Roll validate_minmax_axis into existing validate functions

Author: jbrockmendel

pandas/compat/numpy/function.py

@@ -58,10 +58,30 @@ def __call__(self, args, kwargs, fname=None,
 
 
 ARGMINMAX_DEFAULTS = dict(out=None)
-validate_argmin = CompatValidator(ARGMINMAX_DEFAULTS, fname='argmin',
-                                  method='both', max_fname_arg_count=1)
-validate_argmax = CompatValidator(ARGMINMAX_DEFAULTS, fname='argmax',
-                                  method='both', max_fname_arg_count=1)
+_validate_argmin = CompatValidator(ARGMINMAX_DEFAULTS, fname='argmin',
+                                   method='both', max_fname_arg_count=1)
+_validate_argmax = CompatValidator(ARGMINMAX_DEFAULTS, fname='argmax',
+                                   method='both', max_fname_arg_count=1)
+
+
+def validate_argmin(args, kwargs, axis=None):
+    _validate_argmin(args, kwargs)
+    validate_minmax_axis(axis)
+
+
+def validate_argmax(args, kwargs, axis=None):
+    _validate_argmax(args, kwargs)
+    validate_minmax_axis(axis)
+
+
+def validate_min(args, kwargs, axis=None):
+    _validate_min(args, kwargs)
+    validate_minmax_axis(axis)
+
+
+def validate_max(args, kwargs, axis=None):
+    _validate_max(args, kwargs)
+    validate_minmax_axis(axis)
 
 
 def process_skipna(skipna, args):
@@ -196,10 +216,10 @@ def validate_cum_func_with_skipna(skipna, args, kwargs, name):
 validate_logical_func = CompatValidator(LOGICAL_FUNC_DEFAULTS, method='kwargs')
 
 MINMAX_DEFAULTS = dict(out=None)
-validate_min = CompatValidator(MINMAX_DEFAULTS, fname='min',
-                               method='both', max_fname_arg_count=1)
-validate_max = CompatValidator(MINMAX_DEFAULTS, fname='max',
-                               method='both', max_fname_arg_count=1)
+_validate_min = CompatValidator(MINMAX_DEFAULTS, fname='min',
+                                method='both', max_fname_arg_count=1)
+_validate_max = CompatValidator(MINMAX_DEFAULTS, fname='max',
+                                method='both', max_fname_arg_count=1)
 
 RESHAPE_DEFAULTS = dict(order='C')
 validate_reshape = CompatValidator(RESHAPE_DEFAULTS, fname='reshape',

pandas/core/indexes/datetimelike.py

@@ -430,8 +430,7 @@ def min(self, axis=None, *args, **kwargs):
         --------
         numpy.ndarray.min
         """
-        nv.validate_minmax_axis(axis)
-        nv.validate_min(args, kwargs)
+        nv.validate_min(args, kwargs, axis=axis)
 
         try:
             i8 = self.asi8
@@ -459,8 +458,7 @@ def argmin(self, axis=None, *args, **kwargs):
         --------
         numpy.ndarray.argmin
         """
-        nv.validate_minmax_axis(axis)
-        nv.validate_argmin(args, kwargs)
+        nv.validate_argmin(args, kwargs, axis=axis)
 
         i8 = self.asi8
         if self.hasnans:
@@ -480,8 +478,7 @@ def max(self, axis=None, *args, **kwargs):
         --------
         numpy.ndarray.max
         """
-        nv.validate_minmax_axis(axis)
-        nv.validate_max(args, kwargs)
+        nv.validate_max(args, kwargs, axis=axis)
 
         try:
             i8 = self.asi8
@@ -509,8 +506,7 @@ def argmax(self, axis=None, *args, **kwargs):
         --------
         numpy.ndarray.argmax
         """
-        nv.validate_minmax_axis(axis)
-        nv.validate_argmax(args, kwargs)
+        nv.validate_argmax(args, kwargs, axis=axis)
 
         i8 = self.asi8
         if self.hasnans: