import pandas as pd
import matplotlib.pyplot as plt
url='https://raw.githubusercontent.com/JJTorresDS/ds-data-sources/main/stocks.csv'
df= pd.read_csv(url,index_col='formatted_date',parse_dates=['formatted_date'])
df

df.corr()

import seaborn as sns 
sns.heatmap(df.corr(), cmap='jet')

df.isnull().sum()

# graficando la serie de tiempo
df.plot(kind='line', figsize=(12,8), xlabel='Fecha', ylabel='Precio', title='Acciones en el tiempo')

df_melt=pd.melt(df)
df_melt

# Con atipicos
plt.figure(figsize=(12,6))
sns.boxplot(data=df)

# Sin atipicos
plt.figure(figsize=(12,6))
sns.boxplot(data=df, showfliers=False)

# Cambio porcentual
df.pct_change().plot(kind='line', figsize=(15,6),xlabel='Fecha',ylabel='Cambio %')
plt.legend(fontsize='xx-large', ncol=4, loc='lower left')