净值百分比

app/service/result_service_v2.py

@@ -341,29 +341,55 @@ class UserCustomerResultAdaptor(UserCustomerDataAdaptor):
         for index, row in p_order_df.iterrows():
             cur_fund_id = str(row["fund_id"])
             cur_fund_performance = self.all_fund_performance[cur_fund_id]
-            cur_fund_info_series = cur_fund_performance.iloc[-1]
-            # 基金净值数据
-            fund_basic_info = {"fund_name": row["fund_name"], "confirm_nav": round(row["nav"],4)}
-            fund_basic_info["cur_nav"] = round(float(self.fund_nav_total[cur_fund_id].dropna().values[-1]), 4)
-            fund_basic_info["cur_cnav"] = round(float(self.fund_cnav_total[cur_fund_id].dropna().values[-1]), 4)
-            fund_basic_info["ret_1w"] = round(cur_fund_info_series["ret_1w"]*100, 2) if cur_fund_info_series["ret_1w"] is not None else "-"    # 上周
-            fund_basic_info["ret_cum_1m"] = round(cur_fund_info_series["ret_cum_1m"]*100, 2) if cur_fund_info_series["ret_cum_1m"] is not None else "-"  # 最近一个月
-            fund_basic_info["ret_cum_6m"] = round(cur_fund_info_series["ret_cum_6m"]*100, 2) if cur_fund_info_series["ret_cum_6m"] is not None else "-"  # 最近半年
-            fund_basic_info["ret_cum_1y"] = round(cur_fund_info_series["ret_cum_1y"]*100, 2) if cur_fund_info_series["ret_cum_1y"] is not None else "-"  # 最近一年
-            fund_basic_info["ret_cum_ytd"] = round(cur_fund_info_series["ret_cum_ytd"]*100, 2) if cur_fund_info_series["ret_cum_ytd"] is not None else "-"    # 今年以来
-            fund_basic_info["ret_cum_incep"] = round(cur_fund_info_series["ret_cum_incep"]*100, 2) if cur_fund_info_series["ret_cum_incep"] is not None else "-"    # 成立以来
-            # 申购以来
-            confirm_date = pd.to_datetime(row["confirm_share_date"])
-            confirm_cnav = float(p_result_cnav_data.loc[confirm_date, cur_fund_id])
-            fund_basic_info["ret_after_confirm"] = round((fund_basic_info["cur_cnav"] - confirm_cnav)/confirm_cnav*100, 2)
-            # 分红
-            distribution_df = self.all_fund_distribution[cur_fund_id]
-            if distribution_df.empty:
-                fund_basic_info["distribution"] = "-"
+            if len(cur_fund_performance) <=0:
+                fund_basic_info = {"fund_name": row["fund_name"], "confirm_nav": round(row["nav"], 4)}
+                fund_basic_info["cur_nav"] = round(float(self.fund_nav_total[cur_fund_id].dropna().values[-1]), 4)
+                fund_basic_info["cur_cnav"] = round(float(self.fund_cnav_total[cur_fund_id].dropna().values[-1]), 4)
+                fund_basic_info["ret_1w"] = "-"  # 上周
+                fund_basic_info["ret_cum_1m"] = "-"  # 最近一个月
+                fund_basic_info["ret_cum_6m"] = "-"  # 最近半年
+                fund_basic_info["ret_cum_1y"] = "-"  # 最近一年
+                fund_basic_info["ret_cum_ytd"] = "-"  # 今年以来
+                fund_basic_info["ret_cum_incep"] = "-"  # 成立以来
+
+                # 申购以来
+                confirm_date = pd.to_datetime(row["confirm_share_date"])
+                confirm_cnav = float(p_result_cnav_data.loc[confirm_date, cur_fund_id])
+                fund_basic_info["ret_after_confirm"] = round(
+                    (fund_basic_info["cur_cnav"] - confirm_cnav) / confirm_cnav * 100, 2)
+                # 分红
+                distribution_df = self.all_fund_distribution[cur_fund_id]
+                if distribution_df.empty:
+                    fund_basic_info["distribution"] = "-"
+                else:
+                    distribution_df["price_date"] = pd.to_datetime(distribution_df["price_date"])
+                    distribution = float(
+                        distribution_df[distribution_df["price_date"] > confirm_date]["distribution"].sum())
+                    fund_basic_info["distribution"] = round(distribution, 4) if distribution != 0 else "-"
             else:
-                distribution_df["price_date"] = pd.to_datetime(distribution_df["price_date"])
-                distribution = float(distribution_df[distribution_df["price_date"] > confirm_date]["distribution"].sum())
-                fund_basic_info["distribution"] = round(distribution, 4) if distribution != 0 else "-"
+                cur_fund_info_series = cur_fund_performance.iloc[-1]
+                # 基金净值数据
+                fund_basic_info = {"fund_name": row["fund_name"], "confirm_nav": round(row["nav"],4)}
+                fund_basic_info["cur_nav"] = round(float(self.fund_nav_total[cur_fund_id].dropna().values[-1]), 4)
+                fund_basic_info["cur_cnav"] = round(float(self.fund_cnav_total[cur_fund_id].dropna().values[-1]), 4)
+                fund_basic_info["ret_1w"] = str(round(cur_fund_info_series["ret_1w"]*100, 2)) + "%" if cur_fund_info_series["ret_1w"] is not None else "-"    # 上周
+                fund_basic_info["ret_cum_1m"] = str(round(cur_fund_info_series["ret_cum_1m"]*100, 2)) + "%" if cur_fund_info_series["ret_cum_1m"] is not None else "-"  # 最近一个月
+                fund_basic_info["ret_cum_6m"] = str(round(cur_fund_info_series["ret_cum_6m"]*100, 2)) + "%" if cur_fund_info_series["ret_cum_6m"] is not None else "-"  # 最近半年
+                fund_basic_info["ret_cum_1y"] = str(round(cur_fund_info_series["ret_cum_1y"]*100, 2)) + "%" if cur_fund_info_series["ret_cum_1y"] is not None else "-"  # 最近一年
+                fund_basic_info["ret_cum_ytd"] = str(round(cur_fund_info_series["ret_cum_ytd"]*100, 2)) + "%" if cur_fund_info_series["ret_cum_ytd"] is not None else "-"    # 今年以来
+                fund_basic_info["ret_cum_incep"] = str(round(cur_fund_info_series["ret_cum_incep"]*100, 2)) + "%" if cur_fund_info_series["ret_cum_incep"] is not None else "-"    # 成立以来
+                # 申购以来
+                confirm_date = pd.to_datetime(row["confirm_share_date"])
+                confirm_cnav = float(p_result_cnav_data.loc[confirm_date, cur_fund_id])
+                fund_basic_info["ret_after_confirm"] = str(round((fund_basic_info["cur_cnav"] - confirm_cnav)/confirm_cnav*100, 2)) + "%"
+                # 分红
+                distribution_df = self.all_fund_distribution[cur_fund_id]
+                if distribution_df.empty:
+                    fund_basic_info["distribution"] = "-"
+                else:
+                    distribution_df["price_date"] = pd.to_datetime(distribution_df["price_date"])
+                    distribution = float(distribution_df[distribution_df["price_date"] > confirm_date]["distribution"].sum())
+                    fund_basic_info["distribution"] = round(distribution, 4) if distribution != 0 else "-"
 
             group_fund_basic_info.append(fund_basic_info)