2024-09-13 17:40:03 +04:00
|
|
|
{
|
|
|
|
|
"cells": [
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "markdown",
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"source": [
|
|
|
|
|
"Выгружаем данные при помощи Pandas из csv файла в количестве 10000 строк."
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
|
|
|
|
"execution_count": 4,
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"outputs": [],
|
|
|
|
|
"source": [
|
|
|
|
|
"import pandas as pd\n",
|
|
|
|
|
"import matplotlib.pyplot as plt\n",
|
|
|
|
|
"\n",
|
|
|
|
|
"df = pd.read_csv(\"data/age.csv\", nrows=10000)\n"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "markdown",
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"source": [
|
|
|
|
|
"Смотрим количество и название столбцов таблицы"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
|
|
|
|
"execution_count": 40,
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"outputs": [
|
|
|
|
|
{
|
|
|
|
|
"name": "stdout",
|
|
|
|
|
"output_type": "stream",
|
|
|
|
|
"text": [
|
|
|
|
|
"<class 'pandas.core.frame.DataFrame'>\n",
|
|
|
|
|
"Index: 12359 entries, 0 to 9999\n",
|
|
|
|
|
"Data columns (total 10 columns):\n",
|
|
|
|
|
" # Column Non-Null Count Dtype \n",
|
|
|
|
|
"--- ------ -------------- ----- \n",
|
|
|
|
|
" 0 Id 12359 non-null object \n",
|
|
|
|
|
" 1 Name 12359 non-null object \n",
|
|
|
|
|
" 2 Short description 12354 non-null object \n",
|
|
|
|
|
" 3 Gender 12273 non-null object \n",
|
|
|
|
|
" 4 Country 12080 non-null object \n",
|
|
|
|
|
" 5 Occupation 12188 non-null object \n",
|
|
|
|
|
" 6 Birth year 12359 non-null int64 \n",
|
|
|
|
|
" 7 Death year 12358 non-null float64\n",
|
|
|
|
|
" 8 Manner of death 2486 non-null object \n",
|
|
|
|
|
" 9 Age of death 12358 non-null float64\n",
|
|
|
|
|
"dtypes: float64(2), int64(1), object(7)\n",
|
|
|
|
|
"memory usage: 1.0+ MB\n",
|
|
|
|
|
" count mean std min 25% 50% \\\n",
|
|
|
|
|
"Birth year 12359.0 1773.275993 298.845499 -2284.0 1787.0 1870.0 \n",
|
|
|
|
|
"Death year 12358.0 1840.944813 303.842150 -2200.0 1853.0 1938.0 \n",
|
|
|
|
|
"Age of death 12358.0 67.686519 17.137864 4.0 57.0 70.0 \n",
|
|
|
|
|
"\n",
|
|
|
|
|
" 75% max \n",
|
|
|
|
|
"Birth year 1905.0 1996.0 \n",
|
|
|
|
|
"Death year 1979.0 2021.0 \n",
|
|
|
|
|
"Age of death 80.0 107.0 \n"
|
|
|
|
|
]
|
|
|
|
|
}
|
|
|
|
|
],
|
|
|
|
|
"source": [
|
|
|
|
|
"print(df.describe().transpose())"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "markdown",
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"source": [
|
|
|
|
|
"Узнаем количество людей относящихся к той или иной стране"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
2024-09-13 17:47:57 +04:00
|
|
|
"execution_count": 12,
|
2024-09-13 17:40:03 +04:00
|
|
|
"metadata": {},
|
|
|
|
|
"outputs": [
|
|
|
|
|
{
|
|
|
|
|
"data": {
|
2024-09-13 17:47:57 +04:00
|
|
|
"image/png": "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
|
2024-09-13 17:40:03 +04:00
|
|
|
"text/plain": [
|
|
|
|
|
"<Figure size 640x480 with 1 Axes>"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"output_type": "display_data"
|
|
|
|
|
}
|
|
|
|
|
],
|
|
|
|
|
"source": [
|
|
|
|
|
"df['Country'] = df['Country'].str.split('; ')\n",
|
|
|
|
|
"df1 = df.explode('Country')\n",
|
|
|
|
|
"countrys = df1.groupby(\"Country\").size().reset_index(name=\"Count\") # type: ignore\n",
|
|
|
|
|
"country_counts_sorted = countrys.sort_values(by='Count', ascending=False)\n",
|
|
|
|
|
"top_countries = country_counts_sorted.head(50)\n",
|
|
|
|
|
"\n",
|
|
|
|
|
"top_countries.plot.bar(x='Country', y='Count', color=['green'])\n",
|
|
|
|
|
"plt.title('Top Countries by count of people')\n",
|
|
|
|
|
"plt.xlabel('Country')\n",
|
|
|
|
|
"plt.ylabel('Number of People')\n",
|
|
|
|
|
"plt.show()"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "markdown",
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"source": [
|
|
|
|
|
"Длительность жизни по полу"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
|
|
|
|
"execution_count": 11,
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"outputs": [
|
|
|
|
|
{
|
|
|
|
|
"data": {
|
|
|
|
|
"image/png": "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
|
|
|
|
|
"text/plain": [
|
|
|
|
|
"<Figure size 640x480 with 1 Axes>"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"output_type": "display_data"
|
|
|
|
|
}
|
|
|
|
|
],
|
|
|
|
|
"source": [
|
|
|
|
|
"dfgender = df[df['Gender'].isin(['Male', 'Female'])]\n",
|
2024-09-13 17:47:57 +04:00
|
|
|
"dfgender[0:1000].boxplot(column='Age of death', by='Gender')\n",
|
2024-09-13 17:40:03 +04:00
|
|
|
"plt.title('Lifespan by Gender')\n",
|
|
|
|
|
"plt.suptitle('') # Убираем автоматический заголовок\n",
|
|
|
|
|
"plt.xlabel('Gender')\n",
|
|
|
|
|
"plt.ylabel('Lifespan')\n",
|
|
|
|
|
"plt.show()"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "markdown",
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"source": [
|
|
|
|
|
"Количество людей родившихся в тот или иной год"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
|
|
|
|
"execution_count": 10,
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"outputs": [
|
|
|
|
|
{
|
|
|
|
|
"data": {
|
|
|
|
|
"text/plain": [
|
|
|
|
|
"<Axes: ylabel='Frequency'>"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
"execution_count": 10,
|
|
|
|
|
"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 matplotlib.pyplot import xlim\n",
|
|
|
|
|
"\n",
|
|
|
|
|
"\n",
|
|
|
|
|
"df.plot.hist(column=[\"Birth year\"], xlim=(1900, 2000), bins=4000)"
|
|
|
|
|
]
|
|
|
|
|
}
|
|
|
|
|
],
|
|
|
|
|
"metadata": {
|
|
|
|
|
"kernelspec": {
|
|
|
|
|
"display_name": ".venv",
|
|
|
|
|
"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": "3.12.5"
|
|
|
|
|
}
|
|
|
|
|
},
|
|
|
|
|
"nbformat": 4,
|
|
|
|
|
"nbformat_minor": 2
|
|
|
|
|
}
|
