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df_list = collection.write('dataframe_list')
print(df_list)
#
# EXAMPLE_URL = 'http://json-stat.org/samples/hierarchy.json'
#
# dataset = pyjstat.Dataset.read(EXAMPLE_URL)
# df = dataset.write('dataframe')
# print(df)
EXAMPLE_URL = 'http://web.ons.gov.uk/ons/api/data/dataset/DC1104EW.json?'\
'context=Census&jsontype=json-stat&apikey=DCOpn8BU2i&'\
'geog=2011HTWARDH&diff=&totals=false&'\
'dm/2011HTWARDH=E12000007'
dataset = pyjstat.Dataset.read(EXAMPLE_URL)
df = dataset.write('dataframe')
print(df)
# -*- coding: utf-8 -*-
""" pyjstat 1.X example for JSON-stat 2.0"""
import time
from pyjstat import pyjstat
EXAMPLE_URL = 'http://www.cso.ie/StatbankServices/StatbankServices.svc/' \
'jsonservice/responseinstance/TSM01'
# Elapsed time for pyjstat operations only (without network latency)
start = time.time()
# read dataset from url
dataset_from_json_url = pyjstat.Dataset.read(EXAMPLE_URL)
# write dataframe
dataframe = dataset_from_json_url.write('dataframe')
print(dataframe)
# read dataset from dataframe
dataset_from_dataframe = pyjstat.Dataset.read(dataframe)
print(dataset_from_dataframe)
# write dataset to json-stat string
json_string = dataset_from_dataframe.write()
print(json_string)
# read dataset from json-stat string
dataset_from_json_string = pyjstat.Dataset.read(json_string)
print(dataset_from_json_string)
them to Pandas Dataframes.
Args:
collection (OrderedDict): data in JSON-stat format, previously \
deserialized to a python object by \
json.load() or json.loads(),
df_list (list): list variable which will contain the converted \
datasets.
Returns:
Nothing.
"""
for item in collection['link']['item']:
if item['class'] == 'dataset':
df_list.append(Dataset.read(item['href']).write('dataframe'))
elif item['class'] == 'collection':
nested_collection = request(item['href'])
unnest_collection(nested_collection, df_list)
dataset_from_json_url = pyjstat.Dataset.read(EXAMPLE_URL)
# write dataframe
dataframe = dataset_from_json_url.write('dataframe')
print(dataframe)
# read dataset from dataframe
dataset_from_dataframe = pyjstat.Dataset.read(dataframe)
print(dataset_from_dataframe)
# write dataset to json-stat string
json_string = dataset_from_dataframe.write()
print(json_string)
# read dataset from json-stat string
dataset_from_json_string = pyjstat.Dataset.read(json_string)
print(dataset_from_json_string)
end = time.time()
print("Time: " + str(end - start))
warnings.warn(
"Shouldn't use this function anymore! Now use read() methods of"
"Dataset, Collection or Dimension.",
DeprecationWarning
)
check_input(naming)
results = []
if type(datasets) is list:
for idx, element in enumerate(datasets):
for dataset in element:
js_dict = datasets[idx][dataset]
results.append(generate_df(js_dict, naming, value))
elif isinstance(datasets, OrderedDict) or type(datasets) is dict or \
isinstance(datasets, Dataset):
if 'class' in datasets:
if datasets['class'] == 'dataset':
js_dict = datasets
results.append(generate_df(js_dict, naming, value))
else: # 1.00 bundle type
for dataset in datasets:
js_dict = datasets[dataset]
results.append(generate_df(js_dict, naming, value))
return results
def __init__(self, *args, **kwargs):
super(Dataset, self).__init__(*args, **kwargs)