将值分组到自定义容器中

Question

我有一个带有 'education' 属性的数据框。值是离散的，1-16。出于交叉制表的目的，我想对这个 'education' 变量进行分箱，但使用自定义分箱 (1:8, 9:11, 12, 13:15, 16)。

我一直在玩弄 pd.cut() 但是我得到了一个无效的语法错误

adult_df_educrace['education_bins'] = pd.cut(x=adult_df_educrace['education'], bins=[1:8, 9, 10:11, 12, 13:15, 16], labels = ['Middle School or less', 'Some High School', 'High School Grad', 'Some College', 'College Grad'])

Answer 1

尝试使 bin 落在阈值之间：

bins = [0.5, 8.5, 11.5, 12.5, 15.5, 16.5]
labels=['Middle School or less', 'Some High School', 
        'High School Grad', 'Some College', 'College Grad']

adult_df_educrace['education_bins'] = pd.cut(x=adult_df_educrace['education'],
                                             bins=bins,
                                             labels=labels)

测试：

adult_df_educrace = pd.DataFrame({'education':np.arange(1,17)})

输出：

    education         education_bins
0           1  Middle School or less
1           2  Middle School or less
2           3  Middle School or less
3           4  Middle School or less
4           5  Middle School or less
5           6  Middle School or less
6           7  Middle School or less
7           8  Middle School or less
8           9       Some High School
9          10       Some High School
10         11       Some High School
11         12       High School Grad
12         13           Some College
13         14           Some College
14         15           Some College
15         16           College Grad

将值分组到自定义容器中

Grouping values into custom bins

python

numpy

bins

pandas