numeric only for pandas version 2

microsoft · Jul 19, 2023 · 7e7fdbd · 7e7fdbd
1 parent 43653b1
commit 7e7fdbd
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Showing 2 changed files with 8 additions and 8 deletions.
diff --git a/datamations/datamation_groupby.py b/datamations/datamation_groupby.py
@@ -44,14 +44,14 @@ def mean(self, axis=None):
         self._axis = axis
         self._states.append(self)
         self._operations.append('mean')
-        df = super(DatamationGroupBy, self).mean()
+        df = super(DatamationGroupBy, self).mean(numeric_only=True)
         df = datamation_frame.DatamationFrame(df)
         df._by = self.states[1]._by
         df._states = self._states
         df._operations = self._operations
         self._output = df
         self._axis = axis if axis else df.keys()[0]
-        self._error = super(DatamationGroupBy, self).std()
+        self._error = super(DatamationGroupBy, self).std(numeric_only=True)
         for i in range(len(self._error[self._axis])):
             self._error[self._axis][i] = (0 if pd.isna(self._error[self._axis][i]) else self._error[self._axis][i]) / math.sqrt(len(list(self.states[1].groups.values())[i]))
         return df
@@ -61,14 +61,14 @@ def median(self, axis=None):
         self._axis = axis
         self._states.append(self)
         self._operations.append('median')
-        df = super(DatamationGroupBy, self).median()
+        df = super(DatamationGroupBy, self).median(numeric_only=True)
         df = datamation_frame.DatamationFrame(df)
         df._by = self.states[1]._by
         df._states = self._states
         df._operations = self._operations
         self._output = df
         self._axis = axis if axis else df.keys()[0]
-        self._error = super(DatamationGroupBy, self).std()
+        self._error = super(DatamationGroupBy, self).std(numeric_only=True)
         for i in range(len(self._error[self._axis])):
             self._error[self._axis][i] = (0 if pd.isna(self._error[self._axis][i]) else self._error[self._axis][i]) / math.sqrt(len(list(self.states[1].groups.values())[i]))
         return df
@@ -119,7 +119,7 @@ def sum(self, axis=None):
         self._axis = axis
         self._states.append(self)
         self._operations.append('sum')
-        df = super(DatamationGroupBy, self).sum()
+        df = super(DatamationGroupBy, self).sum(numeric_only=True)
         df = datamation_frame.DatamationFrame(df)
         df._by = self.states[1]._by
         df._states = self._states
@@ -133,7 +133,7 @@ def quantile(self, axis=None, probs=None):
         self._probs = probs
         self._states.append(self)
         self._operations.append('quantile')
-        df = super(DatamationGroupBy, self).quantile(self._probs)
+        df = super(DatamationGroupBy, self).quantile(self._probs, numeric_only=True)
         df = datamation_frame.DatamationFrame(df)
         df._by = self.states[1]._by
         df._states = self._states
@@ -147,7 +147,7 @@ def prod(self, axis=None):
         self._axis = axis
         self._states.append(self)
         self._operations.append('product')
-        df = super(DatamationGroupBy, self).prod()
+        df = super(DatamationGroupBy, self).prod(numeric_only=True)
         df = datamation_frame.DatamationFrame(df)
         df._by = self.states[1]._by
         df._states = self._states

diff --git a/datamations/tests/test_small_salary.py b/datamations/tests/test_small_salary.py
@@ -5,7 +5,7 @@
 
 def test_small_salary(capsys):
     df = small_salary().df
-    print(df.groupby('Work').mean())
+    print(df.groupby('Work').mean(numeric_only=True))
     captured = capsys.readouterr()
 
     assert "Work" in captured.out