python - 如何有效地进行多个 `is not`过滤

Question

这个问题已经有答案了:

How to filter Pandas dataframe using 'in' and 'not in' like in SQL (12 个回答)

已关闭 5 年前。

这是我的代码

df = df[df['scorecard_version'] != '9.0']
df = df[df['scorecard_version'] != '8.0']
df = df[df['scorecard_version'] != '10.0']
df = df[df['scorecard_version'] != '11.0']
df = df[df['scorecard_version'] != '11.1']

有没有更短的替代方案？

Answer 1

使用isin使用 ~ 的反转 bool 掩码:

df[~df['scorecard_version'].isin(['9.0','8.0','10.0','11.0','11.1'])]

替代解决方案 numpy.in1d :

df[~np.in1d(df['scorecard_version'].values, ['9.0','8.0','10.0','11.0','11.1'])]