使用Python中的Pandas,只选择group by group count为1的行

时间:2015-07-12 12:17:53

标签: python pandas dataframe

我按照此处的建议过滤了我的数据:With Pandas in Python, select the highest value row for each group

    author        cat  val
0  author1  category2   15
1  author2  category4    9
2  author3  category1    7
3  author3  category3    7  

现在,我想只让作者出现在这个数据框中一次。我写了这个,但它不起作用:

def where_just_one_exists(group):
        return group.loc[group.count() == 1]
most_expensive_single_category = most_expensive_for_each_model.groupby('author', as_index = False).apply(where_just_one_exists).reset_index(drop = True)
print most_expensive_single_category

错误:

  File "/home/mike/anaconda/lib/python2.7/site-packages/pandas/core/indexing.py", line 1659, in check_bool_indexer
    raise IndexingError('Unalignable boolean Series key provided')
pandas.core.indexing.IndexingError: Unalignable boolean Series key provided

我想要的输出是:

    author        cat  val
0  author1  category2   15
1  author2  category4    9
2  author3  category1    7
3  author3  category3    7 

2 个答案:

答案 0 :(得分:4)

更容易

df.groupby('author').filter(lambda x: len(x)==1)


     author        cat  val
id                         
0   author1  category2   15
1   author2  category4    9

答案 1 :(得分:1)

我的解决方案有点复杂但仍然有效

def groupbyOneOccurrence(df):
    grouped = df.groupby("author")
    retDf = pd.DataFrame()
    for group in grouped:
        if len(group[1]._get_values) == 1:
            retDf = pd.concat([retDf, group[1]])
    return retDf


author        cat val
0  author1  category2  15
1  author2  category4   9