indecol/pymrio

Multi-Regional Input-Output Analysis in Python.

Pymrio

Pymrio: Multi-Regional Input-Output Analysis in Python.

What is it

Pymrio is an open source tool for analysing global environmentally extended multi-regional input-output tables (EE MRIOs). Pymrio aims to provide a high-level abstraction layer for global EE MRIO databases in order to simplify common EE MRIO data tasks. Pymrio includes automatic download functions and parsers for available EE MRIO databases like EXIOBASE, WIOD and EORA26. It automatically checks parsed EE MRIOs for missing data necessary for calculating standard EE MRIO accounts (such as footprint, territorial, impacts embodied in trade) and calculates all missing tables. Various data report and visualization methods help to explore the dataset by comparing the different accounts across countries.

Further functions include:

• analysis methods to identify where certain impacts occur
• modifying region/sector classification
• restructuring extensions
• export to various formats
• visualization routines and
• automated report generation

Where to get it

The full source code is available on Github at: https://github.com/IndEcol/pymrio

Pymrio is registered at PyPI and on the Anaconda Cloud. Install it by:

pip install pymrio --upgrade

or when using conda install it by

conda install -c conda-forge pymrio

or update to the latest version by

conda update -c conda-forge pymrio

The source-code of Pymrio available at the GitHub repo: https://github.com/IndEcol/pymrio

The master branch in that repo is supposed to be ready for use and might be ahead of the official releases. To install directly from the master branch use:

pip install git+https://github.com/IndEcol/pymrio@master

Quickstart

A small test mrio is included in the package.

To use it call

import pymrio
test_mrio = pymrio.load_test()

The test mrio consists of six regions and eight sectors:

print(test_mrio.get_sectors())
print(test_mrio.get_regions())

The test mrio includes tables flow tables and some satellite accounts. To show these:

test_mrio.Z
test_mrio.emissions.F

However, some tables necessary for calculating footprints (like test_mrio.A or test_mrio.emissions.S) are missing. pymrio automatically identifies which tables are missing and calculates them:

test_mrio.calc_all()

Now, all accounts are calculated, including footprints and emissions embodied in trade:

test_mrio.A
test_mrio.emissions.D_cba
test_mrio.emissions.D_exp

To visualize the accounts:

import matplotlib as plt
test_mrio.emissions.plot_account('emission_type1')
plt.show()

Everything can be saved with

test_mrio.save_all('some/folder')

See the documentation , tutorials and Stadler 2021 for further examples.

Tutorials

The documentation includes information about how to use pymrio for automatic downloading and parsing of the EE MRIOs EXIOBASE, WIOD, OECD and EORA26 as well as tutorials for the handling, aggregating and analysis of these databases.

Citation

If you use Pymrio in your research, citing the article describing the package (Stadler 2021) is very much appreciated.

For the full bibtex key see CITATION file.

Contributing

Want to contribute? Great! Please check CONTRIBUTING.rst if you want to help to improve Pymrio.

Communication, issues, bugs and enhancements

Please use the issue tracker for documenting bugs, proposing enhancements and all other communication related to pymrio.

You can follow me on twitter to get the latest news about all my open-source and research projects (and occasionally some random retweets).

Research notice

Please note that this repository is participating in a study into sustainability of open source projects. Data will be gathered about this repository for approximately the next 12 months, starting from June 2021.

Data collected will include number of contributors, number of PRs, time taken to close/merge these PRs, and issues closed.

For more information, please visit the informational page or download the participant information sheet.

pymrio's Issues

EXIOBASE 3 parser

Implement EXIOBASE 3 parser (wrapper around load_all which also works with zip files) and rename the exiobase12 generic methods to make clear they are not used for exiobase3

AttributeError: 'Extension' object has no attribute 'D_fp'

Hi Konstantin,

just downloaded pymrio and cannot wait to use it! Thanks for providing a package for MRIO manipulation!
Here is one thing I realized: When going through the test example in the readme, I get an error:

AttributeError: 'Extension' object has no attribute 'D_fp'

The error occurs when calling test_mrio.emissions.D_fp. I downloaded the latest version directly from github via

pip install git+https://github.com/konstantinstadler/pymrio

Here is my system info: Python 3.7.9 (default, Aug 31 2020, 17:10:11) [MSC v.1916 64 bit (AMD64)] on win32

Maybe the attribute was renamed meanwhile?

WIOD parser

Final demand used in computing exio3.satellite.D_cba_reg

Hello,
I want to benchmark the results I get for consumption-based emissions using household expenditure data against exio3.satellite.D_cba_reg. I am not sure what vector you use as final demand in this calculation? I tried reproducing the output of exio3.satellite.D_cba_reg for particular regions by calculating a vector of final demand from the Y matrix, but the results are not congruent.

Specifically, suppose I want to compute cba for FR for total final demand (both imported and domestically satisfied):
Y_ini_df = exio3.Y.loc[:,'FR']
Y_ini_df.loc[:,'Final consumption'] = [sum(x[0:3]) for x in Y_ini_df.values.tolist()] # summing household, NGO and gov final consumption
Y_ini_df = Y_ini_df['Final consumption']
Y_final = pd.DataFrame(np.zeros([49,200]),index = Y_ini_df.unstack().index,columns=Y_ini_df.unstack().columns)
Y_final.loc['FR'] = Y_ini_df.unstack().sum(axis=0)
Y_final = Y_final.stack() # this final demand vector has dim 9800x1. It only contains the final demand for France and is 0 everywhere else.
CBA = np.matmul(M,Y_final)

The results are about roughly twice as large as the output of exio3.satellite.D_cba_reg.loc['FR'] (so the problem is not that I should have included gross fixed capital formation).
What in my calculation is inconsistent with the calculations outputting D_cba_reg?
Thanks a lot

Warning/Error for aggregation when no absolute values are available

see #21

total impact calcuation

The function calc_e in iomath.py is presumably not necessary. Check that and than either

• remove
• write a proper test and doc

Latex report not working

Warning: docutils not available but the module was installed - check

exio3.impact.get_rows() yields AttributeError: 'IOSystem' object has no attribute 'impact'

I am trying to calculate consumption-based impacts with Exiobase v3.8.1 for which I followed instructions on https://pymrio.readthedocs.io/en/latest/notebooks/working_with_exiobase.html.

import pymrio

exio3_path = 'data-exiobase/IOT_2021_pxp'
exio3 = pymrio.parse_exiobase3(path=exio3_path)

# Exploring EXIOBASE
exio3.meta
exio3.get_sectors()
exio3.get_regions()
list(exio3.get_extensions())

# Calculating the system and extension results
exio3.calc_all()

# The available impact data can be checked with:
list(exio3.impact.get_rows())

The last row returns the error AttributeError: 'IOSystem' object has no attribute 'impact'. Does anyone have a suggestion why?

Instructions for install with conda?

It seems conda does not come with a recent enough version of pandas to install pymrio. Might be worth updating the instructions?

When I try:
guillaume@ciraigLinux:~$ conda create --name io -c konstantinstadler pymrio

I get:

Fetching package metadata ...........
Solving package specifications:

PackageNotFoundError: Packages missing in current channels:

• pymrio -> pandas >=0.22.0
• pymrio -> requests >=2.18

We have searched for the packages in the following channels:

• https://conda.anaconda.org/konstantinstadler/linux-64
• https://conda.anaconda.org/konstantinstadler/noarch
• https://repo.continuum.io/pkgs/free/linux-64
• https://repo.continuum.io/pkgs/free/noarch
• https://repo.continuum.io/pkgs/r/linux-64
• https://repo.continuum.io/pkgs/r/noarch
• https://repo.continuum.io/pkgs/pro/linux-64
• https://repo.continuum.io/pkgs/pro/noarch

Explicit python version - minimum requirement

Pymrio requires python version 3.7 but can be installed (updated?) on 3.6. This causes issues when using the excel parser (probably connected to pandas).

The minimum python version should be stated in the install description/readme and be checked during runtime.

Spelling Error txt file populatino exio2

rewrite index population and check script if the wrong name is used anywhere

"import pymrio" is missing in parser.py

Just a small missing:

At line 190 EXIOError is called through pymrio.core. It's an error: import pymrio is missing and EXIOError is actually available through pymrio.core.mriosystem

I propose to import with from pymrio.core.mriosystem import EXIOError and at line 190 just call raise EXIOError('EXIOBASE files missing')

More info about regions ?

As a beginner user, I somehow feel it would be nice to have a method, other than get_regions() that would return more info about the regions: full name, member of an organisation...

I can propose a first version, and you'll decide whether you want to include it or not

Pypi sdist does not include all package data

Motivation:

• Following my comment in PR #49 , I think that the setup.py and/or the MANIFEST.in are incomplete since the installation using pip does not include the necessary directory pymrio/mrio_models/exio20 and all its content.
• This is probably the same problem behind the comment by @bixiou in issue #9

Idea:

• Try to include it in setup.py and MANIFEST.in
• May also have something to do with the fact that pymrio/mrio_models/exio20 does not have a init.py, such that it may not be considered as part of the package in sdist

Demand Shock with EXIOBASE3

Hi Konstantin,
thank you for your valuable work in developing this library.
I am trying to perform a shock analysis using pymrio and adopting EXIOBASE3 as database.
I was surprised when I realized that increasing the demand considerably in a certain sector implied decrease in use of certain exogenous resources (e.g. water withdrawal).
So, I tried to figure out why. I ended up comparing the baseline database with an identical version (same final demand), in order to check what was going on.

I import the same database in two different variables

baseline = pymrio.parse_exiobase3(path=exio3path)
shock = pymrio.parse_exiobase3(path=exio3path)

Then, I calculate all for both MRIO.

baseline.calc_all()
shock.calc_all()

But now, since I would like to make some changes in the shock version, I reset all to coefficients.
shock.reset_all_to_coefficients()
Of course, to run the model again, I need a final demand. So, in order to check for consistency, I assign the same final demand of the baseline.
shock.Y = baseline.Y
Now I calculate everything expecting to have the same system observable in the baseline.
shock.calc_all()
But when I look at the differences in use of factors, I observe relevant differences in some categories.
DeltaPerF = (shock.satellite.F.sum(axis=1) - baseline.satellite.F.sum(axis=1))/(baseline.satellite.F.sum(axis=1))*100
I print out the most relevant percentual differences between shock and baseline by factors.
This is the situation for the ixi database.

This the situation for the pxp database.

It looks like the F imported from the original database is somehow different from the F that one gets by F = Sx.
I checked and both S and x have no differences. Therefore, I would expect that there’s a problem in how F is recalculated after bringing everything to coefficients.
Maybe I am doing something wrong, could you help me fix it?
Thank you in advance,

Nicolò Golinucci

population.txt file not found

I am trying to follow the Quickstart guide to exploring Exiobase2. when i call pymrio.parse_exiobase2 i get an error which i believe relates to the pymiro package itself missing a file.
the path requested is in the pymiro package in my anaconda environment C:\Users\CummingR\AppData\Local\Continuum\anaconda3\envs\RC37\lib\site-packages\pymrio\mrio_models\exio20\./misc/population.txt
however the path only exists as far as
C:\Users\CummingR\AppData\Local\Continuum\anaconda3\envs\RC37\lib\site-packages\pymrio\mrio_models
where the folder contains a pycache folder, the test_miro folder and an init.py file. Is there a different file which needs to be installed manually?
I have included the full error trace below.

exio2 = pymrio.parse_exiobase2(path=ExioFile,charact=True, popvector='exio2')
Traceback (most recent call last):

File "", line 1, in
exio2 = pymrio.parse_exiobase2(path=ExioFile,charact=True, popvector='exio2')

File "C:\Users\CummingR\AppData\Local\Continuum\anaconda3\envs\RC37\lib\site-packages\pymrio\tools\ioparser.py", line 658, in parse_exiobase2
index_col=0, sep='\t').astype(float)

File "C:\Users\CummingR\AppData\Local\Continuum\anaconda3\envs\RC37\lib\site-packages\pandas\io\parsers.py", line 685, in parser_f
return _read(filepath_or_buffer, kwds)

File "C:\Users\CummingR\AppData\Local\Continuum\anaconda3\envs\RC37\lib\site-packages\pandas\io\parsers.py", line 457, in _read
parser = TextFileReader(fp_or_buf, **kwds)

File "C:\Users\CummingR\AppData\Local\Continuum\anaconda3\envs\RC37\lib\site-packages\pandas\io\parsers.py", line 895, in init
self._make_engine(self.engine)

File "C:\Users\CummingR\AppData\Local\Continuum\anaconda3\envs\RC37\lib\site-packages\pandas\io\parsers.py", line 1135, in _make_engine
self._engine = CParserWrapper(self.f, **self.options)

File "C:\Users\CummingR\AppData\Local\Continuum\anaconda3\envs\RC37\lib\site-packages\pandas\io\parsers.py", line 1917, in init
self._reader = parsers.TextReader(src, **kwds)

File "pandas_libs\parsers.pyx", line 382, in pandas._libs.parsers.TextReader.cinit

File "pandas_libs\parsers.pyx", line 689, in pandas._libs.parsers.TextReader._setup_parser_source

FileNotFoundError: [Errno 2] File b'C:\Users\CummingR\AppData\Local\Continuum\anaconda3\envs\RC37\lib\site-packages\pymrio\mrio_models\exio20\./misc/population.txt' does not exist: b'C:\Users\CummingR\AppData\Local\Continuum\anaconda3\envs\RC37\lib\site-packages\pymrio\mrio_models\exio20\./misc/population.txt'

EEBT

Provide EEBT trade matrix for every stressor

New pandas xls read

In the new pandas version the api for the xls read changed.
Change the xls parser in all parser routines accordingly and add note in the dependencies on the new pandas version.

Missing values in the MR Emissions file

Hi Konstantin,

There are some seemingly missing values from Exiobase V2, I was hoping you could clear up this confusion for me.

I am interested in the emissions intensity.

pop_vec = pd.read_csv("/Users/nash/dev/emitwise-flask/cleaning/data/exiobase/populations.txt", sep="\t", index_col=0)
exio2 = pymrio.parse_exiobase2(path='/Users/nash/dev/data/exio_ixi', charact=True, popvector=pop_vec)
df = exio2.emissions.S

When looking at exio2.emissions.S there are some surprising omissions. For example, under "Cattle Farming", the non combustible methane emissions are zero?

Best,
George

Exio3 parser permission error

Hi,
I am trying to use the parser of exiobase3 and I get a permission error. It seems that the parser only accepts zip files? Yet, when I use the zip file directly downloaded from exiobase website it tells me KeyError: "There is no item named 'mrIot3.0.txt' in the archive", and when i use the unzipped file i get the following error:

io = pymrio.parse_exiobase3('C://Users/Maxime/Desktop/Thesis/Bdd/IOT_2011_pxp/')

PermissionError Traceback (most recent call last)
in ()
----> 1 io = pymrio.parse_exiobase3('C://Users/Maxime/Desktop/Thesis/Bdd/IOT_2011_pxp/')

C://Users/Maxime/Desktop/Thesis/Modules_Python/pymrio-master\pymrio\tools\ioparser.py in parse_exiobase3(zip_file, path_in_zip, version, iosystem, year, charact)
498 # read the data into a dicts as pandas.DataFrame
499 logging.info('Read exiobase3 from {}'.format(zip_file))
--> 500 zip_file = zipfile.ZipFile(zip_file)
501
502 core_data = {exio_table: pd.read_table(

C:\Users\Maxime\Anaconda3\lib\zipfile.py in init(self, file, mode, compression, allowZip64)
1088 while True:
1089 try:
-> 1090 self.fp = io.open(file, filemode)
1091 except OSError:
1092 if filemode in modeDict:

PermissionError: [Errno 13] Permission denied: 'C:\Users\Maxime\Desktop\Thesis\Bdd\IOT_2011_pxp'

Version number hard coded in parser.py needs to be changed for new EXIOPOL versions

parser.py returns "missing files" error for new EXIOPOL version (2.2.2) since it's hard coded for version 2.2.0. Just needs to be changed in file names in parser.py. Maybe change version input parameter to have a three-part name holder (i.e. 2.x.y)?

EXIOBASE parser - version

Provide a parameter to specifiy the exio2 version (eg. 2.2.1) which will be used to specify the filename.

Visualisation maps

Maps with countries coloured according to their footprint

Understanding the calculation and results of a national green water footprint

Hello Konstantin & contributors,

I have a question concerning the calculation of the green water footprint of Germany using PyMrio and Eora26.

eora_storage = ''

eora = pymrio.parse_eora26(year=2015, path=eora_storage)

eora_green = eora.Q.diag_stressor(('WFN: Total water footprint - Green','Total'), name = 'emtype2_diag')
eora.eora_green = eora_green

eora.calc_all() 

source_green = eora.eora_green.D_cba.DEU.sum(axis = 1)
source_green = pd.DataFrame(source_green)

Looking at the results, only 186 out of 2914 sectors have a green water footprint. Of these 186 sectors 172 are "Agriculture" (the other 14 are mainly electricity and gas production and fishing). The way I understand national footprint calculations is that the results show the sectoral contributions to the total footprint of a country (or another specified final demand; see Kitzes 2013). If my understanding is correct, other sectors which consume products from the agriculture sectors should also have a green water footprint e.g. DEU Food & Beverages, Hotels and Restaurants, Textiles and Wearing Apparel etc.

However with the code above, this is not the case. Do you have an idea why?

I also calculated the green water footprint for Germany manually also under use of the Eora26 database (following Kitzes 2013 and multiplying F with the combined final demand of all final demand subcategories). The total water footprint is the same but the sectoral contributions to the national green water footprint are completly different.

The most contributing sectors (including supply chain) are (top - highest contribution):

I thought my results (displayed in the picture) e.g. Germany Food & Beverages, Agriculture, Hotels and Restaurants etc. are plausible as the contributions by these sectors include agricultural products from other countries via the supply chain. However, when I saw the PyMrio results I got confused.

Any idea why our results are so different? Thank you so much for your time! :)

Kitzes, Justin. 2013. “An Introduction to Environmentally-Extended Input-Output Analysis.” Resources 2 (4): 489–503. https://doi.org/10.3390/resources2040489.

F and D_terr

Rename to production
Write to doc that these are F with household, avoid doublng of data

Eora 26 parser

error about the version of files in dictionary files_exio

In the ioparser.py,

files_exio = dict(
        # exiobase 2.2.2
        A='mrIot_version2.2.2.txt',
        Y='mrFinalDemand_version2.2.2.txt',
        S_fac='mrFactorInputs_version2.2.2.txt',
        S_emissions='mrEmissions_version2.2.2.txt',
        S_materials='mrMaterials_version2.2.2.txt',
        S_resources='mrResources_version2.2.2.txt',
        FY_emissions='mrFDEmissions_version2.2.2.txt',
        FY_materials='mrFDMaterials_version2.2.2.txt',
        charact = 'characterisation_CREEA_version2.2.2.xlsx'
        )

but when we download the last version Exiobase 2, the name of the mrFDEmissions is mrFDEmissions_version2.2.2.txt and not mrFDEmissions_version2.2. An error is raised and the code aborted due to the code:

# check if source exiobase is complete
    _intersect = [val for val in files_exio.values()
                  if val in os.listdir(path)]
    if len(_intersect) != len(files_exio.values()):
        raise ParserError('EXIOBASE files missing')

I proposed to add mrFDEmissions_version2.2.txt in the dictionary to avoid the error.

#Bugs with Exiobase 2

There seems to be two issues with the handling of Exiobase 2 by pymrio.
First, when the PxP IO system, which I call exio2p*, is reset, using the method reset_all_to_coefficients(), the matrices A and L are missing (I haven't tested it for IxI but it might be the same).
Second, when one tries to use the method aggregate, an error is raised. If the method is called before calling .calc_all(), the error reads:

WARNING:root:No attributes available to get sectors
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-61-441d56c89f18> in <module>()
----> 1 global_io = exio2p.aggregate(region_agg = 'global', sector_agg='total', inplace=False)

~/anaconda3/lib/python3.5/site-packages/pymrio/core/mriosystem.py in aggregate(self, region_agg, sector_agg, region_names, sector_names, inplace, pre_aggregation)
   1659             region_agg = [region_agg] * len(self.get_regions())
   1660         if type(sector_agg) is str:
-> 1661             sector_agg = [sector_agg] * len(self.get_sectors())
   1662 
   1663         if ioutil.is_vector(region_agg):

TypeError: object of type 'NoneType' has no len()

whereas if ones applies .calc_all() first, the error is:

----> 1 global_io = exio2p.aggregate(region_agg = 'global', sector_agg='total', inplace=False)

~/anaconda3/lib/python3.5/site-packages/pymrio/core/mriosystem.py in aggregate(self, region_agg, sector_agg, region_names, sector_names, inplace, pre_aggregation)
   1752                         data=conc.dot(self.x),
   1753                         index=mi_reg_sec,
-> 1754                         columns=self.x.columns,
   1755                         )
   1756             self.meta._add_modify('Aggregate industry output x')

AttributeError: 'Series' object has no attribute 'columns'

Same errors are raised if other parameters are passed in the .aggregate() method (such as a more complicated aggregation).

*exio2p is defined as follows:

exio2p = pymrio.parse_exiobase2(path=[path to the PxP .zip], charact=True, popvector='exio2')

Exiobase 3 hybrid data

Brilliant solution! Do you support (or plan on supporting) the hybrid (non-monetary) exiobase database?

Autodownload EXIOBASE 3

Exiobase 3 is now available on zenodo. Data on zenodo can be downloaded by API (see for example zenodo_get). As EXIOBASE is saved per year, the structure of the WIOD downloader can probably be reused.

Full Eora

Hello and thank you for providing Pymrio for free and open source!
I am wondering why the full version of Eora is not supported by Pymrio? I am working with the full Eora database and I am happy to write the code for the calculations myself. It helps me to understand what I am actually doing. Still, I noticed that the full Eora is not supported by Pymrio and I am simply curios what the reason is.
Thank you and best regards
Jonas

get year as field in metadata

This is needed for a full meta data record.
Needs to be updated after downloading (which can download multiple years). Each parser, however, works on a single year, so adding a year para should be simple

mrio.x needs to be a dataframe

Otherwise the columns attribute will not work (e.g. in the aggregation routine). see #21

accessing emissions computation from exiobase3

I'm trying to access the GHG emission decomposition for different countries in Europe with consumption/production/net trade along different years. I followed the documentation here https://pymrio.readthedocs.io/en/latest/notebooks/working_with_exiobase.html#Exploring-EXIOBASE starting with year 2015.
year= 2015
exio3 = pymrio.parse_exiobase3(path='IOT_'+str(year)+'_pxp.zip')
exio3.meta
exio3.get_regions()
exio3.calc_all()

I have a satellite extension but no impact.
Thanks in advance for your help
Robin

NTNU mat structure parser

Adopt the standalone script for parsing mat-ntnu-mrio structure:

• make own module with ntnu specific tools
• generic mat parser
• make specific mat parsers for each mrio
• check if mat file is passed (in the standard parsers) and than call the mat parser for the specific

Update contributing.rst - issue driven development

Add some note that all development should first be discussed by filing an issue

TypeError: sum() got an unexpected keyword argument 'sort'

Running on python 3.5.1
numpy==1.10.4

Did not allow 'sort' keyword, had to manually remove 'sort=false' from all lines present in core/mriosystem.py

Worked after those instances were removed!

Thanks for the code 👍

Parse from zipfile on MS Windows

Parsing directly from the zip file does not work (at least for EXIOBASE 3) because the path separator is different in Windows and in the zip file.

Bug: fail pymrio.load_test(); missing file

When I run this

import pymrio
pymrio.load_test()

I get this error:

OSError: File b'/home/bill/documents/praxis/informatique/pymrio/pymrio/mrio_models/test_mrio/finald_demand_Y.txt' does not exist

And indeed that file does not seem there. Here is the list of files in that directory

concordance/ emissions.txt factor_input.txt FDemissions.txt finald_demand_y.txt population.txt readme.txt trade_flows_Z.txt

This is a fresh clone, with HEAD at 92f7546

Pymrio is Exiobase 3 ready?

I would like to know if Exiobase 3 is ready to use. And if no, when it'll be available?
For the moment I use pandas manually, but it is less convenient than the pymrio object.

update exiobase docs

Exiobase docs for version3 need to be updated to account for zenodo upload and download (see also #64 )

Tutorial installing bug

Change path to include master

EORA 26 automatic downloader

eora26 download now requires log in - check if the downloader would work after login or remove it

Citing pymrio as part of academic work

Hi Konstantin,
First, thank you so much for this package, it has been super helpful as part of the EEIO analysis for my thesis: 'Food Waste reduction via sharing economy - environmental analysis and rebound effect.

I am starting to write down the thesis and would like to cite this package.
(e.g. on geopandas citing - http://citebay.com/how-to-cite/geopandas/)
How should I cite this package?
Thank you so much, Tamar

error when trying to parse EORA26

Hello,
The command - eora = pymrio.parse_eora26(year=1990, path=eora_storage)
shows an error (KeyError: "There is no item named 'labels_Q.txt' in the archive")

Kindly help me out.
Thanks a lot

Divide by zero error in iomath.py

Issue on line 109 in iomath.py

I changed:
recix[recix==np.inf]=0

to:
if x == 0:
recix = 0
else:
recix = 1/x

since it was returning a trying to divide by zero error that stopped computation when parsing in EXIOPOL pxp 2.2.2

Include SY calculation

SY is currently used in ioutil and mentioned in the description, but not calculated in iomath. Also the save and load function need to be updated.

Can't find the characterization matrix in parse_exiobase2.

Hi Konstantin,
I'm using parse_exiobase2 and am providing the path to the CREEA characterization xlsx file provided by Exiobase2 and it works fine.
My issue though, I cannot find any characterization dataframe inside the pymrio object. I can only find the associated impacts to each commodity (pymrio.impact.S). Am I missing this characterization matrix dataframe? or is it not possible to isolate it through pymrio?

Thank you!
Maxime Agez

xlrd vs openpyxl

fix the xlsx issue with xlrd - require openpyxl

Refactor metadata for autodownload

Using the io metadata system for recording downloads does not make much sense. One can download multiple files which (as in exio) might already contain metadata.

Proposed solution: a download_meta.yml or similar which records the info from the download. Parsing a io then looks for this file and adds relevant lines to the meta records.