Update indicators/ema.py

indicators/ema.py

@@ -1,31 +1,34 @@
 import pandas as pd
 
-def calculate_ema(prices, period=20):
+def calculate_ema(prices, periods):
  """
- Calculates the Exponential Moving Average (EMA) for the given period.
-
+ Calculates the Exponential Moving Averages (EMA) for the given periods.
+ 
  Parameters:
  - prices (pd.Series): A pandas Series containing the stock's closing prices.
- - period (int): The period over which to calculate the EMA. Defaults to 20.
-
+ - periods (list of int): A list of integers representing the periods over which to calculate the EMAs.
+ 
  Returns:
- - pd.Series: A pandas Series containing the EMA values.
+ - dict of pd.Series: A dictionary where each key is the period, and the value is a pandas Series containing the EMA values for that period.
  """
- ema = prices.ewm(span=period, adjust=False).mean()
- return ema
+ emas = {}
+ for period in periods:
+ ema = prices.ewm(span=period, adjust=False).mean()
+ emas[period] = ema
+ return emas
 
 if __name__ == "__main__":
  # Example usage
- # Create a sample pandas Series of closing prices
  data = {'Close': [22, 24, 23, 25, 26, 28, 27, 29, 30, 32, 31, 33]}
  prices = pd.Series(data['Close'])
  
- # Calculate the 20-period EMA
- ema20 = calculate_ema(prices, 20)
- print("20-period EMA:")
- print(ema20)
+ # User-defined EMA periods
+ periods = [20, 50] # Example: 20-day and 50-day EMAs
+ 
+ # Calculate EMAs for specified periods
+ ema_values = calculate_ema(prices, periods)
  
- # Calculate the 50-period EMA
- ema50 = calculate_ema(prices, 50)
- print("\n50-period EMA:")
- print(ema50)
+ for period, ema in ema_values.items():
+ print(f"{period}-period EMA:")
+ print(ema)
+ print()