AIM-PIbd-32-Smirnov-A-A/lab1/lab1.ipynb
2024-10-26 13:38:50 +04:00

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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Начало лабораторной \n",
"\n",
"Выгрузка данных из csv файла в датафрейм"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Index(['ID', 'Year_Birth', 'Education', 'Marital_Status', 'Income', 'Kidhome',\n",
" 'Teenhome', 'Dt_Customer', 'Recency', 'MntWines', 'MntFruits',\n",
" 'MntMeatProducts', 'MntFishProducts', 'MntSweetProducts',\n",
" 'MntGoldProds', 'NumDealsPurchases', 'NumWebPurchases',\n",
" 'NumCatalogPurchases', 'NumStorePurchases', 'NumWebVisitsMonth',\n",
" 'AcceptedCmp3', 'AcceptedCmp4', 'AcceptedCmp5', 'AcceptedCmp1',\n",
" 'AcceptedCmp2', 'Complain', 'Z_CostContact', 'Z_Revenue', 'Response'],\n",
" dtype='object')\n"
]
}
],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"\n",
"df = pd.read_csv(\"..//..//static//csv//marketing_campaign.csv\", sep=\"\\t\")\n",
"\n",
"print (df.columns)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Эта гистограмма в диапазоне с "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"df "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Out "
]
}
],
"metadata": {
"kernelspec": {
"display_name": "aimenv",
"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": "3.12.7"
}
},
"nbformat": 4,
"nbformat_minor": 2
}