def get_data(area_level, variable, universe_filter=None, redownload=False):
path = get_data_path(area_level, variable, "censo", universe_filter)
if not os.path.isfile(path) or redownload:
query = pyredatam.arealist_query(area_level, variable, {"PROV": "02"}, universe_filter=universe_filter)
df = cpv2010arg.make_arealist_query(query)
if "Código" in df.columns:
df = replace_index(df, AREAS_LENIDS[area_level])
df.to_csv(path, encoding="utf-8")
else:
df = pd.read_csv(path, encoding="utf-8")
if "Código" in df.columns:
df = replace_index(df, AREAS_LENIDS[area_level])
return df
def get_data_from_query(area_level, query, redownload=False):
path = get_data_path(area_level, "query", "censo", unicode(hash(query)))
if not os.path.isfile(path) or redownload:
html = pyredatam.cpv2010arg.make_query(query)
df = pd.read_html(html, header=1, thousands=".")[0].dropna()
if "Código" in df.columns:
df = replace_index(df, AREAS_LENIDS[area_level])
df.to_csv(path, encoding="utf-8")
else:
df = pd.read_csv(path, encoding="utf-8")
if "Código" in df.columns:
df = replace_index(df, AREAS_LENIDS[area_level])
return df
def get_data_from_query(area_level, query, redownload=False):
path = get_data_path(area_level, "query", "censo", unicode(hash(query)))
if not os.path.isfile(path) or redownload:
html = pyredatam.cpv2010arg.make_query(query)
df = pd.read_html(html, header=1, thousands=".")[0].dropna()
if "Código" in df.columns:
df = replace_index(df, AREAS_LENIDS[area_level])
df.to_csv(path, encoding="utf-8")
else:
df = pd.read_csv(path, encoding="utf-8")
if "Código" in df.columns:
df = replace_index(df, AREAS_LENIDS[area_level])
return df
def get_data(area_level, variable, universe_filter=None, redownload=False):
path = get_data_path(area_level, variable, "censo", universe_filter)
if not os.path.isfile(path) or redownload:
query = pyredatam.arealist_query(area_level, variable,
{"PROV": "02"},
universe_filter=universe_filter)
df = cpv2010arg.make_arealist_query(query)
if "Código" in df.columns:
df = replace_index(df, AREAS_LENIDS[area_level])
df.to_csv(path, encoding="utf-8")
else:
df = pd.read_csv(path, encoding="utf-8")
if "Código" in df.columns:
df = replace_index(df, AREAS_LENIDS[area_level])
return df