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{
"cells": [
{
"cell_type": "markdown",
"id": "c3968b76-b939-4c1c-9b84-29e51f8ae69f",
"metadata": {},
"source": [
"# Statystyki miliarderów\n",
"**Zbiór danych zawiera statystyki dotyczące miliarderów na świecie, zawarte są również ich dane osobowe, branże którymi się zajmują oraz firmy.**\n",
"\n",
"[Źródło](https://www.kaggle.com/datasets/nelgiriyewithana/billionaires-statistics-dataset)"
]
},
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{
"cell_type": "markdown",
"id": "79451718",
"metadata": {},
"source": [
"# Potencjalne wykresy\n",
"* Analiza rozkładu majątku: Zbadanie rozkład majątku miliarderów w różnych branżach, krajach i regionach.\n",
"\n",
"* Analiza demograficzna: Przedstawienie wieku, płeci i miejsca urodzenia miliarderów.\n",
"\n",
"* Samodzielnie wytworzone vs. odziedziczone bogactwo: Analiza odseteku samodzielnie stworzonych miliarderów i tych, którzy odziedziczyli swój majątek.\n",
"\n",
"* Wskaźniki ekonomiczne: Zbadanie korelacji między bogactwem miliarderów a wskaźnikami ekonomicznymi, takimi jak PKB, CPI (wskaźnik cen towarów i usług) i stawki podatkowe.\n",
"\n",
"* Analiza geoprzestrzenna: Wizualizacja geograficznego rozmieszczenia miliarderów i ich majątku na mapie.\n",
"\n",
"* Trendy w czasie: Prześledzenie zmian demograficznych i majątkowych miliarderów na przestrzeni lat.\n",
"\n"
]
},
{
"cell_type": "markdown",
"id": "081ecfe0",
"metadata": {},
"source": [
"# Wykresy testowe oraz przedstawienie zbioru danych"
]
},
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{
"cell_type": "code",
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"execution_count": 2,
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"id": "cb8f7a05-40a5-46cf-8900-88da58e8690f",
"metadata": {},
"outputs": [],
"source": [
"import numpy as np # linear algebra\n",
"import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
"import seaborn as sns\n",
"import matplotlib.pyplot as plt\n",
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"import matplotlib.image as mpimg\n",
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"from matplotlib.ticker import FormatStrFormatter, StrMethodFormatter\n",
"plt.style.use('ggplot')"
]
},
{
"cell_type": "code",
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"execution_count": 3,
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"id": "5a5c0cd6-6606-4983-b945-eeed8b5afe24",
"metadata": {},
"outputs": [],
"source": [
"df = pd.read_csv('data.csv')"
]
},
{
"cell_type": "code",
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"execution_count": 4,
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"id": "4b91bc35-5308-49fc-954e-dc278d133c36",
"metadata": {},
"outputs": [
{
"data": {
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"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
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" }\n",
"\n",
" .dataframe thead th {\n",
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" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>rank</th>\n",
" <th>finalWorth</th>\n",
" <th>category</th>\n",
" <th>personName</th>\n",
" <th>age</th>\n",
" <th>country</th>\n",
" <th>city</th>\n",
" <th>source</th>\n",
" <th>industries</th>\n",
" <th>countryOfCitizenship</th>\n",
" <th>...</th>\n",
" <th>cpi_change_country</th>\n",
" <th>gdp_country</th>\n",
" <th>gross_tertiary_education_enrollment</th>\n",
" <th>gross_primary_education_enrollment_country</th>\n",
" <th>life_expectancy_country</th>\n",
" <th>tax_revenue_country_country</th>\n",
" <th>total_tax_rate_country</th>\n",
" <th>population_country</th>\n",
" <th>latitude_country</th>\n",
" <th>longitude_country</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1</td>\n",
" <td>211000</td>\n",
" <td>Fashion & Retail</td>\n",
" <td>Bernard Arnault & family</td>\n",
" <td>74.0</td>\n",
" <td>France</td>\n",
" <td>Paris</td>\n",
" <td>LVMH</td>\n",
" <td>Fashion & Retail</td>\n",
" <td>France</td>\n",
" <td>...</td>\n",
" <td>1.1</td>\n",
" <td>$2,715,518,274,227</td>\n",
" <td>65.6</td>\n",
" <td>102.5</td>\n",
" <td>82.5</td>\n",
" <td>24.2</td>\n",
" <td>60.7</td>\n",
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" <td>67059887.0</td>\n",
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" <td>46.227638</td>\n",
" <td>2.213749</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2</td>\n",
" <td>180000</td>\n",
" <td>Automotive</td>\n",
" <td>Elon Musk</td>\n",
" <td>51.0</td>\n",
" <td>United States</td>\n",
" <td>Austin</td>\n",
" <td>Tesla, SpaceX</td>\n",
" <td>Automotive</td>\n",
" <td>United States</td>\n",
" <td>...</td>\n",
" <td>7.5</td>\n",
" <td>$21,427,700,000,000</td>\n",
" <td>88.2</td>\n",
" <td>101.8</td>\n",
" <td>78.5</td>\n",
" <td>9.6</td>\n",
" <td>36.6</td>\n",
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" <td>328239523.0</td>\n",
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" <td>37.090240</td>\n",
" <td>-95.712891</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>3</td>\n",
" <td>114000</td>\n",
" <td>Technology</td>\n",
" <td>Jeff Bezos</td>\n",
" <td>59.0</td>\n",
" <td>United States</td>\n",
" <td>Medina</td>\n",
" <td>Amazon</td>\n",
" <td>Technology</td>\n",
" <td>United States</td>\n",
" <td>...</td>\n",
" <td>7.5</td>\n",
" <td>$21,427,700,000,000</td>\n",
" <td>88.2</td>\n",
" <td>101.8</td>\n",
" <td>78.5</td>\n",
" <td>9.6</td>\n",
" <td>36.6</td>\n",
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" <td>328239523.0</td>\n",
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" <td>37.090240</td>\n",
" <td>-95.712891</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>4</td>\n",
" <td>107000</td>\n",
" <td>Technology</td>\n",
" <td>Larry Ellison</td>\n",
" <td>78.0</td>\n",
" <td>United States</td>\n",
" <td>Lanai</td>\n",
" <td>Oracle</td>\n",
" <td>Technology</td>\n",
" <td>United States</td>\n",
" <td>...</td>\n",
" <td>7.5</td>\n",
" <td>$21,427,700,000,000</td>\n",
" <td>88.2</td>\n",
" <td>101.8</td>\n",
" <td>78.5</td>\n",
" <td>9.6</td>\n",
" <td>36.6</td>\n",
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" <td>328239523.0</td>\n",
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" <td>37.090240</td>\n",
" <td>-95.712891</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>5</td>\n",
" <td>106000</td>\n",
" <td>Finance & Investments</td>\n",
" <td>Warren Buffett</td>\n",
" <td>92.0</td>\n",
" <td>United States</td>\n",
" <td>Omaha</td>\n",
" <td>Berkshire Hathaway</td>\n",
" <td>Finance & Investments</td>\n",
" <td>United States</td>\n",
" <td>...</td>\n",
" <td>7.5</td>\n",
" <td>$21,427,700,000,000</td>\n",
" <td>88.2</td>\n",
" <td>101.8</td>\n",
" <td>78.5</td>\n",
" <td>9.6</td>\n",
" <td>36.6</td>\n",
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" <td>328239523.0</td>\n",
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" <td>37.090240</td>\n",
" <td>-95.712891</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
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"<p>5 rows ×
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"</div>"
],
"text/plain": [
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" rank finalWorth category personName age \\\n",
"0 1 211000 Fashion & Retail Bernard Arnault & family 74.0 \n",
"1 2 180000 Automotive Elon Musk 51.0 \n",
"2 3 114000 Technology Jeff Bezos 59.0 \n",
"3 4 107000 Technology Larry Ellison 78.0 \n",
"4 5 106000 Finance & Investments Warren Buffett 92.0 \n",
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"\n",
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" country city source industries \\\n",
"0 France Paris LVMH Fashion & Retail \n",
"1 United States Austin Tesla, SpaceX Automotive \n",
"2 United States Medina Amazon Technology \n",
"3 United States Lanai Oracle Technology \n",
"4 United States Omaha Berkshire Hathaway Finance & Investments \n",
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"\n",
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" countryOfCitizenship ... cpi_change_country gdp_country \\\n",
"0 France ... 1.1 $2,715,518,274,227 \n",
"1 United States ... 7.5 $21,427,700,000,000 \n",
"2 United States ... 7.5 $21,427,700,000,000 \n",
"3 United States ... 7.5 $21,427,700,000,000 \n",
"4 United States ... 7.5 $21,427,700,000,000 \n",
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"\n",
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" gross_tertiary_education_enrollment \\\n",
"0 65.6 \n",
"1 88.2 \n",
"2 88.2 \n",
"3 88.2 \n",
"4 88.2 \n",
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"\n",
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" gross_primary_education_enrollment_country life_expectancy_country \\\n",
"0 102.5 82.5 \n",
"1 101.8 78.5 \n",
"2 101.8 78.5 \n",
"3 101.8 78.5 \n",
"4 101.8 78.5 \n",
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"\n",
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" tax_revenue_country_country total_tax_rate_country population_country \\\n",
"0 24.2 60.7 67059887.0 \n",
"1 9.6 36.6 328239523.0 \n",
"2 9.6 36.6 328239523.0 \n",
"3 9.6 36.6 328239523.0 \n",
"4 9.6 36.6 328239523.0 \n",
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"\n",
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" latitude_country longitude_country \n",
"0 46.227638 2.213749 \n",
"1 37.090240 -95.712891 \n",
"2 37.090240 -95.712891 \n",
"3 37.090240 -95.712891 \n",
"4 37.090240 -95.712891 \n",
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"\n",
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"[5 rows x 35 columns]"
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]
},
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"execution_count": 4,
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"metadata": {},
"output_type": "execute_result"
}
],
"source": [
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"df.head()"
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]
},
{
"cell_type": "code",
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"execution_count": 20,
"id": "30486a19",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 2640 entries, 0 to 2639\n",
"Data columns (total 35 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 rank 2640 non-null int64 \n",
" 1 finalWorth 2640 non-null int64 \n",
" 2 category 2640 non-null object \n",
" 3 personName 2640 non-null object \n",
" 4 age 2575 non-null float64\n",
" 5 country 2602 non-null object \n",
" 6 city 2568 non-null object \n",
" 7 source 2640 non-null object \n",
" 8 industries 2640 non-null object \n",
" 9 countryOfCitizenship 2640 non-null object \n",
" 10 organization 325 non-null object \n",
" 11 selfMade 2640 non-null bool \n",
" 12 status 2640 non-null object \n",
" 13 gender 2640 non-null object \n",
" 14 birthDate 2564 non-null object \n",
" 15 lastName 2640 non-null object \n",
" 16 firstName 2637 non-null object \n",
" 17 title 339 non-null object \n",
" 18 date 2640 non-null object \n",
" 19 state 753 non-null object \n",
" 20 residenceStateRegion 747 non-null object \n",
" 21 birthYear 2564 non-null float64\n",
" 22 birthMonth 2564 non-null float64\n",
" 23 birthDay 2564 non-null float64\n",
" 24 cpi_country 2456 non-null float64\n",
" 25 cpi_change_country 2456 non-null float64\n",
" 26 gdp_country 2476 non-null object \n",
" 27 gross_tertiary_education_enrollment 2458 non-null float64\n",
" 28 gross_primary_education_enrollment_country 2459 non-null float64\n",
" 29 life_expectancy_country 2458 non-null float64\n",
" 30 tax_revenue_country_country 2457 non-null float64\n",
" 31 total_tax_rate_country 2458 non-null float64\n",
" 32 population_country 2476 non-null float64\n",
" 33 latitude_country 2476 non-null float64\n",
" 34 longitude_country 2476 non-null float64\n",
"dtypes: bool(1), float64(14), int64(2), object(18)\n",
"memory usage: 704.0+ KB\n"
]
}
],
"source": [
"df.info()"
]
},
{
"cell_type": "code",
"execution_count": 5,
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"id": "165adea3-3cf5-44e7-9555-2dbebd7b824c",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"rank 0\n",
"finalWorth 0\n",
"category 0\n",
"personName 0\n",
"age 65\n",
"country 38\n",
"city 72\n",
"source 0\n",
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"organization 2315\n",
"selfMade 0\n",
"status 0\n",
"gender 0\n",
"birthDate 76\n",
"lastName 0\n",
"firstName 3\n",
"title 2301\n",
"date 0\n",
"state 1887\n",
"residenceStateRegion 1893\n",
"birthYear 76\n",
"birthMonth 76\n",
"birthDay 76\n",
"cpi_country 184\n",
"cpi_change_country 184\n",
"gdp_country 164\n",
"gross_tertiary_education_enrollment 182\n",
"gross_primary_education_enrollment_country 181\n",
"life_expectancy_country 182\n",
"tax_revenue_country_country 183\n",
"total_tax_rate_country 182\n",
"population_country 164\n",
"latitude_country 164\n",
"longitude_country 164\n",
"dtype: int64"
]
},
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"execution_count": 5,
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"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.isnull().sum()"
]
},
{
"cell_type": "code",
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"execution_count": 6,
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"id": "603f6bb5-366d-4978-bafd-c260983caace",
"metadata": {},
"outputs": [
{
"data": {
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"image/png": "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"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"ax = sns.barplot(df.head(10), x='finalWorth',y='personName', hue = 'personName', legend = False,orient='h', palette='rainbow')\n",
"ax.set_title('Najbardziej majętne osoby')\n",
"ax.set_xlabel('Osoba')\n",
"ax.set_ylabel('Majątek')\n",
"for container in ax.containers:\n",
" ax.bar_label(container, fontsize=8)\n",
"plt.show()"
]
},
{
"cell_type": "code",
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"execution_count": 7,
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"id": "d9aa8a3c-4bed-48d3-87db-2356f44b381c",
"metadata": {},
"outputs": [],
"source": [
"ppl_in_countries = df.groupby('countryOfCitizenship')['rank'].count().reset_index().sort_values(by ='rank',ascending=False).head(20)"
]
},
{
"cell_type": "code",
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"execution_count": 8,
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"id": "7c9dbf33-76b6-4f7b-a355-d81e352d7859",
"metadata": {},
"outputs": [
{
"data": {
2024-04-09 21:36:47 +02:00
"image/png": "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
2024-04-09 19:53:24 +02:00
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"ax = sns.barplot(ppl_in_countries,x='rank',y='countryOfCitizenship',orient='h',hue = 'countryOfCitizenship', legend = False, palette='rainbow')\n",
"ax.set_title('Kraj z największą liczbą miliarderów')\n",
"ax.set_ylabel('Kraje')\n",
"ax.set_xlabel('Liczba milarderów')\n",
"for container in ax.containers:\n",
" ax.bar_label(container, fontsize=8)\n",
"plt.show()"
]
},
{
"cell_type": "code",
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"execution_count": 9,
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"id": "dc6c894e-3e60-491b-a7d0-16e434f8a4eb",
"metadata": {},
"outputs": [],
"source": [
"age_and_wealthy = df.groupby('age')['finalWorth'].mean()"
]
},
{
"cell_type": "code",
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"execution_count": 10,
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"id": "4f4918b6-0296-4f5a-8dec-7a65f7653777",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"age\n",
"18.0 3500.000000\n",
"19.0 1700.000000\n",
"20.0 2300.000000\n",
"21.0 2600.000000\n",
"26.0 1450.000000\n",
" ... \n",
"96.0 4366.666667\n",
"97.0 1425.000000\n",
"98.0 1750.000000\n",
"99.0 4375.000000\n",
"101.0 1300.000000\n",
"Name: finalWorth, Length: 79, dtype: float64"
]
},
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"execution_count": 10,
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"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"age_and_wealthy"
]
},
{
"cell_type": "code",
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"execution_count": 11,
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"id": "c97d5224-9a5b-4563-a618-5333e0e15625",
"metadata": {},
"outputs": [
{
"data": {
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"image/png": "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"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.lineplot(df, x='age', y='finalWorth',errorbar=None)\n",
"plt.show()"
]
},
{
"cell_type": "code",
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"execution_count": 12,
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"id": "8a71ce98-835a-4974-8edf-ceeb9ec5e2a7",
"metadata": {},
"outputs": [],
"source": [
"#category = df.explode('category')\n",
"categories = df.groupby('category')['rank'].count().sort_values(ascending=False).reset_index().head(20)\n"
]
},
{
"cell_type": "code",
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"execution_count": 13,
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"id": "4f6a6b8a-f111-4592-b187-9e801cdffa63",
"metadata": {},
"outputs": [
{
"data": {
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"image/png": "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"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"ax = sns.barplot(categories,x='rank',y='category',orient='h',hue = 'category', legend = False, palette='rainbow')\n",
"ax.set_title('Najpopularniejsze kategorie biznesu')\n",
"ax.set_ylabel('Kategoria')\n",
"ax.set_xlabel('Liczba osób')\n",
"for container in ax.containers:\n",
" ax.bar_label(container, fontsize=8)\n",
"plt.show()"
]
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},
{
"cell_type": "code",
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"execution_count": 14,
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"id": "b834c620",
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 800x600 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(8, 6))\n",
"df['category'].value_counts().plot(kind='pie', autopct='%1.1f%%')\n",
"plt.title('Billionaires by Industry')\n",
"plt.axis('equal')\n",
"plt.show()"
]
},
{
"cell_type": "code",
2024-04-10 09:38:37 +02:00
"execution_count": 15,
2024-04-09 21:36:47 +02:00
"id": "fc12442c",
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 1200x600 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"world_map = plt.figure(figsize=(12, 6))\n",
"ax = world_map.add_subplot(111)\n",
"df.groupby('country')['finalWorth'].sum().sort_values(ascending=False).head(10).plot(kind='bar', ax=ax)\n",
"plt.title('Top 10 Countries by Billionaire Wealth')\n",
"plt.xlabel('Country')\n",
"plt.ylabel('Total Wealth (USD)')\n",
"plt.xticks(rotation=90)\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"id": "5228fbaf",
"metadata": {},
"source": [
"# Przykładowe wykresy z internetu\n"
]
},
{
"cell_type": "code",
2024-04-10 09:38:37 +02:00
"execution_count": 19,
2024-04-09 21:36:47 +02:00
"id": "bf671c0e",
"metadata": {},
"outputs": [
{
"data": {
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"text/plain": [
"<Figure size 1500x800 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
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},
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{
"data": {
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"text/plain": [
"<Figure size 1500x800 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
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},
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{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 1500x800 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
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"for i in ['images/kraje.png', 'images/top.png', 'images/world.jpeg']:\n",
" imga = mpimg.imread(i)\n",
" plt.figure(figsize=(15,8))\n",
" imgplot = plt.imshow(imga)\n"
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]
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}
],
"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",
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"version": "3.11.8"
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}
},
"nbformat": 4,
"nbformat_minor": 5
}
