从部分分类列获取值

value_counts 从 Categorical 列(特别是包含月份信息)使用 pandas

import calendar
import random

import pandas as pd

random.seed(1)

month_names = calendar.month_name[1:]
month_names += month_names

df1 = pd.DataFrame({
    'Month': month_names,
    'Flag': [random.choice([True, False]) for _ in month_names]
})

df1['Month'] = pd.Categorical(
    df1['Month'], categories=calendar.month_name[1:], ordered=True
)
print(df1.groupby('Month')['Flag'].value_counts())

按预期打印:

Month      Flag 
January    False    2
February   True     2
March      False    2
April      True     2
May        True     2
June       False    2
July       False    1
           True     1
August     False    1
           True     1
September  False    2
October    True     2
November   False    1
           True     1
December   False    2
Name: Flag, dtype: int64

但是如果我们的 'Month' 列不包含所有可能的类别, 熊猫 抛出 ValueError

month_names = ['January', 'February', 'March']
month_names += month_names

df2 = pd.DataFrame({
    'Month': month_names,
    'Flag': [random.choice([True, False]) for _ in month_names]
})

df2['Month'] = pd.Categorical(
    df2['Month'], categories=calendar.month_name[1:], ordered=True
)
print(df2.groupby('Month')['Flag'].value_counts())

加薪:

ValueError: operands could not be broadcast together with shape (12,) (3,)

我们有什么办法能得到合适的答案吗 值\u计数 部分数据的结果?理想情况下,这将保留完整的类别,但即使没有将是一个开始。