add upgrades downgrades

add upgrades/downgrades (recommendations history)
return data is pandas dataframe
add test for upgrades/downgrades data

tests/ticker.py

@@ -31,9 +31,11 @@
     ("info", dict),
     ("calendar", pd.DataFrame),
     ("recommendations", Union[pd.DataFrame, dict]),
+    ("recommendations_summary", Union[pd.DataFrame, dict]),
+    ("upgrades_downgrades", Union[pd.DataFrame, dict]),
+    ("recommendations_history", Union[pd.DataFrame, dict]),
     ("earnings", pd.DataFrame),
     ("quarterly_earnings", pd.DataFrame),
-    ("recommendations_summary", Union[pd.DataFrame, dict]),
     ("quarterly_cashflow", pd.DataFrame),
     ("cashflow", pd.DataFrame),
     ("quarterly_balance_sheet", pd.DataFrame),
@@ -637,14 +639,27 @@ def test_recommendations(self):
         data_cached = self.ticker.recommendations
         self.assertIs(data, data_cached, "data not cached")
 
-    # def test_recommendations_summary(self):
+    # def test_recommendations_summary(self):  # currently alias for recommendations
     #     data = self.ticker.recommendations_summary
     #     self.assertIsInstance(data, pd.DataFrame, "data has wrong type")
     #     self.assertFalse(data.empty, "data is empty")
 
     #     data_cached = self.ticker.recommendations_summary
     #     self.assertIs(data, data_cached, "data not cached")
 
+    def test_recommendations_history(self):  # alias for upgrades_downgrades
+        data = self.ticker.upgrades_downgrades
+        data_history = self.ticker.recommendations_history
+        self.assertTrue(data.equals(data_history))
+        self.assertIsInstance(data, pd.DataFrame, "data has wrong type")
+        self.assertFalse(data.empty, "data is empty")
+        self.assertTrue(len(data.columns) == 4, "data has wrong number of columns")
+        self.assertEqual(data.columns.values.tolist(), ['Firm', 'ToGrade', 'FromGrade', 'Action'], "data has wrong column names")
+        self.assertIsInstance(data.index, pd.DatetimeIndex, "data has wrong index type")
+
+        data_cached = self.ticker.upgrades_downgrades
+        self.assertIs(data, data_cached, "data not cached")
+
     # def test_analyst_price_target(self):
     #     data = self.ticker.analyst_price_target
     #     self.assertIsInstance(data, pd.DataFrame, "data has wrong type")

yfinance/base.py

@@ -1708,6 +1708,21 @@ def get_recommendations(self, proxy=None, as_dict=False):
             return data.to_dict()
         return data
 
+    def get_recommendations_summary(self, proxy=None, as_dict=False):
+        return self.get_recommendations(proxy=proxy, as_dict=as_dict)
+
+    def get_upgrades_downgrades(self, proxy=None, as_dict=False):
+        """
+        Returns a DataFrame with the recommendations changes (upgrades/downgrades)
+        Index: date of grade
+        Columns: firm toGrade fromGrade action
+        """
+        self._quote.proxy = proxy or self.proxy
+        data = self._quote.upgrades_downgrades
+        if as_dict:
+            return data.to_dict()
+        return data
+
     def get_calendar(self, proxy=None, as_dict=False):
         self._quote.proxy = proxy or self.proxy
         data = self._quote.calendar
@@ -1760,9 +1775,6 @@ def get_sustainability(self, proxy=None, as_dict=False):
             return data.to_dict()
         return data
 
-    def get_recommendations_summary(self, proxy=None, as_dict=False):
-        return self.get_recommendations(proxy=proxy, as_dict=as_dict)
-
     def get_analyst_price_target(self, proxy=None, as_dict=False):
         self._analysis.proxy = proxy or self.proxy
         data = self._analysis.analyst_price_target

yfinance/scrapers/quote.py

@@ -561,6 +561,7 @@ def __init__(self, data: YfData, symbol: str, proxy=None):
         self._retired_info = None
         self._sustainability = None
         self._recommendations = None
+        self._upgrades_downgrades = None
         self._calendar = None
 
         self._already_scraped = False
@@ -592,6 +593,23 @@ def recommendations(self) -> pd.DataFrame:
             self._recommendations = pd.DataFrame(data)
         return self._recommendations
 
+    @property
+    def upgrades_downgrades(self) -> pd.DataFrame:
+        if self._upgrades_downgrades is None:
+            result = self._fetch(self.proxy, modules=['upgradeDowngradeHistory'])
+            try:
+                data = result["quoteSummary"]["result"][0]["upgradeDowngradeHistory"]["history"]
+                if len(data) == 0:
+                    raise YFinanceDataException(f"No upgrade/downgrade history found for {self._symbol}")
+                df = pd.DataFrame(data)
+                df.rename(columns={"epochGradeDate": "GradeDate", 'firm': 'Firm', 'toGrade': 'ToGrade', 'fromGrade': 'FromGrade', 'action': 'Action'}, inplace=True)
+                df.set_index('GradeDate', inplace=True)
+                df.index = pd.to_datetime(df.index, unit='s')
+                self._upgrades_downgrades = df
+            except (KeyError, IndexError):
+                raise YFinanceDataException(f"Failed to parse json response from Yahoo Finance: {result}")
+        return self._upgrades_downgrades
+
     @property
     def calendar(self) -> pd.DataFrame:
         if self._calendar is None:

yfinance/ticker.py

@@ -153,6 +153,18 @@ def calendar(self) -> _pd.DataFrame:
     def recommendations(self):
         return self.get_recommendations()
 
+    @property
+    def recommendations_summary(self):
+        return self.get_recommendations_summary()
+
+    @property
+    def upgrades_downgrades(self):
+        return self.get_upgrades_downgrades()
+
+    @property
+    def recommendations_history(self):
+        return self.get_upgrades_downgrades()
+
     @property
     def earnings(self) -> _pd.DataFrame:
         return self.get_earnings()
@@ -217,10 +229,6 @@ def cashflow(self) -> _pd.DataFrame:
     def quarterly_cashflow(self) -> _pd.DataFrame:
         return self.quarterly_cash_flow
 
-    @property
-    def recommendations_summary(self):
-        return self.get_recommendations_summary()
-
     @property
     def analyst_price_target(self) -> _pd.DataFrame:
         return self.get_analyst_price_target()