# Write a Pandas program to create a plot of adjusted closing prices, 30 days simple moving average and exponential moving average of Alphabet Inc. between two specific dates.  
import pandas as pd
import matplotlib.pyplot as plt
df = pd.read_csv("alphabet_stock_data.csv")
start_date = pd.to_datetime('2020-4-1')
end_date = pd.to_datetime('2020-9-30')                         
df['Date'] = pd.to_datetime(df['Date']) 
new_df = (df['Date']>= start_date) & (df['Date']<= end_date)
df1 = df.loc[new_df]
stock_data = df1.set_index('Date')
close_px = stock_data['Adj Close']
stock_data['SMA_30_days'] = stock_data.iloc[:,4].rolling(window=30).mean() 
stock_data['EMA_20_days'] = stock_data.iloc[:,4].ewm(span=20,adjust=False).mean()
plt.figure(figsize=[15,10])
plt.grid(True)
plt.title('Historical stock prices of Alphabet Inc. [01-04-2020 to 30-09-2020]\n',fontsize=18, color='black')
plt.plot(stock_data['Adj Close'],label='Adjusted Closing Price', color='black')
plt.plot(stock_data['SMA_30_days'],label='30 days Simple moving average', color='red')
plt.plot(stock_data['EMA_20_days'],label='20 days Exponential moving average', color='green')
plt.legend(loc=2)
plt.show()
