import openpyxl, json
wb=openpyxl.load_workbook('data/national-fossil-2025.xlsx',read_only=True,data_only=True)
def load(name,hr):
    rows=list(wb[name].iter_rows(min_row=1,max_row=300,max_col=251,values_only=True));h=rows[hr-1];out={}
    for r in rows[hr:]:
        if isinstance(r[0],(int,float)) and 2005<=r[0]<=2023: out[int(r[0])]={h[i]:r[i] for i in range(1,len(r)) if h[i] is not None}
    return out
t=load('Territorial Emissions',12);c=load('Consumption Emissions',9)
names="Bahamas|Cape Verde|Congo|Curaçao|Democratic Republic of the Congo|Faeroe Islands|Gambia|Macao|Micronesia (Federated States of)|North Korea|Saint Kitts and Nevis|Saint Lucia|Saint Vincent and the Grenadines|Somalia|State of Palestine|Syria|Taiwan|Yemen".split('|')
ok=lambda v:isinstance(v,(int,float)) and v>0
for n in names:
    print(n, 'territorial_complete=',all(ok(t[y].get(n)) for y in t), 'consumption_complete=',all(ok(c[y].get(n)) for y in c))
w=json.load(open('data/worldbank-countries.json'))[1]
import re
for r in w:
    if re.search(r'Bahamas|Cabo|Congo|Cura|Gambia|Macao|Micronesia|Korea|Kitts|Lucia|Vincent|Somalia|West Bank|Syria|Yemen|Faroe',r['name']): print('WB:',r['id'],r['name'])