查找组中最频繁的观察 [英] Find most frequent observation in group

问题描述

DataFrame:

DataFrame:

B = pd.DataFrame({'b':['II','II','II','II','II','I','I','I'],
                  'MOST_FREQUENT':['1', '2', '2', '1', '1','1','2','2']})

我需要在每个组的MOST_FREQUENT列中获得最频繁的值:

I need to get the most frequent value in a column MOST_FREQUENT for each group:

pd.DataFrame({'b':['I','II'],
                      'MOST_FREQUENT':['2','1']})

我找到的唯一线索-mode()，但不适用于DataFrameGroupBy

The only clue i found - mode(), but is not applieble to DataFrameGroupBy

我需要一个解决方案，该解决方案满足熊猫的.agg()功能

I need a solution, which satisfies the pandas' .agg() function

推荐答案

您可以使用apply:

print (B.groupby('b')['MOST_FREQUENT'].apply(lambda x: x.mode())
        .reset_index(level=1, drop=True).reset_index())
    b MOST_FREQUENT
0   I             2
1  II             1

另一种解决方案是使用 SeriesGroupBy.value_counts 并返回第一个index值，因为value_counts对值进行排序:

Another solution is use SeriesGroupBy.value_counts and return first index value, because value_counts sorts values:

print (B.groupby('b')['MOST_FREQUENT'].apply(lambda x: x.value_counts().index[0])
        .reset_index())
    b MOST_FREQUENT
0   I             2
1  II             1

您可以使用 most_common

You can use most_common

from collections import Counter
print (B.groupby(['b']).agg(lambda x: Counter(x).most_common(1)[0][0]).reset_index())
    b MOST_FREQUENT
0   I             2
1  II             1

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