def test_parse_collection(self):
json_string_v1_one_dataset = """
{
"oecd" : {
"value": [1],
"dimension" : {
"id": ["one"],
"size": [1],
"one": { "category": { "index":{"2010":0}} }
}
}
}
"""
ret = jsonstat.from_string(json_string_v1_one_dataset)
self.assertIsInstance(ret, jsonstat.JsonStatCollection)
json_string_v1_two_datasets = """
{
"oecd" : {
"value": [1],
"dimension" : {
"id": ["one"],
"size": [1],
"one": { "category": { "index":{"2010":0}} }
}
},
"canada" : {
"value": [1],
"dimension": {
"id": ["one"],
"size": [1],
"one": { "category": { "index":{"2010":0}} }
}
}
}
"""
ret = jsonstat.from_string(json_string_v1_two_datasets)
self.assertIsInstance(ret, jsonstat.JsonStatCollection)
def test_parse_collection():
json_string_v1_one_dataset = """
{
"oecd" : {
"value": [1],
"dimension" : {
"id": ["one"],
"size": [1],
"one": { "category": { "index":{"2010":0}} }
}
}
}
"""
ret = jsonstat.from_string(json_string_v1_one_dataset)
assert isinstance(ret, jsonstat.JsonStatCollection)
json_string_v1_two_datasets = """
{
"oecd" : {
"value": [1],
"dimension" : {
"id": ["one"],
"size": [1],
"one": { "category": { "index":{"2010":0}} }
}
},
"canada" : {
"value": [1],
"dimension": {
"id": ["one"],
"size": [1],
"one": { "category": { "index":{"2010":0}} }
}
}
}
"""
ret = jsonstat.from_string(json_string_v1_two_datasets)
assert isinstance(ret, jsonstat.JsonStatCollection)
def test_parse_dimension(self):
self.json_string_dimension = """
{
"version" : "2.0",
"class" : "dimension",
"label" : "sex",
"category" : {
"index" : ["T", "M", "F"],
"label" : {
"T" : "total",
"M" : "male",
"F" : "female"
}
}
}
"""
ret = jsonstat.from_string(self.json_string_dimension)
self.assertIsInstance(ret, jsonstat.JsonStatDimension)
def test_parse_dimension():
json_string_dimension = """
{
"version" : "2.0",
"class" : "dimension",
"label" : "sex",
"category" : {
"index" : ["T", "M", "F"],
"label" : {
"T" : "total",
"M" : "male",
"F" : "female"
}
}
}
"""
ret = jsonstat.from_string(json_string_dimension)
assert isinstance(ret, jsonstat.JsonStatDimension)
def llegir_indicador_world_bank(indicador):
# Consultem via API la web del Banc Mundial.
# La funció retorna un Panda DataFrame amb les columnes "ISO3","year","<indicador>"
filename = os.getcwd() + "/" + indicador + ".jsonstat"
url = "https://api.worldbank.org/v2/country/all/indicator/" + indicador + "?format=jsonstat"
if os.path.isfile(filename):
jstat = jsonstat.from_file(filename)
else:
jstat = jsonstat.from_string(jsonstat.download(url, filename))
df = jstat.dataset(0).to_data_frame(content='id')
df.drop(columns="series", inplace=True)
df.rename(columns={"country": "ISO3", "Value": indicador}, inplace=True)
# Assimilem les dades de 2018 a l'any 2019 a l'espera de la seva publicació
j = 0
for i in (df.loc[df.year == '2019']).index:
df.at[i, indicador] = (df.loc[df.year == '2018', indicador]).values[j]
j += 1
return df
