Create indicators/sma.py

indicators/sma.py

@@ -0,0 +1,42 @@
+# indicators/sma.py
+
+import pandas as pd
+
+def calculate_sma(data, period):
+    """
+    Calculates the Simple Moving Average (SMA) for a given period.
+
+    Parameters:
+    - data: DataFrame containing stock prices with a 'Close' column (DataFrame).
+    - period: The period over which to calculate the SMA (int).
+
+    Returns:
+    - sma: The calculated SMA as a Series (pd.Series).
+    """
+    sma = data['Close'].rolling(window=period, min_periods=1).mean()
+    return sma
+
+def add_sma_columns(data):
+    """
+    Adds SMA columns for the 21 and 50 periods to the input DataFrame.
+
+    Parameters:
+    - data: DataFrame containing stock prices. Must include a 'Close' column (DataFrame).
+
+    Modifies:
+    - data: The input DataFrame is modified in-place, adding two new columns: 'SMA_21' and 'SMA_50'.
+    """
+    data['SMA_21'] = calculate_sma(data, 21)
+    data['SMA_50'] = calculate_sma(data, 50)
+
+# Example usage
+if __name__ == "__main__":
+    # Assuming 'data' is a DataFrame that contains stock price data including a 'Close' column.
+    # For the sake of example, let's create a dummy DataFrame.
+    dates = pd.date_range(start="2023-01-01", end="2023-02-28", freq='D')
+    prices = pd.Series([i * 0.01 for i in range(len(dates))], index=dates)
+    data = pd.DataFrame(prices, columns=['Close'])
+    
+    # Add SMA columns
+    add_sma_columns(data)
+    print(data.head())  # Display the first few rows to verify the SMA calculations