Refactoring and add support for timedelta

- Refactored _conv_value
- Added support to write timedelta to xls files
- Added tests for Interval and timedelta support
- Closes issue 9155

Author: cbertinato

doc/source/whatsnew/v0.23.0.txt

@@ -489,6 +489,8 @@ I/O
 - Bug in :func:`DataFrame.to_latex()` where pairs of braces meant to serve as invisible placeholders were escaped (:issue:`18667`)
 - Bug in :func:`read_json` where large numeric values were causing an ``OverflowError`` (:issue:`18842`)
 - Bug in :func:`DataFrame.to_parquet` where an exception was raised if the write destination is S3 (:issue:`19134`)
+- Type ``Interval`` now supported in :func:`DataFrame.to_excel` for all Excel file types (:issue:`19242`)
+- Type ``timedelta`` now supported in :func:`DataFrame.to_excel` for xls file type (:issue:`19242`, :issue:`9155`)
 -
 
 Plotting
@@ -549,4 +551,3 @@ Other
 ^^^^^
 
 - Improved error message when attempting to use a Python keyword as an identifier in a ``numexpr`` backed query (:issue:`18221`)
-- Bug in :func:`DataFrame.to_excel` where an exception was raised indicating unsupported type when writing a data frame containing a column of Interval type (:issue:`19242`)

pandas/io/excel.py

@@ -4,7 +4,7 @@
 
 # ---------------------------------------------------------------------
 # ExcelFile class
-from datetime import datetime, date, time, MINYEAR
+from datetime import datetime, date, time, MINYEAR, timedelta
 
 import os
 import abc
@@ -778,18 +778,19 @@ def _pop_header_name(row, index_col):
 
 
 def _conv_value(val):
-    # Convert numpy types to Python types for the Excel writers.
+    """ Convert numpy types to Python types for the Excel writers.
+        :obj:`datetime` and :obj:`date` formatting must be handled in the
+        writer. :obj:`str` representation is returned for all other types.
+    """
     if is_integer(val):
         val = int(val)
     elif is_float(val):
         val = float(val)
     elif is_bool(val):
         val = bool(val)
-    elif isinstance(val, Period):
-        val = "{val}".format(val=val)
-    elif is_list_like(val):
-        val = str(val)
-    elif isinstance(val, Interval):
+    elif isinstance(val, (datetime, date, timedelta)):
+        pass
+    else:
         val = str(val)
 
     return val
@@ -1464,6 +1465,12 @@ def write_cells(self, cells, sheet_name=None, startrow=0, startcol=0,
             elif isinstance(cell.val, date):
                 num_format_str = self.date_format
 
+            if isinstance(cell.val, timedelta):
+                delta = cell.val
+                val = (delta.days + (float(delta.seconds)
+                                     + float(delta.microseconds) / 1E6)
+                       / (60 * 60 * 24))
+
             stylekey = json.dumps(cell.style)
             if num_format_str:
                 stylekey += num_format_str

pandas/tests/io/test_excel.py

@@ -2,7 +2,7 @@
 import os
 import sys
 import warnings
-from datetime import datetime, date, time
+from datetime import datetime, date, time, timedelta
 from distutils.version import LooseVersion
 from functools import partial
 from warnings import catch_warnings
@@ -1440,6 +1440,62 @@ def test_excel_date_datetime_format(self):
                 # to use df_expected to check the result
                 tm.assert_frame_equal(rs2, df_expected)
 
+    # GH19242 - test writing Interval without labels
+    def test_to_excel_interval_no_label(self):
+        _skip_if_no_xlrd()
+
+        with ensure_clean(self.ext) as path:
+            rand = np.random.randint(-10, 10, size=(20, 2))
+            frame = DataFrame(rand)
+            intervals = pd.cut(frame[0], 10)
+            frame['new'] = intervals
+            frame_expected = DataFrame(rand)
+            frame_expected['new'] = intervals.astype(str)
+            frame.to_excel(path, 'test1')
+            reader = ExcelFile(path)
+            recons = read_excel(reader, 'test1')
+            tm.assert_frame_equal(frame_expected, recons)
+
+    # GH19242 - test writing Interval with labels
+    def test_to_excel_interval_w_label(self):
+        _skip_if_no_xlrd()
+
+        with ensure_clean(self.ext) as path:
+            rand = np.random.randint(-10, 10, size=(20, 2))
+            frame = DataFrame(rand)
+            intervals = pd.cut(frame[0], 10, labels=['A', 'B', 'C', 'D', 'E',
+                                                     'F', 'G', 'H', 'I', 'J'])
+            frame['new'] = intervals
+            frame_expected = DataFrame(rand)
+            frame_expected['new'] = pd.Series(list(intervals))
+            frame.to_excel(path, 'test1')
+            reader = ExcelFile(path)
+            recons = read_excel(reader, 'test1')
+            tm.assert_frame_equal(frame_expected, recons)
+
+    # GH 19242 & GH9155 - test writing timedelta to xls
+    def test_to_excel_timedelta(self):
+        _skip_if_no_xlrd()
+
+        with ensure_clean('.xls') as path:
+            rand = np.random.randint(-10, 10, size=(20, 1))
+            frame = DataFrame(rand, columns=['A'])
+            frame['new'] = frame['A'].apply(lambda x: timedelta(seconds=x))
+            frame_expected = DataFrame(rand, columns=['A'])
+            delta = frame_expected['A'].apply(lambda x: timedelta(seconds=x))
+
+            def timedelta_rep(x):
+                return (x.days + (float(x.seconds)
+                                  + float(x.microseconds) / 1E6)
+                        / (60 * 60 * 24))
+
+            frame_expected['new'] = delta.apply(timedelta_rep)
+            frame.to_excel(path, 'test1')
+            reader = ExcelFile(path)
+            recons = read_excel(reader, 'test1')
+
+            tm.assert_frame_equal(frame_expected, recons)
+
     def test_to_excel_periodindex(self):
         _skip_if_no_xlrd()