Column aliases

pandas/core/frame.py

@@ -1021,15 +1021,17 @@ def to_panel(self):
 
     to_wide = deprecate('to_wide', to_panel)
 
-    def _helper_csvexcel(self, writer, na_rep=None, cols=None, header=True,
-                         index=True, index_label=None):
+    def _helper_csvexcel(self, writer, na_rep=None, cols=None,
+                         header=True, index=True, index_label=None):
         if cols is None:
             cols = self.columns
 
         series = {}
         for k, v in self._series.iteritems():
             series[k] = v.values
-        if header:
+
+        has_aliases = isinstance(header, (tuple, list, np.ndarray))
+        if has_aliases or header:
             if index:
                 # should write something for index label
                 if index_label is None:
@@ -1050,7 +1052,15 @@ def _helper_csvexcel(self, writer, na_rep=None, cols=None, header=True,
                     index_label = [index_label]
 
                 encoded_labels = list(index_label)
-                encoded_cols = list(cols)
+                if has_aliases:
+                    if len(header) != len(cols):
+                        raise ValueError(('Writing %d cols but got %d aliases'
+                                          % (len(cols), len(header))))
+                    else:
+                        write_cols = header
+                else:
+                    write_cols = cols
+                encoded_cols = list(write_cols)
 
                 writer.writerow(encoded_labels + encoded_cols)
             else:
@@ -1075,8 +1085,8 @@ def _helper_csvexcel(self, writer, na_rep=None, cols=None, header=True,
             writer.writerow(row_fields)
 
     def to_csv(self, path_or_buf, sep=",", na_rep='', cols=None,
-               header=True, index=True, index_label=None, mode='w',
-               nanRep=None, encoding=None):
+               header=True, index=True, index_label=None,
+               mode='w', nanRep=None, encoding=None):
         """
         Write DataFrame to a comma-separated values (csv) file
 
@@ -1088,8 +1098,9 @@ def to_csv(self, path_or_buf, sep=",", na_rep='', cols=None,
             Missing data representation
         cols : sequence, optional
             Columns to write
-        header : boolean, default True
-            Write out column names
+        header : boolean or list of string, default True
+            Write out column names. If a list of string is given it is
+            assumed to be aliases for the column names
         index : boolean, default True
             Write row names (index)
         index_label : string or sequence, default None
@@ -1125,6 +1136,7 @@ def to_csv(self, path_or_buf, sep=",", na_rep='', cols=None,
             self._helper_csvexcel(csvout, na_rep=na_rep, cols=cols,
                                   header=header, index=index,
                                   index_label=index_label)
+
         finally:
             if close:
                 f.close()
@@ -1144,8 +1156,9 @@ def to_excel(self, excel_writer, sheet_name='sheet1', na_rep='',
             Missing data rep'n
         cols : sequence, optional
             Columns to write
-        header : boolean, default True
-            Write out column names
+        header : boolean or list of string, default True
+            Write out column names. If a list of string is given it is
+            assumed to be aliases for the column names
         index : boolean, default True
             Write row names (index)
         index_label : string or sequence, default None

pandas/io/parsers.py

@@ -1029,9 +1029,9 @@ def _convert_types(values, na_values):
         return values, na_count
 
     try:
-        result = lib.maybe_convert_numeric(values, na_values)
+        result = lib.maybe_convert_numeric(values, na_values, False)
     except Exception:
-        na_count = lib.sanitize_objects(values, na_values)
+        na_count = lib.sanitize_objects(values, na_values, False)
         result = values
 
     if result.dtype == np.object_:

pandas/io/tests/test_parsers.py

@@ -52,6 +52,32 @@ def setUp(self):
         self.csv2 = os.path.join(self.dirpath, 'test2.csv')
         self.xls1 = os.path.join(self.dirpath, 'test.xls')
 
+    def test_empty_string(self):
+        data = """\
+One,Two,Three
+a,1,one
+b,2,two
+,3,three
+d,4,nan
+e,5,five
+nan,6,
+g,7,seven
+"""
+        df = read_csv(StringIO(data))
+        xp = DataFrame({'One' : ['a', 'b', np.nan, 'd', 'e', np.nan, 'g'],
+                        'Two' : [1,2,3,4,5,6,7],
+                        'Three' : ['one', 'two', 'three', np.nan, 'five',
+                                   np.nan, 'seven']})
+        assert_frame_equal(xp.reindex(columns=df.columns), df)
+
+        df = read_csv(StringIO(data), na_values={'One': [], 'Three': []})
+        xp = DataFrame({'One' : ['a', 'b', '', 'd', 'e', 'nan', 'g'],
+                        'Two' : [1,2,3,4,5,6,7],
+                        'Three' : ['one', 'two', 'three', 'nan', 'five',
+                                   '', 'seven']})
+        assert_frame_equal(xp.reindex(columns=df.columns), df)
+
+
     def test_read_csv(self):
         pass
 

pandas/src/inference.pyx

@@ -241,7 +241,8 @@ def is_date_array(ndarray[object] values):
     return True
 
 
-def maybe_convert_numeric(ndarray[object] values, set na_values):
+def maybe_convert_numeric(ndarray[object] values, set na_values,
+                          convert_empty=True):
     '''
     Type inference function-- convert strings to numeric (potentially) and
     convert to proper dtype array
@@ -275,8 +276,11 @@ def maybe_convert_numeric(ndarray[object] values, set na_values):
             floats[i] = complexes[i] = nan
             seen_float = 1
         elif len(val) == 0:
-            floats[i] = complexes[i] = nan
-            seen_float = 1
+            if convert_empty:
+                floats[i] = complexes[i] = nan
+                seen_float = 1
+            else:
+                raise ValueError('Empty string encountered')
         elif util.is_complex_object(val):
             complexes[i] = val
             seen_complex = 1
@@ -573,7 +577,8 @@ def try_parse_datetime_components(ndarray[object] years, ndarray[object] months,
 
     return result
 
-def sanitize_objects(ndarray[object] values, set na_values):
+def sanitize_objects(ndarray[object] values, set na_values,
+                     convert_empty=True):
     cdef:
         Py_ssize_t i, n
         object val, onan
@@ -585,7 +590,7 @@ def sanitize_objects(ndarray[object] values, set na_values):
 
     for i from 0 <= i < n:
         val = values[i]
-        if val == '' or val in na_values:
+        if (convert_empty and val == '') or (val in na_values):
             values[i] = onan
             na_count += 1
         elif val in memo:

pandas/tests/test_frame.py

@@ -3078,6 +3078,19 @@ def test_to_csv_from_csv(self):
         result = DataFrame.from_csv(path, index_col=[0, 1, 2],
                                     parse_dates=False)
         assert_frame_equal(result, df)
+
+        # column aliases
+        col_aliases = Index(['AA', 'X', 'Y', 'Z'])
+        self.frame2.to_csv(path, header=col_aliases)
+        rs = DataFrame.from_csv(path)
+        xp = self.frame2.copy()
+        xp.columns = col_aliases
+
+        assert_frame_equal(xp, rs)
+
+        self.assertRaises(ValueError, self.frame2.to_csv, path,
+                          header=['AA', 'X'])
+
         os.remove(path)
 
     def test_to_csv_multiindex(self):
@@ -3262,6 +3275,14 @@ def test_to_excel_from_excel(self):
             np.testing.assert_equal('test1', reader.sheet_names[0])
             np.testing.assert_equal('test2', reader.sheet_names[1])
 
+            # column aliases
+            col_aliases = Index(['AA', 'X', 'Y', 'Z'])
+            self.frame2.to_excel(path, 'test1', header=col_aliases)
+            reader = ExcelFile(path)
+            rs = reader.parse('test1', index_col=0)
+            xp = self.frame2.copy()
+            xp.columns = col_aliases
+            assert_frame_equal(xp, rs)
 
             os.remove(path)