我正在尝试运行以下命令,但遇到错误:ValueError: Lengthsmustmatch to compare from sklearn.feature_selection import chi2multi-class-text-classification-with-scikit-learn-12f1e60e0a9f 输出为: ---------------------------------------------------------------------------
Value
= []]ValueError: Lengthsmustmatch to compare.df.loc[len(df['column']) !编辑
实际上,我刚刚注意到,每当我尝试对列表列中的任何值执行df.loc操作时,都会得到ValueError: Lengthsmustmatch to compare错误。
['col2'].isin(pd.unique(relevant_data['col2'].values.ravel()))]['col1'].values.ravel())raise ValueError('Lengthsmustmatch to compare')
ValueError: Lengthsmustmatch to <
df.apply(lambda x: df['P2 Actual Scan Site'] if x in valid_sites else np.nan) 两者都会给出长度错误: 尝试1- raise ValueError("Lengthsmustmatch to compare") ValueError: Lengthsmustmatch to compare 尝试2
VISTAGrantYrStarts, np.nan)-----------------------------------------------------------------------------> 102 raise ValueError("Lengthsmustmatch to compare")
103104 if i
但是,为什么我使用scipy optimize来尝试查找长度值的最低算法输出,我得到了以下错误:"ValueError: MinScore必须匹配才能进行比较“。)].shift(1) < MinBuyScore, True)> line 740, in wrapper raise ValueError('Lengthsmustmatch to compare</e