我正在使用python进行Web编程和javascript.目前,我正在使用NetBeans,但我正在寻找另一个IDE.使用python和javascript编程时,NetBeans不是很好.有什么建议吗?
for rownum in range(0, len(self.sheet.rows) ):
for cell in self.sheet.rows[rownum]:
print cell.value
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我想用openpyxl逐行访问工作表中的所有单元格值.上面的代码工作但速度太慢.如何更快地访问所有单元格值?
lr = lm.LogisticRegression(penalty='l2', dual=True, tol=0.0001,
C=1, fit_intercept=True, intercept_scaling=1.0,
class_weight=None, random_state=None)
rd = AdaBoostClassifier( base_estimator=lr,
learning_rate=1,
n_estimators=20,
algorithm="SAMME")
##here, i am deleting unnecesseary objects
##print X.shape
##(7395, 412605)
print "20 Fold CV Score: ", np.mean(cross_validation.cross_val_score(rd, X, y, cv=20, scoring='roc_auc'))
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当我运行这个我得到这个错误:
TypeError:传递了稀疏矩阵,但需要密集数据.使用X.toarray()转换为密集的numpy数组.
然后,我改变了我的代码:
print "20 Fold CV Score: ", np.mean(cross_validation.cross_val_score(rd, X.toarray(), y, cv=20, scoring='roc_auc'))
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现在,我有以下例外:
File "/usr/lib/python2.7/dist-packages/scipy/sparse/compressed.py", line 559, in toarray
return self.tocoo(copy=False).toarray(order=order, out=out)
File "/usr/lib/python2.7/dist-packages/scipy/sparse/coo.py", line 235, in toarray
B = self._process_toarray_args(order, out)
File "/usr/lib/python2.7/dist-packages/scipy/sparse/base.py", line 628, in _process_toarray_args
return np.zeros(self.shape, …Run Code Online (Sandbox Code Playgroud) 我正在尝试使用谷歌appengine.我有这个型号:
def Human(db.Model):
name = db.StringProperty()
friends = db.SelfReferenceProperty()
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这个人有不止一个朋友.那么,如何使用google appengine来处理这个问题呢?
python ×4
java ×2
excel ×1
ide ×1
javascript ×1
numpy ×1
openpyxl ×1
performance ×1
scikit-learn ×1
tradeoff ×1
xlsx ×1