{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Quick Start Pymrio Tutorial using WIOD" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This notebook contains the interactive version of the quick start given in the Pymrio article (Stadler et al 2018 sub). " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Pymrio requires a Python version >= 3.5. If you don't have Python installed, I recommend to use the [Anaconda Scientific Python package](https://www.anaconda.com/download)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Pymrio is available on [the Python Package Index PyPI](https://pypi.python.org/pypi) and on the [Anaconda Cloud](https://anaconda.org/konstantinstadler/dashboard). Thus, two possibilities exist to install Pymrio and all required packages. \n", "\n", "For using the version on PyPI use:\n", "\n", "```\n", "pip install pymrio --upgrade\n", "```\n", "\n", "To install from the Anaconda Cloud do:\n", "\n", "```\n", "conda install -c konstantinstadler pymrio\n", "```\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "You can than import the Pymrio package with" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import pymrio" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In this example here, we will use the [WIOD MRIO database](http://www.wiod.org/home).\n", "\n", "First, the Pymrio MRIO download function is used to get the WIOD MRIO database with:" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Description: WIOD metadata file for pymrio\n", "MRIO Name: WIOD\n", "System: ixi\n", "Version: data13\n", "File: /tmp/wiod/raw/metadata.json\n", "History:\n", "20180215 14:36:45 - FILEIO - Downloaded http://www.wiod.org/protected3/data13/water/wat_may12.zip to wat_may12.zip\n", "20180215 14:36:44 - FILEIO - Downloaded http://www.wiod.org/protected3/data13/materials/mat_may12.zip to mat_may12.zip\n", "20180215 14:36:44 - FILEIO - Downloaded http://www.wiod.org/protected3/data13/land/lan_may12.zip to lan_may12.zip\n", "20180215 14:36:43 - FILEIO - Downloaded http://www.wiod.org/protected3/data13/AIR/AIR_may12.zip to AIR_may12.zip\n", "20180215 14:36:43 - FILEIO - Downloaded http://www.wiod.org/protected3/data13/CO2/CO2_may12.zip to CO2_may12.zip\n", "20180215 14:36:42 - FILEIO - Downloaded http://www.wiod.org/protected3/data13/EM/EM_may12.zip to EM_may12.zip\n", "20180215 14:36:41 - FILEIO - Downloaded http://www.wiod.org/protected3/data13/EU/EU_may12.zip to EU_may12.zip\n", "20180215 14:36:41 - FILEIO - Downloaded http://www.wiod.org/protected3/data13/SEA/WIOD_SEA_July14.xlsx to WIOD_SEA_July14.xlsx\n", "20180215 14:36:40 - FILEIO - Downloaded http://www.wiod.org/protected3/data13/update_sep12/wiot/wiot08_row_sep12.xlsx to wiot08_row_sep12.xlsx" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "raw_wiod_path = '/tmp/wiod/raw'\n", "pymrio.download_wiod2013(storage_folder=raw_wiod_path,\n", " years=[2008])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This downloads the 2008 MRIO table from WIOD. Omitting the year parameter would result getting all years.\n", "The function returns a Pymrio meta data object, which gives information about the WIOD version, system (in this case industry by industry) and records about from where the data was received." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To parse the database into a Pymrio object use:" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": true }, "outputs": [], "source": [ "wiod = pymrio.parse_wiod(raw_wiod_path, year=2008)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The available data can be explored by for example:" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Index(['AtB', 'C', '15t16', '17t18', '19', '20', '21t22', '23', '24', '25',\n", " '26', '27t28', '29', '30t33', '34t35', '36t37', 'E', 'F', '50', '51',\n", " '52', 'H', '60', '61', '62', '63', '64', 'J', '70', '71t74', 'L', 'M',\n", " 'N', 'O', 'P'],\n", " dtype='object', name='sector')" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "wiod.get_sectors()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "or" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Index(['AUS', 'AUT', 'BEL', 'BGR', 'BRA', 'CAN', 'CHN', 'CYP', 'CZE', 'DEU',\n", " 'DNK', 'ESP', 'EST', 'FIN', 'FRA', 'GBR', 'GRC', 'HUN', 'IDN', 'IND',\n", " 'IRL', 'ITA', 'JPN', 'KOR', 'LTU', 'LUX', 'LVA', 'MEX', 'MLT', 'NLD',\n", " 'POL', 'PRT', 'ROU', 'RUS', 'SVK', 'SVN', 'SWE', 'TUR', 'TWN', 'USA',\n", " 'RoW'],\n", " dtype='object', name='region')" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "wiod.get_regions()" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
regionAUS...RoW
sectorAtBC15t1617t18192021t22232425...6364J7071t74LMNOP
regionsector
AUSAtB4445.32433041.91940015625.681890536.968630154.395870936.835140273.0186000.000000215.70844093.909230...19.7619170.0016270.1400440.04366711.6800063.11382761.7116879.89835910.2569830.000038
C16.2779343838.070873189.93427511.3136863.25306314.27158258.1360674424.333299193.32889520.968263...0.2118880.0343000.0058170.08810114.4188320.3158090.1821570.2733870.4935100.000861
15t161049.495726100.6113476754.11052268.38776119.66369714.57036649.43198036.266290835.58764354.070009...1.6217561.5881103.7016852.74395427.66527414.86558386.09679846.73685279.6371330.006089
17t1836.90842043.779214108.986668355.675875102.26833318.33569150.18823415.53864945.91794345.612614...0.4010320.1813671.4925790.6324271.4927506.5505540.8787642.2526242.4287350.001057
199.51810711.28997828.10596591.72326626.3734104.72848912.9427644.00717611.84152211.762783...0.0397080.0179580.1477860.0626190.1478030.6485940.0870100.2230400.2404780.000105
2036.81981147.49117133.0278787.2969232.098101931.52991729.44785410.27359019.27162519.486462...0.0271230.0827760.0633780.2059540.7905322.3531932.5541661.8271021.2875730.010418
21t22115.900527153.2485061246.42554952.20009715.00922090.3266742821.00042423.198240363.916574142.223056...2.20417210.10268715.4180636.19510748.59688756.89046621.91386817.32666525.3366930.025942
23490.1564191026.213186158.8891009.1795232.63940935.55101277.346703518.540713250.87722141.087803...59.0289954.48727411.18908411.51262836.30351427.56644317.22249518.54970017.8639480.011255
241025.411077395.338597254.52141158.42880116.800175134.600162414.014715254.5337341940.073909858.289530...2.6037111.4441491.1943429.23736819.60961628.26826542.763999112.87026229.3496040.052557
2579.516332189.301500747.54565234.0839139.80023336.346518308.64025035.017383356.994995269.405154...0.9732792.4277530.7048633.3497516.2594122.5769083.1990484.86782737.4459450.008494
2638.658080105.010424262.2240865.2830831.51905440.46974429.7650728.536396105.01169839.029102...0.1868750.4217550.1954260.6575031.6042971.1606101.5143501.3813802.1736740.001937
27t28212.0898061310.988269836.15733642.12545312.112433307.140650183.82164439.748282376.009535192.166872...15.6177447.9594402.38065218.29303425.0941794.1776645.5338384.01213026.9197450.049209
29168.914698614.130627121.5730269.6019572.76087922.27910745.20583636.72684149.85761928.242531...3.64235930.3097296.82596328.60639341.2324057.77530317.2553056.98578919.1452090.031949
30t33100.297729364.65688472.1873145.7014251.63934713.22883026.84220421.80756829.60432716.769776...2.00223616.6615193.75229115.72518122.6658094.2741519.4853903.84014810.5242870.017563
34t3594.161797279.63796868.1657878.2944292.3849178.08055819.63929318.15042525.40681611.405865...12.7032478.76937912.76838412.61067564.71101621.84512512.2218155.288575124.6846980.005111
36t3752.529450213.596124135.68399526.0577597.492447110.34206835.26888321.25291364.35545929.135448...0.2260411.8163511.5010010.7341325.4574323.6536903.0401512.2613016.1769470.330733
E698.4231561719.046355885.61862986.36135524.831684143.282141356.331393124.990480359.975571187.401518...0.1581690.2223140.2985371.8042970.6969230.8190740.4336250.5882910.5428920.000114
F633.7143164242.094785376.75440328.6959218.251007109.473492151.285346935.469320167.74650693.523215...0.9676383.0200026.8226204.4450316.9781643.8204324.2131754.2690643.1356820.006102
501132.3485432138.4196581023.262884159.07338345.738761230.146065723.933947115.779055392.670136231.061142...0.5425761.0553011.1634500.6195500.8201083.1909260.4012450.7154430.3353340.000000
511394.4631931572.4542634088.518869419.871502120.726663276.108617963.440976976.9417461308.409695535.714326...0.8229740.8801882.6170881.3340458.0440248.11213813.16591910.88203617.3352050.125509
521445.5282771659.8167473579.884070371.567853106.837791289.884901858.5924221003.3489171302.437162535.855098...3.5084178.4128202.9431614.18365025.1375969.3504859.91584614.3688759.5058140.045543
H140.934734216.771700561.95667427.4579087.89504123.433113167.690188103.972792168.58329531.931233...13.4170605.80301031.8338366.09382644.01616331.47063122.22212915.1939058.8205620.024843
60476.9769163184.8185531993.405269126.35511136.331187218.706857510.934567264.079532529.984384320.186820...24.16050627.96304034.28431129.29658551.01869166.98797639.6385726.56105544.0379840.014616
619.552743170.42772431.1770724.6118831.3260643.89824915.91988615.31670213.4565745.596796...2.68364527.56501425.181994128.91592266.00383227.0812386.7003472.04126517.2737100.000000
626.86961820.12156011.0677131.7861620.5135811.66955211.2933162.1451386.4689711.904794...56.890998228.034250187.10341540.923609416.402802518.481234387.00286328.960407154.0360710.000035
63297.699414738.7355421195.70668645.97671313.219798325.523642634.16253998.547353630.17489872.132960...23.52300876.26084159.94288523.682097132.257649162.850890120.7924749.26766353.4231420.000042
64223.155110423.626089355.81401835.23662510.13166874.415816321.615785114.934853143.60920571.615890...0.1836983.1952114.1684140.3987771.1363614.4887642.0699591.4761960.8795040.000243
J1299.8420594293.057285967.64685059.13876717.004318111.468536441.55273697.016295296.043420121.990028...10.69120938.70216987.94796949.86278173.17217817.97030040.59436912.82470934.7070570.069814
70551.7971751786.808419797.47490332.5538139.360274300.402024541.707671186.95054498.49401850.868687...1.37104055.15496851.22202381.5071351.32450614.6420117.9113270.55407815.3699710.000000
71t741180.0631045310.4465243035.907428368.573815105.976926557.0093052787.0564931262.5664882654.6526131383.027258...13.60976944.055788110.84009645.92686497.59412130.52956859.53833918.12455133.4681600.097561
.....................................................................
RoW201.6350562.0135660.8203480.2169800.06239459.2546391.9215910.2931890.4190810.896964...80.08917838.34226612.07293726.345271629.0848921884.0543282120.7664301932.161785914.7558720.019687
21t227.72491813.129569217.8776772.0038840.57618210.939833305.2438362.71889843.00535412.827419...2356.5054745432.5808167910.9189291128.08316726948.16519816081.6842479758.3273876011.87510010934.4282732.548514
23388.152158836.37440981.5389312.3902910.68728725.40917452.937556426.332774189.22788725.663685...940.236675261.091828154.913923129.072765789.857491574.234856141.229352242.320646423.8967800.056465
24365.270981132.69673132.70539614.9435344.29675245.776375137.84905388.781323694.935609304.297810...259.00166586.21747590.520415172.2064571469.037784568.857200464.54947010243.4198751465.8647320.523719
258.28621422.57594590.9517882.9644670.8523794.08099938.5780264.43301543.07875133.263153...1122.804886762.399457140.149436493.4589333238.293742384.585818748.5942022193.8422322876.9328930.139278
261.9560646.04373211.1525630.0990520.0284831.5405910.8420930.9919215.2643411.845787...119.94715460.33778818.657645135.596128389.433240439.866913502.9177191116.624356400.0178830.111932
27t289.581514191.52013934.1964542.8721050.82582219.20215617.1079832.89918723.41774140.398734...1298.244145315.873918171.199863733.1406094511.622232548.761711543.615393931.9555521147.9056010.648180
2935.895862148.4069164.0624070.2064930.0593714.2268745.0446324.7107176.1538711.448788...697.828174319.985813314.995799181.2235151068.322357753.097670271.2945753154.318917314.3370840.227289
30t335.43869514.6630994.2887010.9420370.2708620.5815845.5732720.6010503.1751192.472000...818.5466218308.403067731.275786808.30279621372.9866471858.0837322393.9180952193.9402914724.3525921.743540
34t353.5807716.2927621.1431450.0896810.0257860.2950670.5890520.1444170.8731630.518826...1252.4009601279.511149517.703475418.8420546459.7628462627.3534491120.680148392.7613077211.3020260.984097
36t371.42315815.9199152.5206750.9976910.2868711.1447501.8720700.5372752.2122971.106440...103.922288113.850921471.973179181.271520482.787859773.675064852.380832323.697939504.5726810.169314
E0.80264718.5605781.1051870.0524740.0150900.1737610.56752820.4286390.8191550.253561...4605.7092697342.3106965072.9784465141.94135112517.58698615224.24004412110.15894912791.41934110535.6124314.831273
F0.6905874.5503820.3985770.0184750.0053140.2286490.1504370.9846230.2271280.110467...982.3188672242.9100543428.7135887483.1458855407.73167610000.8897516437.55102011354.3193423839.53701722.570339
500.0556380.1584190.0914770.0040710.0011710.0126000.0399600.0498540.0521950.025508...522.931361593.953802533.712735225.393607984.5741831437.815851342.1589341088.152585555.4150780.513696
512.752223189.55414911.6129520.4815970.1384750.8534804.639344230.5370566.0070031.436657...3519.9811957342.0869142956.8020192056.10253313468.3194588755.5787094942.95437019728.4446329261.0027114.393748
521.0318901.5266143.0438620.1762870.0506880.2673431.5891810.5168151.1045950.320696...2200.6481913472.7514672002.6092681022.4447326822.8922024692.9018332286.9246068058.0107824256.9507656.790453
H0.7834621.1082443.5973030.1176330.0338250.1122850.8445760.4716890.8941510.123268...5697.7757362180.1646127534.0734161565.20785512160.45585316699.7144737750.3828555346.8935664441.2799501.070657
600.680310190.9422397.2256730.2819820.0810790.4358692.825101234.3765433.3672190.414917...7703.6490945140.0425687039.5316121167.01724910630.97502810255.3028274952.2501916210.7367125982.70008013.287645
610.0855080.1908330.0405260.0036980.0010630.0081640.0323420.0825250.0468360.007787...319.845929351.739712393.717271249.4551771314.984794916.026979435.280134803.452478647.4228020.257212
627.70393222.05345112.1571622.1379700.6147331.58061713.2457882.3691837.5407982.183210...532.9085841341.3652921312.401998197.5157572930.7951613507.5224432074.276308875.6091101119.2599980.346236
630.3088860.8023050.6987790.0647450.0186140.1510140.5298740.0962190.3987360.083757...3504.2804921807.3146851701.271137373.6437843223.9723744095.4988501417.8989572264.9412712108.9013310.387366
640.1665960.4994860.3489240.0328840.0094600.0651160.3044610.1022100.2315700.101406...2172.19484620440.02004011710.1227371468.9963379246.28228715881.4699286012.4470587642.0692974260.4826128.457208
J4.7743128.1754198.3644390.1284020.0369240.5010543.0412030.5279201.1287150.542113...7415.7097128091.08132538655.9262185758.94063919989.91384723896.3270619546.8357633563.2182908195.76779554.664765
707.33996723.6356638.3859780.2734550.0786273.6902245.9549912.4228230.1762770.184588...1727.9703935199.4103397493.0759882705.7697979495.1637918103.1539815036.2281346230.3030947501.8574460.007471
71t743.65784917.7616489.8272921.1456300.3294141.8603589.4159614.3893238.2780234.489652...6246.24033912482.29868624886.4998286015.47816270478.45350420430.83635913305.63897415560.64783612040.07116183.100716
L0.5474320.7804061.1760730.2009030.0577660.2485890.6369370.2381981.0788930.160527...608.700335709.0041461595.531658620.2539371194.9827054557.146576518.488155921.621306901.6242860.000000
M1.3190369.92757511.7421832.6398740.7590491.0032954.4742554.1207254.5172801.687657...91.678620463.4023981802.804212212.1931331571.9992397706.6763305223.1895391488.980938527.9100830.001030
N7.8948450.29104111.6035072.2794030.6554041.7490956.7932790.16489618.5503740.174962...39.843405106.735687305.27467270.364956895.5996031415.975389840.5305183513.234966395.2446680.000020
O1.2449263.6866204.3813570.1552170.0446330.5626922.5337300.7583052.1410300.484539...5414.9440764371.2406635815.5251022897.01457814958.97052115443.3917457897.3570038895.57057616565.73312744.703532
P0.0010180.0001040.0036660.0001350.0000390.0000310.0000960.0000210.0001160.000052...1.3240620.2446111.1047261.14193450.5520860.0000001.0899084.57010841.5174643.460032
\n", "

1435 rows × 1435 columns

\n", "
" ], "text/plain": [ "region AUS \\\n", "sector AtB C 15t16 17t18 19 \n", "region sector \n", "AUS AtB 4445.324330 41.919400 15625.681890 536.968630 154.395870 \n", " C 16.277934 3838.070873 189.934275 11.313686 3.253063 \n", " 15t16 1049.495726 100.611347 6754.110522 68.387761 19.663697 \n", " 17t18 36.908420 43.779214 108.986668 355.675875 102.268333 \n", " 19 9.518107 11.289978 28.105965 91.723266 26.373410 \n", " 20 36.819811 47.491171 33.027878 7.296923 2.098101 \n", " 21t22 115.900527 153.248506 1246.425549 52.200097 15.009220 \n", " 23 490.156419 1026.213186 158.889100 9.179523 2.639409 \n", " 24 1025.411077 395.338597 254.521411 58.428801 16.800175 \n", " 25 79.516332 189.301500 747.545652 34.083913 9.800233 \n", " 26 38.658080 105.010424 262.224086 5.283083 1.519054 \n", " 27t28 212.089806 1310.988269 836.157336 42.125453 12.112433 \n", " 29 168.914698 614.130627 121.573026 9.601957 2.760879 \n", " 30t33 100.297729 364.656884 72.187314 5.701425 1.639347 \n", " 34t35 94.161797 279.637968 68.165787 8.294429 2.384917 \n", " 36t37 52.529450 213.596124 135.683995 26.057759 7.492447 \n", " E 698.423156 1719.046355 885.618629 86.361355 24.831684 \n", " F 633.714316 4242.094785 376.754403 28.695921 8.251007 \n", " 50 1132.348543 2138.419658 1023.262884 159.073383 45.738761 \n", " 51 1394.463193 1572.454263 4088.518869 419.871502 120.726663 \n", " 52 1445.528277 1659.816747 3579.884070 371.567853 106.837791 \n", " H 140.934734 216.771700 561.956674 27.457908 7.895041 \n", " 60 476.976916 3184.818553 1993.405269 126.355111 36.331187 \n", " 61 9.552743 170.427724 31.177072 4.611883 1.326064 \n", " 62 6.869618 20.121560 11.067713 1.786162 0.513581 \n", " 63 297.699414 738.735542 1195.706686 45.976713 13.219798 \n", " 64 223.155110 423.626089 355.814018 35.236625 10.131668 \n", " J 1299.842059 4293.057285 967.646850 59.138767 17.004318 \n", " 70 551.797175 1786.808419 797.474903 32.553813 9.360274 \n", " 71t74 1180.063104 5310.446524 3035.907428 368.573815 105.976926 \n", "... ... ... ... ... ... \n", "RoW 20 1.635056 2.013566 0.820348 0.216980 0.062394 \n", " 21t22 7.724918 13.129569 217.877677 2.003884 0.576182 \n", " 23 388.152158 836.374409 81.538931 2.390291 0.687287 \n", " 24 365.270981 132.696731 32.705396 14.943534 4.296752 \n", " 25 8.286214 22.575945 90.951788 2.964467 0.852379 \n", " 26 1.956064 6.043732 11.152563 0.099052 0.028483 \n", " 27t28 9.581514 191.520139 34.196454 2.872105 0.825822 \n", " 29 35.895862 148.406916 4.062407 0.206493 0.059371 \n", " 30t33 5.438695 14.663099 4.288701 0.942037 0.270862 \n", " 34t35 3.580771 6.292762 1.143145 0.089681 0.025786 \n", " 36t37 1.423158 15.919915 2.520675 0.997691 0.286871 \n", " E 0.802647 18.560578 1.105187 0.052474 0.015090 \n", " F 0.690587 4.550382 0.398577 0.018475 0.005314 \n", " 50 0.055638 0.158419 0.091477 0.004071 0.001171 \n", " 51 2.752223 189.554149 11.612952 0.481597 0.138475 \n", " 52 1.031890 1.526614 3.043862 0.176287 0.050688 \n", " H 0.783462 1.108244 3.597303 0.117633 0.033825 \n", " 60 0.680310 190.942239 7.225673 0.281982 0.081079 \n", " 61 0.085508 0.190833 0.040526 0.003698 0.001063 \n", " 62 7.703932 22.053451 12.157162 2.137970 0.614733 \n", " 63 0.308886 0.802305 0.698779 0.064745 0.018614 \n", " 64 0.166596 0.499486 0.348924 0.032884 0.009460 \n", " J 4.774312 8.175419 8.364439 0.128402 0.036924 \n", " 70 7.339967 23.635663 8.385978 0.273455 0.078627 \n", " 71t74 3.657849 17.761648 9.827292 1.145630 0.329414 \n", " L 0.547432 0.780406 1.176073 0.200903 0.057766 \n", " M 1.319036 9.927575 11.742183 2.639874 0.759049 \n", " N 7.894845 0.291041 11.603507 2.279403 0.655404 \n", " O 1.244926 3.686620 4.381357 0.155217 0.044633 \n", " P 0.001018 0.000104 0.003666 0.000135 0.000039 \n", "\n", "region \\\n", "sector 20 21t22 23 24 25 \n", "region sector \n", "AUS AtB 936.835140 273.018600 0.000000 215.708440 93.909230 \n", " C 14.271582 58.136067 4424.333299 193.328895 20.968263 \n", " 15t16 14.570366 49.431980 36.266290 835.587643 54.070009 \n", " 17t18 18.335691 50.188234 15.538649 45.917943 45.612614 \n", " 19 4.728489 12.942764 4.007176 11.841522 11.762783 \n", " 20 931.529917 29.447854 10.273590 19.271625 19.486462 \n", " 21t22 90.326674 2821.000424 23.198240 363.916574 142.223056 \n", " 23 35.551012 77.346703 518.540713 250.877221 41.087803 \n", " 24 134.600162 414.014715 254.533734 1940.073909 858.289530 \n", " 25 36.346518 308.640250 35.017383 356.994995 269.405154 \n", " 26 40.469744 29.765072 8.536396 105.011698 39.029102 \n", " 27t28 307.140650 183.821644 39.748282 376.009535 192.166872 \n", " 29 22.279107 45.205836 36.726841 49.857619 28.242531 \n", " 30t33 13.228830 26.842204 21.807568 29.604327 16.769776 \n", " 34t35 8.080558 19.639293 18.150425 25.406816 11.405865 \n", " 36t37 110.342068 35.268883 21.252913 64.355459 29.135448 \n", " E 143.282141 356.331393 124.990480 359.975571 187.401518 \n", " F 109.473492 151.285346 935.469320 167.746506 93.523215 \n", " 50 230.146065 723.933947 115.779055 392.670136 231.061142 \n", " 51 276.108617 963.440976 976.941746 1308.409695 535.714326 \n", " 52 289.884901 858.592422 1003.348917 1302.437162 535.855098 \n", " H 23.433113 167.690188 103.972792 168.583295 31.931233 \n", " 60 218.706857 510.934567 264.079532 529.984384 320.186820 \n", " 61 3.898249 15.919886 15.316702 13.456574 5.596796 \n", " 62 1.669552 11.293316 2.145138 6.468971 1.904794 \n", " 63 325.523642 634.162539 98.547353 630.174898 72.132960 \n", " 64 74.415816 321.615785 114.934853 143.609205 71.615890 \n", " J 111.468536 441.552736 97.016295 296.043420 121.990028 \n", " 70 300.402024 541.707671 186.950544 98.494018 50.868687 \n", " 71t74 557.009305 2787.056493 1262.566488 2654.652613 1383.027258 \n", "... ... ... ... ... ... \n", "RoW 20 59.254639 1.921591 0.293189 0.419081 0.896964 \n", " 21t22 10.939833 305.243836 2.718898 43.005354 12.827419 \n", " 23 25.409174 52.937556 426.332774 189.227887 25.663685 \n", " 24 45.776375 137.849053 88.781323 694.935609 304.297810 \n", " 25 4.080999 38.578026 4.433015 43.078751 33.263153 \n", " 26 1.540591 0.842093 0.991921 5.264341 1.845787 \n", " 27t28 19.202156 17.107983 2.899187 23.417741 40.398734 \n", " 29 4.226874 5.044632 4.710717 6.153871 1.448788 \n", " 30t33 0.581584 5.573272 0.601050 3.175119 2.472000 \n", " 34t35 0.295067 0.589052 0.144417 0.873163 0.518826 \n", " 36t37 1.144750 1.872070 0.537275 2.212297 1.106440 \n", " E 0.173761 0.567528 20.428639 0.819155 0.253561 \n", " F 0.228649 0.150437 0.984623 0.227128 0.110467 \n", " 50 0.012600 0.039960 0.049854 0.052195 0.025508 \n", " 51 0.853480 4.639344 230.537056 6.007003 1.436657 \n", " 52 0.267343 1.589181 0.516815 1.104595 0.320696 \n", " H 0.112285 0.844576 0.471689 0.894151 0.123268 \n", " 60 0.435869 2.825101 234.376543 3.367219 0.414917 \n", " 61 0.008164 0.032342 0.082525 0.046836 0.007787 \n", " 62 1.580617 13.245788 2.369183 7.540798 2.183210 \n", " 63 0.151014 0.529874 0.096219 0.398736 0.083757 \n", " 64 0.065116 0.304461 0.102210 0.231570 0.101406 \n", " J 0.501054 3.041203 0.527920 1.128715 0.542113 \n", " 70 3.690224 5.954991 2.422823 0.176277 0.184588 \n", " 71t74 1.860358 9.415961 4.389323 8.278023 4.489652 \n", " L 0.248589 0.636937 0.238198 1.078893 0.160527 \n", " M 1.003295 4.474255 4.120725 4.517280 1.687657 \n", " N 1.749095 6.793279 0.164896 18.550374 0.174962 \n", " O 0.562692 2.533730 0.758305 2.141030 0.484539 \n", " P 0.000031 0.000096 0.000021 0.000116 0.000052 \n", "\n", "region ... RoW \\\n", "sector ... 63 64 J \n", "region sector ... \n", "AUS AtB ... 19.761917 0.001627 0.140044 \n", " C ... 0.211888 0.034300 0.005817 \n", " 15t16 ... 1.621756 1.588110 3.701685 \n", " 17t18 ... 0.401032 0.181367 1.492579 \n", " 19 ... 0.039708 0.017958 0.147786 \n", " 20 ... 0.027123 0.082776 0.063378 \n", " 21t22 ... 2.204172 10.102687 15.418063 \n", " 23 ... 59.028995 4.487274 11.189084 \n", " 24 ... 2.603711 1.444149 1.194342 \n", " 25 ... 0.973279 2.427753 0.704863 \n", " 26 ... 0.186875 0.421755 0.195426 \n", " 27t28 ... 15.617744 7.959440 2.380652 \n", " 29 ... 3.642359 30.309729 6.825963 \n", " 30t33 ... 2.002236 16.661519 3.752291 \n", " 34t35 ... 12.703247 8.769379 12.768384 \n", " 36t37 ... 0.226041 1.816351 1.501001 \n", " E ... 0.158169 0.222314 0.298537 \n", " F ... 0.967638 3.020002 6.822620 \n", " 50 ... 0.542576 1.055301 1.163450 \n", " 51 ... 0.822974 0.880188 2.617088 \n", " 52 ... 3.508417 8.412820 2.943161 \n", " H ... 13.417060 5.803010 31.833836 \n", " 60 ... 24.160506 27.963040 34.284311 \n", " 61 ... 2.683645 27.565014 25.181994 \n", " 62 ... 56.890998 228.034250 187.103415 \n", " 63 ... 23.523008 76.260841 59.942885 \n", " 64 ... 0.183698 3.195211 4.168414 \n", " J ... 10.691209 38.702169 87.947969 \n", " 70 ... 1.371040 55.154968 51.222023 \n", " 71t74 ... 13.609769 44.055788 110.840096 \n", "... ... ... ... ... \n", "RoW 20 ... 80.089178 38.342266 12.072937 \n", " 21t22 ... 2356.505474 5432.580816 7910.918929 \n", " 23 ... 940.236675 261.091828 154.913923 \n", " 24 ... 259.001665 86.217475 90.520415 \n", " 25 ... 1122.804886 762.399457 140.149436 \n", " 26 ... 119.947154 60.337788 18.657645 \n", " 27t28 ... 1298.244145 315.873918 171.199863 \n", " 29 ... 697.828174 319.985813 314.995799 \n", " 30t33 ... 818.546621 8308.403067 731.275786 \n", " 34t35 ... 1252.400960 1279.511149 517.703475 \n", " 36t37 ... 103.922288 113.850921 471.973179 \n", " E ... 4605.709269 7342.310696 5072.978446 \n", " F ... 982.318867 2242.910054 3428.713588 \n", " 50 ... 522.931361 593.953802 533.712735 \n", " 51 ... 3519.981195 7342.086914 2956.802019 \n", " 52 ... 2200.648191 3472.751467 2002.609268 \n", " H ... 5697.775736 2180.164612 7534.073416 \n", " 60 ... 7703.649094 5140.042568 7039.531612 \n", " 61 ... 319.845929 351.739712 393.717271 \n", " 62 ... 532.908584 1341.365292 1312.401998 \n", " 63 ... 3504.280492 1807.314685 1701.271137 \n", " 64 ... 2172.194846 20440.020040 11710.122737 \n", " J ... 7415.709712 8091.081325 38655.926218 \n", " 70 ... 1727.970393 5199.410339 7493.075988 \n", " 71t74 ... 6246.240339 12482.298686 24886.499828 \n", " L ... 608.700335 709.004146 1595.531658 \n", " M ... 91.678620 463.402398 1802.804212 \n", " N ... 39.843405 106.735687 305.274672 \n", " O ... 5414.944076 4371.240663 5815.525102 \n", " P ... 1.324062 0.244611 1.104726 \n", "\n", "region \\\n", "sector 70 71t74 L M \n", "region sector \n", "AUS AtB 0.043667 11.680006 3.113827 61.711687 \n", " C 0.088101 14.418832 0.315809 0.182157 \n", " 15t16 2.743954 27.665274 14.865583 86.096798 \n", " 17t18 0.632427 1.492750 6.550554 0.878764 \n", " 19 0.062619 0.147803 0.648594 0.087010 \n", " 20 0.205954 0.790532 2.353193 2.554166 \n", " 21t22 6.195107 48.596887 56.890466 21.913868 \n", " 23 11.512628 36.303514 27.566443 17.222495 \n", " 24 9.237368 19.609616 28.268265 42.763999 \n", " 25 3.349751 6.259412 2.576908 3.199048 \n", " 26 0.657503 1.604297 1.160610 1.514350 \n", " 27t28 18.293034 25.094179 4.177664 5.533838 \n", " 29 28.606393 41.232405 7.775303 17.255305 \n", " 30t33 15.725181 22.665809 4.274151 9.485390 \n", " 34t35 12.610675 64.711016 21.845125 12.221815 \n", " 36t37 0.734132 5.457432 3.653690 3.040151 \n", " E 1.804297 0.696923 0.819074 0.433625 \n", " F 4.445031 6.978164 3.820432 4.213175 \n", " 50 0.619550 0.820108 3.190926 0.401245 \n", " 51 1.334045 8.044024 8.112138 13.165919 \n", " 52 4.183650 25.137596 9.350485 9.915846 \n", " H 6.093826 44.016163 31.470631 22.222129 \n", " 60 29.296585 51.018691 66.987976 39.638572 \n", " 61 128.915922 66.003832 27.081238 6.700347 \n", " 62 40.923609 416.402802 518.481234 387.002863 \n", " 63 23.682097 132.257649 162.850890 120.792474 \n", " 64 0.398777 1.136361 4.488764 2.069959 \n", " J 49.862781 73.172178 17.970300 40.594369 \n", " 70 81.507135 1.324506 14.642011 7.911327 \n", " 71t74 45.926864 97.594121 30.529568 59.538339 \n", "... ... ... ... ... \n", "RoW 20 26.345271 629.084892 1884.054328 2120.766430 \n", " 21t22 1128.083167 26948.165198 16081.684247 9758.327387 \n", " 23 129.072765 789.857491 574.234856 141.229352 \n", " 24 172.206457 1469.037784 568.857200 464.549470 \n", " 25 493.458933 3238.293742 384.585818 748.594202 \n", " 26 135.596128 389.433240 439.866913 502.917719 \n", " 27t28 733.140609 4511.622232 548.761711 543.615393 \n", " 29 181.223515 1068.322357 753.097670 271.294575 \n", " 30t33 808.302796 21372.986647 1858.083732 2393.918095 \n", " 34t35 418.842054 6459.762846 2627.353449 1120.680148 \n", " 36t37 181.271520 482.787859 773.675064 852.380832 \n", " E 5141.941351 12517.586986 15224.240044 12110.158949 \n", " F 7483.145885 5407.731676 10000.889751 6437.551020 \n", " 50 225.393607 984.574183 1437.815851 342.158934 \n", " 51 2056.102533 13468.319458 8755.578709 4942.954370 \n", " 52 1022.444732 6822.892202 4692.901833 2286.924606 \n", " H 1565.207855 12160.455853 16699.714473 7750.382855 \n", " 60 1167.017249 10630.975028 10255.302827 4952.250191 \n", " 61 249.455177 1314.984794 916.026979 435.280134 \n", " 62 197.515757 2930.795161 3507.522443 2074.276308 \n", " 63 373.643784 3223.972374 4095.498850 1417.898957 \n", " 64 1468.996337 9246.282287 15881.469928 6012.447058 \n", " J 5758.940639 19989.913847 23896.327061 9546.835763 \n", " 70 2705.769797 9495.163791 8103.153981 5036.228134 \n", " 71t74 6015.478162 70478.453504 20430.836359 13305.638974 \n", " L 620.253937 1194.982705 4557.146576 518.488155 \n", " M 212.193133 1571.999239 7706.676330 5223.189539 \n", " N 70.364956 895.599603 1415.975389 840.530518 \n", " O 2897.014578 14958.970521 15443.391745 7897.357003 \n", " P 1.141934 50.552086 0.000000 1.089908 \n", "\n", "region \n", "sector N O P \n", "region sector \n", "AUS AtB 9.898359 10.256983 0.000038 \n", " C 0.273387 0.493510 0.000861 \n", " 15t16 46.736852 79.637133 0.006089 \n", " 17t18 2.252624 2.428735 0.001057 \n", " 19 0.223040 0.240478 0.000105 \n", " 20 1.827102 1.287573 0.010418 \n", " 21t22 17.326665 25.336693 0.025942 \n", " 23 18.549700 17.863948 0.011255 \n", " 24 112.870262 29.349604 0.052557 \n", " 25 4.867827 37.445945 0.008494 \n", " 26 1.381380 2.173674 0.001937 \n", " 27t28 4.012130 26.919745 0.049209 \n", " 29 6.985789 19.145209 0.031949 \n", " 30t33 3.840148 10.524287 0.017563 \n", " 34t35 5.288575 124.684698 0.005111 \n", " 36t37 2.261301 6.176947 0.330733 \n", " E 0.588291 0.542892 0.000114 \n", " F 4.269064 3.135682 0.006102 \n", " 50 0.715443 0.335334 0.000000 \n", " 51 10.882036 17.335205 0.125509 \n", " 52 14.368875 9.505814 0.045543 \n", " H 15.193905 8.820562 0.024843 \n", " 60 6.561055 44.037984 0.014616 \n", " 61 2.041265 17.273710 0.000000 \n", " 62 28.960407 154.036071 0.000035 \n", " 63 9.267663 53.423142 0.000042 \n", " 64 1.476196 0.879504 0.000243 \n", " J 12.824709 34.707057 0.069814 \n", " 70 0.554078 15.369971 0.000000 \n", " 71t74 18.124551 33.468160 0.097561 \n", "... ... ... ... \n", "RoW 20 1932.161785 914.755872 0.019687 \n", " 21t22 6011.875100 10934.428273 2.548514 \n", " 23 242.320646 423.896780 0.056465 \n", " 24 10243.419875 1465.864732 0.523719 \n", " 25 2193.842232 2876.932893 0.139278 \n", " 26 1116.624356 400.017883 0.111932 \n", " 27t28 931.955552 1147.905601 0.648180 \n", " 29 3154.318917 314.337084 0.227289 \n", " 30t33 2193.940291 4724.352592 1.743540 \n", " 34t35 392.761307 7211.302026 0.984097 \n", " 36t37 323.697939 504.572681 0.169314 \n", " E 12791.419341 10535.612431 4.831273 \n", " F 11354.319342 3839.537017 22.570339 \n", " 50 1088.152585 555.415078 0.513696 \n", " 51 19728.444632 9261.002711 4.393748 \n", " 52 8058.010782 4256.950765 6.790453 \n", " H 5346.893566 4441.279950 1.070657 \n", " 60 6210.736712 5982.700080 13.287645 \n", " 61 803.452478 647.422802 0.257212 \n", " 62 875.609110 1119.259998 0.346236 \n", " 63 2264.941271 2108.901331 0.387366 \n", " 64 7642.069297 4260.482612 8.457208 \n", " J 3563.218290 8195.767795 54.664765 \n", " 70 6230.303094 7501.857446 0.007471 \n", " 71t74 15560.647836 12040.071161 83.100716 \n", " L 921.621306 901.624286 0.000000 \n", " M 1488.980938 527.910083 0.001030 \n", " N 3513.234966 395.244668 0.000020 \n", " O 8895.570576 16565.733127 44.703532 \n", " P 4.570108 41.517464 3.460032 \n", "\n", "[1435 rows x 1435 columns]" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "wiod.Z" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "WIOD includes several satellite accounts, which are stored as child objects in Pymrio. \n", "For example, in order to see the AIR emissions provided by WIOD:\n", "\n" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
regionAUS...RoW
sectorAtBC15t1617t18192021t22232425...6364J7071t74LMNOP
stressor
CO26.471152e+032.331841e+043256.861259392.81989691.570641147.0752932100.1673067928.8506948832.60733182.623337...4.530961e+0423843.71627517594.61741611774.7698705.787274e+041.118612e+0525382.4702484.575128e+044.851286e+040.0
CH43.226169e+061.370016e+061221.45009341.7235746.11247164.722688189.78754433785.867211768.01832522.631731...2.031444e+042430.9697693979.9622455525.3202181.617241e+048.865122e+045001.0120411.394311e+041.360473e+070.0
N2O6.527106e+041.243851e+02527.65244010.7733781.33536214.793543111.798406146.52369810421.1859196.723839...7.185897e+02320.774141342.725185215.4780881.228492e+032.995831e+03272.1083247.680525e+039.170715e+040.0
NOX2.000881e+051.709849e+0570375.5331773875.234721964.7093389146.37383236269.74710818894.32146934546.808023663.707765...1.419601e+0587411.63972068809.56919960385.6014112.027940e+054.224802e+0599579.0169811.666314e+051.565510e+050.0
SOX1.976645e+044.713841e+0445815.6753971068.354291265.9584352521.54216026680.445075150018.06995891733.983039182.976023...6.973313e+0442938.02611533800.38503729662.3943759.961571e+042.075292e+0548914.8406938.185206e+047.690040e+040.0
CO1.496859e+067.159254e+05227663.41313816225.8757074039.30469938296.49960682187.57169256833.653485393632.6862532778.990301...1.385415e+06853066.323392671525.284261589314.2280141.979104e+064.123062e+06971810.0035031.626186e+061.527810e+060.0
NMVOC3.824729e+052.409498e+05141642.7408875460.9334121359.45661012888.95823128691.90175365893.299291105133.073315935.288872...3.377663e+05207978.880902163718.896513143675.7146324.825085e+051.005209e+06236928.7726363.964667e+053.724824e+050.0
NH34.049434e+054.575323e+02112.1579854.3136570.44987413.34297448.3331374.143371366.3289544.740067...4.569925e+02324.340516229.110878244.6634501.643215e+031.357458e+03113.8296146.203676e+024.965187e+030.0
\n", "

8 rows × 1435 columns

\n", "
" ], "text/plain": [ "region AUS \\\n", "sector AtB C 15t16 17t18 \n", "stressor \n", "CO2 6.471152e+03 2.331841e+04 3256.861259 392.819896 \n", "CH4 3.226169e+06 1.370016e+06 1221.450093 41.723574 \n", "N2O 6.527106e+04 1.243851e+02 527.652440 10.773378 \n", "NOX 2.000881e+05 1.709849e+05 70375.533177 3875.234721 \n", "SOX 1.976645e+04 4.713841e+04 45815.675397 1068.354291 \n", "CO 1.496859e+06 7.159254e+05 227663.413138 16225.875707 \n", "NMVOC 3.824729e+05 2.409498e+05 141642.740887 5460.933412 \n", "NH3 4.049434e+05 4.575323e+02 112.157985 4.313657 \n", "\n", "region \\\n", "sector 19 20 21t22 23 \n", "stressor \n", "CO2 91.570641 147.075293 2100.167306 7928.850694 \n", "CH4 6.112471 64.722688 189.787544 33785.867211 \n", "N2O 1.335362 14.793543 111.798406 146.523698 \n", "NOX 964.709338 9146.373832 36269.747108 18894.321469 \n", "SOX 265.958435 2521.542160 26680.445075 150018.069958 \n", "CO 4039.304699 38296.499606 82187.571692 56833.653485 \n", "NMVOC 1359.456610 12888.958231 28691.901753 65893.299291 \n", "NH3 0.449874 13.342974 48.333137 4.143371 \n", "\n", "region ... RoW \\\n", "sector 24 25 ... 63 64 \n", "stressor ... \n", "CO2 8832.607331 82.623337 ... 4.530961e+04 23843.716275 \n", "CH4 768.018325 22.631731 ... 2.031444e+04 2430.969769 \n", "N2O 10421.185919 6.723839 ... 7.185897e+02 320.774141 \n", "NOX 34546.808023 663.707765 ... 1.419601e+05 87411.639720 \n", "SOX 91733.983039 182.976023 ... 6.973313e+04 42938.026115 \n", "CO 393632.686253 2778.990301 ... 1.385415e+06 853066.323392 \n", "NMVOC 105133.073315 935.288872 ... 3.377663e+05 207978.880902 \n", "NH3 366.328954 4.740067 ... 4.569925e+02 324.340516 \n", "\n", "region \\\n", "sector J 70 71t74 L \n", "stressor \n", "CO2 17594.617416 11774.769870 5.787274e+04 1.118612e+05 \n", "CH4 3979.962245 5525.320218 1.617241e+04 8.865122e+04 \n", "N2O 342.725185 215.478088 1.228492e+03 2.995831e+03 \n", "NOX 68809.569199 60385.601411 2.027940e+05 4.224802e+05 \n", "SOX 33800.385037 29662.394375 9.961571e+04 2.075292e+05 \n", "CO 671525.284261 589314.228014 1.979104e+06 4.123062e+06 \n", "NMVOC 163718.896513 143675.714632 4.825085e+05 1.005209e+06 \n", "NH3 229.110878 244.663450 1.643215e+03 1.357458e+03 \n", "\n", "region \n", "sector M N O P \n", "stressor \n", "CO2 25382.470248 4.575128e+04 4.851286e+04 0.0 \n", "CH4 5001.012041 1.394311e+04 1.360473e+07 0.0 \n", "N2O 272.108324 7.680525e+03 9.170715e+04 0.0 \n", "NOX 99579.016981 1.666314e+05 1.565510e+05 0.0 \n", "SOX 48914.840693 8.185206e+04 7.690040e+04 0.0 \n", "CO 971810.003503 1.626186e+06 1.527810e+06 0.0 \n", "NMVOC 236928.772636 3.964667e+05 3.724824e+05 0.0 \n", "NH3 113.829614 6.203676e+02 4.965187e+03 0.0 \n", "\n", "[8 rows x 1435 columns]" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "wiod.AIR.F\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "WIOD, however, does neither provide any normalized data (A-matrix, satellite account coefficient data) nor any consumption based accounts (footprints).\n", "\n", "In order to calculate them, one could go through all the missing data and compute each account. \n", "Pymrio provides the required function, for example to calculate the A-matrix:\n" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "collapsed": true }, "outputs": [], "source": [ "x = pymrio.calc_x(Z=wiod.Z, Y=wiod.Y)\n", "A = pymrio.calc_A(Z=wiod.Z, x=x)" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
regionAUS...RoW
sectorAtBC15t1617t18192021t22232425...6364J7071t74LMNOP
regionsector
AUSAtB0.0954520.0003460.2208110.0867800.0967570.0936370.0095590.0000000.0086430.008967...1.143737e-045.153717e-092.285107e-077.786856e-081.517644e-054.463792e-061.377724e-042.552552e-052.604967e-056.252650e-09
C0.0003500.0317180.0026840.0018280.0020390.0014260.0020350.2209100.0077460.002002...1.226316e-061.086802e-079.492337e-091.571046e-071.873514e-054.527246e-074.066696e-077.050016e-071.253368e-061.432423e-07
15t160.0225350.0008310.0954440.0110520.0123230.0014560.0017310.0018110.0334810.005163...9.386042e-065.031958e-066.040074e-064.893121e-063.594692e-052.131039e-051.922126e-041.205233e-042.022545e-041.013494e-06
17t180.0007930.0003620.0015400.0574810.0640900.0018330.0017570.0007760.0018400.004355...2.321002e-065.746660e-072.435455e-061.127767e-061.939607e-069.390472e-061.961856e-065.808983e-066.168260e-061.759452e-07
190.0002040.0000930.0003970.0148240.0165280.0004730.0004530.0002000.0004740.001123...2.298108e-075.689976e-082.411432e-071.116643e-071.920475e-079.297846e-071.942504e-075.751684e-076.107418e-071.742097e-08
\n", "

5 rows × 1435 columns

\n", "
" ], "text/plain": [ "region AUS \\\n", "sector AtB C 15t16 17t18 19 20 \n", "region sector \n", "AUS AtB 0.095452 0.000346 0.220811 0.086780 0.096757 0.093637 \n", " C 0.000350 0.031718 0.002684 0.001828 0.002039 0.001426 \n", " 15t16 0.022535 0.000831 0.095444 0.011052 0.012323 0.001456 \n", " 17t18 0.000793 0.000362 0.001540 0.057481 0.064090 0.001833 \n", " 19 0.000204 0.000093 0.000397 0.014824 0.016528 0.000473 \n", "\n", "region ... \\\n", "sector 21t22 23 24 25 ... \n", "region sector ... \n", "AUS AtB 0.009559 0.000000 0.008643 0.008967 ... \n", " C 0.002035 0.220910 0.007746 0.002002 ... \n", " 15t16 0.001731 0.001811 0.033481 0.005163 ... \n", " 17t18 0.001757 0.000776 0.001840 0.004355 ... \n", " 19 0.000453 0.000200 0.000474 0.001123 ... \n", "\n", "region RoW \\\n", "sector 63 64 J 70 \n", "region sector \n", "AUS AtB 1.143737e-04 5.153717e-09 2.285107e-07 7.786856e-08 \n", " C 1.226316e-06 1.086802e-07 9.492337e-09 1.571046e-07 \n", " 15t16 9.386042e-06 5.031958e-06 6.040074e-06 4.893121e-06 \n", " 17t18 2.321002e-06 5.746660e-07 2.435455e-06 1.127767e-06 \n", " 19 2.298108e-07 5.689976e-08 2.411432e-07 1.116643e-07 \n", "\n", "region \\\n", "sector 71t74 L M N \n", "region sector \n", "AUS AtB 1.517644e-05 4.463792e-06 1.377724e-04 2.552552e-05 \n", " C 1.873514e-05 4.527246e-07 4.066696e-07 7.050016e-07 \n", " 15t16 3.594692e-05 2.131039e-05 1.922126e-04 1.205233e-04 \n", " 17t18 1.939607e-06 9.390472e-06 1.961856e-06 5.808983e-06 \n", " 19 1.920475e-07 9.297846e-07 1.942504e-07 5.751684e-07 \n", "\n", "region \n", "sector O P \n", "region sector \n", "AUS AtB 2.604967e-05 6.252650e-09 \n", " C 1.253368e-06 1.432423e-07 \n", " 15t16 2.022545e-04 1.013494e-06 \n", " 17t18 6.168260e-06 1.759452e-07 \n", " 19 6.107418e-07 1.742097e-08 \n", "\n", "[5 rows x 1435 columns]" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "A.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Alternatively, Pymrio provides a function which iterates through all missing accounts and calculates them:" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "wiod.calc_all()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "At this point, a basic EE MRIO analysis is accomplished. For example, the regional consumption based accounts of the AIR emissions are now given by:" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
regionAUSAUTBELBGRBRACANCHNCYPCZEDEU...PRTROURUSSVKSVNSWETURTWNUSARoW
stressor
CO24.404070e+051.022100e+051.586176e+0542924.9869754.059629e+055.659664e+055.031700e+0613943.187686108758.7456421.054136e+06...7.658922e+041.173831e+051.311461e+0640459.23337724251.7283419.434506e+043.494179e+052.246294e+056.210161e+065.620778e+06
CH44.275465e+067.599975e+051.030354e+06464018.7486071.352464e+074.068558e+065.433871e+07157009.091900780222.0894246.668537e+06...8.948877e+051.344168e+061.532052e+07411099.098085182504.0045547.352664e+053.652537e+061.104729e+063.917121e+077.560548e+07
N2O9.588178e+043.086814e+044.609171e+0413203.7130815.899229e+051.634371e+051.831795e+063200.30966527441.7285712.914646e+05...3.091511e+045.163863e+044.422776e+0513658.6741827011.7414633.576881e+049.538255e+043.551477e+041.182906e+063.590470e+06
NOX2.359815e+063.324339e+054.508892e+05142917.8187202.786076e+061.904551e+061.925370e+0735972.513098292246.7178212.701648e+06...3.025544e+053.380263e+054.444685e+06125333.62473073379.1825973.524920e+051.797639e+068.632669e+051.845556e+073.504645e+07
SOX2.399335e+061.983047e+053.702525e+05400357.9517501.699074e+062.088103e+063.245490e+0743500.967386225907.7852771.951840e+06...1.918064e+054.979996e+051.398364e+06103186.61082648180.2283652.078760e+051.548830e+061.075249e+061.523013e+072.860410e+07
CO2.173900e+071.371366e+062.167114e+06703172.2847722.681292e+077.525147e+069.904520e+07144686.477852829881.0935711.099191e+07...1.194956e+062.055640e+062.165403e+07455232.910264580264.6810742.048666e+064.860666e+064.927789e+061.005814e+083.566157e+08
NMVOC3.101630e+063.582680e+055.920832e+05190582.6505395.323333e+062.131757e+062.016103e+0743518.270216273912.6551262.923060e+06...4.003833e+056.065405e+054.179851e+06138654.031320142881.8416425.666544e+051.738178e+061.095519e+062.095710e+074.208942e+07
NH33.851776e+059.254548e+041.245648e+0545897.3946391.345046e+064.204562e+056.415339e+068931.59474567224.1404418.505438e+05...8.987684e+041.911781e+057.889417e+0535515.96817023476.6333398.488958e+045.979386e+051.032068e+053.090159e+068.572543e+06
\n", "

8 rows × 41 columns

\n", "
" ], "text/plain": [ "region AUS AUT BEL BGR \\\n", "stressor \n", "CO2 4.404070e+05 1.022100e+05 1.586176e+05 42924.986975 \n", "CH4 4.275465e+06 7.599975e+05 1.030354e+06 464018.748607 \n", "N2O 9.588178e+04 3.086814e+04 4.609171e+04 13203.713081 \n", "NOX 2.359815e+06 3.324339e+05 4.508892e+05 142917.818720 \n", "SOX 2.399335e+06 1.983047e+05 3.702525e+05 400357.951750 \n", "CO 2.173900e+07 1.371366e+06 2.167114e+06 703172.284772 \n", "NMVOC 3.101630e+06 3.582680e+05 5.920832e+05 190582.650539 \n", "NH3 3.851776e+05 9.254548e+04 1.245648e+05 45897.394639 \n", "\n", "region BRA CAN CHN CYP \\\n", "stressor \n", "CO2 4.059629e+05 5.659664e+05 5.031700e+06 13943.187686 \n", "CH4 1.352464e+07 4.068558e+06 5.433871e+07 157009.091900 \n", "N2O 5.899229e+05 1.634371e+05 1.831795e+06 3200.309665 \n", "NOX 2.786076e+06 1.904551e+06 1.925370e+07 35972.513098 \n", "SOX 1.699074e+06 2.088103e+06 3.245490e+07 43500.967386 \n", "CO 2.681292e+07 7.525147e+06 9.904520e+07 144686.477852 \n", "NMVOC 5.323333e+06 2.131757e+06 2.016103e+07 43518.270216 \n", "NH3 1.345046e+06 4.204562e+05 6.415339e+06 8931.594745 \n", "\n", "region CZE DEU ... PRT \\\n", "stressor ... \n", "CO2 108758.745642 1.054136e+06 ... 7.658922e+04 \n", "CH4 780222.089424 6.668537e+06 ... 8.948877e+05 \n", "N2O 27441.728571 2.914646e+05 ... 3.091511e+04 \n", "NOX 292246.717821 2.701648e+06 ... 3.025544e+05 \n", "SOX 225907.785277 1.951840e+06 ... 1.918064e+05 \n", "CO 829881.093571 1.099191e+07 ... 1.194956e+06 \n", "NMVOC 273912.655126 2.923060e+06 ... 4.003833e+05 \n", "NH3 67224.140441 8.505438e+05 ... 8.987684e+04 \n", "\n", "region ROU RUS SVK SVN \\\n", "stressor \n", "CO2 1.173831e+05 1.311461e+06 40459.233377 24251.728341 \n", "CH4 1.344168e+06 1.532052e+07 411099.098085 182504.004554 \n", "N2O 5.163863e+04 4.422776e+05 13658.674182 7011.741463 \n", "NOX 3.380263e+05 4.444685e+06 125333.624730 73379.182597 \n", "SOX 4.979996e+05 1.398364e+06 103186.610826 48180.228365 \n", "CO 2.055640e+06 2.165403e+07 455232.910264 580264.681074 \n", "NMVOC 6.065405e+05 4.179851e+06 138654.031320 142881.841642 \n", "NH3 1.911781e+05 7.889417e+05 35515.968170 23476.633339 \n", "\n", "region SWE TUR TWN USA RoW \n", "stressor \n", "CO2 9.434506e+04 3.494179e+05 2.246294e+05 6.210161e+06 5.620778e+06 \n", "CH4 7.352664e+05 3.652537e+06 1.104729e+06 3.917121e+07 7.560548e+07 \n", "N2O 3.576881e+04 9.538255e+04 3.551477e+04 1.182906e+06 3.590470e+06 \n", "NOX 3.524920e+05 1.797639e+06 8.632669e+05 1.845556e+07 3.504645e+07 \n", "SOX 2.078760e+05 1.548830e+06 1.075249e+06 1.523013e+07 2.860410e+07 \n", "CO 2.048666e+06 4.860666e+06 4.927789e+06 1.005814e+08 3.566157e+08 \n", "NMVOC 5.666544e+05 1.738178e+06 1.095519e+06 2.095710e+07 4.208942e+07 \n", "NH3 8.488958e+04 5.979386e+05 1.032068e+05 3.090159e+06 8.572543e+06 \n", "\n", "[8 rows x 41 columns]" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "wiod.AIR.D_cba_reg" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
unitunit
stressor
CO2Gg
CH4t
N2Ot
NOXundef
SOXundef
COt
NMVOCt
NH3t
\n", "
" ], "text/plain": [ "unit unit\n", "stressor \n", "CO2 Gg\n", "CH4 t\n", "N2O t\n", "NOX undef\n", "SOX undef\n", "CO t\n", "NMVOC t\n", "NH3 t" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "wiod.AIR.unit" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Pymrio can be linked with the [country converter coco](http://joss.theoj.org/papers/af694f2e5994b8aacbad119c4005e113) to ease the aggregation of MRIO and results into different classifications.\n", "Using the country converter, WIOD can be aggregated into EU and non-EU countries with singling out Germany by:" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import country_converter as coco\n", "wiod.aggregate(region_agg = coco.agg_conc(original_countries='WIOD',\n", " aggregates=[{'DEU': 'DEU', 'GBR':'GBR'}, 'EU'],\n", " missing_countries='Other',\n", " merge_multiple_string=None))\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We rename the EU account to reflect that is does not include Germany:" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "wiod.rename_regions({'EU':'Rest of EU'})" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The regional footprint account are now:" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
regionOtherRest of EUDEUGBR
stressor
CO22.436179e+073.472823e+061.054136e+067.397044e+05
CH42.540661e+082.711250e+076.668537e+065.235498e+06
N2O9.705186e+061.128531e+062.914646e+052.118832e+05
NOX1.043111e+081.093267e+072.701648e+062.164933e+06
SOX1.037493e+088.344435e+061.951840e+061.421854e+06
CO7.661455e+085.466639e+071.099191e+071.068169e+07
NMVOC1.280392e+081.577316e+072.923060e+062.986943e+06
NH32.672782e+073.493227e+068.505438e+055.900984e+05
\n", "
" ], "text/plain": [ "region Other Rest of EU DEU GBR\n", "stressor \n", "CO2 2.436179e+07 3.472823e+06 1.054136e+06 7.397044e+05\n", "CH4 2.540661e+08 2.711250e+07 6.668537e+06 5.235498e+06\n", "N2O 9.705186e+06 1.128531e+06 2.914646e+05 2.118832e+05\n", "NOX 1.043111e+08 1.093267e+07 2.701648e+06 2.164933e+06\n", "SOX 1.037493e+08 8.344435e+06 1.951840e+06 1.421854e+06\n", "CO 7.661455e+08 5.466639e+07 1.099191e+07 1.068169e+07\n", "NMVOC 1.280392e+08 1.577316e+07 2.923060e+06 2.986943e+06\n", "NH3 2.672782e+07 3.493227e+06 8.505438e+05 5.900984e+05" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "wiod.AIR.D_cba_reg" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To visualize for example the CH4 accounts:" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAjgAAAFgCAYAAAC2QAPxAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4xLCBo\ndHRwOi8vbWF0cGxvdGxpYi5vcmcvAOZPmwAAIABJREFUeJzt3XdYFFf/NvB7l3XpILACUizYsZfE\n3gIolliiaGzBlsQQYzBqLNEYY4wVYzQYG+qjMcaaYCQ2LMFfND4qNjSKqESNgqFYqLLsef/wZR9X\nlqLALjvcn+viunZmzsx+Z2eVmzNnZmRCCAEiIiIiCZEbuwAiIiKi0saAQ0RERJLDgENERESSw4BD\nREREksOAQ0RERJLDgENERESSw4BD5UKXLl0wduxYY5eh49ixY5DJZLh7926pbK9GjRr46quvSmVb\nRGVl5MiR8PX1NXYZRCXGgEMGkZCQAAsLC7i6uiInJyff8t27d2Pp0qUvvd34+HjIZDK9P0uWLClR\nze3atcP9+/fh5uZWou3kOX36NCZOnFgq2yqu3r17w8zMDHv27DHo+5Y2X19fjBw50qDvefnyZYwY\nMQIeHh4wNzdH9erV0b9/fxw9elTbpqDQWlg41mg08PHxgUwmww8//FBoDV999RVq1Kjx0rXfvXsX\nMpkMx44de+l1K5pX/Yyp/GPAIYNYv349evXqBScnJ4SHh+db7ujoCDs7uwLXf/r0aaHbDw8Px/37\n93V+goKCSlSzUqmEq6sr5PLS+WdSpUoVWFtbl8q2iuPOnTs4cuQIJk+ejDVr1hjsfaXgwIEDaNWq\nFe7du4e1a9fiypUr+PXXX9GmTRu8//77Jdr2l19+CSsrq1KqlIgKJIjKWG5urqhRo4YIDw8XCxcu\nFH5+fvnadO7cWYwZM0ZnevTo0WLmzJnC1dVVqFQqvdu+deuWACCOHz9e4PsfPXpUABARERGiTZs2\nwsLCQrRo0ULExMSImJgY0b59e2FpaSlee+01cfny5Xzr3blzRwghxNOnT8XEiROFu7u7UCqVwtXV\nVQwePFjbPiYmRnTr1k3Y29sLKysrUb9+fbFp0ybt8urVq4u5c+dqpx8/fizee+89oVKphLm5uWjZ\nsqU4cOBAvn3btm2b6N27t7C0tBQ1a9bU2WZhPv/8c9G/f39x7949oVQqxe3bt/O1OXTokOjQoYOw\ntLQUdnZ2olOnTiIuLk67/KeffhItWrQQ5ubmwtHRUfj7+4uUlBTt5zF16lTh5uYmKlWqJBo0aCC2\nbNmis30AYvPmzTrzfHx8RGBgoM7nMmvWLDFhwgTh4OAgnJ2dxaRJk4RarRZCCBEYGCgA6PwcPXpU\nCCHEvHnzRM2aNYVSqRQqlUp069ZNZGRkFOvzKUh6erpwdnYW/v7+epfn7X9e7c8f0zwvfnfyHDly\nRHh6eoqkpCS9n83zNmzYkG+/Z8+eLYQo+rvz4nrVq1cXQghx8+ZN0b9/f1G1alVhaWkpGjVqlO/7\nFBgYKHx8fAr9jJYtWyaaNm0qrK2thYuLixg8eLC4d++eTpu4uDgxcOBA4eDgICwtLUXjxo3Fr7/+\nql1+5swZ0b17d2Frayusra3Fa6+9Jv7880/t8o0bN4oGDRoIpVIp3N3dxWeffSZycnK0y1/8P0MI\nIebOnavd1+f3ZfXq1aJatWrC1tZW9OnTRzx48KDIz5hMH3twqMwdPHgQ6enp6NmzJ0aMGIFjx47h\n5s2bRa63fft2/Pvvvzh8+DCOHDlS4jo+++wzzJs3D2fPnoVSqcSQIUPwwQcfYM6cOdp5o0aNKnD9\nFStWYPv27fjhhx9w/fp17NmzB23atNEuHzJkCJycnHDixAlcunQJS5cuhYODQ4HbGz16NA4cOIAf\nfvgB586dQ/v27dG7d29cvXpVp920adMwYsQIXLx4EYMGDcKoUaNw/fr1Qvc1NzcXYWFhGDlyJKpW\nrQofHx+EhYXptImMjET37t3RsmVLnDx5EqdOncI777yjPYW4YcMGDB8+HP369UN0dDSOHj0Kf39/\n5ObmAgBmzJiBtWvXYtmyZYiJicHw4cMxfPhwHD58uNDa9FmxYgWqVq2KU6dOYfny5Vi2bBk2bdoE\nAPj222/RsWNHDBo0SNs7165dO+zevRsLFizAt99+i+vXr+PQoUPo0aPHS7/3iw4ePIgHDx7gs88+\n07u8sGNamMTERIwYMQKbNm2Ck5NTke0HDx6MqVOnwsPDQ7vfkydPBlD0dyc6OhoAsGvXLty/fx+n\nT58GAKSlpcHHxwf79+/HpUuX8N5772HUqFE6p92Ka8mSJbh06RJ+/vln3L59G2+//bZ2WUJCAtq1\na4fU1FTs2bMHly5dwty5c7W9oZcvX0anTp3g4OCAI0eO4Ny5c5g4cSI0Gg0AICIiAqNHj8aIESNw\n6dIlhISEIDQ0FHPmzHnpOk+fPo2jR48iIiIC+/fvx/nz57WfY2GfMUmAsRMWSV+/fv1EcHCwdrpH\njx5i+vTpOm309eDUqVNH5ObmFrrtvF4OS0tLYW1trfNz4sQJIcT//pr++eeftett375dABA7d+7U\nztu9e7cAIJ48eaKzXt5f4RMmTBBdu3YVGo1Gby12dnZiw4YNBdb6/F/7169f1/YqPa958+Zi1KhR\nOvsWEhKiXZ6TkyOsra3FqlWrCv1cfvnlF1GlShXx9OlTIYQQ27ZtEx4eHtpeESGE6NChg+jVq1eB\n2/D09BQffvih3mXp6elCqVSK0NBQnfn9+vUTXbt21U6jmD04b775pk6b7t27i7fffrvAdYQQYunS\npaJOnTrafSwtCxcuFABEcnJykW2rV68ulEplvu+ehYWFzncnNzdX+Pj4iFmzZmnX1ffZvOjFHgkh\nivfduXPnjk5PV2H69Okjxo4dq50uTg/Oi6KjowUAcffuXSGEEDNnzhQuLi4iLS1Nb/vhw4eLJk2a\nFPjvu0OHDiIgIEBn3rJly4SFhYXIzs4WQhS/B0elUomsrCztvPnz5wtXV9cC1yHpMPkenJUrV2Ls\n2LGYNGlSkW2TkpIwZ84cfPrpp5g8ebL2rxwqO/fv38fevXsRGBionTdy5Ehs2LABarW60HVbtmxZ\n7PEvGzZswPnz53V+mjdvrtOmadOm2teurq4AgCZNmuSb9+DBA73vMWrUKFy6dAm1a9fGuHHjsGvX\nLp2xQZMnT8bYsWPRpUsXfPHFF4V+v65cuQIA6NSpk878Tp064fLlyzrzmjVrpn2tUCjg4uKCxMTE\nArcNAKtXr8bQoUNRqVIlAEDfvn2Rnp6Offv2aducPXsW3bp107v+gwcPcOfOnQKXx8XF4enTp/nq\n79y5c776i+P5fQQAd3f3Ivdx0KBByMnJQfXq1TFy5Ehs3rwZT548KbD9li1bYGNjo/3ZsmWL3nbi\nJZ8//OGHH+b77q1bt06nzddff42srCzMnj37pbatz8t8d16UkZGBadOmoWHDhnB0dISNjQ1+++03\n/P333y9Vw7Fjx9C9e3d4enrC1tYWHTp0AADtds6ePYt27doVOObs7Nmz8PHxKfDfd14Pz/M6d+6M\nrKws3Lhx46VqbdCgAczNzbXTxflukTSYfMDp0qULZsyYUay2u3btQtu2bbFo0SIEBwfn67Kn0hcW\nFga1Wo1WrVpBoVBAoVBg6NChSEhIKPLKnpcZkOvu7o7atWvr/FhYWOi0yftlDwAymazAeXnd5C9q\n1qwZbt26hSVLlkCpVOLjjz9Gs2bN8PjxYwDArFmzEBsbi0GDBiEmJgZt2rTBzJkzi70PwLNfrnl1\n5FEqlTrTMpmswBoB4Pbt2zhw4ABWrFih/cytra2Rmpqab7Dxi+/1opdd/mL9MpksX2DQdxXdy+4j\n8OyYX716FevXr4ezszPmzp2LevXq4c6dO3rb9+nTRyeE9OnTR2+7evXqAfhfkCiKo6Njvu+eu7u7\nTpvIyEicPHkS5ubm2mMCAIGBgahfv36x3qco+r47L5oyZQp++OEHfP755zh69CjOnz+Pnj17FjmI\n/3m3b99Gz549UaNGDfz00084c+aM9t/y89spi+/W8/Plcvkrf7deNsSSaTL5gOPt7Q0bGxudeQkJ\nCZg3bx6mTp2Kzz//HP/88w+AZ1/sjIwMAM/+knnVc+lUPBqNBuvWrcOMGTPy/YU7fPhwk7yyx8bG\nBv3798fy5ctx5swZ/PXXX/j999+1y728vBAUFISdO3fiyy+/xPfff693Ow0bNgQAREVF6cw/fvy4\ndtmrWrt2LRo0aIALFy7ofOY7duzAb7/9pv330LJlSxw4cEDvNpydneHh4VHg8tq1a8Pc3Fxn3/P2\n5/n6nZ2dce/ePe10dnZ2sYPD85RKpXbsz/PMzc3h7++PRYsW4dKlS8jIyMAvv/yidxu2trY6IcTW\n1lZvu27dusHZ2Rnz5s3Tuzw1NfWl69+wYUO+4wEA8+bNw6+//lrgevr2uzjfnbxf6i+uGxUVhWHD\nhmHw4MFo2rQpvLy8EBsb+1L7cvr0aWRmZmLZsmVo37496tWrl69HpGXLlvjjjz+Qnp6udxstW7ZE\nZGRkgSG2YcOGer9blpaW8PLyApD/uwXglXrlC/pukelTGLuAsrBmzRq8++67qFq1Kq5fv45169Zh\n9uzZCAgIwFdffYX9+/cjOzsbs2bNMnapkrZ//37cvn0b77//PqpVq6azbNSoUfDz80N8fHyp3IMi\nJSUFCQkJOvOsra0L/CX2KhYvXgw3Nzc0a9YMVlZW2Lp1K8zMzFC3bl2kpaVh6tSpGDBgAGrWrImH\nDx9i//798Pb21rutWrVqISAgAEFBQVi9ejWqV6+O77//HjExMfjxxx9fuUa1Wo3169dj3LhxaNSo\nkc6yRo0awcPDA2FhYfj8888xa9Ys9OjRA8HBwRg9ejTMzc1x8uRJtG3bFvXq1cPs2bPxwQcfwMXF\nBQMHDoRGo8HRo0fx9ttvQ6VSYcKECZg1axaqVKmCZs2aYceOHQgPD8ehQ4e07+nr64tVq1ahU6dO\nsLW1xbx5816qtyBPzZo1cfToUdy4cQP29vawt7fHpk2boNFo8Prrr6Ny5co4fPgwnjx5UuBnXlxW\nVlbYuHEj+vfvD19fX0yaNAn16tVDeno6Dhw4gLVr1+LatWsvXb8+Hh4eqFOnTqHrJSQk4OTJk6hT\npw6srKyK9d1RqVSwsbHBwYMH0bBhQ5ibm8PBwQH16tVDeHg4BgwYABsbGyxduhT37t2Di4tLsfel\nTp06kMlkCAkJwbBhw3DhwgV8+eWXOm3yauvbty/mzJkDNzc3XL58GWZmZujRowc+/fRTtG7dGsOG\nDcOkSZPg4OCA6OhoeHh4oG3btpg+fTrefPNNLFiwAG+99RbOnz+PL774ApMmTdKGN19fX3zwwQfY\nvn07WrRogZ07d+L48eOoXLlysfeloM+Yl/FLhPGG/5SexMRE8cknnwghhMjMzBRDhw4VkydP1v7k\nDXD99ddfxZ49e4QQQly7dk0EBwcXOYiVXl2fPn1EmzZt9C5Tq9XCxcVFfPbZZ0II/YOMXxxAqE/e\nQFx9P3kDZPVdsnv8+HEBQNy6dUs77+TJkwKAuH79ut71Vq1aJVq0aKG9rLVVq1bil19+EUI8+94N\nGTJE1KhRQ5ibm4sqVaqIQYMG6Vya/eIlxY8ePdJe6qtUKgu8TPzFS+Br1apV4KWseQOlr169qnf5\n5MmTRbVq1bTf+/3792svnbezsxNdunQRN27c0Lb/4YcfRJMmTYRSqRSOjo6iZ8+eIjU1VQhRvMvE\n79+/L3r37i1sbW2Fh4eHWLlypd5Bxi9eaj1mzBjRuXNn7fSNGzdEx44dhbW1tXbw7K5du0Tbtm1F\n5cqVhaWlpWjYsKFYt26d3v1+FRcvXhRDhw4VVatWFZUqVRKenp6if//+4vfffy+0diEKvkz8eSjG\nIOOnT5+KIUOGCAcHB51LmIv67gghxH/+8x9Ro0YNoVAotINob9++Lbp16yasrKyEq6ur+Pzzz8Xo\n0aN1PuviDDL+7rvvhIeHh7CwsBDt27cX+/btyzeo+dq1a6Jfv37Czs5OWFpaiiZNmugMjD516pTw\n8fERVlZWwsbGRrz++uvi1KlT2uUbN24U9evXF5UqVRJubm5ixowZOpeJP336VHz88ceiSpUqwt7e\nXgQFBYlZs2bpvUz8eZs3bxbP/+or6DMm0ycTwvRPRj548AALFy5ESEgIMjIyEBwcrPf0xyeffIIZ\nM2ZApVIBAMaPH4958+bB3t7e0CUTERFRGTL5MTgvsrKygrOzM06ePAng2cC0+Ph4AM+6bWNiYgA8\nu5V5Tk5OoXfPJSIiItNk8j04y5Ytw5UrV/DkyRPY29tj0KBBaNSoEdauXYuHDx9CrVajffv2GDhw\nIO7evYvVq1cjKysLADB8+HCdS4eJiIhIGkw+4BARERG9SHKnqIiIiIgYcIiIiEhyTP4+OC/e6Kki\nUalUSEpKMnYZZCQ8/hUbj3/FVdGPvZubW7HasQeHiIiIJIcBh4iIiCSHAYeIiIgkx+TH4BAREZUH\nQghkZWVBo9EU+bT0kkhMTER2dnaZbb88EEJALpfDwsLilT9LBhwiIqJSkJWVhUqVKkGhKNtfrQqF\nAmZmZmX6HuWBWq1GVlYWLC0tX2l9nqIiIiIqBRqNpszDTUWiUCig0WheeX0GHCIiolJQlqelKqqS\nfKYMOERERCQ57EsjIiIqAwc8RpTq9rrf3VxkG09PT9SvX187vX79enh6er7U+8TExCAxMRE+Pj4v\nXWOfPn2wZ8+eQtusXbsWw4cPf+WxNcXFgENERCQRFhYWOHToUIm2cfnyZVy8ePGlAk5ubi7MzMyK\nDDcAsG7dOgwYMIABR8pcYxeVaH21qmTrExGR9GVlZWH69Om4ePEizMzMMHv2bLRv317v/Ndeew1L\nlixBVlYW/vvf/2L8+PGIi4tDfHw8EhIScO/ePQQFBWHYsGE4ceIEli5dChcXF1y+fBnHjh1DnTp1\ncP36de0yBwcHXLt2DU2aNMGKFSuwfv16JCYmIiAgAA4ODti5c2eZ7TcDDhERkURkZWXBz88PAFCt\nWjWEhYVh48aNAIDDhw8jLi4OQ4YMwfHjxwucP3nyZFy8eBHz5s0DAISEhOCvv/7Cr7/+iszMTHTr\n1k3bu3P+/HkcOXIE1apVy1dLTEwMjhw5AldXV/Tt2xenT5/GmDFjsGbNGuzYsQOOjo5l+lkw4BAR\nEUmEvlNUp0+fxqhRowAAtWvXhoeHB27evFngfH26d+8OS0tLWFpaol27djh//jzs7OzQrFkzveEG\nAJo1a6Z9MGbDhg1x584dvP7666W1q0XiVVREREQSJoR4qfn6vHi5dt60lZVVgesolUrtazMzM6jV\n6mK/X2lgwCEiIpKw1q1b4+effwYA3LhxA//88w9q1apV4HwbGxukpaXpbOPAgQPIyspCSkoKTp48\niaZNm75yPfq2XxZ4ioqIiKgMFOeybkMIDAzEtGnT4OPjAzMzM3zzzTcwNzcvcH67du0QGhoKPz8/\njB8/HgDQvHlzvPPOO/jnn38QHBwMV1fXAk9nFWXYsGEYPnw4nJ2dy3SQsUy8TB9VOXTv3j1jl/DK\nSnwVVbtFSEpKKqVqyNSoVCoe/wqMx7/8ycjIKPSUTWlRKBQGPd0TEhICa2trjBs3zmDvmUffZ5o3\nrqcoPEVFREREksNTVERERFSgSZMmGbuEV8IeHCIiIpIcBhwiIiKSHAYcIiIikhwGHCIiIpIcDjIm\nIiIqAyW9FciLEup+WujylJQUDB48GADw77//wszMTPu8p4iICJ07CxfXggUL0LFjR7Rv3x6rV69G\nYGAgLCwsXmobEydOxIcffojatWsX2KZfv3746quv0KhRo5eusSAMOERERBLg6OiofQ7Vq9y7Jjc3\nF2ZmZtpptVqNadOmaafXrFmDt99++6UCTm5uLr755ptity9NPEVFREQkcdu3b0evXr3g5+eH6dOn\nQ6PRQK1Wo0GDBli4cCF69eqFc+fOoWXLlvjmm2/Qt29f7Nu3Dx999BH279+PNWvWIDk5GW+99Za2\nl2jXrl3w8fHBG2+8gfnz5wOA3m3269cPMTExAIBPP/0UPXr0QNeuXcs8+DDgEBERSdjVq1exf/9+\nhIeH49ChQ8jNzUV4eDgA4PHjx2jcuDEiIiLQqlUrAM8eoBkeHo4333xTu4333nsPTk5O2L17N7Zt\n24Z79+5h0aJF2LFjBw4cOIAzZ85oe4/0bTPP9OnTsW/fPhw6dAhRUVGIjY0ts/02yCmqpKQkhIaG\n4uHDh5DJZPD19UXPnj112ly+fBmLFi2Cs7MzgGcPBxs4cKAhyntlBzxGlGj9wCONS6kSIiIi/Y4f\nP44LFy6gR48eAICsrCxUrVoVwLMnfufNz9OnT58it3nu3Dm0b99eO8anX79+OHXqFLp27ap3m3nC\nw8OxdetW5ObmIiEhAbGxsahbt25Jdq9ABgk4ZmZmGDFiBLy8vJCZmYlp06ahSZMm8PDw0GnXoEED\nnfN9REREVDJCCAwePBiffqo7SFmtVsPCwgIymUxnfnGep1XYYyz1bRMAbt68iXXr1iEiIgL29vb4\n6KOPkJ2dXcy9eHkGOUXl4OAALy8vAIClpSXc3d2RkpJiiLcmIiKq0Dp27Ihff/1V+3s3JSUF//zz\nz0tvx8bGBmlpaQCAFi1a4MSJE0hJSYFarUZ4eDjatGlT6PppaWmwsbGBra0tEhMTcezYsZeu4WUY\n/CqqBw8e4NatW3ovF4uNjcWUKVPg4OCAESNGwNPTM1+byMhIREZGAnh2+ZpKpSrzmssrhUJRofe/\nouPxr9h4/MufxMREKBT/+7Wa5D2jVLf//C/s599HH7lcDrlcDoVCgcaNG2Py5Ml4++23odFoUKlS\nJSxatAju7u75tiWTyaBQKLTzZDKZdjsjRozAkCFD4Obmhp07d2Lq1KkICAiAEALdunWDv7+/9inn\n+rbZsGFD1KtXDz4+PqhWrRpef/11mJmZQaFQ5HvfPObm5q/8PZeJwvqZSllWVhZmz56Nt956C61b\nt9ZZlpGRAblcDgsLC0RHR2Pjxo1Yvnx5kdu8d+9eWZVbJGOPwVG3W4SkpKQSbYNMl0ql4vGvwHj8\ny5+MjIxind4pKYVCoQ0SUqfvM3VzcyvWuga7ikqtViMkJAQdO3bMF26AZ+f88q6tb9GiBXJzc/H4\n8WNDlUdEREQSYpCAI4TAqlWr4O7ujt69e+tt8/DhQ+2gpbi4OGg0Gtja2hqiPCIiIpIYg4zBuXbt\nGqKiolCtWjVMmTIFADBkyBBt92q3bt3w559/4uDBgzAzM4NSqURwcLDeUdhERERERTFIwKlfvz62\nb99eaBt/f3/4+/sbohwiIiKSON7JmIiIiCSHAYeIiIgkh08TJyIiKgOxOFSq26sLvyLb1KlTB9ev\nXy/V9y3MnTt3cObMGfTv399g71lc7MEhIiKil6ZWq3Hnzh38/PPPxi5FL/bgEBERScyJEycQEhIC\nlUqFy5cvo2fPnqhfvz7CwsKQlZWFsLAw1KhRA8HBwTA3N0dsbCz+/fdfzJ49G35+fsjKysL06dNx\n8eJFmJmZYfbs2Wjfvj22bduGw4cPIzs7GxkZGcjMzERcXBz8/PwQEBCAzp0745NPPsHTp08hhMCa\nNWu0j2oyNAYcIiIiCbpy5QqOHTuGypUro127dhgyZAgiIiKwbt06rF+/Hl9++SUA4O7du9i1axfi\n4+MREBCAjh07YuPGjQCAw4cPIy4uDkOGDMHx48cBAGfPnkVkZCQcHBxw4sQJrFq1Cps2bQIAzJw5\nE2PGjMFbb72Fp0+fIjc31yj7DvAUFRERkSQ1bdoULi4uMDc3R/Xq1dG5c2cAz27dcvfuXW27N998\nE3K5HF5eXqhevTri4uJw+vRpDBgwAABQu3ZteHh44ObNmwCATp06wcHBQe97tmzZEitWrEBoaCju\n3r0LS0vLMt7LgjHgEBERSZBSqdS+lsvl2mm5XK7zLKsXb6ork8lQ2GMqC3veVv/+/bFhwwZYWFhg\n2LBh+L//+79XLb/EGHCIiIgqsL1790Kj0SA+Ph5///03atWqhdatW2sHD9+4cQP//PMPatWqlW9d\nGxsbpKena6f//vtvVK9eHWPGjIGfnx/++usvg+3HizgGh4iIqAwU57Lu8sDLywsDBgzAv//+iwUL\nFsDCwgKBgYGYNm0afHx8YGZmhm+++Qbm5ub51m3QoAHMzMzg6+uLQYMGITs7G7t374ZCoYCzszMm\nTpxohD16RiYK64cyAffu3TPaex/wGFGi9QOPNC7R+up2i7TP86KKR6VS8fhXYDz+5U9GRkahp29K\ni0Kh0DnFVBLBwcHw9fUt8EHYxqbvM3VzcyvWujxFRURERJLDU1REREQV1LJly4xdQplhDw4RERFJ\nDgMOERERSQ4DDhEREUkOAw4RERFJDgcZExERlYHpQYdLdXvzV/oU2cbT0xP169fXTvft2xfjx48v\n1Tqet3//fnh5eaFu3bpl9h6vigGHiIhIIiwsLHDo0CGDvJdarcb+/fvh6+tbLgMOT1ERERFJ2OPH\nj9GxY0fExcUBAIKCgrBlyxYAQJ06dTBnzhx0794dgwYNQnJyMgAgJiYGvXv3hq+vL8aMGYOHDx8C\nAAYOHIj58+djwIABCA0NxaFDh/DVV1/Bz88P8fHxCAsLQ5cuXeDr64sPPvjAODv8/7EHh4iISCKy\nsrLg5/e/R0SMHz8effv2xbx58zBx4kSMHTsWjx49wrBhwwA8u1Nw48aNMXv2bHzzzTdYunQp5s2b\nh+DgYMydOxdt27bF4sWLsXTpUnz55ZcAngWmXbt2AQBu3bqlcyfk0NBQnDx5Eubm5nj06JGB914X\nAw4REZFEFHSKqlOnTti7dy9mzJihs1wul6NPnz4AgLfeegtjx47F48eP8ejRI7Rt2xYAEBAQgPff\nf1+7Tl57fRo0aIDx48fD398f/v7+pbVbr4SnqIiIiCROo9Hg+vXrsLCw0J5u0kcmkxW5rcKet7Vp\n0yaMHDkSFy9ehL+/f6k9M+tVMOAQERFJ3Jo1a1CnTh2sXLkSkyZNQk5ODoBnwSciIgIA8PPPP+P1\n11+HnZ0d7O3tcerUKQDArl1pdAYMAAAfXklEQVS70KZNG73btbGxQXp6unZb9+7dQ/v27TFz5kw8\nfvxYu8wYeIqKiIioDBTnsu7S9uIYnK5du2Lw4MHYunUrIiIiYGNjg9atW+Pbb7/F5MmTYWVlhWvX\nrsHf3x+2trZYtWoVgGfPqJo2bRqysrJQrVo1LF26VO/79e3bF1OmTEFYWBhWrlyJyZMn48mTJxBC\n4N1334W9vb1B9lsfmRBCGO3dS8G9e/eM9t4HPEaUaP3AI41LtL663SIkJSWVaBtkulQqFY9/Bcbj\nX/5kZGQUevqmtCgUilI79VOnTh1cv369VLZVFvR9pm5ubsVal6eoiIiISHIYcIiIiCqo8tx7U1IM\nOERERKXAxEd8lEsl+UwZcIiIiEqBXC436mXRUqNWqyGXv3pM4VVUREREpcDCwgJZWVnIzs4u1v1k\nXpW5uTmys7PLbPvlgRACcrkcFhYWr7wNBhwiIqJSIJPJYGlpWebvwyvoioenqIiIiEhyGHCIiIhI\ncgxyiiopKQmhoaF4+PAhZDIZfH190bNnT502Qghs2LAB586dg7m5OYKCguDl5WWI8oiIiEhiDBJw\nzMzMMGLECHh5eSEzMxPTpk1DkyZN4OHhoW1z7tw5JCQkYPny5bh+/TrWrVuHr7/+2hDlERERkcQY\n5BSVg4ODtjfG0tIS7u7uSElJ0Wlz5swZdOrUCTKZDHXr1kV6ejpSU1MNUR4RERFJjMGvonrw4AFu\n3bqF2rVr68xPSUmBSqXSTjs5OSElJQUODg467SIjIxEZGQkAWLBggc46FY1CoajQ+1/R8fhXbDz+\nFRePffEYNOBkZWUhJCQEI0eOzPfwLH13K9R3HwFfX1/4+vpqpyvypXJqtbpC739Fx0tFKzYe/4qr\noh/7cvewTbVajZCQEHTs2BGtW7fOt9zJyUnngCUnJ+frvSEiIiIqDoMEHCEEVq1aBXd3d/Tu3Vtv\nm1atWiEqKgpCCMTGxsLKyooBh4iIiF6JQU5RXbt2DVFRUahWrRqmTJkCABgyZIi2x6Zbt25o3rw5\noqOjMWHCBCiVSgQFBRmiNCIiIpIggwSc+vXrY/v27YW2kclkGDt2rCHKISIiIonjnYyJiIhIchhw\niIiISHIYcIiIiEhyGHCIiIhIchhwiIiISHIYcIiIiEhyGHCIiIhIchhwiIiISHIYcIiIiEhyGHCI\niIhIchhwiIiISHIYcIiIiEhyGHCIiIhIchhwiIiISHIYcIiIiEhyGHCIiIhIchhwiIiISHIYcIiI\niEhyGHCIiIhIchhwiIiISHIYcIiIiEhyGHCIiIhIchhwiIiISHIURTW4efMmoqOj8ffffyMjIwNW\nVlaoXr06mjdvjlq1ahmiRiIiIqKXUmDAuXDhArZu3YrMzEx4e3ujXr16sLS0RGZmJv755x8sX74c\nFhYWGDJkCJo1a2bImomIiIgKVWDAOXToEMaOHYvatWsXuHJcXBzCw8MZcIiIiKhcKTDgTJ48uciV\na9eujUmTJpVqQUREREQlVaxBxp9++qne+dOmTSvVYoiIiIhKQ7ECTkJCQr55QggkJiaWekFERERE\nJVXoVVTfffcdAECtVmtf5/n333/h6elZdpURERERvaJCA46Li4ve1zKZDPXq1UPbtm3LrjIiIiKi\nV1RowAkICAAA1KlTh1dKERERkckocAxOfHy89nVh4eb5dkRERETlQYE9OGFhYbCyskLHjh3h7e0N\nR0dH7bLU1FRcuXIFUVFRyMrKwpw5cwxSLBEREVFxFBhw5s6di7Nnz+LQoUNYtWoV5HK59k7GQgg0\nbtwY3bt3R4sWLYp8k5UrVyI6Ohr29vYICQnJt/zy5ctYtGgRnJ2dAQCtW7fGwIEDS7BbREREVJEV\nOganZcuWaNmyJdRqNRISEpCeng5ra2tUrVoVZmZmxX6TLl26wN/fH6GhoQW2adCgAe+rQ0RERKWi\nyIdtAoBCoYCHh8crv4m3tzcePHjwyusTERERvYxiBRxDiI2NxZQpU+Dg4IARI0YUeI+dyMhIREZG\nAgAWLFgAlUplyDLLFYVCUaH3v6Lj8a/YePwrLh774ikXAadmzZpYuXIlLCwsEB0djcWLF2P58uV6\n2/r6+sLX11c7nZSUZKgyyx21Wl2h97+iU6lUPP4VGI9/xVXRj72bm1ux2hXrUQ1lzcrKChYWFgCA\nFi1aIDc3F48fPzZyVURERGSqXingXL16Fbm5uaVWxMOHDyGEAADExcVBo9HA1ta21LZPREREFUuh\np6g0Go3e+d988w0WLlwIOzs7yOVFZ6Rly5bhypUrePLkCcaNG4dBgwZBrVYDALp164Y///wTBw8e\nhJmZGZRKJYKDgyGTyV5hd4iIiIiKCDhDhgwpcNn7778PANi2bVuRbxIcHFzocn9/f/j7+xe5HSIi\nIqLiKDTgeHt7Q6PRYMSIEbC3twcACCEwY8YMTJ8+HXZ2dgYpkoiIiOhlFHp+afbs2fDz88N3332H\n06dPQ6VSwdnZGXK5HCqVClWqVDFUnURERETFVuQAmg4dOuDrr7/G/fv3MW3aNPz1118cH0NERETl\nWrHug2NlZYUxY8bgxo0bCAsLw8OHD8u6LiIiIqJX9lI3+qtVqxbmzZuHzMxMWFlZlVVNRERERCVS\naMBJTEwscNmTJ08AAC4uLqVbEREREVEJFRpwJkyYUOQGinOZOBEREZEhFRpwXgwvo0aNwoYNG8q0\nICIiIqKSKhfPoiIiIiIqTQw4REREJDkMOERERCQ5hY7BWbFihc5N/bKzs/Hdd9/ptBk/fnzZVEZE\nRET0igoNOK6urjrT/fv3L9NiiIiIiEpDoQEnICDAUHUQERERlZpCx+Bcu3YNP/zwg95lW7ZsQWxs\nbJkURURERFQShQac3bt3w9vbW+8yb29v7N69u0yKIiIiIiqJQgNOfHw8mjVrpndZkyZNcOvWrTIp\nioiIiKgkCg04mZmZUKvVepfl5uYiMzOzTIoiIiIiKolCA467uzsuXLigd9mFCxfg7u5eJkURERER\nlUShAadXr15Ys2YNTp06BY1GAwDQaDQ4deoU1q5di169ehmkSCIiIqKXUehl4h06dMDDhw8RGhqK\nnJwc2NnZ4fHjx1AqlQgICECHDh0MVScRERFRsRUacACgd+/eeOONNxAbG4u0tDTY2Nigbt26sLKy\nMkR9RERERC+tyIADAFZWVgVeTUVERERU3vBhm0RERCQ5DDhEREQkOQw4REREJDkMOERERCQ5DDhE\nREQkOQw4REREJDkMOERERCQ5DDhEREQkOQw4REREJDkMOERERCQ5xXpUQ0mtXLkS0dHRsLe3R0hI\nSL7lQghs2LAB586dg7m5OYKCguDl5WWI0oiIiEiCDNKD06VLF8yYMaPA5efOnUNCQgKWL1+O9957\nD+vWrTNEWURERCRRBgk43t7esLGxKXD5mTNn0KlTJ8hkMtStWxfp6elITU01RGlEREQkQeViDE5K\nSgpUKpV22snJCSkpKUasiIiIiEyZQcbgFEUIkW+eTCbT2zYyMhKRkZEAgAULFugEo4pGoVBU6P2v\n6Hj8KzYe/4qLx754ykXAcXJyQlJSknY6OTkZDg4Oetv6+vrC19dXO/38ehWNWq2u0Ptf0alUKh7/\nCozHv+Kq6Mfezc2tWO3KxSmqVq1aISoqCkIIxMbGwsrKqsCAQ0RERFQUg/TgLFu2DFeuXMGTJ08w\nbtw4DBo0CGq1GgDQrVs3NG/eHNHR0ZgwYQKUSiWCgoIMURYRERFJlEECTnBwcKHLZTIZxo4da4hS\niIiIqAIoF6eoiIiIiEoTAw4RERFJDgMOERERSQ4DDhEREUkOAw4RERFJDgMOERERSQ4DDhEREUkO\nAw4RERFJDgMOERERSQ4DDhEREUkOAw4RERFJDgMOERERSQ4DDhEREUkOAw4RERFJDgMOERERSQ4D\nDhEREUkOAw4RERFJDgMOERERSQ4DDhEREUkOAw4RERFJDgMOERERSQ4DDhEREUmOwtgFkPFMDzpc\novXnr/QppUqIiIhKF3twiIiISHIYcIiIiEhyGHCIiIhIchhwiIiISHIYcIiIiEhyGHCIiIhIchhw\niIiISHIYcIiIiEhyGHCIiIhIchhwiIiISHIYcIiIiEhyDPYsqvPnz2PDhg3QaDTw8fFBv379dJYf\nO3YMmzdvhqOjIwDA398fPj581hERERG9PIMEHI1Gg7CwMMycORNOTk6YPn06WrVqBQ8PD5127dq1\nw5gxYwxREhEREUmYQU5RxcXFwdXVFS4uLlAoFGjXrh1Onz5tiLcmIiKiCsggPTgpKSlwcnLSTjs5\nOeH69ev52p06dQp//fUXqlatisDAQKhUqnxtIiMjERkZCQBYsGCB3jYVhUKhMOr+V+TPvjww9vEn\n4+Lxr7h47IvHIAFHCJFvnkwm05lu2bIl2rdvj0qVKuHgwYMIDQ3F7Nmz863n6+sLX19f7XRSUlLp\nF2wi1Gq1Ufe/In/25YFKpeIxqMB4/Cuuin7s3dzcitXOIAHHyckJycnJ2unk5GQ4ODjotLG1tdW+\n9vX1xZYtWwxRmkk7kbS1hFvgRXRERCRNBvkNV6tWLdy/fx8PHjyAWq3GiRMn0KpVK502qamp2tdn\nzpzJNwCZiIiIqLgM0oNjZmaG0aNHY968edBoNOjatSs8PT2xbds21KpVC61atcK+fftw5swZmJmZ\nwcbGBkFBQYYojYiIiCTIYPfBadGiBVq0aKEzb/DgwdrXQ4cOxdChQw1VDhEREUkYB2EQERGR5DDg\nEBERkeQw4BAREZHkMOAQERGR5DDgEBERkeQw4BAREZHkMOAQERGR5DDgEBERkeQw4BAREZHkMOAQ\nERGR5DDgEBERkeQw4BAREZHkMOAQERGR5DDgEBERkeQojF0Akak64DGiROt3v7u5lCohIqIXsQeH\niIiIJIcBh4iIiCSHAYeIiIgkhwGHiIiIJIcBh4iIiCSHAYeIiIgkhwGHiIiIJIcBh4iIiCSHN/oj\nMlEnkraWaP268CulSoiIyh/24BAREZHksAeHyEhcYxeVaP3Yus1LqRIiIulhDw4RERFJDgMOERER\nSQ4DDhEREUkOAw4RERFJDgMOERERSQ6voiIiegUHPEaUaP3udzeXUiVEpA97cIiIiEhy2INDVEFN\nDzpcovXnr/QppUroVZTkTta8i3XJsPfONBgs4Jw/fx4bNmyARqOBj48P+vXrp7M8JycH3333HW7e\nvAlbW1sEBwfD2dnZUOURERGZBD6mpXgMEnA0Gg3CwsIwc+ZMODk5Yfr06WjVqhU8PDy0bY4cOQJr\na2usWLECf/zxB7Zs2YKJEycaojwiIoPjnawrLh57wzDIGJy4uDi4urrCxcUFCoUC7dq1w+nTp3Xa\nnDlzBl26dAEAtGnTBjExMRBCGKI8IiIikhiD9OCkpKTAyclJO+3k5ITr168X2MbMzAxWVlZ48uQJ\n7OzsdNpFRkYiMjISALBgwQK4ubmVcfUFG6Up2RiGkupS0vV/KY0qKi4e/4rN1I8/vToee9NgkB4c\nfT0xMpnspdsAgK+vLxYsWIAFCxaUXoEmatq0acYugYyIx79i4/GvuHjsi8cgAcfJyQnJycna6eTk\nZDg4OBTYJjc3FxkZGbCxsTFEeURERCQxBgk4tWrVwv379/HgwQOo1WqcOHECrVq10mnTsmVLHDt2\nDADw559/omHDhnp7cIiIiIiKYvbFF198UdZvIpfL4erqihUrVmD//v3o2LEj2rRpg23btiErKwtu\nbm6oVq0a/u///g8//vgj4uPj8d5777EHpxi8vLyMXQIZEY9/xcbjX3Hx2BdNJnipEhEREUkMH9VA\nREREksOAQ0RERJLDgENERESSw4BjQjQaDa5du2bsMoiIqBzIysoydgnlGp8mbkLkcjk2bdqEefPm\nGbsUMqAFCxbo3DJBJpPB1tYWDRs2RKdOnYxYGRnK3r17882zs7ND/fr1+VDiCiAlJQWpqamoXr06\nFAoFHj16hIiICPz+++9YvXq1scsrt3gVlYnZvn07qlWrhtatW/M+QRXElStX8s1LS0tDVFQUqlat\nimHDhhmhKjKkHTt25JuXlpaGCxcuICAgAO3btzdCVWQIERER2L17N1xdXaFWq9GjRw9s2rQJnTp1\nQt++ffPdNJf+hwHHxLzzzjvIzs6GXC6HUqmEEAIymQz/+c9/jF0aGZhGo8HUqVOxePFiY5dCRpKW\nloa5c+di4cKFxi6FysjEiRMxd+5c2NjYICkpCR999BHmzJmDunXrGru0co+nqEzMpk2bjF0ClRNy\nOYfQVXQ2NjZ6n+NH0qFUKrU3vVWpVHBzc2O4KSYGHBMjhMDx48fx4MEDDBw4EElJSXj48CFq165t\n7NKojKSlpemdFxUVBU9PTyNUROVFTEwMrK2tjV0GlaHk5GSsX79eO/3o0SOd6dGjRxujLJPAgGNi\n1q1bB5lMhsuXL2PgwIGwsLBAWFgY5s+fb+zSqIxMnToVMplM+5f684OMx44da+TqyBAmTZqUb8xd\nWloaHBwc8OGHHxqpKjKE4cOH60zzEQ3Fx4BjYuLi4rBw4UJ8+umnAJ51UavVaiNXRWUpNDTU2CWQ\nkU2bNk1nWiaTwcbGBhYWFkaqiAylS5cuxi7BZPEkvokxMzODRqPR/jX3+PFjXk0lceHh4drXJ0+e\n1Fn2448/GrocMoLExERUqVIFVapUgRACKpVKG25OnTpl5OqoLD1+/Bg7duzAb7/9hqysLKxduxaT\nJk3CokWLkJCQYOzyyjUGHBPTo0cPLF68GI8ePcLWrVsxa9Ys9O/f39hlURk6ceKE9vUvv/yis+zC\nhQuGLoeMYPPmzdrXISEhOst2795t6HLIgJYvX46cnBwkJCRg+vTpcHFxwSeffIIWLVpg1apVxi6v\nXOMpKhPTsWNHeHl54dKlSwCAKVOmwMPDw8hVUVl6/iqZF6+Y4RU0FQO/AxXXo0ePMHToUAghEBQU\nhD59+gAA3N3dceDAASNXV74x4JigqlWrwtLSEhqNBgCQlJQElUpl5KqorLx4F+OClpF08TtQceXd\nDkImk8HOzk7vMtKPAcfE7Nu3Dzt37oS9vT3kcrn2Rn9LliwxdmlURuLj4xEYGAghBJ4+fYrAwEAA\nz/5yz8nJMXJ1ZAiJiYlYuHAhhBDa18Cz78CDBw+MXB2VJR77V8c7GZuYjz76CF9//TVsbW2NXQoR\nGYi+x3U8z9vb20CVkKHx2L869uCYGJVKBSsrK2OXQUQG9PwvscePHwNAvtMVJE3p6elITk6Gv78/\nAGD69Onaq2f5HLrCMeCYiLynCTs7O+OLL75AixYtUKlSJe3y3r17G6s0IipjQgjs3LkT+/fvhxAC\nQgjI5XL06NEDAwcONHZ5VIb27NmDjz/+WDutVquxYMECZGdnY+XKlWjbtq0RqyvfGHBMRGZmJoBn\nPTgqlQpqtVp7gz8OMpS2nJwcnTBLFU9ERASuXr2K+fPnw9nZGcCzsRnr1q3D3r17+QeOhKnVap2L\nSOrXrw9bW1vY2toiOzvbiJWVfxyCbSICAgIQEBAADw8P7eu8H3d3d2OXR2Vo5syZAIAVK1YYuRIy\nlqioKHz88cfacAMALi4u+OijjxAVFWXEyqisvfgsujFjxmhf552uJP0YcEzMizd6K2geSYdarcax\nY8cQGxuLU6dO5fsh6cvNzdU75sbOzg65ublGqIgMpU6dOoiMjMw3/9ChQ6hVq5YRKjIdPEVlIs6d\nO4dz584hJSVF50mymZmZvBeCxL377rs4fvw40tPTcfbs2XzLW7dubYSqyJAUioL/qy5sGZm+wMBA\nLF68GH/88Qdq1qwJALh58yZycnIwZcoUI1dXvvEycRMRHx+P+Ph4bNmyBQMGDADw7CZPlStXhre3\nN2xsbIxcIZW1I0eO4I033jB2GWQEgwcP1vtgzbx7IW3dutUIVZEhxcTE4M6dOwAAT09PNGrUyMgV\nlX8MOCZCrVbjp59+wuHDh+Hs7AwhBJKTk9GlSxcMGTKEf8VVAGq1GgcPHsRff/0F4Nmlw35+fjz2\nRER6MOCYiI0bNyIrKwuBgYGwtLQEAGRkZGDz5s1QKpUYNWqUkSuksrZq1Sqo1Wp06dIFwLOBp3K5\nHOPGjTNuYURE5RAHb5iI6OhovP/++9pwAwBWVlZ49913ce7cOSNWRoZy48YNjB8/Ho0aNUKjRo0Q\nFBSEGzduGLssIqJyiQHHRMhkMr33u5HL5bwPTgUhl8uRkJCgnU5MTOQAcyKiAvDkvYlwd3fH77//\njs6dO+vMj4qKgpubm5GqIkMaPnw45syZAxcXFwghkJSUhA8++MDYZRERlUscg2MiUlJSsGTJEiiV\nSnh5eQF4dsri6dOnmDJlChwdHY1cIRlCTk4O7t27ByEE3N3deYdjIqICMOCYmLxLBYUQ8PT0ROPG\njY1dEhERUbnDgENERESSwxGKREREJDkMOEQm4ssvvyzWPCIi4lVUROXe06dP8fTpUzx58kTnycIZ\nGRlITU01YmVEROUXx+AQlXO//fYbIiIikJqaCkdHR+T9k7WysoKPjw/8/f2NXCERUfnDgENkIvbt\n24cePXoYuwwiIpPAMThEJqJy5crIzMwEAOzatQtLlizBzZs3jVwVEVH5xIBDZCJ27doFS0tLXL16\nFRcuXEDnzp2xbt06Y5dFRFQuMeAQmYi8505FR0ejW7dueO2116BWq41cFRFR+cSAQ2QiHB0dsWbN\nGpw8eRLNmzdHTk4OOISOiEg/DjImMhHZ2dk4f/48qlWrhqpVqyI1NRW3b99G06ZNjV0aEVG5wx4c\nIhNhbm4Oe3t7XL16FQBgZmaGqlWrGrkqIqLyiQGHyETs2LEDv/zyC3755RcAgFqtxooVK4xcFRFR\n+cSAQ2Qi/vvf/2Lq1KkwNzcH8GxMTt5l40REpIsBh8hEKBQKyGQyyGQyAEBWVpaRKyIiKr/4LCoi\nE9G2bVusWbMG6enpiIyMxNGjR/HGG28YuywionKJV1ERmZCLFy/iwoULEEKgWbNmaNKkibFLIiIq\nlxhwiEyURqPBH3/8gY4dOxq7FCKicoenqIjKuYyMDBw4cAApKSlo1aoVmjRpggMHDmDPnj2oUaMG\nAw4RkR7swSEq5xYtWgRra2vUrVsXly5dQnp6OtRqNUaNGoUaNWoYuzwionKJPThE5VxiYiJCQkIA\nAD4+PhgzZgxWrlwJS0tLI1dGRFR+8TJxonJOofjf3yFyuRzOzs4MN0REReApKqJybvDgwbCwsAAA\nCCHw9OlTmJubQwgBmUyG//znP0aukIio/GHAISIiIsnhKSoiIiKSHAYcIiIikhwGHCIiIpIcBhwi\nMjlr1qzBzp07jV0GEZVjHGRMRGXmww8/xMOHDyGXy2FhYYFmzZphzJgx2qvCiIjKCntwiKhMTZ06\nFZs3b8bixYsRHx+Pn3/+2dglEVEFwDsZE5FBVK5cGU2bNkV8fDwAICcnB1u3bsXJkyehVqvx2muv\nYeTIkVAqlQCA8PBwREREQCaTYdCgQVi9ejWWL18OV1dXhIaGwsnJCW+//TYAIDIyEuHh4UhLS0P9\n+vXx7rvvwtHREQAwaNAgjB07Fnv37sWTJ0/Qvn17jBkzBjKZDAkJCfj+++8RHx8PhUKBRo0aYeLE\niUb5fIiodLEHh4gMIjk5GefOnYOrqysAYMuWLbh//z4WL16M5cuXIyUlRTuu5vz589i7dy9mzZqF\n5cuX48qVKwVuNyYmBlu3bsXEiROxZs0aVKlSBd9++61Om+joaMyfPx+LFy/GyZMnceHCBQDATz/9\nhKZNm2LDhg34/vvv0aNHjzLaeyIyNAYcIipTixcvxjvvvIMPPvgA9vb2GDRoEIQQOHz4MAIDA2Fj\nYwNLS0u89dZb+OOPPwAAJ06cQNeuXeHp6Qlzc3MEBAQUuP3jx4+ja9eu8PLyQqVKlTB06FDExsbi\nwYMH2jb9+vWDtbU1VCoVGjZsqO1FUigU+Pfff5GamgqlUon69euX6WdBRIbDU1REVKamTJmCJk2a\n4MqVK/j222/x5MkTqNVqZGdnY9q0adp2QghoNBoAQGpqKmrVqqVd5uTkVOD2U1NTUbNmTe20hYUF\nbGxskJKSAmdnZwDPTo/lMTc3R1ZWFgBg+PDh+OmnnzBjxgxYW1ujd+/eeOONN0pnx4nIqBhwiMgg\nvL290aVLF2zatAmTJ0+GUqnE0qVLtWNlnufg4IDk5GTt9POv9bVNSkrSTmdlZSEtLU3vdl9UuXJl\njBs3DgBw9epVzJ07F97e3trTaERkuniKiogMplevXrh06RJu374NHx8fbNy4EY8ePQIApKSk4Pz5\n8wCAtm3b4tixY7h79y6ys7MLvedNhw4dcPToUcTHx2sHLteuXVvbe1OYkydPasOTtbU1gGdPbCci\n08ceHCIyGDs7O3Tq1Ak7d+7EhAkTsHPnTnz22Wd48uQJHB0d4efnh2bNmqF58+bo0aMH5syZA7lc\njgEDBiAqKgoKRf7/sho3bozBgwcjJCQEaWlpqFevHoKDg4tVz40bN7Bx40ZkZGSgcuXKGDVqVLGC\nERGVf7zRHxGVe3fv3sWkSZPw448/wszMzNjlEJEJYF8sEZVL//3vf6FWq5GWloYtW7agZcuWDDdE\nVGw8RUVE5dKhQ4cQGhoKuVwOb29vjB071tglEZEJ4SkqIiIikhyeoiIiIiLJYcAhIiIiyWHAISIi\nIslhwCEiIiLJYcAhIiIiyfl/7WNVYzbzuRgAAAAASUVORK5CYII=\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "with plt.style.context('ggplot'):\n", " wiod.AIR.plot_account('CH4', figsize=(8,5))\n", " plt.savefig('/tmp/wiod/airch4.png', dpi=300)\n", " plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To calculate the source (in terms of regions and sectors) of a certain stressor or impact driven by consumption, one needs to diagonalize this stressor/impact. This can be done with Pymrio by:" ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "collapsed": true }, "outputs": [], "source": [ "diag_CH4 = wiod.AIR.diag_stressor('CH4')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "and be reassigned to the aggregated WIOD system:" ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "collapsed": true }, "outputs": [], "source": [ "wiod.CH4_source = diag_CH4" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In the next step the automatic calculation routine of Pymrio is called again to compute the missing accounts in this new extension:\n", "and be reassigned to the aggregated WIOD system:" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "wiod.calc_all()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The diagonalized CH4 data now shows the source and destination of the specified stressor (CH4):" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
regionOther...GBR
sectorAtBC15t1617t18192021t22232425...6364J7071t74LMNOP
regionsector
OtherAtB6.120041e+078.455234e+043.658411e+072.988418e+06867172.684194230646.602537441913.6279921.766666e+056.045454e+05197135.975631...669.9036913406.9737398805.6780366656.2336334123.12198619984.7278429398.05471144359.67251712305.8954203.055303
C1.008359e+066.714292e+062.047332e+066.420307e+05117665.00513533160.714629281538.5758745.643346e+061.564758e+06231675.430540...1405.7581589357.74272920287.54089918680.2195278586.78304249408.29861815853.40101693562.14655523512.7209794.041194
15t163.968202e+036.218228e+018.736127e+045.178453e+02639.80275524.298048128.9459441.099366e+024.216024e+0283.091425...0.4609653.2151848.8186895.8059413.87107318.6714918.69518444.37065911.7074020.001748
17t189.369869e+012.287802e+012.464623e+021.185856e+04200.1260394.50021968.0170133.330082e+017.862589e+0159.680321...0.0930750.8482781.7384281.4449810.9193676.6088302.03121512.6582183.7655880.001256
195.587156e+001.040420e+001.268140e+011.252185e+021231.9876870.3445684.2052791.580128e+004.194052e+003.043624...0.0086320.1173120.2252150.1710930.1060371.1047010.3433491.4308270.6460120.000075
\n", "

5 rows × 140 columns

\n", "
" ], "text/plain": [ "region Other \\\n", "sector AtB C 15t16 17t18 \n", "region sector \n", "Other AtB 6.120041e+07 8.455234e+04 3.658411e+07 2.988418e+06 \n", " C 1.008359e+06 6.714292e+06 2.047332e+06 6.420307e+05 \n", " 15t16 3.968202e+03 6.218228e+01 8.736127e+04 5.178453e+02 \n", " 17t18 9.369869e+01 2.287802e+01 2.464623e+02 1.185856e+04 \n", " 19 5.587156e+00 1.040420e+00 1.268140e+01 1.252185e+02 \n", "\n", "region \\\n", "sector 19 20 21t22 23 \n", "region sector \n", "Other AtB 867172.684194 230646.602537 441913.627992 1.766666e+05 \n", " C 117665.005135 33160.714629 281538.575874 5.643346e+06 \n", " 15t16 639.802755 24.298048 128.945944 1.099366e+02 \n", " 17t18 200.126039 4.500219 68.017013 3.330082e+01 \n", " 19 1231.987687 0.344568 4.205279 1.580128e+00 \n", "\n", "region ... GBR \\\n", "sector 24 25 ... 63 \n", "region sector ... \n", "Other AtB 6.045454e+05 197135.975631 ... 669.903691 \n", " C 1.564758e+06 231675.430540 ... 1405.758158 \n", " 15t16 4.216024e+02 83.091425 ... 0.460965 \n", " 17t18 7.862589e+01 59.680321 ... 0.093075 \n", " 19 4.194052e+00 3.043624 ... 0.008632 \n", "\n", "region \\\n", "sector 64 J 70 71t74 \n", "region sector \n", "Other AtB 3406.973739 8805.678036 6656.233633 4123.121986 \n", " C 9357.742729 20287.540899 18680.219527 8586.783042 \n", " 15t16 3.215184 8.818689 5.805941 3.871073 \n", " 17t18 0.848278 1.738428 1.444981 0.919367 \n", " 19 0.117312 0.225215 0.171093 0.106037 \n", "\n", "region \\\n", "sector L M N O \n", "region sector \n", "Other AtB 19984.727842 9398.054711 44359.672517 12305.895420 \n", " C 49408.298618 15853.401016 93562.146555 23512.720979 \n", " 15t16 18.671491 8.695184 44.370659 11.707402 \n", " 17t18 6.608830 2.031215 12.658218 3.765588 \n", " 19 1.104701 0.343349 1.430827 0.646012 \n", "\n", "region \n", "sector P \n", "region sector \n", "Other AtB 3.055303 \n", " C 4.041194 \n", " 15t16 0.001748 \n", " 17t18 0.001256 \n", " 19 0.000075 \n", "\n", "[5 rows x 140 columns]" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "wiod.CH4_source.D_cba.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In this square footprint matrix, every column represents the amount of stressor occurring in each region - sector driven by the consumption stated in the column header. Conversly, each row states where the stressor impacts occurring in the row are distributed due (from where they are driven)." ] }, { "cell_type": "code", "execution_count": 21, "metadata": { "collapsed": true }, "outputs": [], "source": [ "CH4_source_reg = wiod.CH4_source.D_cba.groupby(\n", " level='region', axis=0).sum().groupby(\n", " level='region', axis=1).sum()\n" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
regionDEUGBROtherRest of EU
region
DEU1.485343e+064.634238e+042.892830e+053.819713e+05
GBR5.139252e+041.833541e+062.112405e+051.879226e+05
Other3.696832e+062.711860e+062.457410e+081.317725e+07
Rest of EU7.402886e+054.186665e+051.756700e+061.128755e+07
\n", "
" ], "text/plain": [ "region DEU GBR Other Rest of EU\n", "region \n", "DEU 1.485343e+06 4.634238e+04 2.892830e+05 3.819713e+05\n", "GBR 5.139252e+04 1.833541e+06 2.112405e+05 1.879226e+05\n", "Other 3.696832e+06 2.711860e+06 2.457410e+08 1.317725e+07\n", "Rest of EU 7.402886e+05 4.186665e+05 1.756700e+06 1.128755e+07" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "CH4_source_reg" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZUAAAEKCAYAAADaa8itAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nZLhQcRzHcSLDhYrjOI4TGf8PU+IX+IqD35oAAAAASUVORK5CYII=\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import seaborn as sns\n", "CH4_source_reg.columns.name = 'Receiving region'\n", "CH4_source_reg.index.name = 'Source region'\n", "sns.heatmap(CH4_source_reg, vmax=5E6, \n", " annot=True, cmap='YlOrRd', linewidths=0.1,\n", " cbar_kws={'label': 'CH4 emissions ({})'.format(wiod.CH4_source.unit.unit[0])})\n", "plt.savefig('/tmp/wiod/airch4_source_reg.png', dpi=300)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "With the help of [flowweaver sankey package](https://github.com/ricklupton/floweaver) the flows can easily be depicted in a sankey diagram:" ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "d42ad8b43a1049f38744c62e3ad7a226", "version_major": 2, "version_minor": 0 }, "text/plain": [ "A Jupyter Widget" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import floweaver as fw\n", "\n", "flows = CH4_source_reg.unstack().reset_index().rename(columns={0: 'value',\n", " 'Receiving region': 'target',\n", " 'Source region': 'source'})\n", "regions = list(flows.target.unique())\n", "\n", "partition_receiving = fw.Partition.Simple('target', regions)\n", "partition_source = fw.Partition.Simple('source', regions)\n", "\n", "sdd = fw.SankeyDefinition(\n", " nodes={'sources': fw.ProcessGroup(regions, partition_source, title='impact in'),\n", " 'targets': fw.ProcessGroup(regions, partition_receiving, title='consumption in')},\n", " bundles=[fw.Bundle('sources', 'targets')],\n", " ordering=[['sources'], ['targets']],\n", " flow_partition=partition_source)\n", "fw.weave(sdd, flows).to_widget()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Storing the MRIO database can be done with " ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [ "storage_path = '/tmp/wiod/aly'\n", "wiod.save_all(storage_path)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "From where it can be received subsequently by:" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [ "wiod = pymrio.load_all(storage_path)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The meta attribute of Pymrio mentioned at the beginning kept track of all modifications of the system.\n", "This can be shown with:" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [ "wiod.meta" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Custom notes can be added to the meta with:" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [ "wiod.meta.note(\"Custom note\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The history of the meta data can be filtered for specific entries like:" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [ "wiod.meta.file_io_history" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This tutorial gave a short overview about the basic functionality of Pymrio. For more information about the capabilities of pymrio check the [online documentation](http://pymrio.readthedocs.io/en/latest/index.html)." ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.3" }, "nikola": { "category": "", "date": "2018-01-11 19:18:16 UTC+01:00", "description": "", "link": "", "slug": "pymrio-tutorial-for-wiod", "tags": "SI", "title": "Quick Start Pymrio Tutorial using WIOD", "type": "text" }, "widgets": { "application/vnd.jupyter.widget-state+json": { "state": { "a71886ee8dfa46118c9a485d64975724": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.0.0", "model_name": "LayoutModel", "state": { "height": "500", "width": "700" } }, "e3195e1568f448bd84263639a2f4d09b": { "model_module": "jupyter-sankey-widget", "model_module_version": "^0.2.3", "model_name": "SankeyModel", "state": { "_model_module_version": "^0.2.3", "_view_module_version": "^0.2.3", "groups": [ { "id": "sources", "nodes": [ "sources^DEU", "sources^GBR", "sources^Rest of EU", "sources^Other" ], "rect": { "bottom": 418.5, "left": 0, "right": 1, "top": 46.5 }, "title": "consumption in", "type": "process" }, { "id": "targets", "nodes": [ "targets^DEU", "targets^GBR", "targets^Rest of EU", "targets^Other" ], "rect": { "bottom": 418.5, "left": 439, "right": 440, "top": 46.5 }, "title": "impact in", "type": "process" } ], "layout": "IPY_MODEL_a71886ee8dfa46118c9a485d64975724", "links": [ { "color": "#FBB4AE", "opacity": 1, "source": "sources^DEU", "target": "targets^DEU", "time": "*", "title": "DEU", "type": "DEU", "value": 1485342.976363776 }, { "color": "#B3CDE3", "opacity": 1, "source": "sources^DEU", "target": "targets^GBR", "time": "*", "title": "GBR", "type": "GBR", "value": 46342.37904832413 }, { "color": "#CCEBC5", "opacity": 1, "source": "sources^DEU", "target": "targets^Other", "time": "*", "title": "Other", "type": "Other", "value": 289282.9623595793 }, { "color": "#DECBE4", "opacity": 1, "source": "sources^DEU", "target": "targets^Rest of EU", "time": "*", "title": "Rest of EU", "type": "Rest of EU", "value": 381971.2922283213 }, { "color": "#FBB4AE", "opacity": 1, "source": "sources^GBR", "target": "targets^DEU", "time": "*", "title": "DEU", "type": "DEU", "value": 51392.51865044936 }, { "color": "#B3CDE3", "opacity": 1, "source": "sources^GBR", "target": "targets^GBR", "time": "*", "title": "GBR", "type": "GBR", "value": 1833540.7472363757 }, { "color": "#CCEBC5", "opacity": 1, "source": "sources^GBR", "target": "targets^Other", "time": "*", "title": "Other", "type": "Other", "value": 211240.46138641148 }, { "color": "#DECBE4", "opacity": 1, "source": "sources^GBR", "target": "targets^Rest of EU", "time": "*", "title": "Rest of EU", "type": "Rest of EU", "value": 187922.57272676047 }, { "color": "#FBB4AE", "opacity": 1, "source": "sources^Rest of EU", "target": "targets^DEU", "time": "*", "title": "DEU", "type": "DEU", "value": 740288.5886528839 }, { "color": "#B3CDE3", "opacity": 1, "source": "sources^Rest of EU", "target": "targets^GBR", "time": "*", "title": "GBR", "type": "GBR", "value": 418666.45247666055 }, { "color": "#CCEBC5", "opacity": 1, "source": "sources^Rest of EU", "target": "targets^Other", "time": "*", "title": "Other", "type": "Other", "value": 1756699.5535771872 }, { "color": "#DECBE4", "opacity": 1, "source": "sources^Rest of EU", "target": "targets^Rest of EU", "time": "*", "title": "Rest of EU", "type": "Rest of EU", "value": 11287546.095293269 }, { "color": "#FBB4AE", "opacity": 1, "source": "sources^Other", "target": "targets^DEU", "time": "*", "title": "DEU", "type": "DEU", "value": 3696832.404386417 }, { "color": "#B3CDE3", "opacity": 1, "source": "sources^Other", "target": "targets^GBR", "time": "*", "title": "GBR", "type": "GBR", "value": 2711859.644300266 }, { "color": "#CCEBC5", "opacity": 1, "source": "sources^Other", "target": "targets^Other", "time": "*", "title": "Other", "type": "Other", "value": 245740971.44904166 }, { "color": "#DECBE4", "opacity": 1, "source": "sources^Other", "target": "targets^Rest of EU", "time": "*", "title": "Rest of EU", "type": "Rest of EU", "value": 13177252.736708682 } ], "margins": { "bottom": 10, "left": 130, "right": 130, "top": 25 }, "nodes": [ { "direction": "r", "hidden": false, "id": "sources^DEU", "title": "DEU", "type": "process" }, { "direction": "r", "hidden": false, "id": "sources^GBR", "title": "GBR", "type": "process" }, { "direction": "r", "hidden": false, "id": "sources^Rest of EU", "title": "Rest of EU", "type": "process" }, { "direction": "r", "hidden": false, "id": "sources^Other", "title": "Other", "type": "process" }, { "direction": "r", "hidden": false, "id": "targets^DEU", "title": "DEU", "type": "process" }, { "direction": "r", "hidden": false, "id": "targets^GBR", "title": "GBR", "type": "process" }, { "direction": "r", "hidden": false, "id": "targets^Rest of EU", "title": "Rest of EU", "type": "process" }, { "direction": "r", "hidden": false, "id": "targets^Other", "title": "Other", "type": "process" } ], "order": [ [ [ "sources^DEU", "sources^GBR", "sources^Rest of EU", "sources^Other" ] ], [ [ "targets^DEU", "targets^GBR", "targets^Rest of EU", "targets^Other" ] ] ], "png": "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", "scale": 8.186125298408717e-07, "svg": "consumption inimpact inDEU → GBR\nGBR\n46.3kGBR → DEU\nDEU\n51.4kGBR → Rest of EU\nRest of EU\n188kGBR → Other\nOther\n211kDEU → Other\nOther\n289kDEU → Rest of EU\nRest of EU\n382kRest of EU → GBR\nGBR\n419kRest of EU → DEU\nDEU\n740kDEU → DEU\nDEU\n1.49MRest of EU → Other\nOther\n1.76MGBR → GBR\nGBR\n1.83MOther → GBR\nGBR\n2.71MOther → DEU\nDEU\n3.70MRest of EU → Rest of EU\nRest of EU\n11.3MOther → Rest of EU\nRest of EU\n13.2MOther → Other\nOther\n246MDEUDEUGBRGBRRest of EURest of EUOtherOtherDEUDEUGBRGBRRest of EURest of EUOtherOther" } } }, "version_major": 2, "version_minor": 0 } } }, "nbformat": 4, "nbformat_minor": 2 }