Datawhale组队学习(Pandas) task9-分类数据

最新推荐文章于 2024-10-10 17:14:16 发布

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最新推荐文章于 2024-10-10 17:14:16 发布 · 353 阅读

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第九章分类数据

import numpy as np
import pandas as pd

cat对象

cat对象的属性

category类型，处理分类类型变量，将普通序列转化成分类变量可使用astype方法

df = pd.read_csv('data/learn_pandas.csv',usecols=['Grade', 'Name', 'Gender', 'Height', 'Weight'])
df.head()

	Grade	Name	Gender	Height	Weight
0	Freshman	Gaopeng Yang	Female	158.9	46.0
1	Freshman	Changqiang You	Male	166.5	70.0
2	Senior	Mei Sun	Male	188.9	89.0
3	Sophomore	Xiaojuan Sun	Female	NaN	41.0
4	Sophomore	Gaojuan You	Male	174.0	74.0

s = df.Grade.astype('category')

s.head()

0     Freshman
1     Freshman
2       Senior
3    Sophomore
4    Sophomore
Name: Grade, dtype: category
Categories (4, object): ['Freshman', 'Junior', 'Senior', 'Sophomore']

# 组成部分之一：类别本身，以Index类型存储
s.cat.categories

Index(['Freshman', 'Junior', 'Senior', 'Sophomore'], dtype='object')

# 组成部分之二：是否有序
s.cat.ordered

False

# 每个序列类别会被赋予唯一整数编号，编号取决于cat.categories中的顺序
# 通过codes访问该属性
s.cat.codes.head()

0    0
1    0
2    2
3    3
4    3
dtype: int8

类别的增加、删除和修改

# 类别的增加
s = s.cat.add_categories('Graduate')
s.cat.categories

Index(['Freshman', 'Junior', 'Senior', 'Sophomore', 'Graduate'], dtype='object')

# 类别的删除
s = s.cat.remove_categories('Freshman')
s.cat.categories

Index(['Junior', 'Senior', 'Sophomore', 'Graduate'], dtype='object')

# 直接设置序列的新类别，原来类别中如果存在元素不属于新类别 则被设置为缺失
s = s.cat.set_categories(['Sophomore','PhD'])
s.cat.categories
s.head()

0          NaN
1          NaN
2          NaN
3    Sophomore
4    Sophomore
Name: Grade, dtype: category
Categories (2, object): ['Sophomore', 'PhD']

# 删除未出现在序列中的类别
s = s.cat.remove_unused_categories()  # 移除了未出现的博士类别
s.cat.categories

Index(['Sophomore'], dtype='object')

# 修改
s = s.cat.rename_categories({
   
   'Sophomore':'本科二年级学生'})
s.head()

有序分类

序的建立

s = df.Grade.astype('category')
s.head

<bound method NDFrame.head of 0       Freshman
1       Freshman
2         Senior
3      Sophomore
4      Sophomore
         ...    
195       Junior
196       Senior
197       Senior
198       Senior
199    Sophomore
Name: Grade, Length: 200, dtype: category
Categories (4, object): ['Freshman', 'Junior', 'Senior', 'Sophomore']>

s = s.cat.reorder_categories(['Freshman', 'Sophomore', 'Junior', 'Senior'],ordered=True)
s.head()

0     Freshman
1     Freshman
2       Senior
3    Sophomore
4    Sophomore
Name: Grade, dtype: category
Categories (4, object): ['Freshman' < 'Sophomore' < 'Junior' < 'Senior']