BUG: Delegate more of Excel parsing to CSV

The idea is that we read the Excel file,
get the data, and then let the TextParser
handle the reading and parsing.

We shouldn't be doing a lot of work that
is already defined in parsers.py

In doing so, we identified several bugs:

* index_col=None was not being respected

* usecols behavior was inconsistent with
that of read_csv for list of strings and
callable inputs

* usecols was not being validated as proper
Excel column names when passed as a string.

Closes gh-18273.
Closes gh-20480.

Author: gfyoung

doc/source/io.rst

@@ -2861,7 +2861,13 @@ to be parsed.
 
    read_excel('path_to_file.xls', 'Sheet1', usecols=2)
 
-If `usecols` is a list of integers, then it is assumed to be the file column
+You can also specify a comma-delimited set of Excel columns and ranges as a string:
+
+.. code-block:: python
+
+   read_excel('path_to_file.xls', 'Sheet1', usecols='A,C:E')
+
+If ``usecols`` is a list of integers, then it is assumed to be the file column
 indices to be parsed.
 
 .. code-block:: python
@@ -2870,6 +2876,27 @@ indices to be parsed.
 
 Element order is ignored, so ``usecols=[0, 1]`` is the same as ``[1, 0]``.
 
+.. versionadded:: 0.24
+
+If ``usecols`` is a list of strings, it is assumed that each string corresponds
+to a column name provided either by the user in ``names`` or inferred from the
+document header row(s). Those strings define which columns will be parsed:
+
+.. code-block:: python
+
+    read_excel('path_to_file.xls', 'Sheet1', usecols=['foo', 'bar'])
+
+Element order is ignored, so ``usecols=['baz', 'joe']`` is the same as ``['joe', 'baz']``.
+
+.. versionadded:: 0.24
+
+If ``usecols`` is callable, the callable function will be evaluated against
+the column names, returning names where the callable function evaluates to ``True``.
+
+.. code-block:: python
+
+    read_excel('path_to_file.xls', 'Sheet1', usecols=lambda x: x.isalpha())
+
 Parsing Dates
 +++++++++++++
 

doc/source/whatsnew/v0.24.0.txt

@@ -238,6 +238,7 @@ Other Enhancements
 - Added :meth:`Interval.overlaps`, :meth:`IntervalArray.overlaps`, and :meth:`IntervalIndex.overlaps` for determining overlaps between interval-like objects (:issue:`21998`)
 - :func:`~DataFrame.to_parquet` now supports writing a ``DataFrame`` as a directory of parquet files partitioned by a subset of the columns when ``engine = 'pyarrow'`` (:issue:`23283`)
 - :meth:`Timestamp.tz_localize`, :meth:`DatetimeIndex.tz_localize`, and :meth:`Series.tz_localize` have gained the ``nonexistent`` argument for alternative handling of nonexistent times. See :ref:`timeseries.timezone_nonexsistent` (:issue:`8917`)
+- :meth:`read_excel()` now accepts ``usecols`` as a list of column names or callable (:issue:`18273`)
 
 .. _whatsnew_0240.api_breaking:
 
@@ -1299,6 +1300,8 @@ Notice how we now instead output ``np.nan`` itself instead of a stringified form
 - Bug in :meth:`HDFStore.append` when appending a :class:`DataFrame` with an empty string column and ``min_itemsize`` < 8 (:issue:`12242`)
 - Bug in :meth:`read_csv()` in which :class:`MultiIndex` index names were being improperly handled in the cases when they were not provided (:issue:`23484`)
 - Bug in :meth:`read_html()` in which the error message was not displaying the valid flavors when an invalid one was provided (:issue:`23549`)
+- Bug in :meth:`read_excel()` in which ``index_col=None`` was not being respected and parsing index columns anyway (:issue:`20480`)
+- Bug in :meth:`read_excel()` in which ``usecols`` was not being validated for proper column names when passed in as a string (:issue:`20480`)
 
 Plotting
 ^^^^^^^^

pandas/io/excel.py

@@ -17,8 +17,7 @@
 import pandas._libs.json as json
 import pandas.compat as compat
 from pandas.compat import (
-    OrderedDict, add_metaclass, lrange, map, range, reduce, string_types, u,
-    zip)
+    OrderedDict, add_metaclass, lrange, map, range, string_types, u, zip)
 from pandas.errors import EmptyDataError
 from pandas.util._decorators import Appender, deprecate_kwarg
 
@@ -93,13 +92,22 @@
     .. deprecated:: 0.21.0
        Pass in `usecols` instead.
 
-usecols : int or list, default None
-    * If None then parse all columns,
-    * If int then indicates last column to be parsed
-    * If list of ints then indicates list of column numbers to be parsed
-    * If string then indicates comma separated list of Excel column letters and
-      column ranges (e.g. "A:E" or "A,C,E:F").  Ranges are inclusive of
+usecols : int, str, list-like, or callable default None
+    * If None, then parse all columns,
+    * If int, then indicates last column to be parsed
+    * If string, then indicates comma separated list of Excel column letters
+      and column ranges (e.g. "A:E" or "A,C,E:F"). Ranges are inclusive of
       both sides.
+    * If list of ints, then indicates list of column numbers to be parsed.
+    * If list of strings, then indicates list of column names to be parsed.
+
+    .. versionadded:: 0.24.0
+
+    * If callable, then evaluate each column name against it and parse the
+      column if the callable returns ``True``.
+
+    .. versionadded:: 0.24.0
+
 squeeze : boolean, default False
     If the parsed data only contains one column then return a Series
 dtype : Type name or dict of column -> type, default None
@@ -466,39 +474,6 @@ def parse(self,
                                  convert_float=convert_float,
                                  **kwds)
 
-    def _should_parse(self, i, usecols):
-
-        def _range2cols(areas):
-            """
-            Convert comma separated list of column names and column ranges to a
-            list of 0-based column indexes.
-
-            >>> _range2cols('A:E')
-            [0, 1, 2, 3, 4]
-            >>> _range2cols('A,C,Z:AB')
-            [0, 2, 25, 26, 27]
-            """
-            def _excel2num(x):
-                "Convert Excel column name like 'AB' to 0-based column index"
-                return reduce(lambda s, a: s * 26 + ord(a) - ord('A') + 1,
-                              x.upper().strip(), 0) - 1
-
-            cols = []
-            for rng in areas.split(','):
-                if ':' in rng:
-                    rng = rng.split(':')
-                    cols += lrange(_excel2num(rng[0]), _excel2num(rng[1]) + 1)
-                else:
-                    cols.append(_excel2num(rng))
-            return cols
-
-        if isinstance(usecols, int):
-            return i <= usecols
-        elif isinstance(usecols, compat.string_types):
-            return i in _range2cols(usecols)
-        else:
-            return i in usecols
-
     def _parse_excel(self,
                      sheet_name=0,
                      header=0,
@@ -527,10 +502,6 @@ def _parse_excel(self,
             raise NotImplementedError("chunksize keyword of read_excel "
                                       "is not implemented")
 
-        if parse_dates is True and index_col is None:
-            warnings.warn("The 'parse_dates=True' keyword of read_excel was "
-                          "provided without an 'index_col' keyword value.")
-
         import xlrd
         from xlrd import (xldate, XL_CELL_DATE,
                           XL_CELL_ERROR, XL_CELL_BOOLEAN,
@@ -620,17 +591,13 @@ def _parse_cell(cell_contents, cell_typ):
                 sheet = self.book.sheet_by_index(asheetname)
 
             data = []
-            should_parse = {}
+            usecols = _maybe_convert_usecols(usecols)
 
             for i in range(sheet.nrows):
                 row = []
                 for j, (value, typ) in enumerate(zip(sheet.row_values(i),
                                                      sheet.row_types(i))):
-                    if usecols is not None and j not in should_parse:
-                        should_parse[j] = self._should_parse(j, usecols)
-
-                    if usecols is None or should_parse[j]:
-                        row.append(_parse_cell(value, typ))
+                    row.append(_parse_cell(value, typ))
                 data.append(row)
 
             if sheet.nrows == 0:
@@ -642,31 +609,30 @@ def _parse_cell(cell_contents, cell_typ):
 
             # forward fill and pull out names for MultiIndex column
             header_names = None
-            if header is not None:
-                if is_list_like(header):
-                    header_names = []
-                    control_row = [True] * len(data[0])
-                    for row in header:
-                        if is_integer(skiprows):
-                            row += skiprows
-
-                        data[row], control_row = _fill_mi_header(
-                            data[row], control_row)
-                        header_name, data[row] = _pop_header_name(
-                            data[row], index_col)
-                        header_names.append(header_name)
-                else:
-                    data[header] = _trim_excel_header(data[header])
+            if header is not None and is_list_like(header):
+                header_names = []
+                control_row = [True] * len(data[0])
+
+                for row in header:
+                    if is_integer(skiprows):
+                        row += skiprows
+
+                    data[row], control_row = _fill_mi_header(
+                        data[row], control_row)
+                    header_name, _ = _pop_header_name(
+                        data[row], index_col)
+                    header_names.append(header_name)
 
             if is_list_like(index_col):
-                # forward fill values for MultiIndex index
+                # Forward fill values for MultiIndex index.
                 if not is_list_like(header):
                     offset = 1 + header
                 else:
                     offset = 1 + max(header)
 
                 for col in index_col:
                     last = data[offset][col]
+
                     for row in range(offset + 1, len(data)):
                         if data[row][col] == '' or data[row][col] is None:
                             data[row][col] = last
@@ -693,11 +659,14 @@ def _parse_cell(cell_contents, cell_typ):
                                     thousands=thousands,
                                     comment=comment,
                                     skipfooter=skipfooter,
+                                    usecols=usecols,
                                     **kwds)
 
                 output[asheetname] = parser.read(nrows=nrows)
+
                 if names is not None:
                     output[asheetname].columns = names
+
                 if not squeeze or isinstance(output[asheetname], DataFrame):
                     output[asheetname].columns = output[
                         asheetname].columns.set_names(header_names)
@@ -726,6 +695,97 @@ def __exit__(self, exc_type, exc_value, traceback):
         self.close()
 
 
+def _excel2num(x):
+    """
+    Convert Excel column name like 'AB' to 0-based column index.
+
+    Parameters
+    ----------
+    x : str
+        The Excel column name to convert to a 0-based column index.
+
+    Returns
+    -------
+    num : int
+        The column index corresponding to the name.
+
+    Raises
+    ------
+    ValueError
+        Part of the Excel column name was invalid.
+    """
+    index = 0
+
+    for c in x.upper().strip():
+        cp = ord(c)
+
+        if cp < ord("A") or cp > ord("Z"):
+            raise ValueError("Invalid column name: {x}".format(x=x))
+
+        index = index * 26 + cp - ord("A") + 1
+
+    return index - 1
+
+
+def _range2cols(areas):
+    """
+    Convert comma separated list of column names and ranges to indices.
+
+    Parameters
+    ----------
+    areas : str
+        A string containing a sequence of column ranges (or areas).
+
+    Returns
+    -------
+    cols : list
+        A list of 0-based column indices.
+
+    Examples
+    --------
+    >>> _range2cols('A:E')
+    [0, 1, 2, 3, 4]
+    >>> _range2cols('A,C,Z:AB')
+    [0, 2, 25, 26, 27]
+    """
+    cols = []
+
+    for rng in areas.split(","):
+        if ":" in rng:
+            rng = rng.split(":")
+            cols.extend(lrange(_excel2num(rng[0]), _excel2num(rng[1]) + 1))
+        else:
+            cols.append(_excel2num(rng))
+
+    return cols
+
+
+def _maybe_convert_usecols(usecols):
+    """
+    Convert `usecols` into a compatible format for parsing in `parsers.py`.
+
+    Parameters
+    ----------
+    usecols : object
+        The use-columns object to potentially convert.
+
+    Returns
+    -------
+    converted : object
+        The compatible format of `usecols`.
+    """
+    if usecols is None:
+        return usecols
+
+    if is_integer(usecols):
+        return lrange(usecols + 1)
+
+    if isinstance(usecols, compat.string_types):
+        return _range2cols(usecols)
+
+    return usecols
+
+
 def _validate_freeze_panes(freeze_panes):
     if freeze_panes is not None:
         if (