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- android - 多次调用 OnPrimaryClipChangedListener
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- android.database.CursorIndexOutOfBoundsException : Index 0 requested, 光标大小为 0
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<分区>
数据:
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我正在研究来自 Kaggle 的泰坦尼克号数据集。我试图找出每个 Pclass 的男性和女性幸存者的百分比。
分组示例:
train_df.groupby(['Pclass','Sex','Survived']).apply(lambda x: len(x)).unstack(2).plot(kind='bar')
这向我展示了每个类(class)中有多少男性和女性幸存下来以及多少人没有幸存下来，但从视觉上看每个类(class)中男性和女性的存活率会更好。
期望的结果:
train_df.groupby(['Pclass','Sex','Survived']).apply(lambda x: len(x)).unstack(2)[1]/(train_df.groupby(['Pclass','Sex','Survived']).apply(lambda x: len(x)).unstack(2)[1]+train_df.groupby(['Pclass','Sex','Survived']).apply(lambda x: len(x)).unstack(2)[0])
这看起来像是得到了想要的结果，但我想知道是否有更多的 pythonic 方法来做到这一点？就像 normalize=True 选项会很巧妙。
最终目标:
每个 Pclass 中每个性别的存活率条形图
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