CEADS parser walkthrough#

This notebook is the practical guide for parsing the currently supported CEADS China provincial MRIO workbooks in MARIO.

What this notebook covers#

where the supported CEADS workbooks come from;
which workbook family MARIO currently parses;
what format= means;
how to use path= and year=;
how MARIO maps imports, exports, and the optional CO2 row.

Source pages#

CEADS portal: Input-Output Tables
Scientific Data descriptor: China’s Provincial Multi-Regional Input-Output Database for 2018 and 2020
Dataset DOI: 10.6084/m9.figshare.29927291

MARIO does not download the CEADS workbook automatically. Download the workbook locally before running this notebook.

Main entry point#

For normal user workflows, the public entry point is mario.parse_ceads(...).

At the moment, that entry point supports only table="IOT".

What MARIO currently parses#

The current backend is intentionally narrow:

it parses local Excel workbooks only;
it currently supports the verified CEADS provincial MRIO workbook family for 2018 and 2020;
it reads the English table sheet, not the Chinese one;
it uses the Sector and Province sheets as metadata support.

What `format` means#

format= is the parser-side layout selector. It does not mean “which CEADS dataset” you are using; it means “which workbook structure” MARIO should expect.

At the moment, MARIO supports:

format="auto": inspect the workbook and resolve the known layout automatically;
format="ceads_provincial_workbook": force the verified 2018/2020 workbook structure.

Configure local paths#

Set MARIO_DOC_DATA to the root folder where you keep real parser datasets, or set MARIO_CEADS_PATH directly to the CEADS folder.

Expected local structure:

CEADS/
├── MRIO 2018.xlsx
└── MRIO 2020.xlsx

[1]:

from pathlib import Path
import os

import mario

Parse one explicit workbook#

Use this form when you want to parse a specific downloaded workbook.

[2]:

db_2018 = mario.parse_ceads(
    path="/path/to/MRIO 2018.xlsx",
    format="auto",
    calc_all=False,
)

db_2018

INFO Parser: inspecting CEADS workbook MRIO 2018.xlsx.
INFO Parser: detected CEADS workbook format ceads_provincial_workbook for year 2018 using sheet Table_2018_English Version.
INFO Parser: reading CEADS workbook MRIO 2018.xlsx sheet Table_2018_English Version.
INFO Parser: CEADS payload ready with shapes Z=(1302, 1302), Y=(1302, 186), V=(5, 1302), E=(1, 1302), EY=(1, 186).
INFO Metadata: initialized.

[2]:

name = CEADS China Provincial MRIO 2018
table = IOT
scenarios = ['baseline']
Factor of production = 5
Satellite account = 1
Consumption category = 6
Region = 31
Sector = 42

Parse from a directory#

Use this form when one folder contains multiple CEADS workbooks. In that case, year= selects which workbook to parse.

[3]:

db_2020 = mario.parse_ceads(
    path="/path/to/MRIO 2020.xlsx",
    year=2020,
    calc_all=False,
)

db_2020

INFO Parser: inspecting CEADS workbook MRIO 2020.xlsx.
INFO Parser: detected CEADS workbook format ceads_provincial_workbook for year 2020 using sheet Table_2020_English Version.
INFO Parser: reading CEADS workbook MRIO 2020.xlsx sheet Table_2020_English Version.
INFO Parser: CEADS payload ready with shapes Z=(1302, 1302), Y=(1302, 186), V=(5, 1302), E=(1, 1302), EY=(1, 186).
INFO Metadata: initialized.

[3]:

name = CEADS China Provincial MRIO 2020
table = IOT
scenarios = ['baseline']
Factor of production = 5
Satellite account = 1
Consumption category = 6
Region = 31
Sector = 42

How the parsed table is mapped#

For the verified CEADS workbook family:

Z comes from the main intermediate-transactions block;
Y contains the domestic final-demand block plus one Exports column per province;
V contains Imports plus the four value-added rows exposed by the workbook;
E contains the optional CO2 (Mt) row when it exists;
EY is initialized at zero.

[4]:

db_2020["baseline"].keys()

[4]:

dict_keys(['Z', 'Y', 'V', 'E', 'EY'])

inspect the parsed database#

Once parsed, the result is a standard MARIO database.

[5]:

db_2020.get_index("Region")

[5]:

['Beijing',
 'Tianjin',
 'Hebei',
 'Shanxi',
 'Inner Mongolia',
 'Liaoning',
 'Jilin',
 'Heilongjiang',
 'Shanghai',
 'Jiangsu',
 'Zhejiang',
 'Anhui',
 'Fujian',
 'Jiangxi',
 'Shandong',
 'He0',
 'Hubei',
 'Hu0',
 'Guangdong',
 'Guangxi',
 'Hai0',
 'Chongqing',
 'Sichuan',
 'Guizhou',
 'Yun0',
 'Xizang',
 'Shaanxi',
 'Gansu',
 'Qinghai',
 'Ningxia',
 'Xinjiang']

[6]:

db_2020.get_index("Sector")

[6]:

['Agriculture, Forestry, Animal Husbandry and Fishery',
 'Mining and washing of coal',
 'Extraction of petroleum and natural gas',
 'Mining and processing of metal ores',
 'Mining and processing of nonmetal and other ores',
 'Food and tobacco processing',
 'Textile industry',
 'Manufacture of leather, fur, feather and related products',
 'Processing of timber and furniture',
 'Manufacture of paper, printing and articles for culture, education and sport activity',
 'Processing of petroleum, coking, processing of nuclear fuel',
 'Manufacture of chemical products',
 'Manuf. of non -metallic mineral products',
 'Smelting and processing of metals',
 'Manufacture of metal products',
 'Manufacture of general purpose machinery',
 'Manufacture of special purpose machinery',
 'Manufacture of transport equipment',
 'Manufacture of electrical machinery and equipment',
 'Manufacture of communication equipment, computers and other electronic equipment',
 'Manufacture of measuring instruments',
 'Other manufacturing',
 'Comprehensive use of waste resources',
 'Repair of metal products, machinery and equipment',
 'Production and distribution of electric power and heat power',
 'Production and distribution of gas',
 'Production and distribution of tap water',
 'Construction',
 'Wholesale and retail trades',
 'Transport, storage, and postal services',
 'Accommodation and catering',
 'Information transfer, software and information technology services',
 'Fi0ce',
 'Real estate',
 'Leasing and commercial services',
 'Scientific research and polytechnic services',
 'Administration of water, environment, and public facilities',
 'Resident, repair and other services',
 'Education',
 'Health care and social work',
 'Culture, sports, and entertainment',
 'Public administration, social insurance, and social organizations']

[7]:

db_2020.get_index("Satellite account")

[7]:

['CO2']

Caveats#

The CEADS portal lists older provincial MRIO releases too, such as 2012, 2015, and 2017. MARIO does not assume those older workbook families are compatible until they are checked explicitly.
The parser intentionally relies on the English worksheet. If only a Chinese worksheet is available, that workbook is not currently supported.
The workbook metadata sheets can contain minor naming inconsistencies. For the verified 2018/2020 family, MARIO treats the main transaction axis as canonical when such conflicts appear.

Download this notebook