用最频繁的列项目替换缺失值。 (Imputer())-Python scikit-learn
[英]Replace missing value with most frequent column item. (Imputer())-Python scikit-learn
问题描述
How do I replace missing value with most frequent column item.
如何用最频繁的列项目替换缺失值。 (Imputer()) in this dataset " https://archive.ics.uci.edu/ml/machine-learning-databases/voting-records/house-votes-84.data " (Imputer()) 在这个数据集中“ https://archive.ics.uci.edu/ml/machine-learning-databases/voting-records/house-votes-84.data ”
1 个解决方案
解决方案1
0 2017-10-07 17:24:08
You are going to want to replace you NaN values.您将要替换 NaN 值。
Try this -- Imputation of missing values for categories in pandas试试这个—— 对熊猫中类别的缺失值进行插补
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