AIM-PIbd-32-Kurbanova-A-A/lab_1/lab_1.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Solarize_Light2', '_classic_test_patch', '_mpl-gallery', '_mpl-gallery-nogrid', 'bmh', 'classic', 'dark_background', 'fast', 'fivethirtyeight', 'ggplot', 'grayscale', 'seaborn-v0_8', 'seaborn-v0_8-bright', 'seaborn-v0_8-colorblind', 'seaborn-v0_8-dark', 'seaborn-v0_8-dark-palette', 'seaborn-v0_8-darkgrid', 'seaborn-v0_8-deep', 'seaborn-v0_8-muted', 'seaborn-v0_8-notebook', 'seaborn-v0_8-paper', 'seaborn-v0_8-pastel', 'seaborn-v0_8-poster', 'seaborn-v0_8-talk', 'seaborn-v0_8-ticks', 'seaborn-v0_8-white', 'seaborn-v0_8-whitegrid', 'tableau-colorblind10']\n"
     ]
    },
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1400x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from statsmodels.tsa.seasonal import seasonal_decompose\n",
    "\n",
    "from dateutil import parser\n",
    "\n",
    "from statsmodels.tsa.arima.model import ARIMA\n",
    "\n",
    "\n",
    "import matplotlib.dates as mdates\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "df = pd.read_csv('C:\\\\Users\\\\Алина\\\\source\\\\repos\\\\mii\\\\AIM-PIbd-32-Kurbanova-A-A\\\\static\\\\csv\\\\neo.csv')\n",
    "\n",
    "df['Date'] = pd.to_datetime(df['Date'])\n",
    "df.set_index('Date', inplace=True)\n",
    "# Checking available styles\n",
    "print(plt.style.available)\n",
    "\n",
    "plt.style.use('seaborn-v0_8-dark-palette')\n",
    "plt.figure(figsize=(14, 7))\n",
    "\n",
    "plt.plot(df['Close'], label='Closing Price')\n",
    "plt.title('Gold Closing Prices Over Time')\n",
    "plt.xlabel('Date')\n",
    "plt.ylabel('Closing Price')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Данная диаграмма отображает цену закрытия (Close Price), что позволяет сделать вывод о том, что  цена на золото с 2013 года до 2016 года стремительно снижалась, а после  держалась стабильно"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 2200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Boxplot of Stock Close Price per Month\n",
    "_, ax = plt.subplots(figsize=(22,8))\n",
    "sns.boxplot(x=df.index.month_name(), y= df.values[:, 0],ax=ax)\n",
    "plt.title('Stock Close Price per Month')\n",
    "plt.xlabel('Month')\n",
    "plt.ylabel('Close Price')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Данная диаграмма отображает цену закрытия(Close price) по месяцам,что позволяет сделать вывод о том, что в январе-марте цена на золота стабильнее, чем в другие месяцы; осенью и декаре цена на золото \"скачет\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt \n",
    "\n",
    "# Предполагаем, что df уже определен и содержит данные \n",
    "datal = df[:100].copy() \n",
    "\n",
    "plt.figure(figsize=(12, 6))\n",
    "plt.hist(datal['Close'], bins=30, color='skyblue', edgecolor='black')\n",
    "plt.title('Histogram of Gold Prices')\n",
    "plt.xlabel('Gold Close Price')\n",
    "plt.ylabel('Frequency')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Данная диаграмма отображает цену закрытия на золото на маленьком срезе данных, что позволяет сделать вывод о том, что цена нестабильна и быстро меняется"
   ]
  }
 ],
 "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
}