diff --git a/lab3.ipynb b/lab3.ipynb
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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "id": "24359ac1-37a0-4e08-aa35-b787d396aeef",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "3"
+      ]
+     },
+     "execution_count": 48,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "(23 + 4) % 5 + 1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "id": "3f35943f-cf4d-486c-9459-85227daab9cd",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "   Id       Name  Year Gender  Count\n",
+      "0   1       Mary  1880      F   7065\n",
+      "1   2       Anna  1880      F   2604\n",
+      "2   3       Emma  1880      F   2003\n",
+      "3   4  Elizabeth  1880      F   1939\n",
+      "4   5     Minnie  1880      F   1746\n",
+      "5   6   Margaret  1880      F   1578\n",
+      "6   7        Ida  1880      F   1472\n",
+      "7   8      Alice  1880      F   1414\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "data = pd.read_csv(r\"C:\\Users\\skiba\\Downloads\\NationalNames.csv\")\n",
+    "\n",
+    "print(data.head(8))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "id": "80b2aade-5879-440b-98bf-0e7d616fe025",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "              Id     Name  Year Gender  Count\n",
+      "1825425  1825426       Zo  2014      M      5\n",
+      "1825426  1825427    Zyeir  2014      M      5\n",
+      "1825427  1825428     Zyel  2014      M      5\n",
+      "1825428  1825429   Zykeem  2014      M      5\n",
+      "1825429  1825430   Zymeer  2014      M      5\n",
+      "1825430  1825431  Zymiere  2014      M      5\n",
+      "1825431  1825432    Zyran  2014      M      5\n",
+      "1825432  1825433    Zyrin  2014      M      5\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "\n",
+    "data = pd.read_csv(r\"C:\\Users\\skiba\\Downloads\\NationalNames.csv\")\n",
+    "\n",
+    "print(data.tail(8))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "id": "bced77b4-a7c2-4539-8e33-4bdc5c99ffa5",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "                 Id          Year         Count\n",
+      "count  1.825433e+06  1.825433e+06  1.825433e+06\n",
+      "mean   9.127170e+05  1.972620e+03  1.846879e+02\n",
+      "std    5.269573e+05  3.352891e+01  1.566711e+03\n",
+      "min    1.000000e+00  1.880000e+03  5.000000e+00\n",
+      "25%    4.563590e+05  1.949000e+03  7.000000e+00\n",
+      "50%    9.127170e+05  1.982000e+03  1.200000e+01\n",
+      "75%    1.369075e+06  2.001000e+03  3.200000e+01\n",
+      "max    1.825433e+06  2.014000e+03  9.968000e+04\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "data = pd.read_csv(r\"C:\\Users\\skiba\\Downloads\\NationalNames.csv\")\n",
+    "\n",
+    "print(data.describe())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "id": "930bb0db-c5d5-4073-b90b-4b2faf54b09b",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "93889\n"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "import pandas as pd\n",
+    "\n",
+    "\n",
+    "data = pd.read_csv(r\"C:\\Users\\skiba\\Downloads\\NationalNames.csv\")\n",
+    "\n",
+    "unique_names_count = data['Name'].nunique()\n",
+    "\n",
+    "print(unique_names_count)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "id": "229bb8f5-b2f2-43f9-ba48-2f6aeae5402e",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Gender\n",
+      "F    64911\n",
+      "M    39199\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "\n",
+    "data = pd.read_csv(r\"C:\\Users\\skiba\\Downloads\\NationalNames.csv\")\n",
+    "\n",
+    "unique_names_by_gender = data.groupby('Gender')['Name'].nunique()\n",
+    "\n",
+    "print(unique_names_by_gender.to_string())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "id": "8a21170a-3453-486c-bb23-72c038b0b35b",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "              Id     Name  Year Gender  Count\n",
+      "1677392  1677393    Jacob  2010      M  22082\n",
+      "1677393  1677394    Ethan  2010      M  17985\n",
+      "1677394  1677395  Michael  2010      M  17308\n",
+      "1677395  1677396   Jayden  2010      M  17152\n",
+      "1677396  1677397  William  2010      M  17030\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "data = pd.read_csv(r\"C:\\Users\\skiba\\Downloads\\NationalNames.csv\")\n",
+    "\n",
+    "male_names_2010 = data[(data['Gender'] == 'M') & (data['Year'] == 2010)]\n",
+    "\n",
+    "top_5_male_names_2010 = male_names_2010.sort_values(by='Count', ascending=False).head(5)\n",
+    "\n",
+    "print(top_5_male_names_2010)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "id": "5d703d4a-5925-4825-ae73-d7c0f6612d81",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The most popular name is 'Linda' in 1947\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "data = pd.read_csv(r\"C:\\Users\\skiba\\Downloads\\NationalNames.csv\")\n",
+    "\n",
+    "most_popular_name = data.loc[data['Count'].idxmax()]\n",
+    "\n",
+    "\n",
+    "print(f\"The most popular name is '{most_popular_name['Name']}' in {most_popular_name['Year']}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "id": "8f7cca93-5963-495c-8781-4954b8a34af5",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "254615\n"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "import pandas as pd\n",
+    "data = pd.read_csv(r\"C:\\Users\\skiba\\Downloads\\NationalNames.csv\")\n",
+    "\n",
+    "min_count = data['Count'].min()\n",
+    "\n",
+    "min_count_records = data[data['Count'] == min_count].shape[0]\n",
+    "\n",
+    "\n",
+    "print(min_count_records)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "id": "aa57c3b3-df2b-4baa-8106-673180a18fff",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Year\n",
+      "1880    1889\n",
+      "1881    1830\n",
+      "1882    2012\n",
+      "1883    1962\n",
+      "1884    2158\n"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "import pandas as pd\n",
+    "data = pd.read_csv(r\"C:\\Users\\skiba\\Downloads\\NationalNames.csv\")\n",
+    "\n",
+    "unique_names_per_year = data.groupby('Year')['Name'].nunique()\n",
+    "\n",
+    "\n",
+    "\n",
+    "print(unique_names_per_year.head(5).to_string())\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "id": "5c4b1d82-dfdd-4e4a-adba-413837a45349",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "year  2008 with 32488 unique names.\n"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "import pandas as pd\n",
+    "data = pd.read_csv(r\"C:\\Users\\skiba\\Downloads\\NationalNames.csv\")\n",
+    "\n",
+    "unique_names_per_year = data.groupby('Year')['Name'].nunique()\n",
+    "\n",
+    "year_with_most_unique_names = unique_names_per_year.idxmax()\n",
+    "max_unique_names = unique_names_per_year.max()\n",
+    "\n",
+    "\n",
+    "print(f\"year  {year_with_most_unique_names} with {max_unique_names} unique names.\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "id": "4ad64ee0-09bf-447f-a791-2236d164f7dc",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Jacob\n"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "import pandas as pd\n",
+    "data = pd.read_csv(r\"C:\\Users\\skiba\\Downloads\\NationalNames.csv\")\n",
+    "\n",
+    "names_2008 = data[data['Year'] == 2008]\n",
+    "\n",
+    "most_popular_name_2008 = names_2008.loc[names_2008['Count'].idxmax()]['Name']\n",
+    "\n",
+    "\n",
+    "print(most_popular_name_2008)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "id": "dcb3f7a6-4a51-4e0b-b59a-66847b85829a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "54\n"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "import pandas as pd\n",
+    "data = pd.read_csv(r\"C:\\Users\\skiba\\Downloads\\NationalNames.csv\")\n",
+    "\n",
+    "births_per_year_gender = data.groupby(['Year', 'Gender'])['Count'].sum().unstack()\n",
+    "\n",
+    "years_more_female_births = (births_per_year_gender['F'] > births_per_year_gender['M']).sum()\n",
+    "\n",
+    "\n",
+    "print(years_more_female_births)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "id": "df949e94-f0bd-4b0d-8d96-0e875eb48a67",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "data = pd.read_csv(r\"C:\\Users\\skiba\\Downloads\\NationalNames.csv\")\n",
+    "\n",
+    "births_per_year_gender = data.groupby(['Year', 'Gender'])['Count'].sum().unstack()\n",
+    "\n",
+    "births_per_year_gender.plot()\n",
+    "\n",
+    "plt.title('Total births per year by gender')\n",
+    "plt.xlabel('Year')\n",
+    "plt.ylabel('Total births per year')\n",
+    "\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "id": "94ffcd43-3945-4371-ad44-a883a842f33d",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "10221\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "data = pd.read_csv(r\"C:\\Users\\skiba\\Downloads\\NationalNames.csv\")\n",
+    "\n",
+    "gender_neutral_names = data.groupby('Name')['Gender'].nunique()\n",
+    "\n",
+    "neutral_name_count = (gender_neutral_names == 2).sum()\n",
+    "\n",
+    "print(neutral_name_count)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "id": "c23dc98e-acc4-4c29-b46d-d6a646fff899",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "4139\n"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "import pandas as pd\n",
+    "data = pd.read_csv(r\"C:\\Users\\skiba\\Downloads\\NationalNames.csv\")\n",
+    "\n",
+    "barbara_boys_count = data[(data['Name'] == 'Barbara') & (data['Gender'] == 'M')]['Count'].sum()\n",
+    "\n",
+    "\n",
+    "print(barbara_boys_count)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "id": "8a96540b-6d88-47af-9ec0-267df3c57426",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Index(['James', 'John', 'Robert', 'Michael', 'Mary', 'William', 'David',\n",
+      "       'Joseph', 'Richard', 'Charles', 'Thomas', 'Christopher', 'Daniel',\n",
+      "       'Elizabeth', 'Patricia'],\n",
+      "      dtype='object', name='Name')\n"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "import pandas as pd\n",
+    "\n",
+    "data = pd.read_csv(r\"C:\\Users\\skiba\\Downloads\\NationalNames.csv\")\n",
+    "\n",
+    "gender_neutral_names = data.groupby('Name')['Gender'].nunique()\n",
+    "\n",
+    "neutral_names = gender_neutral_names[gender_neutral_names == 2].index\n",
+    "\n",
+    "names_year_count = data[data['Name'].isin(neutral_names)].groupby('Name')['Year'].nunique()\n",
+    "\n",
+    "most_popular_neutral_names = data[data['Name'].isin(neutral_names)].groupby('Name')['Count'].sum().sort_values(ascending=False)\n",
+    "\n",
+    "print(most_popular_neutral_names.head(15).index)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "id": "8341cc37-c11d-4366-a039-423cda5bc1f3",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "data = pd.read_csv(r\"C:\\Users\\skiba\\Downloads\\NationalNames.csv\")\n",
+    "\n",
+    "john_data = data[data['Name'] == 'John'].groupby('Year')['Count'].sum()\n",
+    "mary_data = data[data['Name'] == 'Mary'].groupby('Year')['Count'].sum()\n",
+    "\n",
+    "plt.plot(john_data.index, john_data.values, label='John')\n",
+    "plt.plot(mary_data.index, mary_data.values, label='Mary')\n",
+    "\n",
+    "plt.title(\"Distribution of the names 'John' and 'Mary' over the years\")\n",
+    "plt.xlabel('Year')\n",
+    "plt.ylabel('Count')\n",
+    "plt.legend(title='Name')\n",
+    "\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "id": "cb409075-b622-4a6d-a44b-e91050ef343a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "     Year      Name  Count\n",
+      "0    1880      John   9655\n",
+      "1    1881      John   8769\n",
+      "2    1882      John   9557\n",
+      "3    1883      John   8894\n",
+      "4    1884      John   9388\n",
+      "..    ...       ...    ...\n",
+      "130  2010  Isabella  22883\n",
+      "131  2011    Sophia  21816\n",
+      "132  2012    Sophia  22267\n",
+      "133  2013    Sophia  21147\n",
+      "134  2014      Emma  20799\n",
+      "\n",
+      "[135 rows x 3 columns]\n"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "import pandas as pd\n",
+    "data = pd.read_csv(r\"C:\\Users\\skiba\\Downloads\\NationalNames.csv\")\n",
+    "\n",
+    "most_popular_names_per_year = data.loc[data.groupby('Year')['Count'].idxmax()][['Year', 'Name', 'Count']]\n",
+    "\n",
+    "most_popular_names_per_year = most_popular_names_per_year.reset_index(drop=True)\n",
+    "\n",
+    "\n",
+    "print(most_popular_names_per_year)\n",
+    "\n"
+   ]
+  }
+ ],
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