diff --git a/akshare/__init__.py b/akshare/__init__.py
index ab78cef083f9c15dbcc30fbd6c1639af0765594a..d1141ed2f7bc20a9d947187cfd8209b2d8cec0f8 100644
--- a/akshare/__init__.py
+++ b/akshare/__init__.py
@@ -942,9 +942,10 @@ amac_manager_cancelled_info # 中国证券投资基金业协会-信息公示-诚
 0.5.14: add: stock_market_fund_flow, stock_sector_fund_flow, stock_individual_fund_flow_rank
 0.5.15: fix: baidu_index
 0.5.16: add: fund_em_value_estimation
+0.5.17: fix: delete macro_euro zero value
 """
 
-__version__ = "0.5.16"
+__version__ = "0.5.17"
 __author__ = "Albert King"
 
 """
diff --git a/akshare/air/air_zhenqi.py b/akshare/air/air_zhenqi.py
index 581a49fdca420f3ab8e793bafc14b6479c509570..d1d7ac8c2e6b60e19029001830a7d8f16be12bb7 100644
--- a/akshare/air/air_zhenqi.py
+++ b/akshare/air/air_zhenqi.py
@@ -278,12 +278,12 @@ if __name__ == "__main__":
     print(air_city_list_map)
 
     air_quality_watch_point_df = air_quality_watch_point(
-        city="杭州", start_date="2018-01-01", end_date="2020-05-01"
+        city="杭州", start_date="2018-01-01", end_date="2020-05-13"
     )
     print(air_quality_watch_point_df)
 
     air_quality_hist_df = air_quality_hist(
-        city="北京", period="month", start_date="2019-04-25", end_date="2020-05-01"
+        city="北京", period="day", start_date="2019-04-25", end_date="2020-05-13"
     )
     print(air_quality_hist_df)
 
diff --git a/akshare/economic/macro_euro.py b/akshare/economic/macro_euro.py
index 4759a92fa4159cd4b13c03d686220c190afedfc6..ed5c3656d432541f76fcb826b9002954c3c12b16 100644
--- a/akshare/economic/macro_euro.py
+++ b/akshare/economic/macro_euro.py
@@ -42,6 +42,8 @@ def macro_euro_gdp_yoy():
     value_df.index = pd.to_datetime(date_list)
     temp_df = value_df["今值(%)"]
     temp_df.name = "gdp_yoy"
+    temp_df = temp_df.astype(float)
+    temp_df = temp_df[temp_df != 0]
     return temp_df
 
 
@@ -66,6 +68,8 @@ def macro_euro_cpi_mom():
     value_df.index = pd.to_datetime(date_list)
     temp_df = value_df["今值(%)"]
     temp_df.name = "cpi_mom"
+    temp_df = temp_df.astype(float)
+    temp_df = temp_df[temp_df != 0]
     return temp_df
 
 
@@ -90,6 +94,8 @@ def macro_euro_cpi_yoy():
     value_df.index = pd.to_datetime(date_list)
     temp_df = value_df["今值(%)"]
     temp_df.name = "cpi_yoy"
+    temp_df = temp_df.astype(float)
+    temp_df = temp_df[temp_df != 0]
     return temp_df
 
 
@@ -114,6 +120,8 @@ def macro_euro_ppi_mom():
     value_df.index = pd.to_datetime(date_list)
     temp_df = value_df["今值(%)"]
     temp_df.name = "ppi_mom"
+    temp_df = temp_df.astype(float)
+    temp_df = temp_df[temp_df != 0]
     return temp_df
 
 
@@ -162,6 +170,8 @@ def macro_euro_employment_change_qoq():
     value_df.index = pd.to_datetime(date_list)
     temp_df = value_df["今值(%)"]
     temp_df.name = "employment_change_qoq"
+    temp_df = temp_df.astype(float)
+    temp_df = temp_df[temp_df != 0]
     return temp_df
 
 
@@ -186,6 +196,8 @@ def macro_euro_unemployment_rate_mom():
     value_df.index = pd.to_datetime(date_list)
     temp_df = value_df["今值(%)"]
     temp_df.name = "unemployment_rate_mom"
+    temp_df = temp_df.astype(float)
+    temp_df = temp_df[temp_df != 0]
     return temp_df
 
 
@@ -210,6 +222,8 @@ def macro_euro_trade_balance():
     value_df.index = pd.to_datetime(date_list)
     temp_df = value_df["今值(亿欧元)"]
     temp_df.name = "trade_balance"
+    temp_df = temp_df.astype(float)
+    temp_df = temp_df[temp_df != 0]
     return temp_df
 
 
@@ -234,6 +248,8 @@ def macro_euro_current_account_mom():
     value_df.index = pd.to_datetime(date_list)
     temp_df = value_df["今值(亿欧元)"]
     temp_df.name = "current_account_mom"
+    temp_df = temp_df.astype(float)
+    temp_df = temp_df[temp_df != 0]
     return temp_df
 
 
@@ -282,6 +298,8 @@ def macro_euro_manufacturing_pmi():
     value_df.index = pd.to_datetime(date_list)
     temp_df = value_df["今值"]
     temp_df.name = "manufacturing_pmi"
+    temp_df = temp_df.astype(float)
+    temp_df = temp_df[temp_df != 0]
     return temp_df
 
 
@@ -306,6 +324,8 @@ def macro_euro_services_pmi():
     value_df.index = pd.to_datetime(date_list)
     temp_df = value_df["今值"]
     temp_df.name = "services_pmi"
+    temp_df = temp_df.astype(float)
+    temp_df = temp_df[temp_df != 0]
     return temp_df
 
 
@@ -330,6 +350,8 @@ def macro_euro_zew_economic_sentiment():
     value_df.index = pd.to_datetime(date_list)
     temp_df = value_df["今值"]
     temp_df.name = "zew_economic_sentiment"
+    temp_df = temp_df.astype(float)
+    temp_df = temp_df[temp_df != 0]
     return temp_df
 
 
diff --git a/akshare/economic/macro_usa.py b/akshare/economic/macro_usa.py
index 3a6443ccfef102508161f98ba0a2867b99012893..bc2cb15e8c58ad94a60d584acd6c499518a6fad8 100644
--- a/akshare/economic/macro_usa.py
+++ b/akshare/economic/macro_usa.py
@@ -2290,7 +2290,7 @@ def macro_usa_nfib_small_business():
 def macro_usa_michigan_consumer_sentiment():
     """
     美国密歇根大学消费者信心指数初值报告, 数据区间从19700301-至今
-    https://cdn.jin10.com/dc/reports/dc_usa_michigan_consumer_sentiment_all.js?v=1578576228
+    https://datacenter.jin10.com/reportType/dc_usa_michigan_consumer_sentiment
     :return: 美国密歇根大学消费者信心指数初值报告-今值
     :rtype: pandas.Series
     """
@@ -2635,4 +2635,4 @@ if __name__ == "__main__":
     # plt.show()
     # 金十数据中心-经济指标-美国-其他-美国原油产量报告
     macro_usa_crude_inner_df = macro_usa_crude_inner()
-    print(macro_usa_crude_inner_df.columns)
+    print(macro_usa_crude_inner_df)
diff --git a/docs/changelog.md b/docs/changelog.md
index d33bccd8ab5023008064414e79d7510283a86499..8d82ec1eb26d61b3593429fbee5eeb66e5b5df6b 100644
--- a/docs/changelog.md
+++ b/docs/changelog.md
@@ -1303,4 +1303,6 @@ amac_manager_cancelled_info # 中国证券投资基金业协会-信息公示-诚
 0.5.15: fix: baidu_index
 
 0.5.16: add: fund_em_value_estimation
+
+0.5.17: fix: delete macro_euro zero value
 ```
diff --git a/docs/introduction.md b/docs/introduction.md
index 08a5a2116283ea9c61148b6d10bdbe50b47c150f..58fbd66d5a5aee03ea01b373018d0f8afef8bfb6 100644
--- a/docs/introduction.md
+++ b/docs/introduction.md
@@ -3,7 +3,7 @@
 **风险提示:[AkShare](https://github.com/jindaxiang/akshare) 项目所采集的数据皆来自公开的数据源,不涉及任何个人隐私数据和非公开数据。
 同时本项目提供的数据接口及相关数据仅用于学术研究,任何个人、机构及团体使用本项目的数据接口及相关数据请注意商业风险。**
 
-1. 本文档更新于 **2020-05-13**;
+1. 本文档更新于 **2020-05-14**;
 
 2. 如有库、文档及数据的相关问题, 请在 [AkShare Issues](https://github.com/jindaxiang/akshare/issues) 中提 Issues;