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Update EMDAT VARNAMES for version 2023 #701

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merged 4 commits into from
Apr 27, 2023
Merged

Update EMDAT VARNAMES for version 2023 #701

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3fd0b13
Update EMDAT VARNAMES for version 2023
simonameiler Apr 19, 2023
0350325
impact_data: use the newest version of EM-DAT files instead of fixing…
emanuel-schmid Apr 26, 2023
1a384e5
Merge branch 'develop' into feature/emdat_datastructure_update
emanuel-schmid Apr 27, 2023
e517219
clean_emdat_df: add inline comments for 2018 case
emanuel-schmid Apr 27, 2023
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52 changes: 51 additions & 1 deletion climada/engine/impact_data.py
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Original file line number Diff line number Diff line change
Expand Up @@ -114,7 +114,57 @@
"Reconstruction Costs ('000 US$)": "Reconstruction Costs ('000 US$)",
"Insured Damages ('000 US$)": "Insured Damages ('000 US$)",
"Total Damages ('000 US$)": "Total Damages ('000 US$)",
'CPI': 'CPI'}}
'CPI': 'CPI'},
2023: {'Dis No': 'Dis No',
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To make sure that all key-value pairs here are exactly the same, you could do something like this:

VARNAMES_EMDAT_2023 = ["Dis No", "Year", ...]  # List every variable only once
VARNAMES_EMDAT = {
    2018: {...},
    2020: {...},
    2023: dict(zip(VARNAMES_EMDAT_2023, VARNAMES_EMDAT_2023)),
}

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🤔 Don't know. With the current change it is at least uniform. After introducing VARNAMES_EMDAT_2023 it's partly less redundant but loses uniformity. Which looks like an increase of entropy to me. 😁
Imho we should keep it uniform or get rid of all the redundancy when we start in this direction. E.g. by making a dictionary for only the values that are different from the keys.

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I very much like your last suggestion! Let's get back to this when the actual issue is resolved ✌️

'Year': 'Year',
'Seq': 'Seq',
'Glide': 'Glide',
'Disaster Group': 'Disaster Group',
'Disaster Subgroup': 'Disaster Subgroup',
'Disaster Type': 'Disaster Type',
'Disaster Subtype': 'Disaster Subtype',
'Disaster Subsubtype': 'Disaster Subsubtype',
'Event Name': 'Event Name',
'Country': 'Country',
'ISO': 'ISO',
'Region': 'Region',
'Continent': 'Continent',
'Location': 'Location',
'Origin': 'Origin',
'Associated Dis': 'Associated Dis',
'Associated Dis2': 'Associated Dis2',
'OFDA Response': 'OFDA Response',
'Appeal': 'Appeal',
'Declaration': 'Declaration',
"AID Contribution ('000 US$)": "AID Contribution ('000 US$)",
'Dis Mag Value': 'Dis Mag Value',
'Dis Mag Scale': 'Dis Mag Scale',
'Latitude': 'Latitude',
'Longitude': 'Longitude',
'Local Time': 'Local Time',
'River Basin': 'River Basin',
'Start Year': 'Start Year',
'Start Month': 'Start Month',
'Start Day': 'Start Day',
'End Year': 'End Year',
'End Month': 'End Month',
'End Day': 'End Day',
'Total Deaths': 'Total Deaths',
'No Injured': 'No Injured',
'No Affected': 'No Affected',
'No Homeless': 'No Homeless',
'Total Affected': 'Total Affected',
"Reconstruction Costs ('000 US$)": "Reconstruction Costs ('000 US$)",
"Reconstruction Costs, Adjusted ('000 US$)": "Reconstruction Costs, Adjusted ('000 US$)",
"Insured Damages ('000 US$)": "Insured Damages ('000 US$)",
"Insured Damages, Adjusted ('000 US$)": "Insured Damages, Adjusted ('000 US$)",
"Total Damages ('000 US$)": "Total Damages ('000 US$)",
"Total Damages, Adjusted ('000 US$)": "Total Damages, Adjusted ('000 US$)",
'CPI': 'CPI',
'Adm Level': 'Adm Level',
'Admin1 Code': 'Admin1 Code',
'Admin2 Code': 'Admin2 Code',
'Geo Locations': 'Geo Locations'}}


def assign_hazard_to_emdat(certainty_level, intensity_path_haz, names_path_haz,
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