import pandas as p
import matplotlib.pyplot as g
df_load = p.read_csv('BTC-USD.csv')
df_load
df = df_load.sort_values('Close' ,ascending=False)
stores = 5
g.bar(df['Date'].head(stores), df['Close'].head(stores))
g.grid()
g.title('Mayores precios del Bitcoin')
g.ylabel('Precios')
g.xlabel('Fechas')
g.xticks(rotation=25)
g.show()
g.bar(df['Date'].tail(stores), df['Close'].tail(stores), color='#FF3333')
g.grid()
g.title('Menores precios del Bitcoin')
g.ylabel('Precios')
g.xlabel('Fechas')
g.xticks(rotation=25)
g.show()
g.hist(df['Volume'])
g.grid()
g.title('Numbres of bitcoins in trading')
g.xlabel('Number of Bitcoins')
g.ylabel('Días')
g.show()
df.tail(1)
df = df_load.sort_values('Open', ascending=False)
df.head(1)
df = df_load.sort_values('High', ascending=False)
df.head()
g.hist(df['Open'])
g.grid()
g.title('Bitcoin open prices')
g.xlabel('Bitcoin prices')
g.ylabel('Days')
g.show()
g.hist(df['Close'])
g.grid()
g.title('Bitcoin Close Price')
g.xlabel('Bitcoin Price')
g.ylabel('Days')
g.show()
g.hist(df['High'])
g.grid()
g.title('Most Common Maximum daily price of Bitcoin')
g.xlabel('Bitcoin maximun price')
g.ylabel('Days')
g.show()