Changed fillna, iloc, and added test for changes

ranaroussi · Dec 7, 2023 · e988afc · e988afc
1 parent f08fe83
commit e988afc
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Showing 2 changed files with 11 additions and 6 deletions.
diff --git a/tests/ticker.py b/tests/ticker.py
@@ -199,10 +199,15 @@ def test_goodTicker_withProxy(self):
         self.assertIsNotNone(v)
         self.assertFalse(v.empty)
 
-        dat.get_history_metadata(proxy=self.proxy)
+        v = dat.get_history_metadata(proxy=self.proxy)
         self.assertIsNotNone(v)
         self.assertTrue(len(v) > 0)
 
+        v = dat._reconstruct_intervals_batch(dat.history(period="3mo", interval="5d", prepost=True), "1d", True)
+        self.assertIsNotNone(v)
+        self.assertTrue(len(v) > 0)
+
+
         # Below will fail because not ported to Yahoo API
 
         # v = dat.stats(proxy=self.proxy)

diff --git a/yfinance/base.py b/yfinance/base.py
@@ -704,26 +704,26 @@ def _reconstruct_intervals_batch(self, df, interval, prepost, tag=-1):
                     # But in case are repairing a chunk of bad 1d data, back/forward-fill the 
                     # good div-adjustments - not perfect, but a good backup.
                     div_adjusts[f_tag] = np.nan
-                    div_adjusts = div_adjusts.fillna(method='bfill').fillna(method='ffill')
+                    div_adjusts = div_adjusts.ffill().bfill()
                     for idx in np.where(f_tag)[0]:
                         dt = df_new_calib.index[idx]
                         n = len(div_adjusts)
                         if df_new.loc[dt, "Dividends"] != 0:
                             if idx < n - 1:
                                 # Easy, take div-adjustment from next-day
-                                div_adjusts[idx] = div_adjusts[idx + 1]
+                                div_adjusts[idx] = div_adjusts.iloc[idx + 1]
                             else:
                                 # Take previous-day div-adjustment and reverse todays adjustment
                                 div_adj = 1.0 - df_new_calib["Dividends"].iloc[idx] / df_new_calib['Close'].iloc[
                                     idx - 1]
-                                div_adjusts[idx] = div_adjusts[idx - 1] / div_adj
+                                div_adjusts.iloc[idx] = div_adjusts.iloc[idx - 1] / div_adj
                         else:
                             if idx > 0:
                                 # Easy, take div-adjustment from previous-day
-                                div_adjusts[idx] = div_adjusts[idx - 1]
+                                div_adjusts[idx] = div_adjusts.iloc[idx - 1]
                             else:
                                 # Must take next-day div-adjustment
-                                div_adjusts[idx] = div_adjusts[idx + 1]
+                                div_adjusts[idx] = div_adjusts.iloc[idx + 1]
                                 if df_new_calib["Dividends"].iloc[idx + 1] != 0:
                                     div_adjusts[idx] *= 1.0 - df_new_calib["Dividends"].iloc[idx + 1] / \
                                                         df_new_calib['Close'].iloc[idx]