## 11 PMI Analysis > Interfaces implemented in this chapter are listed below; uncovered indicators are noted under “To be added” at the end. #### Purchasing Managers’ Index Interface: macro_china_pmi Source URL: http://data.eastmoney.com/cjsj/pmi.html Description: Purchasing Managers’ Index; monthly data from 200801 to present Limits: Returns all historical data in a single call Input | Name | Type | Description | |-----|-----|-----| | - | - | - | Output | Name | Type | Description | |-----------|---------|---------| | Month | object | - | | Manufacturing-Index | float64 | - | | Manufacturing-YoY | float64 | Unit: % | | Non-manufacturing-Index | float64 | - | | Non-manufacturing-YoY | float64 | Unit: % | Example ```python import meshare as ms macro_china_pmi_df = ms.macro_china_pmi() print(macro_china_pmi_df) ``` Sample data ``` Month Manufacturing-Index Manufacturing-YoY Non-manufacturing-Index Non-manufacturing-YoY 0 Oct 2022 49.2 0.000000 48.7 -7.061069 1 Sep 2022 50.1 1.008065 50.6 -4.887218 2 Aug 2022 49.4 -1.397206 52.6 10.736842 3 Jul 2022 49.0 -2.777778 53.8 0.938086 4 Jun 2022 50.2 -1.375246 54.7 2.242991 .. ... ... ... ... ... 173 May 2008 53.3 -4.308797 57.4 -7.717042 174 Apr 2008 59.2 1.023891 58.4 -3.311258 175 Mar 2008 58.4 4.099822 58.9 1.202749 176 Feb 2008 53.4 0.564972 59.3 -2.145215 177 Jan 2008 53.0 -3.811252 60.2 -0.331126 ``` #### Official manufacturing PMI Interface: macro_china_pmi_yearly Source URL: https://datacenter.jin10.com/reportType/dc_chinese_manufacturing_pmi Description: China official manufacturing PMI; data from 20050201 to present Limits: Returns all historical data in a single call Input | Name | Type | Description | |----|----|----| | - | - | - | Output | Name | Type | Description | |-----|---------|----| | Item | object | - | | Date | object | - | | Actual | float64 | - | | Forecast | float64 | - | | Previous | float64 | - | Example ```python import meshare as ms macro_china_pmi_yearly_df = ms.macro_china_pmi_yearly() print(macro_china_pmi_yearly_df) ``` Sample data ``` Item Date Actual Forecast Previous 0 China official manufacturing PMI 2005-02-01 54.7 NaN NaN 1 China official manufacturing PMI 2005-03-01 54.5 NaN 54.7 2 China official manufacturing PMI 2005-04-01 57.9 NaN 54.5 3 China official manufacturing PMI 2005-05-01 56.7 NaN 57.9 4 China official manufacturing PMI 2005-06-01 52.9 NaN 56.7 .. ... ... ... ... ... 228 China official manufacturing PMI 2023-11-30 49.4 49.7 49.5 229 China official manufacturing PMI 2023-12-31 49.0 49.5 49.4 230 China official manufacturing PMI 2024-01-31 49.2 49.2 49.0 231 China official manufacturing PMI 2024-03-01 49.1 49.1 49.2 232 China official manufacturing PMI 2024-03-31 50.8 50.1 49.1 [233 rows x 5 columns] ``` #### Official non-manufacturing PMI Interface: macro_china_non_man_pmi Source URL: https://datacenter.jin10.com/reportType/dc_chinese_non_manufacturing_pmi Description: China official non-manufacturing PMI; data from 20160101 to present Limits: Returns all historical data in a single call Input | Name | Type | Description | |----|----|----| | - | - | - | Output | Name | Type | Description | |-----|---------|---------| | Item | object | - | | Date | object | - | | Actual | float64 | Unit: % | | Forecast | float64 | Unit: % | | Previous | float64 | Unit: % | Example ```python import meshare as ms macro_china_non_man_pmi_df = ms.macro_china_non_man_pmi() print(macro_china_non_man_pmi_df) ``` Sample data ``` Item Date Actual Forecast Previous 0 China official non-manufacturing PMI report 2007-02-01 60.4 NaN NaN 1 China official non-manufacturing PMI report 2007-03-01 60.6 NaN 60.4 2 China official non-manufacturing PMI report 2007-04-01 58.2 NaN 60.6 3 China official non-manufacturing PMI report 2007-05-01 60.4 NaN 58.2 4 China official non-manufacturing PMI report 2007-06-01 62.2 NaN 60.4 .. ... ... ... ... ... 204 China official non-manufacturing PMI report 2023-11-30 50.2 51.1 50.6 205 China official non-manufacturing PMI report 2023-12-31 50.4 50.5 50.2 206 China official non-manufacturing PMI report 2024-01-31 50.7 50.6 50.4 207 China official non-manufacturing PMI report 2024-03-01 51.4 50.9 50.7 208 China official non-manufacturing PMI report 2024-03-31 53.0 51.3 51.4 [209 rows x 5 columns] ``` #### Caixin manufacturing PMI final Interface: macro_china_cx_pmi_yearly Source URL: https://datacenter.jin10.com/reportType/dc_chinese_caixin_manufacturing_pmi Description: China Caixin manufacturing PMI final; data from 20120120 to present Limits: Returns all historical data in a single call Input | Name | Type | Description | |----|----|----| | - | - | - | Output | Name | Type | Description | |-----|---------|----| | Item | object | - | | Date | object | - | | Actual | float64 | - | | Forecast | float64 | - | | Previous | float64 | - | Example ```python import meshare as ms macro_china_cx_pmi_yearly_df = ms.macro_china_cx_pmi_yearly() print(macro_china_cx_pmi_yearly_df) ``` Sample data ``` Item Date Actual Forecast Previous 0 China Caixin manufacturing PMI final report 2012-01-20 48.8 NaN 48.7 1 China Caixin manufacturing PMI final report 2012-02-22 49.7 NaN 48.8 2 China Caixin manufacturing PMI final report 2012-03-22 48.1 NaN 49.6 3 China Caixin manufacturing PMI final report 2012-04-23 49.1 NaN 48.3 4 China Caixin manufacturing PMI final report 2012-05-02 49.3 NaN 49.1 .. ... ... ... ... ... 196 China Caixin manufacturing PMI final report 2023-12-01 50.7 49.3 49.5 197 China Caixin manufacturing PMI final report 2024-01-02 50.8 50.4 50.7 198 China Caixin manufacturing PMI final report 2024-02-01 50.8 50.8 50.8 199 China Caixin manufacturing PMI final report 2024-03-01 50.9 50.7 50.8 200 China Caixin manufacturing PMI final report 2024-04-01 51.1 51.0 50.9 [201 rows x 5 columns] ``` #### Caixin services PMI Interface: macro_china_cx_services_pmi_yearly Source URL: https://datacenter.jin10.com/reportType/dc_chinese_caixin_services_pmi Description: China Caixin services PMI report; data from 20120405 to present Limits: Returns all historical data in a single call Input | Name | Type | Description | |----|----|----| | - | - | - | Output | Name | Type | Description | |-----|---------|----| | Item | object | - | | Date | object | - | | Actual | float64 | - | | Forecast | float64 | - | | Previous | float64 | - | Example ```python import meshare as ms macro_china_cx_services_pmi_yearly_df = ms.macro_china_cx_services_pmi_yearly() print(macro_china_cx_services_pmi_yearly_df) ``` Sample data ``` Item Date Actual Forecast Previous 0 China Caixin services PMI report 2012-04-05 53.3 NaN 53.9 1 China Caixin services PMI report 2012-05-04 54.1 NaN 53.3 2 China Caixin services PMI report 2012-06-05 54.7 NaN 54.1 3 China Caixin services PMI report 2012-07-04 52.3 NaN 54.7 4 China Caixin services PMI report 2012-08-03 53.1 NaN 52.3 .. ... ... ... ... ... 143 China Caixin services PMI report 2023-12-05 51.5 50.7 50.4 144 China Caixin services PMI report 2024-01-04 52.9 51.6 51.5 145 China Caixin services PMI report 2024-02-05 52.7 53.0 52.9 146 China Caixin services PMI report 2024-03-05 52.5 52.9 52.7 147 China Caixin services PMI report 2024-04-03 52.7 52.7 52.5 [148 rows x 5 columns] ```