def build_files(df, meta_function, meta_map, gen_2_dir, prefix, suffix):
filelist = []
countrylist = []
for iso3 in statmart_utils.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"]
idf["source"] = idf["source"].apply(lambda x : meta_map["source"])
idf["notes"] = idf["notes"].apply(lambda x : get_notes(str(x), meta_map))
filestem = prefix + "_" + iso3.lower() + "_" + suffix
filename = filestem + ".csv"
filepath = gen_2_dir + filename
idf.to_csv(filepath, encoding="utf8", index=False)
meta = meta_function(iso3, meta_map)
meta.append(("file", filename))
meta.append(("filehash", statmart_utils.githash(filepath)))
meta.append(("columns", "year,value,source,notes"))
metafile = gen_2_dir + filestem + "_meta.csv"
pd.DataFrame(meta,columns = ["key","value"]).to_csv(metafile, encoding="utf8", index=False)
filelist.append([filestem])
countrylist.append(statmart_utils.get_country_by_iso3(iso3))
except Exception as strerror:
print ("ERROR: Failed to build data for %s" % iso3)
print (strerror)
fldf = pd.DataFrame(filelist, index=countrylist).sort_index()
fldf.to_csv(gen_2_dir + "_" + prefix + ".csv", encoding="utf8", float_format='%.1f', index=False, header=False)
return fldf
def get_metadata(iso3, meta_map):
country = statmart_utils.get_country_by_iso3(iso3)
return [("name", "%s - Contraceptive use [CEPALStat]" % (country)),
("originalsource", meta_map["source"]),
("proximatesource", "CEPALStat"),
("dataset", meta_map["indicator"] + " [" + indicator_id + "]"),
("description", meta_map["definition"]), ("category", "Social"),
("type", "Health")]
def get_metadata(iso3, meta_map):
country = statmart_utils.get_country_by_iso3(iso3)
return [("name", "%s - %s [CEPALStat]" % (country, indicator_name)),
("originalsource", meta_map["source"]),
("proximatesource", "CEPALStat"),
("dataset", meta_map["indicator"] + " [" + indicator_id + "]"),
("description", meta_map["definition"]),
("category", indicator_category), ("type", indicator_type)]
def get_metadata(iso3, meta_map):
country = statmart_utils.get_country_by_iso3(iso3)
return [("name", "%s - %s [CEPALStat]" % (country, indicator_name)),
("originalsource", meta_map["source"]),
("proximatesource", "CEPALStat"),
("dataset", meta_map["indicator"] + " [" + indicator_id + "]"),
("description", meta_map["definition"]),
("category", indicator_category),
("type", indicator_type)
]
def get_metadata(iso3, meta_map):
country = statmart_utils.get_country_by_iso3(iso3)
return [
("name", "%s - Contraceptive use [CEPALStat]" % (country)),
("originalsource", meta_map["source"]),
("proximatesource", "CEPALStat"),
("dataset", meta_map["indicator"] + " [" + indicator_id + "]"),
("description", meta_map["definition"]),
("category", "Social"),
("type", "Health"),
]
def build_files(df, meta_function, meta_map, gen_2_dir, prefix, suffix):
filelist = []
countrylist = []
for iso3 in statmart_utils.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"]
idf["source"] = idf["source"].apply(lambda x: meta_map["source"])
idf["notes"] = idf["notes"].apply(
lambda x: get_notes(str(x), meta_map))
filestem = prefix + "_" + iso3.lower() + "_" + suffix
filename = filestem + ".csv"
filepath = gen_2_dir + filename
idf.to_csv(filepath, encoding="utf8", index=False)
meta = meta_function(iso3, meta_map)
meta.append(("file", filename))
meta.append(("filehash", statmart_utils.githash(filepath)))
meta.append(("columns", "year,value,source,notes"))
metafile = gen_2_dir + filestem + "_meta.csv"
pd.DataFrame(meta, columns=["key",
"value"]).to_csv(metafile,
encoding="utf8",
index=False)
filelist.append([filestem])
countrylist.append(statmart_utils.get_country_by_iso3(iso3))
except Exception as strerror:
print("ERROR: Failed to build data for %s" % iso3)
print(strerror)
fldf = pd.DataFrame(filelist, index=countrylist).sort_index()
fldf.to_csv(gen_2_dir + "_" + prefix + ".csv",
encoding="utf8",
float_format='%.1f',
index=False,
header=False)
return fldf
