pandas中 透视表与交叉表常用属性

pandas中透视表与交叉表使用pivot_table()和crosstab()实现

透视表pivot_table()

import pandas as pd
import numpy as np
detail=pd.Dataframe({'order_id':[1,2,3,4,5],
                     'counts':[1,2,1,3,1],
                     'amounts':[35,66,23,12,44]，
                     'dishes_name':['铁板牛肉','土豆丝','白饭','辣椒','豆腐']
})
#1.pivot_table:默认聚合方式，自动过滤掉非数值型数据, aggfunc = 'mean',默认返回均值，返回order_id为行索引
detail_pivot=pd.pivot_table(detail[['order_id','counts','dishes_name']],index='order_id')
print(detail_pivot)

#多个index：使用order_id,dishes_name作为行所有索引的透视表
detail_pivot=pd.pivot_table(detail[['order_id','counts','amounts','dishes_name']],index=['order_id','dishes_name'],aggfunc=np.sum)
print(detail_pivot)

#columns 表列分组键：#values显示自己的想要的列，当不存在时显示NAN
detail_pivot=pd.pivot_table(detail[['order_id','counts','amounts','dishes_name']],
                             index=['order_id'],columns='dishes_name',
                            aggfunc=np.sum,values='counts')
print(detail_pivot)
#填充缺失值为0，加一个函数   fill_value=0
#添加汇总开关，   margins = True

交叉表crosstab()

不同：crosstab函数index,columns,values,输入都是从dataframe中直接取值

detail_crosstab = pd.crosstab(
index=detail['order_id'],
columns=detail['dishes_name'],
values=detail['counts'],
aggfunc=np.sum
)