319 lines
9.5 KiB
Plaintext
319 lines
9.5 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "43d948e5-c6ab-49bc-af02-cce09d448c0a",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Первый взгляд на данные:\n",
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" Имя Возраст Баллы\n",
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"0 Анна 21 89\n",
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"1 Борис 22 76\n",
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"2 Виктор 23 95\n",
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"3 Галина 24 82\n",
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"<class 'pandas.core.frame.DataFrame'>\n",
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"RangeIndex: 4 entries, 0 to 3\n",
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"Data columns (total 3 columns):\n",
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" # Column Non-Null Count Dtype \n",
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"--- ------ -------------- ----- \n",
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" 0 Имя 4 non-null object\n",
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" 1 Возраст 4 non-null int64 \n",
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" 2 Баллы 4 non-null int64 \n",
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"dtypes: int64(2), object(1)\n",
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"memory usage: 228.0+ bytes\n",
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"None\n",
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" Возраст Баллы\n",
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"count 4.000000 4.000000\n",
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"mean 22.500000 85.500000\n",
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"std 1.290994 8.266398\n",
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"min 21.000000 76.000000\n",
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"25% 21.750000 80.500000\n",
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"50% 22.500000 85.500000\n",
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"75% 23.250000 90.500000\n",
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"max 24.000000 95.000000\n",
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"Имя 0\n",
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"Возраст 0\n",
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"Баллы 0\n",
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"dtype: int64\n"
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]
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}
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],
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"source": [
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"import pandas as pd\n",
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"\n",
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"# Создадим DataFrame\n",
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"data = {\n",
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" \"Имя\": [\"Анна\", \"Борис\", \"Виктор\", \"Галина\"],\n",
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" \"Возраст\": [21, 22, 23, 24],\n",
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" \"Баллы\": [89, 76, 95, 82]\n",
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"}\n",
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"df = pd.DataFrame(data)\n",
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"\n",
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"print(\"Первый взгляд на данные:\")\n",
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"print(df.head())\n",
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"print(df.info())\n",
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"print(df.describe())\n",
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"print(df.isnull().sum())"
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]
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},
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{
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"cell_type": "markdown",
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"id": "22288d55-04b9-4e80-8120-2da41b1a32b0",
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"metadata": {},
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"source": [
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"стандартный код, без изменений"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "4d8c96fc-1e83-4218-a96b-81575c28f0d7",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Первый взгляд на данные:\n",
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" Имя Возраст Баллы\n",
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"0 Анна 21 89\n",
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"1 Борис 22 76\n",
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"2 Виктор 23 95\n",
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"3 Галина 24 82\n",
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"<class 'pandas.core.frame.DataFrame'>\n",
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"RangeIndex: 4 entries, 0 to 3\n",
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"Data columns (total 3 columns):\n",
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" # Column Non-Null Count Dtype \n",
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"--- ------ -------------- ----- \n",
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" 0 Имя 4 non-null object\n",
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" 1 Возраст 4 non-null int64 \n",
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" 2 Баллы 4 non-null int64 \n",
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"dtypes: int64(2), object(1)\n",
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"memory usage: 228.0+ bytes\n",
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"None\n",
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" Возраст Баллы\n",
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"count 4.000000 4.000000\n",
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"mean 22.500000 85.500000\n",
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"std 1.290994 8.266398\n",
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"min 21.000000 76.000000\n",
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"25% 21.750000 80.500000\n",
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"50% 22.500000 85.500000\n",
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"75% 23.250000 90.500000\n",
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"max 24.000000 95.000000\n",
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"Имя 0\n",
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"Возраст 0\n",
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"Баллы 0\n",
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"dtype: int64\n"
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]
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},
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>Имя</th>\n",
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" <th>Возраст</th>\n",
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" <th>Баллы</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>Анна</td>\n",
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" <td>21</td>\n",
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" <td>89</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td>Борис</td>\n",
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" <td>22</td>\n",
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" <td>76</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td>Виктор</td>\n",
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" <td>23</td>\n",
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" <td>95</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td>Галина</td>\n",
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" <td>24</td>\n",
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" <td>82</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" Имя Возраст Баллы\n",
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"0 Анна 21 89\n",
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"1 Борис 22 76\n",
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"2 Виктор 23 95\n",
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"3 Галина 24 82"
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]
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},
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"execution_count": 2,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"import pandas as pd\n",
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"\n",
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"# Создадим DataFrame\n",
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"data = {\n",
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" \"Имя\": [\"Анна\", \"Борис\", \"Виктор\", \"Галина\"],\n",
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" \"Возраст\": [21, 22, 23, 24],\n",
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" \"Баллы\": [89, 76, 95, 82]\n",
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"}\n",
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"df = pd.DataFrame(data)\n",
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"\n",
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"print(\"Первый взгляд на данные:\")\n",
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"print(df.head())\n",
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"print(df.info())\n",
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"print(df.describe())\n",
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"print(df.isnull().sum())\n",
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"df"
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]
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},
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{
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"cell_type": "markdown",
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"id": "e2b6ea08-81e6-4e0d-a9b6-be6559349c7e",
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"metadata": {},
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"source": [
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"добавил df в конце кода"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"id": "b1361266-d103-4766-9337-c9afe7c1873f",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Первый взгляд на данные:\n",
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" Имя Возраст Баллы\n",
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"0 Анна 21 89\n",
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"1 Борис 22 76\n",
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"2 Виктор 23 95\n",
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"3 Галина 24 82\n",
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"<class 'pandas.core.frame.DataFrame'>\n",
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"RangeIndex: 4 entries, 0 to 3\n",
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"Data columns (total 3 columns):\n",
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" # Column Non-Null Count Dtype \n",
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"--- ------ -------------- ----- \n",
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" 0 Имя 4 non-null object\n",
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" 1 Возраст 4 non-null int64 \n",
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" 2 Баллы 4 non-null int64 \n",
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"dtypes: int64(2), object(1)\n",
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"memory usage: 228.0+ bytes\n",
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"None\n",
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" Возраст Баллы\n",
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"count 4.000000 4.000000\n",
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"mean 22.500000 85.500000\n",
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"std 1.290994 8.266398\n",
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"min 21.000000 76.000000\n",
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"25% 21.750000 80.500000\n",
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"50% 22.500000 85.500000\n",
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"75% 23.250000 90.500000\n",
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"max 24.000000 95.000000\n",
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"Имя 0\n",
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"Возраст 0\n",
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"Баллы 0\n",
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"dtype: int64\n",
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" Имя Возраст Баллы Баллы с коэффициентом\n",
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"0 Анна 21 89 97.9\n",
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"1 Борис 22 76 83.6\n",
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"2 Виктор 23 95 104.5\n",
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"3 Галина 24 82 90.2\n"
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]
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}
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],
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"source": [
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"import pandas as pd\n",
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"\n",
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"# Создадим DataFrame\n",
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"data = {\n",
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" \"Имя\": [\"Анна\", \"Борис\", \"Виктор\", \"Галина\"],\n",
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" \"Возраст\": [21, 22, 23, 24],\n",
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" \"Баллы\": [89, 76, 95, 82]\n",
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"}\n",
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"df = pd.DataFrame(data)\n",
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"\n",
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"print(\"Первый взгляд на данные:\")\n",
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"print(df.head())\n",
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"print(df.info())\n",
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"print(df.describe())\n",
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"print(df.isnull().sum())\n",
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"\n",
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"# Добавляем новый столбец с вычисляемыми значениями\n",
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"df[\"Баллы с коэффициентом\"] = df[\"Баллы\"] * 1.1\n",
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"\n",
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"print(df)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "5d658850-1ef4-41cc-81c2-afda9213bd6d",
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"metadata": {},
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"source": [
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"добавил новый столбец с вычисляемыми значениями"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "d27ebb99-d8b7-44b6-9d6f-59062c18eb81",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.13.2"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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