如何获取一列中最频繁出现的值的数量? [英] How to get the number of the most frequent value in a column?

问题描述

我有一个数据框，我想知道给定列具有最频繁值的次数.

I have a data frame and I would like to know how many times a given column has the most frequent value.

我尝试通过以下方式进行操作:

I try to do it in the following way:

items_counts = df['item'].value_counts()
max_item = items_counts.max()

结果是:

ValueError: cannot convert float NaN to integer

据我了解，在第一行中，我得到了一系列，其中列中的值用作键，而这些值的频率用作值.因此，我只需要在系列中找到最大的值，由于某种原因，它是行不通的.有人知道如何解决这个问题吗?

As far as I understand, with the first line I get series in which the values from a column are used as key and frequency of these values are used as values. So, I just need to find the largest value in the series and, because of some reason, it does not work. Does anybody know how this problem can be solved?

推荐答案

该列中可能包含一些空值.您可以使用df = df.dropna(subset=['item'])删除它们.然后df['item'].value_counts().max()应该为您提供最大计数，而df['item'].value_counts().idxmax()应该为您提供最频繁的值.

It looks like you may have some nulls in the column. You can drop them with df = df.dropna(subset=['item']). Then df['item'].value_counts().max() should give you the max counts, and df['item'].value_counts().idxmax() should give you the most frequent value.

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