diff --git a/week2_analysis.ipynb b/week2_analysis.ipynb new file mode 100644 index 0000000..ee61670 --- /dev/null +++ b/week2_analysis.ipynb @@ -0,0 +1,153 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "id": "6ea73c34-1679-48e5-a566-8b1f4cea9652", + "metadata": {}, + "outputs": [], + "source": [ + "# Анализ данных - Неделя 2\n", + "**Автор:** Александр Писцов \n", + "Этот блокнот содержит базовый анализ с pandas и matplotlib." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "4b73c60f-cd31-402a-b3a8-97e9fa0eacb7", + "metadata": {}, + "outputs": [ + { + "ename": "ModuleNotFoundError", + "evalue": "No module named 'pandas'", + "output_type": "error", + "traceback": [ + "\u001b[31m---------------------------------------------------------------------------\u001b[39m", + "\u001b[31mModuleNotFoundError\u001b[39m Traceback (most recent call last)", + "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[3]\u001b[39m\u001b[32m, line 1\u001b[39m\n\u001b[32m----> \u001b[39m\u001b[32m1\u001b[39m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mpandas\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mas\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mpd\u001b[39;00m\n\u001b[32m 3\u001b[39m \u001b[38;5;66;03m# Создаем таблицу\u001b[39;00m\n\u001b[32m 4\u001b[39m data = {\n\u001b[32m 5\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mИмя\u001b[39m\u001b[33m\"\u001b[39m: [\u001b[33m\"\u001b[39m\u001b[33mАнна\u001b[39m\u001b[33m\"\u001b[39m, \u001b[33m\"\u001b[39m\u001b[33mБорис\u001b[39m\u001b[33m\"\u001b[39m, \u001b[33m\"\u001b[39m\u001b[33mВиктор\u001b[39m\u001b[33m\"\u001b[39m, \u001b[33m\"\u001b[39m\u001b[33mГалина\u001b[39m\u001b[33m\"\u001b[39m],\n\u001b[32m 6\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mВозраст\u001b[39m\u001b[33m\"\u001b[39m: [\u001b[32m21\u001b[39m, \u001b[32m22\u001b[39m, \u001b[32m23\u001b[39m, \u001b[32m24\u001b[39m],\n\u001b[32m 7\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mБаллы\u001b[39m\u001b[33m\"\u001b[39m: [\u001b[32m89\u001b[39m, \u001b[32m76\u001b[39m, \u001b[32m95\u001b[39m, \u001b[32m82\u001b[39m]\n\u001b[32m 8\u001b[39m }\n", + "\u001b[31mModuleNotFoundError\u001b[39m: No module named 'pandas'" + ] + } + ], + "source": [ + "import pandas as pd\n", + "\n", + "# Создаем таблицу\n", + "data = {\n", + " \"Имя\": [\"Анна\", \"Борис\", \"Виктор\", \"Галина\"],\n", + " \"Возраст\": [21, 22, 23, 24],\n", + " \"Баллы\": [89, 76, 95, 82]\n", + "}\n", + "df = pd.DataFrame(data)\n", + "\n", + "# Добавляем столбец\n", + "df[\"Бонусные баллы\"] = df[\"Баллы\"] * 1.1\n", + "df" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "c2e25c6c-bbda-4bb7-8b27-56579b481174", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Произведение матриц:\n", + " [[ 7 10]\n", + " [15 22]]\n" + ] + } + ], + "source": [ + "import numpy as np\n", + "\n", + "# Создаем матрицу 2x2\n", + "matrix = np.array([[1, 2], [3, 4]])\n", + "print(\"Произведение матриц:\\n\", np.dot(matrix, matrix))" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "d8412aa4-fb69-4da4-9d5e-ce6e1924c7ae", + "metadata": {}, + "outputs": [ + { + "ename": "ModuleNotFoundError", + "evalue": "No module named 'matplotlib'", + "output_type": "error", + "traceback": [ + "\u001b[31m---------------------------------------------------------------------------\u001b[39m", + "\u001b[31mModuleNotFoundError\u001b[39m Traceback (most recent call last)", + "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[2]\u001b[39m\u001b[32m, line 1\u001b[39m\n\u001b[32m----> \u001b[39m\u001b[32m1\u001b[39m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mmatplotlib\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01mpyplot\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mas\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mplt\u001b[39;00m\n\u001b[32m 3\u001b[39m plt.figure(figsize=(\u001b[32m8\u001b[39m, \u001b[32m4\u001b[39m))\n\u001b[32m 4\u001b[39m plt.bar(df[\u001b[33m\"\u001b[39m\u001b[33mИмя\u001b[39m\u001b[33m\"\u001b[39m], df[\u001b[33m\"\u001b[39m\u001b[33mБаллы\u001b[39m\u001b[33m\"\u001b[39m], color=\u001b[33m'\u001b[39m\u001b[33mskyblue\u001b[39m\u001b[33m'\u001b[39m)\n", + "\u001b[31mModuleNotFoundError\u001b[39m: No module named 'matplotlib'" + ] + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "plt.figure(figsize=(8, 4))\n", + "plt.bar(df[\"Имя\"], df[\"Баллы\"], color='skyblue')\n", + "plt.title(\"Баллы студентов\")\n", + "plt.xlabel(\"Имя\")\n", + "plt.ylabel(\"Баллы\")\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2b5c128b-f9a8-408e-b128-6360630b4f9f", + "metadata": {}, + "outputs": [], + "source": [ + "import seaborn as sns\n", + "\n", + "sns.scatterplot(data=df, x=\"Возраст\", y=\"Баллы\", hue=\"Имя\", s=100)\n", + "plt.title(\"Зависимость баллов от возраста\")\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "652d456d-8a78-40a2-84ea-b76caf74224f", + "metadata": {}, + "outputs": [], + "source": [ + "from tqdm import tqdm\n", + "import time\n", + "\n", + "print(\"Обработка данных:\")\n", + "for i in tqdm(range(100), desc=\"Прогресс\"):\n", + " time.sleep(0.02) # Имитация работы" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "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": "3.11.9" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +}