DOC: improve some Excel docstring (#16658)

(cherry picked from commit d915c7e)

Author: chris-b1

doc/source/io.rst

@@ -712,6 +712,16 @@ index column inference and discard the last column, pass ``index_col=False``:
     pd.read_csv(StringIO(data))
     pd.read_csv(StringIO(data), index_col=False)
 
+If a subset of data is being parsed using the ``usecols`` option, the
+``index_col`` specification is based on that subset, not the original data.
+
+.. ipython:: python
+
+    data = 'a,b,c\n4,apple,bat,\n8,orange,cow,'
+    print(data)
+    pd.read_csv(StringIO(data), usecols=['b', 'c'])
+    pd.read_csv(StringIO(data), usecols=['b', 'c'], index_col=0)
+
 .. _io.parse_dates:
 
 Date Handling

pandas/io/excel.py

@@ -79,7 +79,9 @@
 index_col : int, list of ints, default None
     Column (0-indexed) to use as the row labels of the DataFrame.
     Pass None if there is no such column.  If a list is passed,
-    those columns will be combined into a ``MultiIndex``
+    those columns will be combined into a ``MultiIndex``.  If a
+    subset of data is selected with ``parse_cols``, index_col
+    is based on the subset.
 names : array-like, default None
     List of column names to use. If file contains no header row,
     then you should explicitly pass header=None
@@ -90,7 +92,7 @@
     content.
 dtype : Type name or dict of column -> type, default None
     Data type for data or columns. E.g. {'a': np.float64, 'b': np.int32}
-    Use `str` or `object` to preserve and not interpret dtype.
+    Use `object` to preserve data as stored in Excel and not interpret dtype.
     If converters are specified, they will be applied INSTEAD
     of dtype conversion.
 
@@ -110,8 +112,9 @@
     * 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 column names and
-      column ranges (e.g. "A:E" or "A,C,E:F")
+    * 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.
 squeeze : boolean, default False
     If the parsed data only contains one column then return a Series
 na_values : scalar, str, list-like, or dict, default None