def do_import_table():
minyear = min(config.STUDY_YEARS)
maxyear = max(config.STUDY_YEARS)
sector = 'CONS_h'
fd = {}
fd_imports = {}
for year in (minyear, maxyear):
strings = {
"schema": config.WIOD_SCHEMA,
"year": year,
}
stmt = db.prepare(
"""SELECT country, sum(value)
FROM %(schema)s.niot_%(year)d
WHERE to_ind = $1
AND is_import = $2
GROUP BY country""" % strings)
fd[year] = {}
fd_imports[year] = {}
for (country, value) in stmt(sector, True):
fd_imports[year][country] = value
fd[year][country] = value
for (country, value) in stmt(sector, False):
fd[year][country] += value
shares = {}
for (country, total) in fd[maxyear].items():
share = fd_imports[maxyear][country] / total
shares[share] = country
sorted_shares = sorted(shares.keys(), reverse=True)
midpoint = int(len(sorted_shares) / 2)
for i in range(midpoint):
values = []
for index in (i, i + midpoint):
country = shares[sorted_shares[index]]
minval = imfdata.convert_to_2005(
fd_imports[minyear][country], country, minyear)
maxval = imfdata.convert_to_2005(
fd_imports[maxyear][country], country, maxyear)
minshare = fd_imports[minyear][country] / fd[minyear][country]
maxshare = fd_imports[maxyear][country] / fd[maxyear][country]
values += [
config.countries[country],
utils.add_commas(minval), utils.add_commas(maxval),
"%.1f" % (minshare * 100), "%.1f" % (maxshare * 100),
""] # want blank space between two halves
values.pop() # remove trailing empty string
print(" & ".join(values) + " \\NN")
def get_national_value(country, year, measurement, env_series="CO2"):
strings = {
"schema": config.WIOD_SCHEMA,
"year": year,
"fd_sectors": sqlhelper.set_repr(config.default_fd_sectors),
}
if measurement == "env":
envsql = """SELECT value FROM %(schema)s.env_%(year)d
WHERE country = $1 AND measurement = $2
AND industry = 'total'"""
envstmt = db.prepare(envsql % strings)
return envstmt(country, env_series)[0][0]
if measurement == "gdp":
gdpsql = """SELECT sum(value) FROM %(schema)s.indbyind_%(year)d
WHERE country = $1 AND to_ind in %(fd_sectors)s"""
gdpstmt = db.prepare(gdpsql % strings)
gdp = gdpstmt(country)[0][0]
return imfdata.convert_to_2005(gdp, country, year)
if measurement == "ppppc":
ppppc = imfdata.get_imf_value(country, year, "ppp_pc")
if ppppc is None:
# above is worldbank version. imf version might not be chained
ppppc = imfdata.get_imf_value(country, year, "PPPPC")
return ppppc
if measurement == "pop":
return imfdata.get_imf_value(country, year, "pop")
return imfdata.get_imf_value(country, year, measurement)
