Contest

import pandas as pd
import matplotlib.pyplot as plt

# Leggi i dati demografici
demography_data = pd.read_csv(r'Contest StatLearning\population-and-demography.csv',delimiter=',')

plt.plot(demography_data['Year'], demography_data['Population'], )
plt.xlabel('Year')
plt.ylabel('Population')
plt.title('Italy Population, 1950 to 2021')
plt.grid(linestyle=':')
plt.show()

# Leggi i dati GDP per capita
gdp_data = pd.read_csv(r'Contest StatLearning\gdp-per-capita-maddison-2020.csv',delimiter=',')

plt.plot(gdp_data['Year'], gdp_data['GDP per capita'])
plt.xlabel('Year')
plt.ylabel('GDP per Capita ($)')
plt.title('GDP per Capita in Italy, 1900 to 2018')
plt.grid(linestyle=':')
plt.show()

# Leggi i dati GDP vs population density
density_data = pd.read_csv(r'Contest StatLearning\population-density-vs-prosperity.csv',delimiter=',')

plt.scatter(density_data['Year'], density_data['GDP per capita'], c=density_data['Population density'])
plt.colorbar(label='Number of people per km²')
plt.xlabel('Year')
plt.ylabel('GDP per Capita ($)')
plt.title('Population density and GDP per Capita Relationship, 1990 to 2020')
plt.grid(linestyle=':')
plt.show()

# Plotto tutti i grafici insieme
plt.plot(demography_data['Year'], demography_data['Population'])
plt.plot(gdp_data['Year'], gdp_data['GDP per capita'])
plt.scatter(density_data['Year'], density_data['GDP per capita'], c=density_data['Population density'])
plt.colorbar(label='Number of people per km²')
plt.xlabel('Year')
plt.title('All charts')
plt.grid(linestyle=':')
plt.yscale('log')
plt.show()