python - 如何计算 Pandas 每一行出现次数最多的次数？

Question

df = pd.DataFrame([[1,2,3,1,5],
                   [2,3,4,4,6],
                   [7,2,2,2,5],
                   [21,3,4,3,6]], index=[1,2,3,4], columns=list('ABCDE'))

df的结果值

    A   B   C   D   E
1   1   2   3   1   5
2   2   3   4   4   6
3   7   2   2   2   5
4   21  3   4   3   6

我怎么知道每行中哪个数字出现次数最多？

例如:

row 1: 1    appears two times
row 2: 4    appears two times
row 3: 2    appears three times

等等....

Answer 1

你可以使用 apply和 value_counts获得值和出现次数 concat加入他们:

value = df.apply(lambda x: x.value_counts().index[0], axis=1)
count = df.apply(lambda x: x.value_counts().iloc[0], axis=1)

out = pd.concat([value, count], axis=1).reset_index()

out.columns = ['row_num', 'val', 'appearing']
out['row_num'] = 'row ' + out['row_num'].astype(str) + ':'
out['appearing'] = 'appears ' + out['appearing'].astype(str) + ' times'

In [64]: out
Out[64]:
  row_num  val        appearing
0  row 1:    1  appears 2 times
1  row 2:    4  appears 2 times
2  row 3:    2  appears 3 times
3  row 4:    3  appears 2 times