traders_copilot_mzza_25.indicators
==================================

.. py:module:: traders_copilot_mzza_25.indicators


Functions
---------

.. autoapisummary::

   traders_copilot_mzza_25.indicators.calculate_sma
   traders_copilot_mzza_25.indicators.calculate_rsi


Module Contents
---------------

.. py:function:: calculate_sma(data, window=50, fillna=False)

   Calculate the Simple Moving Average (SMA) for the given data.

   :param data: DataFrame containing stock price data with a 'Close' column.
   :type data: pandas.DataFrame
   :param window: The number of periods to calculate the SMA (default is 50).
   :type window: int, optional
   :param fillna: Whether to fill NaN values (default is False).
   :type fillna: bool, optional

   :returns: DataFrame with an additional column for the SMA.
   :rtype: pandas.DataFrame

   .. rubric:: Examples

   >>> data = pd.DataFrame({'Close': [100, 102, 104, 106, 108]})
   >>> result = calculate_sma(data, window=3)
   >>> print(result['SMA_3'])


.. py:function:: calculate_rsi(data, window=14, fillna=False)

   Calculate the Relative Strength Index (RSI) measuring the speed and change of price movements.

   :param data: DataFrame containing stock price data with a 'Close' column.
   :type data: pandas.DataFrame
   :param window: Number of periods for RSI calculation (default is 14).
   :type window: int, optional
   :param fillna: Whether to fill NaN values (default is False).
   :type fillna: bool, optional

   :returns: DataFrame with an additional column for RSI.
   :rtype: pandas.DataFrame

   .. rubric:: Examples

   >>> data = pd.DataFrame({'Close': [100, 102, 104, 106, 108]})
   >>> result = calculate_rsi(data, window=3)
   >>> print(result['RSI'])