如何使用 Pandas (.map) 进行标注？

Question

在下面table

中用pandas(.map)标注

m2m_similarity.columns = ['MoviId 1','MoviId 2','similarity_score']
m2m_similarity.head(3)

我试过把label弄的有点像，很像，exacly

m2m_similarity['analysis'] = m2m_similarity['similarity_score'].map({
    0.1: 'slightly-similar', 0.2: 'slightly-similar', 0.3: 'slightly-similar', 0.4: 'slightly-similar',
    0.5: 'similar', 0.6: 'similar', 0.7: 'similar', 0.8: 'similar',0.9: 'similar', 
    1.0: 'Exacly'
})
m2m_similarity.head(3)

结果是Nan

Answer 1

尝试使用：

m2m_similarity['analysis'] = m2m_similarity['similarity_score'].replace({
    0.1: 'slightly-similar', 0.2: 'slightly-similar', 0.3: 'slightly-similar', 0.4: 'slightly-similar',
    0.5: 'similar', 0.6: 'similar', 0.7: 'similar', 0.8: 'similar',0.9: 'similar', 
    1.0: 'Exacly'
})

Answer 2

更好的方法是：

m2m_similarity['analysis'] = m2m_similarity['similarity_score'].map(lambda s: 'Exacly' if round(s, 2) == 1 else ('similar' if round(s, 2) >= 0.5 else 'slightly-similar'))

因为它将涵盖两者之间的所有选项。并且无论如何确保在 similarity_score 中你有数字而不是 strings，如果它们实际上不是高精度浮点数，你只显示第一个数字。

如何使用 Pandas (.map) 进行标注？

How to labeling with Pandas (.map)?

python

pandas

data-science

jupyter-notebook