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本文小編為大家詳細介紹“python應用實例分析”，內容詳細，步驟清晰，細節處理妥當，希望這篇“python應用實例分析”文章能幫助大家解決疑惑，下面跟著小編的思路慢慢深入，一起來學習新知識吧。
在本季度中，求買合生元益生菌帶動了多少奶粉新客
#naifen_vipflow.columnsss1= naifen_vipflow[[ 'flow_no','shopid_cardid','item_name']].rename(columns={'item_name':'item_name_naifen'})ss2 = ysj_vipflow[['flow_no','item_name']].rename(columns={'item_name':'item_name_ysj'})flow_no_naifen_ysj= ss1.merge(ss2, on='flow_no') # 同時購買益生菌和奶粉的 訂單 和會員#flow_no_naifen_ysjformer_quarter_start_end=['2019-10-01 00:00:00','2020-01-01 00:00:00']after_quarter_start_end=['2020-01-01 00:00:00','2020-04-01 00:00:00']groupby_list_vip =['shopid_cardid','shopid_branch','段位']groupby_list_branch=['shopid_branch','段位']#naifen_vipflow.columns#奶粉新客#每個會員第一次購買 , 也就是 新客的流水saleflow= naifen_vipflowsaleflow_first = saleflow.groupby(groupby_list_vip).oper_date.min().reset_index().rename(columns={'oper_date':'date_1st'})# 挑選出 前面季度的新客former_new =saleflow_first[(saleflow_first['date_1st']<pd.to_datetime(former_quarter_start_end[1]))&(saleflow_first['date_1st']>pd.to_datetime(former_quarter_start_end[0]))]# 后一季度的新客 ，也就是本季度after_new =saleflow_first[(saleflow_first['date_1st']<pd.to_datetime(after_quarter_start_end[1]))&(saleflow_first['date_1st']>pd.to_datetime(after_quarter_start_end[0]))]#挑選出 后一季度的流水，也就是本季度after_flow = saleflow[(saleflow['oper_date']<pd.to_datetime(after_quarter_start_end[1]))&(saleflow['oper_date']>pd.to_datetime(after_quarter_start_end[0]))]##后一季度新客中， 同時買了奶粉和益生菌的訂單號after_new_naifen_ysj= after_new.merge(flow_no_naifen_ysj)#.shopid_cardid.nunique()
整理為函數
def ysj_naifen_new(ysj_hsy_vipflow, naifen_vipflow, former_quarter_start_end=['2019-10-01 00:00:00','2020-01-01 00:00:00'] , after_quarter_start_end=['2020-01-01 00:00:00','2020-04-01 00:00:00'] , groupby_list_vip =['shopid_cardid','shopid_branch','段位']): """ 參數 ： ysj_hsy_vipflow: 益生菌的會員流水 naifen_vipflow : 奶粉 會員流水 former_quarter_start_end：上一時間段的范圍 after_quarter_start_end : 下一時間段的范圍 groupby_list_vip : 會員級別的分組，包含在groupby() 中，即groupby(groupby_list_vip) """ ss1= naifen_vipflow[[ 'flow_no','shopid_cardid','item_name']].rename(columns={'item_name':'item_name_naifen'}) ss2 = ysj_vipflow[['flow_no','item_name']].rename(columns={'item_name':'item_name_ysj'}) flow_no_naifen_ysj= ss1.merge(ss2, on='flow_no') # 同時購買合生元益生菌和 奶粉的訂單號 商品名稱 saleflow= naifen_vipflow saleflow_first = saleflow.groupby(groupby_list_vip).oper_date.min().reset_index().rename(columns={'oper_date':'date_1st'}) # 挑選出 前面季度的新客 former_new =saleflow_first[(saleflow_first['date_1st']<pd.to_datetime(former_quarter_start_end[1]))&(saleflow_first['date_1st']>pd.to_datetime(former_quarter_start_end[0]))] # 后一季度的新客 after_new =saleflow_first[(saleflow_first['date_1st']<pd.to_datetime(after_quarter_start_end[1]))&(saleflow_first['date_1st']>pd.to_datetime(after_quarter_start_end[0]))] #挑選出 后一季度的流水 after_flow = saleflow[(saleflow['oper_date']<pd.to_datetime(after_quarter_start_end[1]))&(saleflow['oper_date']>pd.to_datetime(after_quarter_start_end[0]))] ##后一季度新客中， 買了奶粉和益生菌的 after_new_naifen_ysj= after_new.merge(flow_no_naifen_ysj)#.shopid_cardid.nunique() return after_new_naifen_ysj
對結果中的會員id 計數
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