFdLbACFzIN5HCxyX9AfAI8FvAeyJiY90jMzOzWaV/sMjT1ixpdBi55bkOdG5KmBsryn43Iq6ta2RmZjZrFIfHuO+hXfzxyqMbHUpuebpwvyvpcABJyyVdBLyzrlGZmdms0r9nBG5rDCCCfAn0XcB/SXoHcDXwrYh4Xn3DMjOz2aSvPAfuyta5yCPPOdBrJb2M7K4s74uI/6h/WGZmNpv0DxaZ09XB0UtbYwQuHNhcuIcAX5L0LgDPhWtmZtOlMDDUUiNwIf9cuN3APwHfAj5W14jMzGzW6RsocuJjW2cELuQ7B7od+DSwOD12pjlxzczMDtqONAK3VWYgKsuTQP8bOD8ingn8P+BqSa+vb1hmZjZblEfgrm2ROXDL8iTQ10bEtwEi4uvAM4DWuVDHzMyaWnkS+VZrgeYZhfvzqtc7yO7OYmZmdtAKg0PM6WytEbjg+3qamVmDFQaKPO7wBXR1tlZKaq1ozcys7RQGh1pqAoUyJ1AzM2uYnSNjbNq2q6Wm8CvLM5HCOuDDwLHAvHJ5RDyujnGZmdks8KvBHUDrDSCCfC3QfwM+C4wBzwG+CFxSz6DMzGx2KM+B22qXsEC+BDo/Iq4GFBH3RMR7gefWNywzM5sNCoNFujvFY5e11ghcyDeV325JHUBB0huA+4AV9Q3LzMxmg/7BIR63fCHdLTYCF/K1QN9CNpH8m4ATgVcCZ9cxJjMzmyX6BoqsbcHzn5CvBboyIm4EisCr6xyPmZnNErtGxtm0fSf/66mrGx1KTfK0QN9X9yjMzGzW+dWWIhGwro1boIdI+m1gn5u0RcRP6hOSmZnNBoXBbARuK14DCvkS6CrgH9g3gQYeiWtmZgehMFCkq0OsWb6g0aHUJE8C7Y8IJ0szM5tWfQNFjlm+oCVH4EL+G2qbmZlNq/7BIda34By4ZVMm0INtfUrqlPRTSd9Mr5dK2iipkH4uqVj3HZL6Jd0p6bSK8hMl3ZqWnS9JqXyupEtT+Q2S1lRsc3Y6RkGSL7sxM2siu0fHuWfbTta26PlPyJFAJa2TdLmk2yXdVX4cwDHeDNxR8frtwNURsQ64Or1G0rHAmcCTgNOBz0jqTNt8FjgXWJcep6fyc4DtEbEW+CTw0bSvpcB5wNOBk4DzKhO1mZk1VquPwIU6z4UraTXwfODzFcVnABen5xcDL64o/2pEDEfE3UA/cJKkI4BDI+K6iIh0/BdPsK/LgVNS6/Q0YGNEbIuI7cBG9iZdMzNrsMJAEaC9u3A5uLlwPwX8DVCqKFsZEQ8ApJ/laQFXAZsq1tucylal59Xl+2wTEWPAw8Cy/ezLzMyaQGFwKBuBu6w1R+BCHefClfQCYDAibpbUk+M4mqAs9lNe6zaVMZ5L1jXMypUr6e3tzRFmaysWi7PifdaD6642rrfatXPdXXfbblbMhx9d+4O67H8m6i5PAn0Le+fCfT9Z6zPPoJzfAV4k6Xlk9xE9VNKXgAFJR0TEA6l7djCtvxk4qmL71cD9qXz1BOWV22yW1AUsBral8p6qbXqrA4yIC4ALADZs2BA9PT3Vq7Sd3t5eZsP7rAfXXW1cb7Vr57r7u5t6OeGYRfT0nFiX/c9E3eUZhXtjRBQjYnNEvDoiXhoR1+fY7h0RsToi1pANDromIl4JXMneBHw2cEV6fiVwZhpZewzZYKEfp27eIUknp/ObZ1VtU97Xy9IxArgKOFXSkjR46NRUZmZmDbZ7dJx7tu5gXQuf/4QcLVBJt0xUHhHH13jMjwCXSToHuBd4edrfbZIuA24nG7D0+ogYT9u8DrgImA98Jz0AvgBcIqmfrOV5ZtrXNknvB25M670vIrbVGK+ZmU2ju7bsoBStO4VfWZ4u3E7geQdzkIjoJXWhRsRW4JRJ1vsg8MEJym8CjpugfDcpAU+w7ELgwlpjNjOz+tgzB24LX8IC+RLoGPAQMJwSlpmZWc36B4t0dohjWnQO3LI8l7EsBm4BNkl6UNI3JD2+znGZmVmb6hsY4rHLDmFuV+fUKzexKVugaRAQkE2dR9ZlehHwrLpFZWZmbaswWGT9itYeQAT5unD3iIhh4EuSinWKx8zM2tjw2Dj3bN3J8598RKNDOWh5RuGeNROBmJlZ+7v7wR2Ml6KlJ5Evy9MC/TjwVR59Q+0v1iUiMzNrW+0wB25ZngR6X0S8qe6RmJlZ2ysMDNEhWn4ELuQbhfuoOWTNzMxqURgssmbZAuZ1t/YIXMjXAl0t6fzqQrdKzczsQPUNDLXF+U/Il0D/uu5RmJlZ2xsZK/HrrTs5/bjHNDqUaZHnOtCLJc0BnkDWnXtnRIzUPTIzM2sr5RG47TCACPJdxvI84HPAr8hG4h4j6c8i4jv739LMzGyv8hy4s6kL9xPAcyKiHyBN4/ct9t4RxczMbEqFgSIdgscf3h4JNM8o3MFy8kzuYu9NsM3MzHIpDA5x9NJD2mIELuRrgd4m6dvAZWTnQF8O3CjppQAR8fU6xmdmZm2iMFBkbRvMgVuWpwU6DxgAfg/oAbYAS4EXAi+oW2RmZtY2RsZK3P3gDta3+D1AK+UZhfvqmQjEzMza1z1bdzBWipa/iXalPKNw5wHnAE8ia40CEBF/Wse4zMysjRQGszlw182yLtxLgMcApwHfB1YDQ/UMyszM2kvfwBBqoxG4kC+Bro2IvwV2RMTFwPOBJ9c3LDMzayeFwSJHLTmE+XPaYwQu5Eugo+nnQ5KOAxYDa+oWkZmZtZ3CwFBbDSCCfAn0AklLgL8FrgRuBz5a16jMzKxtjI5nI3Db6RIWyDcK9/Pp6feBx9U3HDMzazf3bN3B6HjMnhaopHmS3i7pzyV1SjpP0jckvVtSngkYzMzMKAy03whc2H8X7j8BK4DjyVqfK4CPAYeln2ZmZlMqDBaR2mcS+bL9tSRPjIinSuogm4no2RFRkvRD4OaZCc/MzFpd38AQq5fMb6sRuLD/FugIQESUgM3pJxERMxGYmZm1h/7BYtt138IUo3AlHZqePqOi7Cj2XtpiZmY2qbHxEndt2dFWU/iV7S+Bnk129xUiYndF+Vzgz+oZlJmZtYd7tu1kZLzUli3QSc+BRsSdk5T3T1RuZmZWrTwCt90uYYF8EymYmZnVpDCQTZ3eTnPgljmBmplZ3RQGi6w6bD4L5rbf9AFOoGZmVjd9bTgHbpkTqJmZ1cXYeIm7HtzBupXtN4AInEDNzKxONm3fxchYiXVtNgNRmROomZnVRV8aQOQWqJmZ2QHoH8wuYWm3OXDLnEDNzKwu+gaGWHXYfBa24QhccAI1M7M6KQwU27b1CU6gZmZWB+Ol4Fdbim17CQs4gZqZWR1s2raT4bH2nAO3zAnUzMymXaE8gMgtUDMzs/z2XMLic6BmZmb59Q8WOWLxPBbN6250KHXjBGpmZtOub2CobSdQKHMCNTOzaTVeCvoHi23dfQtOoGZmNs3u274rjcB1Aq2JpKMkfU/SHZJuk/TmVL5U0kZJhfRzScU275DUL+lOSadVlJ8o6da07HxJSuVzJV2aym+QtKZim7PTMQqSzq7X+zQzs321+xy4ZfVsgY4BfxURTwROBl4v6Vjg7cDVEbEOuDq9Ji07E3gScDrwGUmdaV+fBc4F1qXH6an8HGB7RKwFPgl8NO1rKXAe8HTgJOC8ykRtZmb1U2jzOXDL6pZAI+KBiPhJej4E3AGsAs4ALk6rXQy8OD0/A/hqRAxHxN1AP3CSpCOAQyPiuogI4ItV25T3dTlwSmqdngZsjIhtEbEd2MjepGtmZnVUGBjiMYfOY/H89h2BCzN0DjR1rf42cAOwMiIegCzJAivSaquATRWbbU5lq9Lz6vJ9tomIMeBhYNl+9mVmZnVWGCyyro0nUCir+xT5khYCXwPeEhGPpNOXE646QVnsp7zWbSpjO5esa5iVK1fS29s7WWxto1gszor3WQ+uu9q43mrXinVXiuDO3+ykZ3VXQ2OfibqrawKV1E2WPL8cEV9PxQOSjoiIB1L37GAq3wwcVbH5auD+VL56gvLKbTZL6gIWA9tSeU/VNr3V8UXEBcAFABs2bIienp7qVdpOb28vs+F91oPrrjaut9q1Yt1t2raTkau+x3NOfCI9Jx3dsDhmou7qOQpXwBeAOyLiExWLrgTKo2LPBq6oKD8zjaw9hmyw0I9TN++QpJPTPs+q2qa8r5cB16TzpFcBp0pakgYPnZrKzMysjgqD7T+FX1k9W6C/A/wJcKukn6WydwIfAS6TdA5wL/BygIi4TdJlwO1kI3hfHxHjabvXARcB84HvpAdkCfoSSf1kLc8z0762SXo/cGNa730Rsa1O79PMzJK+gWwEbjvfhaWsbgk0Iq5l4nORAKdMss0HgQ9OUH4TcNwE5btJCXiCZRcCF+aN18zMDl5hoMiKRXNZfEh7j8AFz0RkZmbTqDA4xPo2n0ChzAnUzMymRSnNgdvuEyiUOYGamdm0uP/hXewcGZ8V14CCE6iZmU2TQhpA5C5cMzOzAzCbLmEBJ1AzM5smfQNFDl80l8MOmdPoUGaEE6iZmU2Lwiy4iXYlJ1AzMztoEUH/wJATqJmZ2YG4/+Hd7BgZb/ubaFdyAjUzs4NWGJhdA4jACdTMzKbBbLuEBZxAzcxsGhQGh1i+cA5LFsyOEbjgBGpmZtOgb2D2TOFX5gRqZmYHJSKbA3c2dd+CE6iZmR2k3zyym+Lw2KwaQAROoGZmdpD23ETbLVAzM7P8ZuMlLOAEamZmB6kwUGTZgjksWzi30aHMKCdQMzM7KIXBoVk3AhecQM3M7CBERDaJ/Cy5iXYlJ1AzM6vZwCPDDO0em3WXsIATqJmZHYTyTbTdhWtmZnYA+mbhHLhlTqBmZlaz/sEhlhzSzbJZNAdumROomZnVrDBQZN2KRUhqdCgzzgnUzMxqEhH0DQzNyhG44ARqZmY12jI0zCO7Z98cuGVOoGZmVpPZPIAInEDNzKxGey5hcReumZlZfn0DRRbP7+bwWTYHbpkTqJmZ1aR/cIj1KxfOyhG44ARqZmY1yEbgFlm7Ynae/wQnUDMzq8GW4jAP7xpl/Sw9/wlOoGZmVoP+NAJ3nVugZmZm+fUNZCNwZ+skCuAEamZmNSgMFjl0XhcrFs3OEbgAXY0OwMzMWkNEsHNknK3FEX5x38OsWzk758AtcwI1M5vFdo+Os23HCNt2jPBgcZitxRG27hhm646R7Hmx4vmOYXaPlvZse9YzHtvAyBvPCdTMrI2MjZfYtjNLiFuLe5Pith1ZAnwwJcXy8qHhsQn3M6ezg2UL52SPBXNZu2IhyxbMYdnCuennHE46ZtkMv7vm4gRqZtbESqXg4V2jqRU4XPVzb1Lclsq37xydcD+dHWLpgjl7kt/xSw5LyXHfpLhswVyWLZzDwrlds7p7Ng8nUDOzGoyXgt2j49ljrLT3+WiJ4dFxdo+Ns2sklY9l5btHx9Oyfdev3MdwuWxsnO1Du9jx3e8wXooJY1hySDfLFs5l6YI5rF+5kGWPW8bSBXNYvvDRSXHx/G46OpwQp5MTqJnlUioFw2OPTgi7K77wh0erysdK3Nk/ws/HCo0Of0JBMDYek7+nR5XvTY6j4xMntTzmdXcwr7uTeV2de57P7e5kXlcHhx0yh/ndWflDD45w3Lo1Wctx4RyWL8xah0sXzGHpIXPo6vSFFI3kBGrWYkqlYLRUYmw8GB0vMToejIyX2DWSffEPV33hH0wLqLzP3WMlRsZKUwc3mf6+6auAadYhsmSWEtieZNbdwfzuTg6d350lua695dXJb08SrCibX95nxfpzuzuY29WRu2u0t7eXnp7fqnMNWK2cQK2tRQRjpWA8PcZKQalUURbB+Hj6WSrtd91btowxdvtAlrRKwehYibFSiZHxYGy8tCeZ7UlspRKjY8FYae+y0fHKxJcdb2Qs+7nvOhXP07FGS1nZZN15B2KqFtCky1NS2ZMYujrTsomSSvb8+v/5IT2/13Pwv8w6kfC5PquJE2gbGi/t/YIeTV/uI+mL+/5iib6BIcbGKxJIas1kz/eTbCqSzlgpGB8vMR7sSTylSbaZOFlVrlva95gRVfFlr0uxv/2X9omvXB4Hn2v2dfNNuVbrEHR3dqSH6OrsoLtDdHd10NWhRy2b393JonlddHV0MKdLdHXsXd7d2UFXp5iTfmbrVO5HzOl6dAtoXnXCq6EFNB06JJ97s7bkBDqN+gaGuGvLDsZSQhqpam2Uk9loaYJWxp5Wy6NbNnv2lVo0o6lFk21Tta9Saeqkce0P6l4X3Z2iQ6KrI/vy7OoQnR0ddHZAV0cHnR3a+5D2ed2Vfs7p6nhUWWfaT1fHRPufaN20/07ts01nZwedk2xf3see8hTfrT//GU9/2ga6OrVvYuwU3R0d+yTHTicMs7bnBDqNLrtxE5+/9u5c63Z3llsZe1sj1a2M7q7UaunsYFF3195lnR3Z89Si6e4of5FP0GLpqFi/U/T98pc8+bgnTZwoqhOIRFfn3gTS1dFBx0QJsHL7Nm5t7Lq3kyevXtzoMMysSbR1ApV0OvCPQCfw+Yj4SD2P96e/ewwveeqqvQmxY9+Wyt7kqIadc+l9pJ+e449oyLHNzNpJ2yZQSZ3APwN/AGwGbpR0ZUTcXq9jHnnYfI48bH69dm9mZk2knS8iOgnoj4i7ImIE+CpwRoNjMjOzNtHOCXQVsKni9eZUZmZmdtDatgsXmOgk4z7jUyWdC5wLsHLlSnp7e2cgrMYqFouz4n3Wg+uuNq632rnuajcTddfOCXQzcFTF69XA/ZUrRMQFwAUAGzZsiJ6enhkLrlGymU16Gh1GS3Ld1cb1VjvXXe1mou7auQv3RmCdpGMkzQHOBK5scExmZtYm2rYFGhFjkt4AXEV2GcuFEXFbg8MyM7M20bYJFCAivg18u9FxmJlZ+2nnLlwzM7O6cQI1MzOrgROomZlZDRTTfr+n1iRpC3BPo+OYAcuBBxsdRIty3dXG9VY7113tpqvuHhsRh0+0wAl0lpF0U0RsaHQcrch1VxvXW+1cd7WbibpzF66ZmVkNnEDNzMxq4AQ6+1zQ6ABamOuuNq632rnualf3uvM5UDMzsxq4BWpmZlYDJ9A2JOl0SXdK6pf09gmWv0LSLenxI0knNCLOZjRV3VWs9zRJ45JeNpPxNbM8dSepR9LPJN0m6fszHWOzyvGZXSzpG5J+nuru1Y2Is9lIulDSoKRfTLJcks5P9XqLpKdOawAR4UcbPcgmzv8V8DhgDvBz4NiqdZ4JLEnP/xC4odFxN8MjT91VrHcN2TzLL2t03M3wyPl3dxhwO3B0er2i0XE3wyNn3b0T+Gh6fjiwDZjT6Ngb/QCeDTwV+MUky58HfIfs/tAnT/d3nVug7eckoD8i7oqIEeCrwBmVK0TEjyJie3p5Pdm9Ui1H3SVvBL4GDM5kcE0uT939MfD1iLgXICJcf5k8dRfAIkkCFpIl0LGZDbP5RMQPyOpiMmcAX4zM9cBhko6YruM7gbafVcCmitebU9lkziH7D81y1J2kVcBLgH+ZwbhaQZ6/u/XAEkm9km6WdNaMRdfc8tTdp4EnAvcDtwJvjojSzITX0g70+/CAtPXtzGYpTVA24VBrSc8hS6C/W9eIWkeeuvsU8LaIGM8aA5bkqbsu4ETgFGA+cJ2k6yOir97BNbk8dXca8DPgucDjgY2SfhgRj9Q5tlaX+/uwFk6g7WczcFTF69Vk/7XuQ9LxwOeBP4yIrTMUW7PLU3cbgK+m5LkceJ6ksYj4zxmJsHnlqbvNwIMRsQPYIekHwAnAbE+geeru1cBHIjux1y/pbuAJwI9nJsSWlev7sFbuwm0/NwLrJB0jaQ5wJnBl5QqSjga+DvyJ//vfx5R1FxHHRMSaiFgDXA78hZMnkKPugCuAZ0nqknQI8HTgjhmOsxnlqbt7yVruSFoJ/BZw14xG2ZquBM5Ko3FPBh6OiAema+dugbaZiBiT9AbgKrLRfRdGxG2S/jwt/xfgPcAy4DOpJTUWnrA6b93ZBPLUXUTcIem/gFuAEvD5iJjw8oPZJOff3fuBiyTdStYt+baImPV3aZH0FaAHWC5pM3Ae0A176u3bZCNx+4GdZC356Tt+GuprZmZmB8BduGZmZjVwAjUzM6uBE6iZmVkNnEDNzMxq4ARqZmZWA1/GYtaEJI2TTdlWthS4MiLe0KCQzKyKE6hZc9oVEU8pv5D0KrJZkMysSbgL16zFSDpc0tck3Zgev5PK3yvpEknXSCpIem0q75H0zYrt3yrpvel5p6SPpf3cIunP9reNpGel+3neLmlXev6ztM6vJS1Pz79UeY9GSa+StCWtv618H1VJxYp1flh5TLNm5xaoWev5R+CTEXFtmpbxKrI7dQAcT3bfwwXATyV9a4p9nUM2vdnTJM0F/kfSdydbOSJ+CDxF0hrgm5Wt5DJJTwaOqyruBL4SEW+SdNEE2zwfWAw8PEW8Zk3DCdSs9fw+cGzF3WAOlbQoPb8iInYBuyR9j+xekw/tZ1+nAseXW4RkSWwdMEI2b+3PUvnhwL/mjO8DZFOqfbCibD6we6KV0z0u3wV8CHhlzmOYNZwTqFnr6QCekRLlHimhVs/NOdVcnQLeGBFXVe2rB/hhRLwgvX4r2Y2cp/JMoAj8vKr8SCa/C8b/AXqB3+TYv1nT8DlQs9bzXWDPaFxJT6lYdoakeZKWkU2yfeMU+7oKeJ2k7rSv9ZIWHERs7yW7WcEekuYDLwD+Z4L1O4C/BP7+II5p1hBugZq1njcB/yzpFrLP8A+AP0/Lfgx8CzgaeH9E3C9pPfBMSdemdVYBnZKuILsn7BrgJ6krdQvw4oOI7YaI+FU6R1r2HeDSiJgomc8HLo+Ih3yDcms1vhuLWZtII2uLEfHxnOv2RkRvncMya1tugZrNTtcA9zQ6CLNW5haomZlZDTyIyMzMrAZOoGZmZjVwAjUzM6uBE6iZmVkNnEDNzMxq4ARqZmZWg/8Pz3wIcTsqZZsAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 504x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(7, 5)) \n",
+    "plt.title('Перцентили по заработной плате у женщин') \n",
+    "plt.xlabel('Перцентили') \n",
+    "plt.ylabel('Зарплата женщин') \n",
+    "plt.grid() \n",
+    "\n",
+    "plt.plot(women_salary)  \n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c88b63aa",
+   "metadata": {},
+   "source": [
+    "### 7.Построить графики распределения по заработной плате мужчин и женщин в зависимости от высшего образования"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "ee70fbc2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "men_salary = works.groupby('educationType').agg('mean').reset_index()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "caeab8e6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "men_salary = works.query('gender == \"Мужской\"').groupby('educationType').agg('mean').reset_index()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "9f56dc2e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "women_salary = works.query('gender == \"Женский\"').groupby('educationType').agg('mean').reset_index()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "20055466",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "educationTypes = men_salary['educationType'].values\n",
+    "men_salaries = men_salary['salary'].values\n",
+    "women_salaries = women_salary['salary'].values\n",
+    "\n",
+    "index = np.arange(len(educationTypes))\n",
+    "\n",
+    "bw = 0.4\n",
+    "plt.bar(index-bw/2, men_salaries, bw, color='b', label='Средняя зарплата мужчин')\n",
+    "plt.bar(index+bw/2, women_salaries, bw, color='r', label='Средняя зарплата женщин')\n",
+    "plt.xticks(index, educationTypes, rotation=45)\n",
+    "plt.legend()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d7fa662f",
+   "metadata": {},
+   "source": [
+    "##### Графики для мужчин"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "c217564f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "men_height = works.query('gender == \"Мужской\" and educationType == \"Высшее\"')\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "bae25412",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 720x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(10, 5)) \n",
+    "plt.title('Распределение по заработной плате у мужчин с высшим образованием') \n",
+    "plt.xlabel('Зарплата мужчин') \n",
+    "plt.ylabel('Количество мужчин') \n",
+    "plt.grid() \n",
+    "\n",
+    "plt.hist(men_height['salary'], \n",
+    "         bins=50) \n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "17af0b5a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "men_not_height = works.query('gender == \"Мужской\" and educationType == \"Незаконченное высшее\"')\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "61538fe4",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 720x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(10, 5))  \n",
+    "plt.title('Распределение по заработной плате у мужчин с незаконченным высшим образованием') \n",
+    "plt.xlabel('Зарплата мужчин') \n",
+    "plt.ylabel('Количество мужчин') \n",
+    "plt.grid() \n",
+    "\n",
+    "plt.hist(men_not_height['salary'], \n",
+    "         bins=50) \n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "e46b82b6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "men_mean = works.query('gender == \"Мужской\" and educationType == \"Среднее\"')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "3b6b6a15",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 720x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(10, 5))  \n",
+    "plt.title('Распределение по заработной плате у мужчин с незаконченным высшим образованием') \n",
+    "plt.xlabel('Зарплата мужчин') \n",
+    "plt.ylabel('Количество мужчин') \n",
+    "plt.grid() \n",
+    "\n",
+    "plt.hist(men_mean['salary'], \n",
+    "         bins=50) \n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "4b005501",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "men_mean_prof = works.query('gender == \"Мужской\" and educationType == \"Среднее профессиональное\"')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "f490ddb6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 720x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(10, 5))  \n",
+    "plt.title('Распределение по заработной плате у мужчин с незаконченным высшим образованием') \n",
+    "plt.xlabel('Зарплата мужчин') \n",
+    "plt.ylabel('Количество мужчин') \n",
+    "plt.grid() \n",
+    "\n",
+    "plt.hist(men_mean_prof['salary'], \n",
+    "         bins=50) \n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0291f9c3",
+   "metadata": {},
+   "source": [
+    "##### Графики для женщин"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "0d5dcfdb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "women_height = works.query('gender == \"Женский\" and educationType == \"Высшее\"')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "25bfe921",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 720x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(10, 5))  \n",
+    "plt.title('Распределение по заработной плате у женщин с высшим образованием') \n",
+    "plt.xlabel('Зарплата женщин') \n",
+    "plt.ylabel('Количество женщин') \n",
+    "plt.grid() \n",
+    "\n",
+    "plt.hist(women_height['salary'], \n",
+    "         bins=50) \n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "e0550dbc",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "women_not_height = works.query('gender == \"Женский\" and educationType == \"Незаконченное высшее\"')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "64176909",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 720x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(10, 5))  \n",
+    "plt.title('Распределение по заработной плате у женщин с незаконченным высшим образованием') \n",
+    "plt.xlabel('Зарплата женщин') \n",
+    "plt.ylabel('Количество женщин') \n",
+    "plt.grid() \n",
+    "\n",
+    "plt.hist(women_not_height['salary'], \n",
+    "         bins=50) \n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "id": "284c6cff",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "women_mean = works.query('gender == \"Женский\" and educationType == \"Среднее\"')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "id": "b3a21b35",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 720x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(10, 5))  \n",
+    "plt.title('Распределение по заработной плате у женщин с незаконченным высшим образованием') \n",
+    "plt.xlabel('Зарплата женщин') \n",
+    "plt.ylabel('Количество женщин') \n",
+    "plt.grid() \n",
+    "\n",
+    "plt.hist(women_mean['salary'], \n",
+    "         bins=50) \n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "id": "2edd9659",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "women_mean_prof = works.query('gender == \"Женский\" and educationType == \"Среднее профессиональное\"')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "id": "c6da0874",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 720x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(10, 5))  \n",
+    "plt.title('Распределение по заработной плате у женщин с незаконченным высшим образованием') \n",
+    "plt.xlabel('Зарплата женщин') \n",
+    "plt.ylabel('Количество женщин') \n",
+    "plt.grid() \n",
+    "\n",
+    "plt.hist(women_mean_prof['salary'], \n",
+    "         bins=50) \n",
+    "plt.show()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/task_8.ipynb b/task_8.ipynb
new file mode 100644
index 0000000..b862213
--- /dev/null
+++ b/task_8.ipynb
@@ -0,0 +1,531 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "8e57c2fe",
+   "metadata": {},
+   "source": [
+    "# Oчистить и визуализировать данные по профессии инженер и должности менеджер"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "ea24d33c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "504841ac",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>salary</th>\n",
+       "      <th>educationType</th>\n",
+       "      <th>jobTitle</th>\n",
+       "      <th>qualification</th>\n",
+       "      <th>gender</th>\n",
+       "      <th>dateModify</th>\n",
+       "      <th>skills</th>\n",
+       "      <th>otherInfo</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>60000</td>\n",
+       "      <td>Высшее</td>\n",
+       "      <td>Специалист пресс-службы</td>\n",
+       "      <td>Магистр</td>\n",
+       "      <td>Мужской</td>\n",
+       "      <td>2021-04-01</td>\n",
+       "      <td>&lt;p&gt;Аналитическое&amp;nbsp;мышление,&amp;nbsp;&lt;span cla...</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>85000</td>\n",
+       "      <td>Высшее</td>\n",
+       "      <td>менеджер проектов</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Мужской</td>\n",
+       "      <td>2021-04-01</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>15000</td>\n",
+       "      <td>Среднее профессиональное</td>\n",
+       "      <td>....</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Женский</td>\n",
+       "      <td>2021-06-01</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>30000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Женский</td>\n",
+       "      <td>2021-04-03</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>45000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Мужской</td>\n",
+       "      <td>2021-06-28</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</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>32678</th>\n",
+       "      <td>15000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Женский</td>\n",
+       "      <td>2021-06-23</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32679</th>\n",
+       "      <td>13000</td>\n",
+       "      <td>Среднее</td>\n",
+       "      <td>уборщица</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Женский</td>\n",
+       "      <td>2021-07-29</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32680</th>\n",
+       "      <td>16000</td>\n",
+       "      <td>Среднее профессиональное</td>\n",
+       "      <td>кочегар машинист котельной</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Мужской</td>\n",
+       "      <td>2021-11-11</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32681</th>\n",
+       "      <td>35000</td>\n",
+       "      <td>Высшее</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Мужской</td>\n",
+       "      <td>2020-04-21</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32682</th>\n",
+       "      <td>30000</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>Мужской</td>\n",
+       "      <td>2021-06-20</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>32683 rows × 8 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       salary             educationType                    jobTitle  \\\n",
+       "0       60000                    Высшее     Специалист пресс-службы   \n",
+       "1       85000                    Высшее           менеджер проектов   \n",
+       "2       15000  Среднее профессиональное                        ....   \n",
+       "3       30000                       NaN                         NaN   \n",
+       "4       45000                       NaN                         NaN   \n",
+       "...       ...                       ...                         ...   \n",
+       "32678   15000                       NaN                         NaN   \n",
+       "32679   13000                   Среднее                    уборщица   \n",
+       "32680   16000  Среднее профессиональное  кочегар машинист котельной   \n",
+       "32681   35000                    Высшее                         NaN   \n",
+       "32682   30000                       NaN                         NaN   \n",
+       "\n",
+       "      qualification   gender  dateModify  \\\n",
+       "0           Магистр  Мужской  2021-04-01   \n",
+       "1               NaN  Мужской  2021-04-01   \n",
+       "2               NaN  Женский  2021-06-01   \n",
+       "3               NaN  Женский  2021-04-03   \n",
+       "4               NaN  Мужской  2021-06-28   \n",
+       "...             ...      ...         ...   \n",
+       "32678           NaN  Женский  2021-06-23   \n",
+       "32679           NaN  Женский  2021-07-29   \n",
+       "32680           NaN  Мужской  2021-11-11   \n",
+       "32681           NaN  Мужской  2020-04-21   \n",
+       "32682           NaN  Мужской  2021-06-20   \n",
+       "\n",
+       "                                                  skills otherInfo  \n",
+       "0      <p>Аналитическое&nbsp;мышление,&nbsp;<span cla...       NaN  \n",
+       "1                                                    NaN       NaN  \n",
+       "2                                                    NaN       NaN  \n",
+       "3                                                    NaN       NaN  \n",
+       "4                                                    NaN       NaN  \n",
+       "...                                                  ...       ...  \n",
+       "32678                                                NaN       NaN  \n",
+       "32679                                                NaN       NaN  \n",
+       "32680                                                NaN       NaN  \n",
+       "32681                                                NaN       NaN  \n",
+       "32682                                                NaN       NaN  \n",
+       "\n",
+       "[32683 rows x 8 columns]"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "works = pd.read_csv(\"works.csv\")\n",
+    "works"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "e8158874",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Удалим строки, где 'jobTitle' и 'qualification' равны NaN\n",
+    "works.dropna(subset=['jobTitle'], inplace=True)\n",
+    "works.dropna(subset=['qualification'], inplace=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "a65c07ef",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "10130"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Осталось 10130 человек\n",
+    "works.shape[0]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c50f397e",
+   "metadata": {},
+   "source": [
+    "## Без рассмотрения случаев, когда  \"jobTitle\" и \"qualification\" состоят из нескольких слов"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "595cdc5f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Приведем значения к нижнему регистру и заменим дефис на пробел\n",
+    "works['qualification'] = works['qualification'].str.replace('-', ' ').str.lower()\n",
+    "works[\"jobTitle\"] = works[\"jobTitle\"].str.replace('-', ' ').str.lower()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "ddc9b4ee",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "False    9876\n",
+       "True      254\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# У 9876 человек не совпадает профессия и должность\n",
+    "(works['jobTitle'] == works['qualification']).value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "79675c18",
+   "metadata": {},
+   "source": [
+    "## Рассматриваем случаи когда  \"jobTitle\" и \"qualification\" состоят из нескольких слов"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "70537d8f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def coincidences(column1, column2):\n",
+    "    list1 = column1.split()\n",
+    "    for word in list1:\n",
+    "        if word in column2:\n",
+    "            return True\n",
+    "    return False"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "4041a14d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "7714"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# У 7714 человек не совпадает профессия и должность\n",
+    "count = 0\n",
+    "for (column1, column2) in zip(works[\"jobTitle\"], works[\"qualification\"]):\n",
+    "    if coincidences(column1, column2) or coincidences(column2, column1):\n",
+    "        count += 1\n",
+    "\n",
+    "works.shape[0] - count"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1bb3a49b",
+   "metadata": {},
+   "source": [
+    "## ТОП-5 образований и графики к ним"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "4483602c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "бакалавр              98\n",
+       "экономист             86\n",
+       "менеджер              79\n",
+       "юрист                 41\n",
+       "экономист менеджер    38\n",
+       "Name: qualification, dtype: int64"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Топ-5 образований, после которых люди становятся менеджерами\n",
+    "managers = works[works[\"jobTitle\"].str.contains(\"менедж\")]\n",
+    "managers['qualification'].value_counts().head(5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "0f22eb56",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "инженер            25\n",
+       "главный инженер    23\n",
+       "директор           21\n",
+       "менеджер           13\n",
+       "водитель           11\n",
+       "Name: jobTitle, dtype: int64"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Топ-5 образований, после которых люди становятся инженерами\n",
+    "engineers = works[works[\"qualification\"].str.contains(\"инженер\")]\n",
+    "engineers['jobTitle'].value_counts().head(5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "84496195",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "managers_list = managers['qualification'].value_counts().head(5)\n",
+    "engineers_list = engineers['jobTitle'].value_counts().head(5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "255a34e8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 504x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "names = managers_list.index.tolist()\n",
+    "values = managers_list.tolist()\n",
+    "\n",
+    "fig = plt.figure()\n",
+    "fig.set_figwidth(7)\n",
+    "plt.bar(names, values)\n",
+    "plt.title('ТОП-5 образований, после которых становятся менеджерами') \n",
+    "plt.xlabel('Должность') \n",
+    "plt.ylabel('Количество человек') \n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "617ea494",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 504x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "names = engineers_list.index.tolist()\n",
+    "values = engineers_list.tolist()\n",
+    "\n",
+    "fig = plt.figure()\n",
+    "fig.set_figwidth(7)\n",
+    "plt.bar(names, values)\n",
+    "plt.title('ТОП-5 образований, после которых становятся инженерами') \n",
+    "plt.xlabel('Должность') \n",
+    "plt.ylabel('Количество человек') \n",
+    "\n",
+    "plt.show()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}