BUG: NaN values not converted to Stata missing values (GH6684)

doc/source/release.rst

@@ -269,6 +269,7 @@ Bug Fixes
 - Bug in ``DataFrame.to_stata`` when columns have non-string names (:issue:`4558`)
 - Bug in compat with ``np.compress``, surfaced in (:issue:`6658`)
 - Bug in binary operations with a rhs of a Series not aligning (:issue:`6681`)
+- Bug in ``DataFrame.to_stata`` which incorrectly handles nan values and ignores 'with_index' keyword argument (:issue:`6685`)
 
 pandas 0.13.1
 -------------

pandas/core/frame.py

@@ -1258,7 +1258,8 @@ def to_stata(
         from pandas.io.stata import StataWriter
         writer = StataWriter(fname, self, convert_dates=convert_dates,
                              encoding=encoding, byteorder=byteorder,
-                             time_stamp=time_stamp, data_label=data_label)
+                             time_stamp=time_stamp, data_label=data_label,
+                             write_index=write_index)
         writer.write_file()
 
     @Appender(fmt.docstring_to_string, indents=1)

pandas/io/stata.py

@@ -990,8 +990,6 @@ def _dtype_to_stata_type(dtype):
         return chr(255)
     elif dtype == np.float32:
         return chr(254)
-    elif dtype == np.int64:
-        return chr(253)
     elif dtype == np.int32:
         return chr(253)
     elif dtype == np.int16:
@@ -1025,8 +1023,6 @@ def _dtype_to_default_stata_fmt(dtype):
         return "%10.0g"
     elif dtype == np.float32:
         return "%9.0g"
-    elif dtype == np.int64:
-        return "%9.0g"
     elif dtype == np.int32:
         return "%12.0g"
     elif dtype == np.int8 or dtype == np.int16:
@@ -1108,6 +1104,21 @@ def _write(self, to_write):
             self._file.write(to_write)
 
 
+    def _replace_nans(self, data):
+        # return data
+        """Checks floating point data columns for nans, and replaces these with
+        the generic Stata for missing value (.)"""
+        for c in data:
+            dtype = data[c].dtype
+            if dtype in (np.float32, np.float64):
+                if dtype == np.float32:
+                    replacement = self.MISSING_VALUES['f']
+                else:
+                    replacement = self.MISSING_VALUES['d']
+                data[c] = data[c].fillna(replacement)
+
+        return data
+
     def _check_column_names(self, data):
         """Checks column names to ensure that they are valid Stata column names.
         This includes checks for:
@@ -1197,6 +1208,8 @@ def __iter__(self):
         data = _cast_to_stata_types(data)
         # Ensure column names are strings
         data = self._check_column_names(data)
+        # Replace NaNs with Stata missing values
+        data = self._replace_nans(data)
         self.datarows = DataFrameRowIter(data)
         self.nobs, self.nvar = data.shape
         self.data = data
@@ -1340,8 +1353,6 @@ def _write_data_dates(self):
                         var = _pad_bytes(var, typ)
                     self._write(var)
                 else:
-                    if isnull(var):  # this only matters for floats
-                        var = MISSING_VALUES[TYPE_MAP[typ]]
                     self._file.write(struct.pack(byteorder+TYPE_MAP[typ], var))
 
     def _null_terminate(self, s, as_string=False):

pandas/io/tests/test_stata.py

@@ -13,7 +13,8 @@
 import pandas as pd
 from pandas.core.frame import DataFrame, Series
 from pandas.io.parsers import read_csv
-from pandas.io.stata import read_stata, StataReader, InvalidColumnName
+from pandas.io.stata import (read_stata, StataReader, InvalidColumnName,
+    PossiblePrecisionLoss)
 import pandas.util.testing as tm
 from pandas.util.misc import is_little_endian
 from pandas import compat
@@ -142,8 +143,7 @@ def test_read_dta2(self):
             parsed_117 = self.read_dta(self.dta2_117)
             # 113 is buggy due ot limits date format support in Stata
             # parsed_113 = self.read_dta(self.dta2_113)
-
-            np.testing.assert_equal(
+            tm.assert_equal(
                 len(w), 1)  # should get a warning for that format.
 
         # buggy test because of the NaT comparison on certain platforms
@@ -206,7 +206,7 @@ def test_read_write_dta5(self):
         original.index.name = 'index'
 
         with tm.ensure_clean() as path:
-            original.to_stata(path, None, False)
+            original.to_stata(path, None)
             written_and_read_again = self.read_dta(path)
             tm.assert_frame_equal(written_and_read_again.set_index('index'),
                                   original)
@@ -221,7 +221,7 @@ def test_write_dta6(self):
         original['quarter'] = original['quarter'].astype(np.int32)
 
         with tm.ensure_clean() as path:
-            original.to_stata(path, None, False)
+            original.to_stata(path, None)
             written_and_read_again = self.read_dta(path)
             tm.assert_frame_equal(written_and_read_again.set_index('index'),
                                   original)
@@ -257,7 +257,7 @@ def test_read_write_dta10(self):
         original['integer'] = original['integer'].astype(np.int32)
 
         with tm.ensure_clean() as path:
-            original.to_stata(path, {'datetime': 'tc'}, False)
+            original.to_stata(path, {'datetime': 'tc'})
             written_and_read_again = self.read_dta(path)
             tm.assert_frame_equal(written_and_read_again.set_index('index'),
                                   original)
@@ -295,9 +295,9 @@ def test_read_write_dta11(self):
 
         with tm.ensure_clean() as path:
             with warnings.catch_warnings(record=True) as w:
-                original.to_stata(path, None, False)
-                np.testing.assert_equal(
-                    len(w), 1)  # should get a warning for that format.
+                original.to_stata(path, None)
+                # should get a warning for that format.
+            tm.assert_equal(len(w), 1)
 
             written_and_read_again = self.read_dta(path)
             tm.assert_frame_equal(written_and_read_again.set_index('index'), formatted)
@@ -324,13 +324,12 @@ def test_read_write_dta12(self):
 
         with tm.ensure_clean() as path:
             with warnings.catch_warnings(record=True) as w:
-                original.to_stata(path, None, False)
-                np.testing.assert_equal(
-                    len(w), 1)  # should get a warning for that format.
+                original.to_stata(path, None)
+                tm.assert_equal(len(w), 1)  # should get a warning for that format.
 
             written_and_read_again = self.read_dta(path)
             tm.assert_frame_equal(written_and_read_again.set_index('index'), formatted)
-            
+
     def test_read_write_dta13(self):
         s1 = Series(2**9, dtype=np.int16)
         s2 = Series(2**17, dtype=np.int32)
@@ -366,7 +365,7 @@ def test_read_write_reread_dta14(self):
         tm.assert_frame_equal(parsed_114, parsed_115)
 
         with tm.ensure_clean() as path:
-            parsed_114.to_stata(path, {'date_td': 'td'}, write_index=False)
+            parsed_114.to_stata(path, {'date_td': 'td'})
             written_and_read_again = self.read_dta(path)
             tm.assert_frame_equal(written_and_read_again.set_index('index'), parsed_114)
 
@@ -406,7 +405,7 @@ def test_numeric_column_names(self):
             with warnings.catch_warnings(record=True) as w:
                 tm.assert_produces_warning(original.to_stata(path), InvalidColumnName)
             # should produce a single warning
-            np.testing.assert_equal(len(w), 1)
+            tm.assert_equal(len(w), 1)
 
             written_and_read_again = self.read_dta(path)
             written_and_read_again = written_and_read_again.set_index('index')
@@ -415,7 +414,102 @@ def test_numeric_column_names(self):
             written_and_read_again.columns = map(convert_col_name, columns)
             tm.assert_frame_equal(original, written_and_read_again)
 
+    def test_nan_to_missing_value(self):
+        s1 = Series(np.arange(4.0), dtype=np.float32)
+        s2 = Series(np.arange(4.0), dtype=np.float64)
+        s1[::2] = np.nan
+        s2[1::2] = np.nan
+        original = DataFrame({'s1': s1, 's2': s2})
+        original.index.name = 'index'
+        with tm.ensure_clean() as path:
+            original.to_stata(path)
+            written_and_read_again = self.read_dta(path)
+            written_and_read_again = written_and_read_again.set_index('index')
+            tm.assert_frame_equal(written_and_read_again, original)
+
+    def test_no_index(self):
+        columns = ['x', 'y']
+        original = DataFrame(np.reshape(np.arange(10.0), (5, 2)),
+                             columns=columns)
+        original.index.name = 'index_not_written'
+        with tm.ensure_clean() as path:
+            original.to_stata(path, write_index=False)
+            written_and_read_again = self.read_dta(path)
+            tm.assertRaises(KeyError,
+                            lambda: written_and_read_again['index_not_written'])
+
+    def test_string_no_dates(self):
+        s1 = Series(['a', 'A longer string'])
+        s2 = Series([1.0, 2.0], dtype=np.float64)
+        original = DataFrame({'s1': s1, 's2': s2})
+        original.index.name = 'index'
+        with tm.ensure_clean() as path:
+            original.to_stata(path)
+            written_and_read_again = self.read_dta(path)
+            tm.assert_frame_equal(written_and_read_again.set_index('index'),
+                                  original)
+
+    def test_large_value_conversion(self):
+        s0 = Series([1, 99], dtype=np.int8)
+        s1 = Series([1, 127], dtype=np.int8)
+        s2 = Series([1, 2 ** 15 - 1], dtype=np.int16)
+        s3 = Series([1, 2 ** 63 - 1], dtype=np.int64)
+        original = DataFrame({'s0': s0, 's1': s1, 's2': s2, 's3': s3})
+        original.index.name = 'index'
+        with tm.ensure_clean() as path:
+            with warnings.catch_warnings(record=True) as w:
+                tm.assert_produces_warning(original.to_stata(path),
+                                           PossiblePrecisionLoss)
+            # should produce a single warning
+            tm.assert_equal(len(w), 1)
+
+            written_and_read_again = self.read_dta(path)
+            modified = original.copy()
+            modified['s1'] = Series(modified['s1'], dtype=np.int16)
+            modified['s2'] = Series(modified['s2'], dtype=np.int32)
+            modified['s3'] = Series(modified['s3'], dtype=np.float64)
+            tm.assert_frame_equal(written_and_read_again.set_index('index'),
+                                  modified)
+
+    def test_dates_invalid_column(self):
+        original = DataFrame([datetime(2006, 11, 19, 23, 13, 20)])
+        original.index.name = 'index'
+        with tm.ensure_clean() as path:
+            with warnings.catch_warnings(record=True) as w:
+                tm.assert_produces_warning(original.to_stata(path, {0: 'tc'}),
+                                           InvalidColumnName)
+            tm.assert_equal(len(w), 1)
+
+            written_and_read_again = self.read_dta(path)
+            modified = original.copy()
+            modified.columns = ['_0']
+            tm.assert_frame_equal(written_and_read_again.set_index('index'),
+                                  modified)
+
+    def test_date_export_formats(self):
+        columns = ['tc', 'td', 'tw', 'tm', 'tq', 'th', 'ty']
+        conversions = dict(((c, c) for c in columns))
+        data = [datetime(2006, 11, 20, 23, 13, 20)] * len(columns)
+        original = DataFrame([data], columns=columns)
+        original.index.name = 'index'
+        expected_values = [datetime(2006, 11, 20, 23, 13, 20),  # Time
+                           datetime(2006, 11, 20),  # Day
+                           datetime(2006, 11, 19),  # Week
+                           datetime(2006, 11, 1),  # Month
+                           datetime(2006, 10, 1),  # Quarter year
+                           datetime(2006, 7, 1),  # Half year
+                           datetime(2006, 1, 1)]  # Year
+
+        expected = DataFrame([expected_values], columns=columns)
+        expected.index.name = 'index'
+        with tm.ensure_clean() as path:
+            original.to_stata(path, conversions)
+            written_and_read_again = self.read_dta(path)
+            tm.assert_frame_equal(written_and_read_again.set_index('index'),
+                                  expected)
+
 
 if __name__ == '__main__':
     nose.runmodule(argv=[__file__, '-vvs', '-x', '--pdb', '--pdb-failure'],
                    exit=False)
+