add Combine dataframes with pct_change

freqtrade/data/metrics.py

@@ -30,8 +30,24 @@ def calculate_market_change(data: Dict[str, pd.DataFrame], column: str = "close"
     return float(np.mean(tmp_means))
 
 
-def combine_dataframes_with_mean(data: Dict[str, pd.DataFrame],
-                                 column: str = "close") -> pd.DataFrame:
+def combine_dataframes_by_column(
+        data: Dict[str, pd.DataFrame], column: str = "close") -> pd.DataFrame:
+    """
+    Combine multiple dataframes "column"
+    :param data: Dict of Dataframes, dict key should be pair.
+    :param column: Column in the original dataframes to use
+    :return: DataFrame with the column renamed to the dict key.
+    :raise: ValueError if no data is provided.
+    """
+    if not data:
+        raise ValueError("No data provided.")
+    df_comb = pd.concat([data[pair].set_index('date').rename(
+        {column: pair}, axis=1)[pair] for pair in data], axis=1)
+    return df_comb
+
+
+def combined_dataframes_with_rel_mean(
+        data: Dict[str, pd.DataFrame], column: str = "close") -> pd.DataFrame:
     """
     Combine multiple dataframes "column"
     :param data: Dict of Dataframes, dict key should be pair.
@@ -40,8 +56,24 @@ def combine_dataframes_with_mean(data: Dict[str, pd.DataFrame],
         named mean, containing the mean of all pairs.
     :raise: ValueError if no data is provided.
     """
-    df_comb = pd.concat([data[pair].set_index('date').rename(
-        {column: pair}, axis=1)[pair] for pair in data], axis=1)
+    df_comb = combine_dataframes_by_column(data, column)
+    df_comb['count'] = df_comb.count(axis=1)
+    df_comb['mean'] = df_comb.mean(axis=1)
+    df_comb['rel_mean'] = df_comb['mean'].pct_change().fillna(0)
+    return df_comb[['mean', 'rel_mean', 'count']]
+
+
+def combine_dataframes_with_mean(
+        data: Dict[str, pd.DataFrame], column: str = "close") -> pd.DataFrame:
+    """
+    Combine multiple dataframes "column"
+    :param data: Dict of Dataframes, dict key should be pair.
+    :param column: Column in the original dataframes to use
+    :return: DataFrame with the column renamed to the dict key, and a column
+        named mean, containing the mean of all pairs.
+    :raise: ValueError if no data is provided.
+    """
+    df_comb = combine_dataframes_by_column(data, column)
 
     df_comb['mean'] = df_comb.mean(axis=1)
 

tests/data/test_btanalysis.py

@@ -16,7 +16,7 @@ from freqtrade.data.metrics import (calculate_cagr, calculate_calmar, calculate_
                                     calculate_expectancy, calculate_market_change,
                                     calculate_max_drawdown, calculate_sharpe, calculate_sortino,
                                     calculate_underwater, combine_dataframes_with_mean,
-                                    create_cum_profit)
+                                    combined_dataframes_with_rel_mean, create_cum_profit)
 from freqtrade.exceptions import OperationalException
 from freqtrade.util import dt_utc
 from tests.conftest import CURRENT_TEST_STRATEGY, create_mock_trades
@@ -251,10 +251,22 @@ def test_combine_dataframes_with_mean(testdatadir):
     assert "mean" in df.columns
 
 
+def test_combined_dataframes_with_rel_mean(testdatadir):
+    pairs = ["ETH/BTC", "ADA/BTC"]
+    data = load_data(datadir=testdatadir, pairs=pairs, timeframe='5m')
+    df = combined_dataframes_with_rel_mean(data)
+    assert isinstance(df, DataFrame)
+    assert "ETH/BTC" not in df.columns
+    assert "ADA/BTC" not in df.columns
+    assert "mean" in df.columns
+    assert "rel_mean" in df.columns
+    assert "count" in df.columns
+
+
 def test_combine_dataframes_with_mean_no_data(testdatadir):
     pairs = ["ETH/BTC", "ADA/BTC"]
     data = load_data(datadir=testdatadir, pairs=pairs, timeframe='6m')
-    with pytest.raises(ValueError, match=r"No objects to concatenate"):
+    with pytest.raises(ValueError, match=r"No data provided\."):
         combine_dataframes_with_mean(data)