Add some checks for assuring that the left_index and right_index parameters have correct types. Tests added.

Author: ivallesp

doc/source/whatsnew/v0.19.1.txt

@@ -25,6 +25,13 @@ Performance Improvements
 
 
 
+.. _whatsnew_0191.new_features:
+
+New features
+~~~~~~~~~~~~
+- Add checks to assure that left_index and right_index are of type bool
+
+
 
 .. _whatsnew_0191.bug_fixes:
 

pandas/tools/merge.py

@@ -472,6 +472,15 @@ def __init__(self, left, right, how='inner', on=None,
                 'can not merge DataFrame with instance of '
                 'type {0}'.format(type(right)))
 
+        if not is_bool(left_index):
+            raise ValueError(
+                'left_index parameter must be of type bool, not '
+                '{0}'.format(type(left_index)))
+        if not is_bool(right_index):
+            raise ValueError(
+                'right_index parameter must be of type bool, not '
+                '{0}'.format(type(right_index)))
+
         # warn user when merging between different levels
         if left.columns.nlevels != right.columns.nlevels:
             msg = ('merging between different levels can give an unintended '

pandas/tools/tests/test_merge.py

@@ -109,6 +109,15 @@ def test_merge_misspecified(self):
         self.assertRaises(ValueError, merge, self.df, self.df2,
                           left_on=['key1'], right_on=['key1', 'key2'])
 
+    def test_index_and_on_parameters_confusion(self):
+        self.assertRaises(ValueError, merge, self.df, self.df2, how='left',
+                          left_index=False, right_index=['key1', 'key2'])
+        self.assertRaises(ValueError, merge, self.df, self.df2, how='left',
+                          left_index=['key1', 'key2'], right_index=False)
+        self.assertRaises(ValueError, merge, self.df, self.df2, how='left',
+                          left_index=['key1', 'key2'],
+                          right_index=['key1', 'key2'])
+
     def test_merge_overlap(self):
         merged = merge(self.left, self.left, on='key')
         exp_len = (self.left['key'].value_counts() ** 2).sum()