Fix low_memory C engine parser

Author: kprestel

pandas/_libs/parsers.pyx

@@ -986,7 +986,6 @@ cdef class TextReader:
                                             footer=footer,
                                             upcast_na=True)
         self._end_clock('Type conversion')
-
         self._start_clock()
         if len(columns) > 0:
             rows_read = len(list(columns.values())[0])
@@ -1241,7 +1240,7 @@ cdef class TextReader:
                     try:
                         # use _from_sequence_of_strings if the class defines it
                         result = array_type._from_sequence_of_strings(result,
-                                                                    dtype=dtype) # noqa
+                                                                      dtype=dtype) # noqa
                     except AbstractMethodError:
                         result = array_type._from_sequence(result, dtype=dtype)
                 else:
@@ -2201,7 +2200,11 @@ def _concatenate_chunks(list chunks):
             result[name] = union_categoricals(arrs,
                                               sort_categories=sort_categories)
         else:
-            result[name] = np.concatenate(arrs)
+            if is_extension_array_dtype(dtype):
+                result[name] = dtype \
+                    .construct_array_type()._concat_same_type(arrs)
+            else:
+                result[name] = np.concatenate(arrs)
 
     if warning_columns:
         warning_names = ','.join(warning_columns)

pandas/core/internals/construction.py

@@ -559,7 +559,7 @@ def sanitize_array(data, index, dtype=None, copy=False,
 
             # possibility of nan -> garbage
             if is_float_dtype(data.dtype) and is_integer_dtype(dtype) \
-                and not is_extension_array_dtype(dtype):
+                    and not is_extension_array_dtype(dtype):
                 if not isna(data).any():
                     subarr = _try_cast(data, True, dtype, copy,
                                        raise_cast_failure)

pandas/io/parsers.py

@@ -1669,8 +1669,8 @@ def _convert_to_ndarrays(self, dct, na_values, na_fvalues, verbose=False,
                     try_num_bool)
 
                 # type specified in dtype param
-                if cast_type and not is_dtype_equal(cvals, cast_type):
-                        # or is_extension_array_dtype(cast_type)):
+                if cast_type and (not is_dtype_equal(cvals, cast_type)
+                                  or is_extension_array_dtype(cast_type)):
                     try:
                         if (is_bool_dtype(cast_type) and
                                 not is_categorical_dtype(cast_type)

pandas/tests/extension/base/io.py

@@ -26,15 +26,19 @@ def data(dtype):
 
 
 class ExtensionParsingTests(BaseExtensionTests):
-    def test_EA_types(self):
+
+    @pytest.mark.parametrize('engine', ['c', 'python'])
+    def test_EA_types(self, engine):
         df = pd.DataFrame({'Int': pd.Series([1, 2, 3], dtype='Int64'),
                            'A': [1, 2, 1]})
         data = df.to_csv(index=False)
-        result = pd.read_csv(StringIO(data), dtype={'Int': Int64Dtype})
+        result = pd.read_csv(StringIO(data), dtype={'Int': Int64Dtype},
+                             engine=engine)
         assert result is not None
 
         df = pd.DataFrame({'Int': pd.Series([1, 2, 3], dtype='Int8'),
                            'A': [1, 2, 1]})
         data = df.to_csv(index=False)
-        result = pd.read_csv(StringIO(data), dtype={'Int': 'Int8'})
+        result = pd.read_csv(StringIO(data), dtype={'Int': 'Int8'},
+                             engine=engine)
         assert result is not None