python 按列分组并按层次结构选择

Question

我有一个数据框，例如:

col-a   col-b
1       None
1       Failed
1       Passed
2       None
2       Passed
3       Inconclusive
3       Passed

以及术语的层次结构:

Failed > Inconclusive > Passed > None

我怎样才能得到类似的东西:

1       Failed
2       Passed
3       Inconclusive

谢谢!

Answer 1

您可以为 Series.map 创建的列创建字典，然后使用 DataFrame.sort_values 按两列排序并通过 DataFrame.drop_duplicates 获取每组的第一个唯一行:

d = {'Failed':0,'Inconclusive':1, 'Passed':2, None: 3}
df['new'] = df['col-b'].map(d)
df = df.sort_values(['col-a', 'new']).drop_duplicates('col-a').drop('new', 1)
print (df)
   col-a         col-b
1      1        Failed
4      2        Passed
5      3  Inconclusive

另一个想法 DataFrameGroupBy.idxmin :

d = {'Failed':0,'Inconclusive':1, 'Passed':2, None: 3}
df =  df.loc[df['col-b'].map(d).groupby(df['col-a']).idxmin()]
print (df)
   col-a         col-b
1      1        Failed
4      2        Passed
5      3  Inconclusive