Oups. 9.1.52
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@ -21,7 +21,8 @@ class StatsMoyenne:
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Les valeurs NAN ou non numériques sont toujours enlevées.
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Les valeurs NAN ou non numériques sont toujours enlevées.
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Si vals is None, renvoie des zéros (utilisé pour UE bonus)
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Si vals is None, renvoie des zéros (utilisé pour UE bonus)
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"""
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"""
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if vals is None or len(vals) == 0:
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try:
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if vals is None or len(vals) == 0 or np.isnan(vals).all():
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self.moy = self.min = self.max = self.size = self.nb_vals = 0
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self.moy = self.min = self.max = self.size = self.nb_vals = 0
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else:
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else:
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self.moy = np.nanmean(vals)
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self.moy = np.nanmean(vals)
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@ -29,6 +30,8 @@ class StatsMoyenne:
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self.max = np.nanmax(vals)
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self.max = np.nanmax(vals)
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self.size = len(vals)
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self.size = len(vals)
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self.nb_vals = self.size - np.count_nonzero(np.isnan(vals))
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self.nb_vals = self.size - np.count_nonzero(np.isnan(vals))
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except TypeError: # que des NaN dans un array d'objets, ou ce genre de choses exotiques...
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self.moy = self.min = self.max = self.size = self.nb_vals = 0
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def to_dict(self):
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def to_dict(self):
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"Tous les attributs dans un dict"
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"Tous les attributs dans un dict"
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@ -1,7 +1,7 @@
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# -*- mode: python -*-
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# -*- mode: python -*-
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# -*- coding: utf-8 -*-
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# -*- coding: utf-8 -*-
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SCOVERSION = "9.1.50"
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SCOVERSION = "9.1.52"
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SCONAME = "ScoDoc"
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SCONAME = "ScoDoc"
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