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Python Discussion :

invalid literal for int() with base 10:


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Python

  1. #1
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    Par défaut invalid literal for int() with base 10:
    bonjour les amis il y a un bug dans le problème de détection de spam
    ci joint le code et l'erreur
    merci s'il vous plait pour votre aide
    Code : Sélectionner tout - Visualiser dans une fenêtre à part
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    spam_training = 100*int(y_train.sum())/int(len(y_train))
    spam_testing  = 100*int(y_test.sum())/int(len(y_test))
     
    print("Pourcentage de spam dans les données d'entrainement \t : {:0.2f}%.".format(spam_training))
    print("pourcentage dans les données de test \t : {:0.2f}%.".format(spam_testing))

    ci joint les logs
    invalid literal for int() with base 10: '0.21,0.28,0.5,0,0.14,0.28,0.21,0.07,0,0.94,0.21,0.79,0.65,0.21,0.14,0.14,0.07,0.28,3.47,0,1.59,0,0.43,0.43,0,0,0,0,0,0,0,0,0,0,0,0,0.07,0,0,0,0,0,0,0,0,0,0,0,0,0.132,0,0.372,0.18,0.048,5.114,101,1028

  2. #2
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    Par défaut
    Vérifier le résultat de y_train.sum() et de y_test.sum().

    Remarque :
    len() retourne nativement un entier, pourquoi le caster ?

    Edit :
    Pour info,
    Ceci fonctionne : int(12.5).
    Ceci ne fonctionne pas : int('12.5').
    Ceci encore moins : int('12.5, 12.6, 12.7').

  3. #3
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    Par défaut
    Salut,

    Le message d'erreur a la bonne idée d'afficher la chaine de caractères qu'on lui a demandé de convertir en entier:
    Citation Envoyé par s2a07 Voir le message
    ci joint les logs
    invalid literal for int() with base 10: '0.21,0.28,0.5,0,0.14,0.28,0.21,0.07,0,0.94,0.21,0.79,0.65,0.21,0.14,0.14,0.07,0.28,3.47,0,1.59,0,0.43,0.43,0,0,0,0,0,0,0,0,0,0,0,0,0.07,0,0,0,0,0,0,0,0,0,0,0,0,0.132,0,0.372,0.18,0.048,5.114,101,1028
    Et si on regarde d'où ça vient, c'est manifestement le retour de l'appel à y_train.sum

    S'il y a une solution, elle dépendra de ce que vous cherchiez à faire (l'intention)... et ça c'est dans votre tête.

    edit: désolé je n'avais pas vu qu'une réponse avait déjà été postée. Mon approche étant différente, je ne la détruis pas.

    - W
    Architectures post-modernes.
    Python sur DVP c'est aussi des FAQs, des cours et tutoriels

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    Par défaut
    bonjour les amis merci beaucoup pour vos reponses le résultat de print(ytrain) est un fichier csv de pourcentage de spam mais il me sort enfin je pense
    0 0.21\t0.28\t0.5\t0\t0.14\t0.28\t0.21\t0.07\t0\...
    2 0\t0\t0\t0\t0.63\t0\t0.31\t0.63\t0.31\t0.63\t0...
    3 0\t0\t0\t0\t0.63\t0\t0.31\t0.63\t0.31\t0.63\t0...
    4 0\t0\t0\t0\t1.85\t0\t0\t1.85\t0\t0\t0\t0\t0\t0...
    5 0\t0\t0\t0\t1.92\t0\t0\t0\t0\t0.64\t0.96\t1.28...
    ...
    4595 0.31\t0\t0.62\t0\t0\t0.31\t0\t0\t0\t0\t0\t1.88...
    4596 0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0...
    4597 0.3\t0\t0.3\t0\t0\t0\t0\t0\t0\t0\t0\t1.8\t0.3\...
    4598 0.96\t0\t0\t0\t0.32\t0\t0\t0\t0\t0\t0\t0.32\t0...
    4599 0\t0\t0.65\t0\t0\t0\t0\t0\t0\t0\t0\t0\t0.65\t0...
    Name: Spam, Length: 3692, dtype: object
    je reprends une étude de l'université d'harvard
    et je ne vois pas et la somme me donne
    9,0,0.58,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.19,0,0,0.39,0,0.19,0,0,0.239,0,0.444,0,0,1.626,8,122,00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.31 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.65 0 0 0 0.127 0 0 0 0 0 1.137 3 33 0 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1.31,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.65,0,0,0,0.127,0,0,0,0,0,1.137,3,33,00.35 0 0.71 0 0 0 0 0 0 0.35 0 0.71 0 0 0 0 0 0 7.47 0 1.06 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.35 0 0 0 0 0.067 0 0 0 0 1 1 40 0 0.35,0,0.71,0,0,0,0,0,0,0.35,0,0.71,0,0,0,0,0,0,7.47,0,1.06,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.35,0,0,0,0,0.067,0,0,0,0,1,1,40,00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.29 0 0 4.38 0 0.58 0 0 0 0 0 0 0 0.29 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.58 0 0 0 0.055 0.167 0 0 0 0 1.122 3 55 0 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.29,0,0,4.38,0,0.58,0,0,0,0,0,0,0,0.29,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.58,0,0,0,0.055,0.167,0,0,0,0,1.122,3,55,00 0 0 0 0 0 0 0 0 0 0 1.25 0 0 0 0 0 0 2.5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.62 0 0 0 0 0.62 0.62 0 0 0 0 0.356 0 0.594 0 0 2.125 16 34 0 0,0,0,0,0,0,0,0,0,0,0,1.25,0,0,0,0,0,0,2.5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.62,0,0,0,0,0.62,0.62,0,0,0,0,0.356,0,0.594,0,0,2.125,16,34,00 0 1.09 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2.19 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3.29 0 0 0 0.191 0 0 0 0 3 15 51 0 0,0,1.09,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2.19,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3.29,0,0,0,0.191,0,0,0,0,3,15,51,00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0 0 3.176 15 54 0 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,3.176,15,54,00 0 0 0 0 0 0 0 0 0 0 1.36 0 0 0 0 0 0 4.1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.36 0 0 0 0 0 1.36 1.36 0 0 0 0 0 0.234 0 0 2.076 15 27 0 0,0,0,0,0,0,0,0,0,0,0,1.36,0,0,0,0,0,0,4.1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1.36,0,0,0,0,0,1.36,1.36,0,0,0,0,0,0.234,0,0,2.076,15,27,00 0 0 0 0 0 0 0 0 0 0 0.95 0 0 0 0 0 0 3.8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.95 0 0 0 0 0 0 0 0 2.85 0 0 0 0 0 0.175 0 0 3.125 15 50 0 0,0,0,0,0,0,0,0,0,0,0,0.95,0,0,0,0,0,0,3.8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.95,0,0,0,0,0,0,0,0,2.85,0,0,0,0,0,0.175,0,0,3.125,15,50,00 0 0 0 0.35 0.35 0 0 0 0 0 0 0 0 0 0 0 0 1.79 0 0.71 0 0 0 0.35 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.35 0 0 0 0.064 0 0 0 0 1.27 8 61 0 0,0,0,0,0.35,0.35,0,0,0,0,0,0,0,0,0,0,0,0,1.79,0,0.71,0,0,0,0.35,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.35,0,0,0,0.064,0,0,0,0,1.27,8,61,00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3.17 0 0 0 0 0 3.17 0 0 0 0 0 0 0 0 0 0 0 0 0 1.58 0 0 0 0 0 1.58 1.58 0 0 0 0 0 0 0 0 2.071 14 29 0 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3.17,0,0,0,0,0,3.17,0,0,0,0,0,0,0,0,0,0,0,0,0,1.58,0,0,0,0,0,1.58,1.58,0,0,0,0,0,0,0,0,2.071,14,29,00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.61 0 1.61 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.61 0 0 0 0 0 0 0 0 4.83 0 0 0 0 0 0 0 0 3.117 15 53 0 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1.61,0,1.61,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1.61,0,0,0,0,0,0,0,0,4.83,0,0,0,0,0,0,0,0,3.117,15,53,00 0 0 0 0 0.74 0 0 0 0 0 0.74 1.49 0 0 0 0 0 1.49 0 1.49 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.74 0 0 0 0 0 0 0 0 0 1.36 3 34 0 0,0,0,0,0,0.74,0,0,0,0,0,0.74,1.49,0,0,0,0,0,1.49,0,1.49,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.74,0,0,0,0,0,0,0,0,0,1.36,3,34,00.78 0 0 0 0 0 0 0 0 0 0 0.78 0 0 0 0 0 0 2.36 0 0.78 0 0 0 0 0.78 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.78 0 0 0 0 0 0 0 0 0 0 1.875 8 30 0 0.78,0,0,0,0,0,0,0,0,0,0,0.78,0,0,0,0,0,0,2.36,0,0.78,0,0,0,0,0.78,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.78,0,0,0,0,0,0,0,0,0,0,1.875,8,30,00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3.84 0 1.28 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.28 0 0 0 0 0 0 0 1.28 0 0 0 0 0 0 1.548 0 0 3.222 14 58 0 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3.84,0,1.28,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1.28,0,0,0,0,0,0,0,1.28,0,0,0,0,0,0,1.548,0,0,3.222,14,58,00 0 0 0 0 0 0 0 0 0 0 2.38 0 0 0 0 0 0 2.38 0 2.38 0 0 0 2.38 2.38 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.404 0 0.809 0.809 0 3 11 27 0 0,0,0,0,0,0,0,0,0,0,0,2.38,0,0,0,0,0,0,2.38,0,2.38,0,0,0,2.38,2.38,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.404,0,0.809,0.809,0,3,11,27,00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2.08 0 0 0 0 0 0 0 0 6.25 0 0 0 0 0 0 0 0 3.125 15 50 0 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2.08,0,0,0,0,0,0,0,0,6.25,0,0,0,0,0,0,0,0,3.125,15,50,00 0 0.64 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3.22 0 0 0 0 0 0.64 0 0 0 0 0 0 0 0 0 0 0 0.64 0 0.64 0 0 0 0 0 1.29 2.58 0 0 0 0.348 0 1.16 0 0 3.121 15 103 0 0,0,0.64,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3.22,0,0,0,0,0,0.64,0,0,0,0,0,0,0,0,0,0,0,0.64,0,0.64,0,0,0,0,0,1.29,2.58,0,0,0,0.348,0,1.16,0,0,3.121,15,103,00 0 0 0 0 0 0 0 0 0 0 2.22 0 0 0 0 0 0 0.74 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.74 0 0 0 0 0 0 0 0 2.22 0 0 0 0 0 0 0.277 0 2.72 15 68 0 0,0,0,0,0,0,0,0,0,0,0,2.22,0,0,0,0,0,0,0.74,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.74,0,0,0,0,0,0,0,0,2.22,0,0,0,0,0,0,0.277,0,2.72,15,68,00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.01 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.01 0 0 0 0 0 0 0 0 5.05 0 0 0 0 0 0 0 0 3.043 15 70 0 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1.01,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1.01,0,0,0,0,0,0,0,0,5.05,0,0,0,0,0,0,0,0,3.043,15,70,00.23 0 0 0 0 0.11 0 0 0 0.11 0 0.11 0.11 0 0 0 0 0.23 2.15 0 0.35 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.23 0 0 0 0 0 0 0.71 0.11 0 0 0 0.126 0 0.021 0 0 1.198 5 145 0 0.23,0,0,0,0,0.11,0,0,0,0.11,0,0.11,0.11,0,0,0,0,0.23,2.15,0,0.35,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.23,0,0,0,0,0,0,0.71,0.11,0,0,0,0.126,0,0.021,0,0,1.198,5,145,00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2.13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.85 0 0.42 0 0 0 0 0 0.85 3.84 0 0 0 0 0 0 0 0 2.769 15 180 0 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0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.58 0 0 0 0.185 0 0 0 0.092 2.468 11 79 0 0,0,0,0,0,0,0,0,0,0,0,0.58,0,0,0,0.58,0,0,2.9,0,0.58,0.58,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.58,0,0,0,0.185,0,0,0,0.092,2.468,11,79,00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6.89 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3.44 0 0 0 0 0 0 0 0 1 1 8 0 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6.89,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3.44,0,0,0,0,0,0,0,0,1,1,8,00 0 1.25 0 2.5 0 0 0 0 0 0 0 0.62 0 0 0 0 0 0.62 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.62 0 0 1.25 0.62 0.62 0 0 0 0.111 0 0 0 0 1.285 4 27 0 0,0,1.25,0,2.5,0,0,0,0,0,0,0,0.62,0,0,0,0,0,0.62,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.62,0,0,1.25,0.62,0.62,0,0,0,0.111,0,0,0,0,1.285,4,27,00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7.69 0 0 0 0 0 1.052 0 0 1 1 6 0 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7.69,0,0,0,0,0,1.052,0,0,1,1,6,00 0 0 0 0 0 0 0 0 0 0 1.61 0 0 0 0 0 0 6.45 0 0 0 0 0 0 0 0 0 0 1.61 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.61 0 0 0 0.63 0 0 0 0 1.727 5 19 0 0,0,0,0,0,0,0,0,0,0,0,1.61,0,0,0,0,0,0,6.45,0,0,0,0,0,0,0,0,0,0,1.61,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1.61,0,0,0,0.63,0,0,0,0,1.727,5,19,00 0 1.19 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.59 3.57 0 1.19 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.59 0 0 0 0 0 0 0 0 1 1 24 0 0,0,1.19,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.59,3.57,0,1.19,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.59,0,0,0,0,0,0,0,0,1,1,24,00.31 0 0.62 0 0 0.31 0 0 0 0 0 1.88 0 0 0 0 0 0 0.62 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.31 0.31 0.31 0 0 0 0.232 0 0 0 0 1.142 3 88 0 0.31,0,0.62,0,0,0.31,0,0,0,0,0,1.88,0,0,0,0,0,0,0.62,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.31,0.31,0.31,0,0,0,0.232,0,0,0,0,1.142,3,88,00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0.353 0 0 1.555 4 14 0 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0.353,0,0,1.555,4,14,00.3 0 0.3 0 0 0 0 0 0 0 0 1.8 0.3 0 0 0 0 0.9 1.5 0 0.3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.2 0 0 0.102 0.718 0 0 0 0 1.404 6 118 0 0.3,0,0.3,0,0,0,0,0,0,0,0,1.8,0.3,0,0,0,0,0.9,1.5,0,0.3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1.2,0,0,0.102,0.718,0,0,0,0,1.404,6,118,00.96 0 0 0 0.32 0 0 0 0 0 0 0.32 0 0 0 0 0 0 1.93 0 0.32 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.32 0 0.32 0 0 0 0.057 0 0 0 0 1.147 5 78 0 0.96,0,0,0,0.32,0,0,0,0,0,0,0.32,0,0,0,0,0,0,1.93,0,0.32,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.32,0,0.32,0,0,0,0.057,0,0,0,0,1.147,5,78,00 0 0.65 0 0 0 0 0 0 0 0 0 0.65 0 0 0 0 0 4.6 0 0.65 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1.97 0.65 0 0 0 0 0 0.125 0 0 1.25 5 40 0 0,0,0.65,0,0,0,0,0,0,0,0,0,0.65,0,0,0,0,0,4.6,0,0.65,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1.97,0.65,0,0,0,0,0,0.125,0,0,1.25,5,40,0
    bref pour celui qui peux comprendre ça chapeau

    merci d'avance

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    Citation Envoyé par s2a07 Voir le message
    bref pour celui qui peux comprendre ça chapeau
    Si ces données sortent d'une étude, leur interprétation (ce que ça représente et ce qu'on peut en faire) devrait être décrite dans le document. Mais je ne vois pas en quoi l'interprétation de ces données (et la lecture de cette étude) concerne la programmation Python: on est plutôt dans le domaine de la sécurité ou dans des mesures de la pollution des réseaux sociaux (côté interprétation).

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    merci mais la variable dont le label est spam est de type object qui est un fichier csv avec separateur tab est le pourcentage de spam et j'utilise python pour détecter si c'est un spam ou pas
    a tu compris ma demarche moi aussi je ne suis pas dans la tete de celui qui a fait l'étude je reprends ces traveau et je constate qu il calcul une somme de pourcentage si j'ai bien compris
    es ce que l'on est dacccord
    en tout cas merci
    donc comment calcul t'ont une somme sur un fichier csv voila le problème svp ?

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    Citation Envoyé par s2a07 Voir le message
    donc comment calcul t'ont une somme sur un fichier csv voila le problème svp ?
    Le préalable est de savoir ce que représentent ces données et de justifier les éventuels traitements qu'on voudra/pourra faire dessus.
    Sinon à partir d'un tableau de dimension MxN, faire la somme de l'ensemble, de certaines colonnes, des x premiers nombres tirés au hasard,... produira un résultat sans aucune signification.

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    tu parles d'une étude existante ? est-elle dispo en ligne? si oui, mettre un lien.
    tu dis que ta variable contient des pourcentages, ok mais des pourcentages de quoi par rapport à quoi ?
    tu as 4600 lignes et un certain nombre de colonnes, à quoi correspondent ces lignes et ces colonnes ?

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    merci mais aprés une reflexion je crois qu'il calcul la moyenne d'une liste afin de calculer une fréquence de spam
    qu'en pensez vous

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    Citation Envoyé par s2a07 Voir le message
    merci mais aprés une reflexion je crois qu'il calcul la moyenne d'une liste afin de calculer une fréquence de spam
    Le fichier CSV est un tableau à 2 dimensions et non une liste, qu'allez vous bien pouvoir faire avec cela?
    Puis comment passer de "pourcentage de spam" à des fréquences (des occurrences par unité de temps)?

    Vous en êtes toujours à définir la nature des données (ce qui passe par lire l'étude qui va avec...).

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    merci a mon avis le fichier csv est convertit en liste avec separateur (,) et il calcul le pourcentage de spam par unite de longeur je pense que c'est ca
    les donnée viennent je crois de l'uci spambase mais il n'y pas de texte c'est ca qui est bizzare
    merci d'avance

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    Citation Envoyé par s2a07 Voir le message
    merci a mon avis le fichier csv est convertit en liste avec separateur (,) et il calcul le pourcentage de spam par unite de longeur je pense que c'est ca
    Par unité de longueur de quoi?
    Rien ne vous empêche de charger le CSV dans un tableau numpy et de faire ce que vous voulez côté calcul avec (ça pourrait servir à choisir les numéros du prochain loto...)

    Citation Envoyé par s2a07 Voir le message
    les donnée viennent je crois de l'uci spambase mais il n'y pas de texte c'est ca qui est bizzare
    Ce qui est bizarre, c'est votre attitude: plutôt que de ne pas trop savoir ce qu'est ce fichier autant aller en récupérer un à la source.

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    si tu dis que ça vient de uci spam base, une recherche google mène à ça (parmi les résultats) => https://archive.ics.uci.edu/dataset/94/spambase
    et sur cette page, il y a la description des colonnes. Dans le fichier zip à télécharger du site, on retrouve les infos de colonnes dans les fichiers spambase.Documentation et aussi dans spambase.names (tous les fichiers sont lisibles par le bloc-note ou autre éditeur texte)
    chaque ligne correspond un email du lot de test, les colonnes a des fréquences de mots et de caractères (correspondant au nom des colonnes) et à d'autres critères (longueur des mots en majuscule par exemple) et dans la dernière, si le mail a été identifié comme spam ou pas.

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