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 # ä¸å›½è¯åˆ¸æŠ•资基金业å会-ä¿¡æ¯å…¬ç¤º-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="æå·ž", start_date="2018-01-01", end_date="2020-05-01" + city="æå·ž", 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(): """ ç¾Žå›½å¯†æ‡æ ¹å¤§å¦æ¶ˆè´¹è€…信心指数åˆå€¼æŠ¥å‘Š, æ•°æ®åŒºé—´ä»Ž19700301-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: ç¾Žå›½å¯†æ‡æ ¹å¤§å¦æ¶ˆè´¹è€…信心指数åˆå€¼æŠ¥å‘Š-今值 :rtype: pandas.Series """ @@ -2635,4 +2635,4 @@ if __name__ == "__main__": # plt.show() # 金忕°æ®ä¸å¿ƒ-ç»æµŽæŒ‡æ ‡-美国-å…¶ä»–-ç¾Žå›½åŽŸæ²¹äº§é‡æŠ¥å‘Š 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 # ä¸å›½è¯åˆ¸æŠ•资基金业å会-ä¿¡æ¯å…¬ç¤º-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æç¤ºï¼š[AkShare](https://github.com/jindaxiang/akshare) 项目所采集的数æ®çš†æ¥è‡ªå…¬å¼€çš„æ•°æ®æºï¼Œä¸æ¶‰åŠä»»ä½•个人éšç§æ•°æ®å’Œéžå…¬å¼€æ•°æ®ã€‚ åŒæ—¶æœ¬é¡¹ç›®æä¾›çš„æ•°æ®æŽ¥å£åŠç›¸å…³æ•°æ®ä»…ç”¨äºŽå¦æœ¯ç ”ç©¶ï¼Œä»»ä½•ä¸ªäººã€æœºæž„åŠå›¢ä½“ä½¿ç”¨æœ¬é¡¹ç›®çš„æ•°æ®æŽ¥å£åŠç›¸å…³æ•°æ®è¯·æ³¨æ„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. å¦‚æœ‰åº“ã€æ–‡æ¡£åŠæ•°æ®çš„相关问题, 请在 [AkShare Issues](https://github.com/jindaxiang/akshare/issues) 䏿 Issues;