series数据转化为dataframe数据
转化的同时进行筛选
temp数据类型
import pandas as pd
import matplotlib.pyplot as plt
#筛选理财客户
cust_isn_list = data.loc[(data.purchase_date.dt.month == data.last_etl_acg_dt.dt.month+1)&(data.financial_balance>0),['cust_isn','purchase_date','purchase_account']].drop_duplicates()
#做关联
data_temp = pd.merge(data,cust_isn_list,on = ['cust_isn','purchase_date','purchase_account'],how = 'inner')
#选出购买大额存单当月和后一个月的快照
data_temp = data_temp.loc[(data_temp.purchase_date.dt.month == data_temp.last_etl_acg_dt.dt.month+1) | (data_temp.purchase_date.dt.month == data_temp.last_etl_acg_dt.dt.month),:]
#求出每个用户差额
temp = data_temp.groupby([data_temp.cust_isn,data_temp.purchase_date,data_temp.purchase_account]).apply(lambda x: x.financial_balance.iloc[-1]-x.financial_balance.iloc[0])
#temp为series类型数据， 把 series 类型转化为datafram数据
cust_temp = pd.DataFrame({'cust_isn':[x[0] for x in temp.loc[temp>=0].index],
'purchase_date':[x[1] for x in temp.loc[temp>=0].index],
'purchase_account':[x[2] for x in temp.loc[temp>=0].index]})