{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "## Начало лабораборной\n", "\n", "Выгрузка данных из csv файла в датафрейм" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Index(['gender', 'race/ethnicity', 'parental level of education', 'lunch',\n", " 'test preparation course', 'math score', 'reading score',\n", " 'writing score'],\n", " dtype='object')\n" ] } ], "source": [ "import pandas as pd\n", "\n", "df = pd.read_csv(\"..//..//static//csv//StudentsPerformance.csv\")\n", "print (df.columns)" ] } ], "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": "3.12.6" } }, "nbformat": 4, "nbformat_minor": 2 }