本文整理汇总了Python中orangecontrib.timeseries.Timeseries.from_url方法的典型用法代码示例。如果您正苦于以下问题：Python Timeseries.from_url方法的具体用法？Python Timeseries.from_url怎么用？Python Timeseries.from_url使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类orangecontrib.timeseries.Timeseries的用法示例。
在下文中一共展示了Timeseries.from_url方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: quandl_data
# 需要导入模块: from orangecontrib.timeseries import Timeseries [as 别名]
# 或者: from orangecontrib.timeseries.Timeseries import from_url [as 别名]
def quandl_data(symbol,
since=None,
until=None,
*,
collapse='daily',
api_key=''):
"""
Parameters
----------
symbol
since
until
collapse: none|daily|weekly|monthly|quarterly|annual
api_key
Returns
-------
"""
if since is None:
since = date(1900, 1, 1).isoformat()
if until is None:
until = date.today().isoformat()
QUANDL_URL = ('https://www.quandl.com/api/v3/datasets/WIKI/{SYMBOL}/data.csv?'
'start_date={START_DATE}&end_date={END_DATE}&order=asc&'
'collapse={COLLAPSE}&transform=rdiff&api_key={API_KEY}')
url = QUANDL_URL.format(SYMBOL=symbol,
START_DATE=since,
END_DATE=until,
COLLAPSE=collapse,
API_KEY=api_key)
ts = Timeseries.from_url(url)
return ts示例2: finance_data
# 需要导入模块: from orangecontrib.timeseries import Timeseries [as 别名]
# 或者: from orangecontrib.timeseries.Timeseries import from_url [as 别名]
def finance_data(symbol,
since=None,
until=None,
granularity='d'):
"""Fetch Yahoo Finance data for stock or index `symbol` within the period
after `since` and before `until` (both inclusive).
Parameters
----------
symbol: str
A stock or index symbol, as supported by Yahoo Finance.
since: date
A start date (default: 1900-01-01).
until: date
An end date (default: today).
granularity: 'd' or 'w' or 'm' or 'v'
What data to get: daily, weekly, monthly, or dividends.
Returns
-------
data : Timeseries
"""
if since is None:
since = date(1900, 1, 1)
if until is None:
until = date.today()
YAHOO_URL = ('http://chart.finance.yahoo.com/table.csv?'
's={SYMBOL}&d={TO_MONTH}&e={TO_DAY}&f={TO_YEAR}&'
'g={GRANULARITY}&a={FROM_MONTH}&b={FROM_DAY}&c={FROM_YEAR}&ignore=.csv')
url = YAHOO_URL.format(SYMBOL=symbol,
GRANULARITY=granularity,
TO_MONTH=until.month - 1,
TO_DAY=until.day,
TO_YEAR=until.year,
FROM_MONTH=since.month - 1,
FROM_DAY=since.day,
FROM_YEAR=since.year)
data = Timeseries.from_url(url)[::-1]
# Make Adjusted Close a class variable
attrs = [var.name for var in data.domain.attributes]
attrs.remove('Adj Close')
data = Timeseries(Domain(attrs, [data.domain['Adj Close']], None, source=data.domain), data)
data.name = symbol
data.time_variable = data.domain['Date']
return data