计算某个值在数据帧列中出现的频率 [英] Count the frequency that a value occurs in a dataframe column

问题描述

我有一个数据集

category
cat a
cat b
cat a

我希望能够返回类似(显示唯一值和频率)

I'd like to be able to return something like (showing unique values and frequency)

category   freq 
cat a       2
cat b       1

推荐答案

使用groupby和count:

In [37]:
df = pd.DataFrame({'a':list('abssbab')})
df.groupby('a').count()

Out[37]:

   a
a   
a  2
b  3
s  2

[3 rows x 1 columns]

查看在线文档:https://pandas.pydata.org/pandas-docs/stable/user_guide/groupby.html

还有 value_counts() 正如@DSM 所评论的，这里有很多给猫剥皮的方法

Also value_counts() as @DSM has commented, many ways to skin a cat here

In [38]:
df['a'].value_counts()

Out[38]:

b    3
a    2
s    2
dtype: int64

如果您想将频率添加回原始数据帧，请使用 transform 返回对齐的索引:

If you wanted to add frequency back to the original dataframe use transform to return an aligned index:

In [41]:
df['freq'] = df.groupby('a')['a'].transform('count')
df

Out[41]:

   a freq
0  a    2
1  b    3
2  s    2
3  s    2
4  b    3
5  a    2
6  b    3

[7 rows x 2 columns]

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