@@ -6809,7 +6809,8 @@ def hist(self, x, bins=None, range=None, density=None, weights=None,
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return tops , bins , cbook .silent_list ('Lists of Patches' , patches )
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@_preprocess_data (replace_names = ["x" , "y" , "weights" ])
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- def hist2d (self , x , y , bins = 10 , range = None , normed = False , weights = None ,
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+ @cbook ._rename_parameter ("3.1" , "normed" , "density" )
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+ def hist2d (self , x , y , bins = 10 , range = None , density = False , weights = None ,
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cmin = None , cmax = None , ** kwargs ):
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"""
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Make a 2D histogram plot.
@@ -6843,8 +6844,9 @@ def hist2d(self, x, y, bins=10, range=None, normed=False, weights=None,
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xmax], [ymin, ymax]]``. All values outside of this range will be
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considered outliers and not tallied in the histogram.
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- normed : bool, optional, default: False
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- Normalize histogram.
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+ density : bool, optional, default: False
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+ Normalize histogram. *normed* is a deprecated synonym for the
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+ same functionality.
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weights : array_like, shape (n, ), optional, default: None
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An array of values w_i weighing each sample (x_i, y_i).
@@ -6903,7 +6905,7 @@ def hist2d(self, x, y, bins=10, range=None, normed=False, weights=None,
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"""
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h , xedges , yedges = np .histogram2d (x , y , bins = bins , range = range ,
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- normed = normed , weights = weights )
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+ normed = density , weights = weights )
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if cmin is not None :
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h [h < cmin ] = None
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