BUG: Fix tests for google & yahoo options.

Currently only 4 expiries for GOOG options.
Datatype on open interest & volume changed to float to deal with NaNs

Author: David Stephens

pandas_datareader/google/options.py

@@ -137,6 +137,11 @@ def _process_data(self, jd, expiry):
         indexes = ['Strike', 'Expiry', 'Type', 'Symbol']
         rows_list, index = self._process_rows(jd, now, expiry)
         df = DataFrame(rows_list, columns=columns, index=MultiIndex.from_tuples(index, names=indexes))
+
+        # Make dtype consistent, requires float64 as there can be NaNs
+        df['Vol'] = df['Vol'].astype('float64')
+        df['Open_Int'] = df['Open_Int'].astype('float64')
+
         return df.sort_index()
 
     def _process_rows(self, jd, now, expiry):

pandas_datareader/tests/test_google_options.py

@@ -31,7 +31,7 @@ def assert_option_result(self, df):
         tm.assert_index_equal(df.columns, exp_columns)
         tm.assert_equal(df.index.names, [u'Strike', u'Expiry', u'Type', u'Symbol'])
 
-        dtypes = ['float64'] * 6 + ['int64', 'object', 'float64', 'datetime64[ns]']
+        dtypes = ['float64'] * 7 + ['object', 'float64', 'datetime64[ns]']
         dtypes = [np.dtype(x) for x in dtypes]
         tm.assert_series_equal(df.dtypes, pd.Series(dtypes, index=exp_columns))
 
@@ -54,7 +54,7 @@ def test_expiry_dates(self):
         except RemoteDataError as e:  # pragma: no cover
             raise nose.SkipTest(e)
 
-        self.assertTrue(len(dates) >= 5)
+        self.assertTrue(len(dates) >= 4)
         self.assertIsInstance(dates, list)
         self.assertTrue(all(isinstance(dt, date) for dt in dates))
 

pandas_datareader/tests/test_yahoo_options.py

@@ -50,8 +50,8 @@ def assert_option_result(self, df):
         tm.assert_index_equal(df.columns, exp_columns)
         tm.assert_equal(df.index.names, [u'Strike', u'Expiry', u'Type', u'Symbol'])
 
-        dtypes = [np.dtype(x) for x in ['float64'] * 5 +
-                  ['int64', 'int64', 'float64', 'object', 'bool', 'object', 'float64', 'datetime64[ns]',
+        dtypes = [np.dtype(x) for x in ['float64'] * 7 +
+                  ['float64', 'object', 'bool', 'object', 'float64', 'datetime64[ns]',
                    'datetime64[ns]', 'object']]
         tm.assert_series_equal(df.dtypes, pd.Series(dtypes, index=exp_columns))
 

pandas_datareader/yahoo/options.py

@@ -684,6 +684,10 @@ def _process_data(self, jd):
 
         df['IsNonstandard'] = df['Root'] != self.symbol.replace('-', '')
 
+        # Make dtype consistent, requires float64 as there can be NaNs
+        df['Vol'] = df['Vol'].astype('float64')
+        df['Open_Int'] = df['Open_Int'].astype('float64')
+
         return df.sort_index()
 
     def _process_rows(self, jd):