Merge pull request #8973 from artemyk/notnulldtype_sql

ENH: Infer dtype from non-nulls when pushing to SQL

doc/source/whatsnew/v0.15.2.txt

@@ -115,6 +115,7 @@ Enhancements
 - ``to_datetime`` gains an ``exact`` keyword to allow for a format to not require an exact match for a provided format string (if its ``False). ``exact`` defaults to ``True`` (meaning that exact matching is still the default)  (:issue:`8904`)
 - Added ``axvlines`` boolean option to parallel_coordinates plot function, determines whether vertical lines will be printed, default is True
 - Added ability to read table footers to read_html (:issue:`8552`)
+- ``to_sql`` now infers datatypes of non-NA values for columns that contain NA values and have dtype ``object`` (:issue:`8778`).
 
 .. _whatsnew_0152.performance:
 

pandas/io/sql.py

@@ -885,37 +885,56 @@ def _harmonize_columns(self, parse_dates=None):
             except KeyError:
                 pass  # this column not in results
 
+    def _get_notnull_col_dtype(self, col):
+        """
+        Infer datatype of the Series col.  In case the dtype of col is 'object' 
+        and it contains NA values, this infers the datatype of the not-NA 
+        values.  Needed for inserting typed data containing NULLs, GH8778.
+        """
+        col_for_inference = col
+        if col.dtype == 'object':
+            notnulldata = col[~isnull(col)]
+            if len(notnulldata):
+                col_for_inference = notnulldata
+
+        return lib.infer_dtype(col_for_inference)
+
     def _sqlalchemy_type(self, col):
-        from sqlalchemy.types import (BigInteger, Float, Text, Boolean,
-            DateTime, Date, Time)
 
         dtype = self.dtype or {}
         if col.name in dtype:
             return self.dtype[col.name]
 
-        if com.is_datetime64_dtype(col):
+        col_type = self._get_notnull_col_dtype(col)
+
+        from sqlalchemy.types import (BigInteger, Float, Text, Boolean,
+            DateTime, Date, Time)
+
+        if col_type == 'datetime64': 
             try:
                 tz = col.tzinfo
                 return DateTime(timezone=True)
             except:
                 return DateTime
-        if com.is_timedelta64_dtype(col):
+        if col_type == 'timedelta64':
             warnings.warn("the 'timedelta' type is not supported, and will be "
                           "written as integer values (ns frequency) to the "
                           "database.", UserWarning)
             return BigInteger
-        elif com.is_float_dtype(col):
+        elif col_type == 'floating':
             return Float
-        elif com.is_integer_dtype(col):
+        elif col_type == 'integer':
             # TODO: Refine integer size.
             return BigInteger
-        elif com.is_bool_dtype(col):
+        elif col_type == 'boolean':
             return Boolean
-        inferred = lib.infer_dtype(com._ensure_object(col))
-        if inferred == 'date':
+        elif col_type == 'date':
             return Date
-        if inferred == 'time':
+        elif col_type == 'time':
             return Time
+        elif col_type == 'complex':
+            raise ValueError('Complex datatypes not supported')
+
         return Text
 
     def _numpy_type(self, sqltype):
@@ -1187,15 +1206,15 @@ def _create_sql_schema(self, frame, table_name, keys=None):
 # SQLAlchemy installed
 # SQL type convertions for each DB
 _SQL_TYPES = {
-    'text': {
+    'string': {
         'mysql': 'VARCHAR (63)',
         'sqlite': 'TEXT',
     },
-    'float': {
+    'floating': {
         'mysql': 'FLOAT',
         'sqlite': 'REAL',
     },
-    'int': {
+    'integer': {
         'mysql': 'BIGINT',
         'sqlite': 'INTEGER',
     },
@@ -1211,12 +1230,13 @@ def _create_sql_schema(self, frame, table_name, keys=None):
         'mysql': 'TIME',
         'sqlite': 'TIME',
     },
-    'bool': {
+    'boolean': {
         'mysql': 'BOOLEAN',
         'sqlite': 'INTEGER',
     }
 }
 
+
 # SQL enquote and wildcard symbols
 _SQL_SYMB = {
     'mysql': {
@@ -1291,8 +1311,8 @@ def _create_table_setup(self):
         br_l = _SQL_SYMB[flv]['br_l']  # left val quote char
         br_r = _SQL_SYMB[flv]['br_r']  # right val quote char
 
-        create_tbl_stmts = [(br_l + '%s' + br_r + ' %s') % (cname, ctype)
-                            for cname, ctype, _ in column_names_and_types]
+        create_tbl_stmts = [(br_l + '%s' + br_r + ' %s') % (cname, col_type)
+                            for cname, col_type, _ in column_names_and_types]
         if self.keys is not None and len(self.keys):
             cnames_br = ",".join([br_l + c + br_r for c in self.keys])
             create_tbl_stmts.append(
@@ -1317,30 +1337,27 @@ def _sql_type_name(self, col):
         dtype = self.dtype or {}
         if col.name in dtype:
             return dtype[col.name]
-        pytype = col.dtype.type
-        pytype_name = "text"
-        if issubclass(pytype, np.floating):
-            pytype_name = "float"
-        elif com.is_timedelta64_dtype(pytype):
+
+        col_type = self._get_notnull_col_dtype(col)
+        if col_type == 'timedelta64':
             warnings.warn("the 'timedelta' type is not supported, and will be "
                           "written as integer values (ns frequency) to the "
                           "database.", UserWarning)
-            pytype_name = "int"
-        elif issubclass(pytype, np.integer):
-            pytype_name = "int"
-        elif issubclass(pytype, np.datetime64) or pytype is datetime:
-            # Caution: np.datetime64 is also a subclass of np.number.
-            pytype_name = "datetime"
-        elif issubclass(pytype, np.bool_):
-            pytype_name = "bool"
-        elif issubclass(pytype, np.object):
-            pytype = lib.infer_dtype(com._ensure_object(col))
-            if pytype == "date":
-                pytype_name = "date"
-            elif pytype == "time":
-                pytype_name = "time"
-
-        return _SQL_TYPES[pytype_name][self.pd_sql.flavor]
+            col_type = "integer"
+
+        elif col_type == "datetime64":
+            col_type = "datetime"
+
+        elif col_type == "empty":
+            col_type = "string"
+
+        elif col_type == "complex":
+            raise ValueError('Complex datatypes not supported')
+
+        if col_type not in _SQL_TYPES:
+            col_type = "string"
+
+        return _SQL_TYPES[col_type][self.pd_sql.flavor]
 
 
 class SQLiteDatabase(PandasSQL):

pandas/io/tests/test_sql.py

@@ -560,6 +560,11 @@ def test_timedelta(self):
         result = sql.read_sql_query('SELECT * FROM test_timedelta', self.conn)
         tm.assert_series_equal(result['foo'], df['foo'].astype('int64'))
 
+    def test_complex(self):
+        df = DataFrame({'a':[1+1j, 2j]})
+        # Complex data type should raise error
+        self.assertRaises(ValueError, df.to_sql, 'test_complex', self.conn)
+
     def test_to_sql_index_label(self):
         temp_frame = DataFrame({'col1': range(4)})
 
@@ -1175,19 +1180,38 @@ def test_dtype(self):
                 (0.9, None)]
         df = DataFrame(data, columns=cols)
         df.to_sql('dtype_test', self.conn)
-        df.to_sql('dtype_test2', self.conn, dtype={'B': sqlalchemy.Boolean})
+        df.to_sql('dtype_test2', self.conn, dtype={'B': sqlalchemy.TEXT})
+        meta = sqlalchemy.schema.MetaData(bind=self.conn)
+        meta.reflect()
+        sqltype = meta.tables['dtype_test2'].columns['B'].type
+        self.assertTrue(isinstance(sqltype, sqlalchemy.TEXT))
+        self.assertRaises(ValueError, df.to_sql,
+                          'error', self.conn, dtype={'B': str})
+
+    def test_notnull_dtype(self):
+        cols = {'Bool': Series([True,None]),
+                'Date': Series([datetime(2012, 5, 1), None]),
+                'Int' : Series([1, None], dtype='object'),
+                'Float': Series([1.1, None])
+               }
+        df = DataFrame(cols)
+
+        tbl = 'notnull_dtype_test'
+        df.to_sql(tbl, self.conn)
+        returned_df = sql.read_sql_table(tbl, self.conn)
         meta = sqlalchemy.schema.MetaData(bind=self.conn)
         meta.reflect()
-        self.assertTrue(isinstance(meta.tables['dtype_test'].columns['B'].type,
-                                   sqltypes.TEXT))
         if self.flavor == 'mysql':
             my_type = sqltypes.Integer
         else:
             my_type = sqltypes.Boolean
-        self.assertTrue(isinstance(meta.tables['dtype_test2'].columns['B'].type,
-                                   my_type))
-        self.assertRaises(ValueError, df.to_sql,
-                          'error', self.conn, dtype={'B': bool})
+
+        col_dict = meta.tables[tbl].columns
+
+        self.assertTrue(isinstance(col_dict['Bool'].type, my_type))
+        self.assertTrue(isinstance(col_dict['Date'].type, sqltypes.DateTime))
+        self.assertTrue(isinstance(col_dict['Int'].type, sqltypes.Integer))
+        self.assertTrue(isinstance(col_dict['Float'].type, sqltypes.Float))
 
 
 class TestSQLiteAlchemy(_TestSQLAlchemy):
@@ -1507,6 +1531,13 @@ def test_to_sql_save_index(self):
     def test_transactions(self):
         self._transaction_test()
 
+    def _get_sqlite_column_type(self, table, column):
+        recs = self.conn.execute('PRAGMA table_info(%s)' % table)
+        for cid, name, ctype, not_null, default, pk in recs:
+            if name == column:
+                return ctype
+        raise ValueError('Table %s, column %s not found' % (table, column))
+
     def test_dtype(self):
         if self.flavor == 'mysql':
             raise nose.SkipTest('Not applicable to MySQL legacy')
@@ -1515,20 +1546,35 @@ def test_dtype(self):
                 (0.9, None)]
         df = DataFrame(data, columns=cols)
         df.to_sql('dtype_test', self.conn)
-        df.to_sql('dtype_test2', self.conn, dtype={'B': 'bool'})
+        df.to_sql('dtype_test2', self.conn, dtype={'B': 'STRING'})
 
-        def get_column_type(table, column):
-            recs = self.conn.execute('PRAGMA table_info(%s)' % table)
-            for cid, name, ctype, not_null, default, pk in recs:
-                if name == column:
-                    return ctype
-            raise ValueError('Table %s, column %s not found' % (table, column))
-
-        self.assertEqual(get_column_type('dtype_test', 'B'), 'TEXT')
-        self.assertEqual(get_column_type('dtype_test2', 'B'), 'bool')
+        # sqlite stores Boolean values as INTEGER
+        self.assertEqual(self._get_sqlite_column_type('dtype_test', 'B'), 'INTEGER')
+
+        self.assertEqual(self._get_sqlite_column_type('dtype_test2', 'B'), 'STRING')
         self.assertRaises(ValueError, df.to_sql,
                           'error', self.conn, dtype={'B': bool})
 
+    def test_notnull_dtype(self):
+        if self.flavor == 'mysql':
+            raise nose.SkipTest('Not applicable to MySQL legacy')
+
+        cols = {'Bool': Series([True,None]),
+                'Date': Series([datetime(2012, 5, 1), None]),
+                'Int' : Series([1, None], dtype='object'),
+                'Float': Series([1.1, None])
+               }
+        df = DataFrame(cols)
+
+        tbl = 'notnull_dtype_test'
+        df.to_sql(tbl, self.conn)
+
+        self.assertEqual(self._get_sqlite_column_type(tbl, 'Bool'), 'INTEGER')
+        self.assertEqual(self._get_sqlite_column_type(tbl, 'Date'), 'TIMESTAMP')
+        self.assertEqual(self._get_sqlite_column_type(tbl, 'Int'), 'INTEGER')
+        self.assertEqual(self._get_sqlite_column_type(tbl, 'Float'), 'REAL')
+
+
 class TestMySQLLegacy(TestSQLiteFallback):
     """
     Test the legacy mode against a MySQL database.