AIM-PIbd-32-kuznetsov-A-V/lab_1/lab1.ipynb

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2024-10-28 13:36:23 +04:00
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Лабораторная работа 1\n",
"Мониторинг акций Ямана Голд Инк"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='Date', ylabel='Volume'>"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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"text/plain": [
"<Figure size 3000x400 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"\n",
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"from datetime import date\n",
"\n",
"df = pd.read_csv(\".//static//csv//Yamana_Gold_Inc._AUY.csv\")\n",
"\n",
"viborka = df.groupby(df.index // 500).head(1)\n",
"viborka.plot.scatter(x=\"Date\", y=\"Volume\", figsize=(30, 4))\n",
"# Диаграмма объема каждые 2 года:"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
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"text/plain": [
"<Figure size 1500x1500 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"df_subset = df.groupby(df.index // 1000).head(1)\n",
"\n",
"value_counts = df_subset['Volume'].value_counts()\n",
"year = df_subset[\"Date\"]\n",
"\n",
"plt.figure(figsize=(15, 15))\n",
"plt.pie(\n",
" df_subset[\"Volume\"],\n",
" labels= df_subset[\"Date\"], # type: ignore\n",
" autopct=\"%1.1f%%\", rotatelabels=True\n",
")\n",
"plt.show()\n",
"#Сравнение объема продаж каждые 4 года:"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='Date'>"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from sqlite3 import Date\n",
"\n",
"#Цены открытия и закрытия за последние 5 дней\n",
"df.tail(5).plot(x=\"Date\", y=[\"Open\", \"Close\"])"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "aisenv",
"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
}