fix: Pandas FutureWarning for concat with empty Series

concat None if Series is empty

FutureWarning: The behavior of array concatenation with empty entries is deprecated. In a future version, this will no longer exclude empty items when determining the result dtype. To retain the old behavior, exclude the empty entries before the concat operation.

main.py

@@ -1,11 +1,6 @@
 import matplotlib.pyplot as plt
 import okama as ok
 
-indexes = ["RGBITR.INDX", "RUCBTRNS.INDX", "MCFTR.INDX", "GC.COMM"]
-bounds = [(0, 0.7), (0, 0.7), (0, 1), (0, 0.19)]
-ef = ok.EfficientFrontier(indexes, ccy="RUB", full_frontier=False, bounds=bounds, inflation=False)
-tg = ef.get_tangency_portfolio(rf_return=0.08)
-s = tg["Weights"].sum()
-print(s)
-## TODO: replace ValueError: Weights sum is not equal to one. with custom error mesage
-
+weights = [0.32, 0.31,  0.18, .19]
+portf = ok.Portfolio(['RGBITR.INDX', 'RUCBTRNS.INDX', 'MCFTR.INDX', 'GC.COMM'], ccy="RUB", weights=weights, inflation=True, symbol="portf.PF", rebalancing_period='year')
+portf.describe()

okama/common/helpers/helpers.py

@@ -390,11 +390,7 @@ def wealth_ts(self, weights: list, ror: pd.DataFrame) -> pd.Series:
                 inv_period_spread = np.asarray(weights) * initial_inv  # rebalancing
                 assets_wealth_indexes = inv_period_spread * (1 + df).cumprod()
                 wealth_index_local = assets_wealth_indexes.sum(axis=1)
-                wealth_index = pd.concat([wealth_index, wealth_index_local], verify_integrity=True, sort=False)
-                # TODO: FutureWarning: The behavior of array concatenation with empty entries is deprecated.
-                #  In a future version, this will no longer exclude empty items when determining the result dtype.
-                #  To retain the old behavior, exclude the empty entries before the concat operation.
-
+                wealth_index = pd.concat([None if wealth_index.empty else wealth_index, wealth_index_local], sort=False)
                 initial_inv = wealth_index.iloc[-1]
         return wealth_index
 
@@ -421,7 +417,7 @@ def assets_wealth_ts(self, weights: list, ror: pd.DataFrame) -> pd.DataFrame:
                     sort=False,
                 )
                 wealth_index_local = assets_wealth_indexes_local.sum(axis=1)
-                wealth_index = pd.concat([wealth_index, wealth_index_local], verify_integrity=True, sort=False)
+                wealth_index = pd.concat([None if wealth_index.empty else wealth_index, wealth_index_local], sort=False)
                 initial_inv = wealth_index.iloc[-1]
         return assets_wealth_indexes