BUG: Fixed passing keep_default_na=False when na_values=None (GH4318)

doc/source/io.rst

@@ -546,6 +546,53 @@ The ``thousands`` keyword allows integers to be parsed correctly
 
    os.remove('tmp.csv')
 
+.. _io.na_values:
+
+NA Values
+~~~~~~~~~
+
+To control which values are parsed as missing values (which are signified by ``NaN``), specifiy a
+list of strings in ``na_values``. If you specify a number (a ``float``, like ``5.0`` or an ``integer`` like ``5``),
+the corresponding equivalent values will also imply a missing value (in this case effectively
+``[5.0,5]`` are recognized as ``NaN``.
+
+To completely override the default values that are recognized as missing, specify ``keep_default_na=False``.
+The default ``NaN`` recognized values are ``['-1.#IND', '1.#QNAN', '1.#IND', '-1.#QNAN', '#N/A N/A', 'NA',
+'#NA', 'NULL', 'NaN', 'nan']``.
+
+.. code-block:: python
+
+   read_csv(path, na_values=[5])
+
+the default values, in addition to ``5`` , ``5.0`` when interpreted as numbers are recognized as ``NaN``
+
+.. code-block:: python
+
+   read_csv(path, keep_default_na=False, na_values=[""])
+
+only an empty field will be ``NaN``
+
+.. code-block:: python
+
+   read_csv(path, keep_default_na=False, na_values=["NA", "0"])
+
+only ``NA`` and ``0`` as strings are ``NaN``
+
+.. code-block:: python
+
+   read_csv(path, na_values=["Nope"])
+
+the default values, in addition to the string ``"Nope"`` are recognized as ``NaN``
+
+.. _io.infinity:
+
+Infinity
+~~~~~~~~
+
+``inf`` like values will be parsed as ``np.inf`` (positive infinity), and ``-inf`` as ``-np.inf`` (negative infinity).
+These will ignore the case of the value, meaning ``Inf``, will also be parsed as ``np.inf``.
+
+
 .. _io.comments:
 
 Comments

doc/source/release.rst

@@ -82,6 +82,7 @@ pandas 0.13
     local variable was undefined (:issue:`4381`)
   - In ``to_json``, raise if a passed ``orient`` would cause loss of data because
     of a duplicate index (:issue:`4359`)
+  - Fixed passing ``keep_default_na=False`` when ``na_values=None`` (:issue:`4318`)
 
 pandas 0.12
 ===========

pandas/io/parsers.py

@@ -1774,8 +1774,11 @@ def _try_convert_dates(parser, colspec, data_dict, columns):
 
 def _clean_na_values(na_values, keep_default_na=True):
 
-    if na_values is None and keep_default_na:
-        na_values = _NA_VALUES
+    if na_values is None:
+        if keep_default_na:
+            na_values = _NA_VALUES
+        else:
+            na_values = []
         na_fvalues = set()
     elif isinstance(na_values, dict):
         if keep_default_na:

pandas/io/tests/test_parsers.py

@@ -108,6 +108,27 @@ def test_empty_string(self):
                                   np.nan, 'seven']})
         tm.assert_frame_equal(xp.reindex(columns=df.columns), df)
 
+
+        # GH4318, passing na_values=None and keep_default_na=False yields 'None' as a na_value
+        data = """\
+One,Two,Three
+a,1,None
+b,2,two
+,3,None
+d,4,nan
+e,5,five
+nan,6,
+g,7,seven
+"""
+        df = self.read_csv(
+            StringIO(data), keep_default_na=False)
+        xp = DataFrame({'One': ['a', 'b', '', 'd', 'e', 'nan', 'g'],
+                        'Two': [1, 2, 3, 4, 5, 6, 7],
+                        'Three': ['None', 'two', 'None', 'nan', 'five', '',
+                                  'seven']})
+        tm.assert_frame_equal(xp.reindex(columns=df.columns), df)
+
+
     def test_read_csv(self):
         if not compat.PY3:
             if 'win' in sys.platform: