def build_files(df, config):
filelist = []
countrylist = []
for iso3 in us.get_index_set(df):
try:
idf = df.ix[iso3]
if (
type(idf) == pd.Series
): # idf a Series if there is only one element in it, but we want a DataFrame always
idf = pd.DataFrame([idf])
idf = idf[["Year", "Value", "Source", "Notes"]]
idf.columns = ["year", "value", "source", "note"]
mult = config["multiplier"]
if mult:
if (mult <= 1 and mult >= -1) or not type(mult) is int:
idf["value"] = idf["value"].apply(lambda x: x * mult)
else:
idf["value"] = idf["value"].apply(lambda x: int(x * mult)).astype(object)
idf["source"] = idf["source"].apply(lambda x: config["source"])
idf["note"] = idf["note"].apply(lambda x: get_notes(str(x), config))
filestem = config["prefix"] + "_" + iso3.lower() + "_" + config["suffix"]
filename = filestem + ".csv"
filepath = config["gen_2_dir"] + filename
us.log(filepath)
idf.to_csv(filepath, encoding="utf8", index=False)
country = us.get_country_by_iso3(iso3)
meta = [
("name", "%s - %s [CEPALStat]" % (country, config["indicator"])),
("originalsource", config["source"]),
("proximatesource", "CEPALStat"),
("dataset", config["indicator"] + " [" + config["indicator_id"] + "]"),
("description", config["definition"]),
("category", config["indicator_category"]),
("type", config["indicator_type"]),
("file", filename),
("filehash", us.githash(filepath)),
("columns", "year,value,source,notes"),
]
metafile = config["gen_2_dir"] + filestem + "_meta.csv"
pd.DataFrame(meta, columns=["key", "value"]).to_csv(
metafile, encoding="utf8", float_format="%.3f", index=False
)
filelist.append([filestem])
countrylist.append(country)
except Exception as strerror:
us.log("ERROR: Failed to build data for %s" % iso3)
us.log(sys.exc_info())
traceback.print_tb(sys.exc_info()[2])
fldf = pd.DataFrame(filelist, index=countrylist).sort_index()
fldf.to_csv(
config["gen_2_dir"] + "_" + config["prefix"] + ".csv",
encoding="utf8",
float_format="%.1f",
index=False,
header=False,
)
return fldf
def build_files(df, config):
filelist = []
countrylist = []
for iso3 in us.get_index_set(df):
try:
idf = df.ix[iso3]
if type(idf) == pd.Series: #idf a Series if there is only one element in it, but we want a DataFrame always
idf = pd.DataFrame([idf])
idf = idf[["Year","Value","Source","Notes"]]
idf.columns = ["year","value","source","notes"]
mult = config["multiplier"]
if mult:
if (mult <= 1 and mult >= -1) or not type(mult) is int:
idf["value"] = idf["value"].apply(lambda x : x * mult)
else:
idf["value"] = idf["value"].apply(lambda x : int(x * mult)).astype(object)
idf["source"] = idf["source"].apply(lambda x : config["source"])
idf["notes"] = idf["notes"].apply(lambda x : get_notes(str(x), config))
filestem = config["prefix"] + "_" + iso3.lower() + "_" + config["suffix"]
filename = filestem + ".csv"
filepath = config["gen_2_dir"] + filename
us.log(filepath)
idf.to_csv(filepath, encoding="utf8", index=False)
country = us.get_country_by_iso3(iso3)
meta = [("name", "%s - %s [CEPALStat]" % (country, config["indicator"])),
("originalsource", config["source"]),
("proximatesource", "CEPALStat"),
("dataset", config["indicator"] + " [" + config["indicator_id"] + "]"),
("description", config["definition"]),
("category", config["indicator_category"]),
("type", config["indicator_type"]),
("file", filename),
("filehash", us.githash(filepath)),
("columns", "year,value,source,notes")
]
metafile = config["gen_2_dir"] + filestem + "_meta.csv"
pd.DataFrame(meta,columns = ["key","value"]).to_csv(metafile, encoding="utf8", float_format='%.3f',index=False)
filelist.append([filestem])
countrylist.append(country)
except Exception as strerror:
us.log("ERROR: Failed to build data for %s" % iso3)
us.log(sys.exc_info())
traceback.print_tb(sys.exc_info()[2])
fldf = pd.DataFrame(filelist, index=countrylist).sort_index()
fldf.to_csv(config["gen_2_dir"] + "_" + config["prefix"] + ".csv", encoding="utf8", float_format='%.1f', index=False, header=False)
return fldf
filelist = []
us.mkdirs(config["gen_2_dir"])
for (iso3, df, mf) in dataset:
us.log(iso3)
try:
df.columns = ["description", "value"]
except Exception: # The data for St Kitts only has one column. We are excluding it for now.
us.log(sys.exc_info())
continue
filestem = config["prefix"] + "_" + iso3.lower() + "_" + config["suffix"]
filename = filestem + ".csv"
filepath = config["gen_2_dir"] + filename
df.to_csv(filepath, encoding="utf8", float_format='%.3f', index=False)
country = us.get_country_by_iso3(iso3)
meta = [("name", "%s - %s [SIDS RCM]" % (country, config["indicator"])),
("originalsource", mf.ix["Capacity"]["Source"]),
("proximatesource", "SIDS RCM"), ("dataset", config["indicator"]),
("description", config["description"]),
("note", mf.ix["Capacity"]["Note"]),
("unit", mf.ix["Capacity"]["Unit"]),
("category", config["indicator_category"]),
("type", config["indicator_type"]), ("file", filename),
("filehash", us.githash(filepath)),
("columns", "description,value")]
metafile = config["gen_2_dir"] + filestem + "_meta.csv"
pd.DataFrame(meta, columns=["key", "value"]).to_csv(metafile,
encoding="utf8",
float_format='%.3f',
us.log(iso3)
try:
if len(df.columns) == 2:
df.columns = ["year", "value"]
else:
df.columns = ["year", "value", "notes"]
except Exception: # The data for St Kitts only has one column. We are excluding it for now.
us.log(sys.exc_info())
continue
filestem = config["prefix"] + "_" + iso3.lower() + "_" + config["suffix"]
filename = filestem + ".csv"
filepath = config["gen_2_dir"] + filename
df.to_csv(filepath, encoding="utf8", float_format='%.3f', index=False)
country = us.get_country_by_iso3(iso3)
meta = [("name", "%s - %s [SIDS RCM]" % (country, config["indicator"])),
# ("originalsource", mf.ix[keycol]["Source"]),
("originalsource", "SIDS RCM"),
("proximatesource", "SIDS RCM"),
("dataset", config["indicator"]),
("description", config["description"]),
# ("note", mf.ix[keycol]["Note"]),
# ("unit", mf.ix[keycol]["Unit"]),
("category", config["indicator_category"]),
("type", config["indicator_type"]),
("file", filename),
("filehash", us.githash(filepath)),
("columns", "description,value")
]