@@ -10724,7 +10724,7 @@ def all(self, axis=0, bool_only=None, skipna=True, level=None, **kwargs):
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@doc (
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desc = "Return the mean absolute deviation of the values "
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- "for the requested axis." ,
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+ "over the requested axis." ,
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name1 = name1 ,
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name2 = name2 ,
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axis_descr = axis_descr ,
@@ -10860,7 +10860,7 @@ def cumprod(self, axis=None, skipna=True, *args, **kwargs):
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@doc (
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_num_doc ,
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- desc = "Return the sum of the values for the requested axis.\n \n "
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+ desc = "Return the sum of the values over the requested axis.\n \n "
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"This is equivalent to the method ``numpy.sum``." ,
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name1 = name1 ,
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name2 = name2 ,
@@ -10886,7 +10886,7 @@ def sum(
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@doc (
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_num_doc ,
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- desc = "Return the product of the values for the requested axis." ,
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+ desc = "Return the product of the values over the requested axis." ,
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name1 = name1 ,
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name2 = name2 ,
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axis_descr = axis_descr ,
@@ -10912,7 +10912,7 @@ def prod(
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@doc (
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_num_doc ,
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- desc = "Return the mean of the values for the requested axis." ,
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+ desc = "Return the mean of the values over the requested axis." ,
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name1 = name1 ,
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name2 = name2 ,
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axis_descr = axis_descr ,
@@ -10961,7 +10961,7 @@ def kurt(self, axis=None, skipna=None, level=None, numeric_only=None, **kwargs):
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@doc (
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_num_doc ,
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- desc = "Return the median of the values for the requested axis." ,
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+ desc = "Return the median of the values over the requested axis." ,
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name1 = name1 ,
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name2 = name2 ,
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axis_descr = axis_descr ,
@@ -10978,7 +10978,7 @@ def median(
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@doc (
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_num_doc ,
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- desc = "Return the maximum of the values for the requested axis.\n \n "
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+ desc = "Return the maximum of the values over the requested axis.\n \n "
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"If you want the *index* of the maximum, use ``idxmax``. This is"
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"the equivalent of the ``numpy.ndarray`` method ``argmax``." ,
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name1 = name1 ,
@@ -10995,7 +10995,7 @@ def max(self, axis=None, skipna=None, level=None, numeric_only=None, **kwargs):
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@doc (
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_num_doc ,
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- desc = "Return the minimum of the values for the requested axis.\n \n "
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+ desc = "Return the minimum of the values over the requested axis.\n \n "
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"If you want the *index* of the minimum, use ``idxmin``. This is"
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"the equivalent of the ``numpy.ndarray`` method ``argmin``." ,
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name1 = name1 ,
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