ecospold2matrix Data Flowchart

[michaelweinold]

Ecospold xml Ingestion

flowchart TD
Ain[IntermediateExchanges.xml] --> A["extract_products()"] --> Aout[products: pd.DataFrame]
Bin[ActivityIndex.xml <br> ActivityNames.xml] --> B["extract_activities()"] -->  Bout[activities: pd.DataFrame]
C["get_labels()"] --> Cextract1 --> Cout[PRO: pd.DataFrame <br> STR: pd.DataFrame]
Cin[ElementaryExchanges.xml <br> spold files] --> C --> Cextract2 --> Cout
Din[spold files] --> D["get_flows()"] --> Dextract["extract_flows()"] --> Dout[inflows: pd.DataFrame <br> outflows: pd.DataFrame <br> elementary_flows: pd.DataFrame]
Cextract1["build_PRO()"]
Cextract2["build_STR()"]

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DataFrame Table

object	type	columns (e2m)	columns correspondence (bw) or Ecospold	comment
inflows	pd.DataFrame	fileId sourceActivityId productId amount row_index	.spold file name activityLinkId intermediateExchangeId amount ???	extracted from .spold files
outflows	pd.DataFrame	fileId productId amount productionVolume outputGroup	.spold file name intermediateExchangeId amount productionVolume outputGroup	extracted from .spold files
elementary_flows	pd.DataFrame	fileId elementaryExchangeId amount	.spold file name elementaryExchangeId amount	extracted from .spold files
activities	pd.DataFrame	activityId activityNameId activityType startDate endDate activityName	id activityNameId activityType startDate endDate activityName	extracted from ActivityIndex.xml with activityName data merged from ActivityNames.xml
products	pd.DataFrame	productName unitName productId unitId cpc properties	name unitName id unitId classification == 'cpc' properties	extracted from IntermediateExchanges.xml
STR	pd.DataFrame	id name unit cas comp subcomp	id name unitName casNumber compartment subcompartment	extracted from ElementaryExchanges.xml
PRO	pd.DataFrame	'activityId' 'productId' 'activityName' 'ISIC' 'price' 'priceUnit' 'EcoSpoldCategory' 'geography' 'technologyLevel' 'macroEconomicScenario' properties_x 'productionVolume' 'productName' 'unitName' 'cpc' properties_y 'activityNameId' 'activityType' 'startDate' 'endDate' 'activityName_duplicate'	'id' 'productId' 'activityName' 'ISIC' 'price' 'priceUnit' 'EcoSpoldCategory' 'geography' 'technologyLevel' 'macroEconomicScenario' properties_x 'productionVolume' 'productName' 'unitName' 'cpc' properties_y 'activityNameId' 'activityType' 'startDate' 'endDate' 'activityName_duplicate'	extracted from .spold files

Preparation and Cleanup

flowchart TD
in[activities: pd.DataFrame <br> products: pd.DataFrame] --> F["complement_labels()"] --> out[PRO: pd.DataFrame <br> STR: pd.DataFrame]

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DataFrame Table

object	type	columns (e2m)	columns correspondence (bw) or Ecospold	comment
PRO	pd.DataFrame	all prev. columns 'productionVolume' all cols. from products all cols. from activities	all prev. columns 'productionVolume' all cols. from products all cols. from activities	for merge keys, see below

Join Table

left	right	left_key	right_key	added cols.
PRO	outflows	index = 'abc'	index = 'abc'	'productionVolume'
PRO	products	index = 'abc'	index = 'abc'	all except potential duplicates
PRO	activities	index = 'abc'	index = 'abc'	all except potential duplicates

DataFrame Construction (change heading)

flowchart TD
in[inflows: pd.DataFrame <br> elementary_flows: pd.DataFrame <br> outflows: pd.DataFrame] --> F["build_AF()"] --> out[A: pd.DataFrame <br> F: pd.DataFrame]

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DataFrame Table

Pivot Table

output	input	index	columns	values	output index	output cols.
A	inflows	'row_index' = 'fileId' + 'productId'	'fileId'	'amount'	PRO.index = 'abc'	PRO.index = 'abc'
F	elementary_flows	'elementaryExchangeId'	'fileId'	'amount'	STR.index = 'abc'	PRO.index = 'abc'

Characterization

flowchart TD
in["LCIA Implementation v3.8.xlsx"] --> F1["if-else"]  --> F2["simple_characterisation_matching()"] --> out[A: pd.DataFrame <br> C: pd.DataFrame]

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Pivot Table

output	input	index	columns	values	output index	output cols.
C	C_long	'impact_label'	'stressorId'	'CF'	N/A	N/A