ENH: Improve error message for read_csv header argument containing non int types. GH16338.

Adds error "header must be integer or list of integers" when the header argument is a list, tuple or numpy array containing non-integers. Initially intended to read_csv, but applies to other functions with similar header arguments. GH16338 refers to a case in which the user mixes up the "names" and "header" arguments.

Revising PR16351 based on feedback

Author: mjlove12

pandas/io/parsers.py

@@ -1164,6 +1164,8 @@ def __init__(self, kwds):
         # validate header options for mi
         self.header = kwds.get('header')
         if isinstance(self.header, (list, tuple, np.ndarray)):
+            if not all(map(is_integer, self.header)):
+                raise ValueError("header must be integer or list of integers")
             if kwds.get('as_recarray'):
                 raise ValueError("cannot specify as_recarray when "
                                  "specifying a multi-index header")
@@ -1184,6 +1186,10 @@ def __init__(self, kwds):
                     raise ValueError("index_col must only contain row numbers "
                                      "when specifying a multi-index header")
 
+        #GH 16338
+        elif self.header is not None and not is_integer(self.header):
+            raise ValueError("header must be integer or list of integers")
+
         self._name_processed = False
 
         self._first_chunk = True

pandas/tests/io/parser/header.py

@@ -277,3 +277,12 @@ def test_no_header(self):
         tm.assert_index_equal(df.columns, Index(lrange(5)))
 
         tm.assert_index_equal(df2.columns, Index(names))
+
+    def test_non_int_header(self):
+        #GH 16338
+        msg = 'header must be integer or list of integers'
+        data = """1,2\n3,4"""
+        with tm.assert_raises_regex(ValueError, 'header must be integer or list of integers'):
+            self.read_csv(StringIO(data), sep=',', header = ['a','b'])
+        with tm.assert_raises_regex(ValueError, 'header must be integer or list of integers'):
+            self.read_csv(StringIO(data), sep=',', header = 'string_header')