{ "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)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "RangeIndex: 1000 entries, 0 to 999\n", "Data columns (total 8 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 gender 1000 non-null object\n", " 1 race/ethnicity 1000 non-null object\n", " 2 parental level of education 1000 non-null object\n", " 3 lunch 1000 non-null object\n", " 4 test preparation course 1000 non-null object\n", " 5 math score 1000 non-null int64 \n", " 6 reading score 1000 non-null int64 \n", " 7 writing score 1000 non-null int64 \n", "dtypes: int64(3), object(5)\n", "memory usage: 62.6+ KB\n" ] } ], "source": [ "df.info()" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " count mean std min 25% 50% 75% max\n", "math score 1000.0 66.089 15.163080 0.0 57.00 66.0 77.0 100.0\n", "reading score 1000.0 69.169 14.600192 17.0 59.00 70.0 79.0 100.0\n", "writing score 1000.0 68.054 15.195657 10.0 57.75 69.0 79.0 100.0\n" ] } ], "source": [ "print(df.describe().transpose())" ] } ], "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 }