cryptodatapy.util.utils
=======================

.. py:module:: cryptodatapy.util.utils


Functions
---------

.. autoapisummary::

   cryptodatapy.util.utils.compute_reference_price
   cryptodatapy.util.utils.stitch_dataframes
   cryptodatapy.util.utils.rebase_fx_to_foreign_vs_usd


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

.. py:function:: compute_reference_price(dfs: List[pandas.DataFrame], method: str = 'median', trim_pct: float = 0.25) -> pandas.DataFrame

   Computes the reference price from a list of dataframes.

   :param dfs: List of dataframes containing price data.
   :type dfs: pd.DataFrame
   :param method: Method to compute the reference price. Options are 'median' or 'trimmed_mean'.
                  Default is 'median'.
   :type method: str, optional
   :param trim_pct: Percentage of data to trim from both ends for 'trimmed_mean' method.
                    Default is 0.25 (25%).
   :type trim_pct: float, optional

   :returns: Dataframe with the reference price.
   :rtype: pd.DataFrame


.. py:function:: stitch_dataframes(df1: pandas.DataFrame, df2: pandas.DataFrame) -> pandas.DataFrame

   Stitches together dataframes with different start dates.

   :param df1: First dataframe to be stitched.
   :type df1: pd.DataFrame
   :param df2: Second dataframe to be stitched.
   :type df2: pd.DataFrame

   :returns: **combined_df** -- Combined or stitched dataframes with extended data.
   :rtype: pd.DataFrame


.. py:function:: rebase_fx_to_foreign_vs_usd(df) -> pandas.DataFrame

   Rebase FX rates to foreign currency vs. USD format, so that an increase
   means the foreign currency is appreciating. Works for both MultiIndex
   (date, ticker) and single-index (date index, tickers as columns).

   :param df: FX DataFrame with either:
              - MultiIndex (date, ticker)
              - Datetime index and tickers as columns
   :type df: pd.DataFrame

   :returns: Rebased FX rates with tickers as foreign currency (e.g., 'EUR', 'JPY').
   :rtype: pd.DataFrame