本文整理汇总了Python中influxdb.influxdb08.DataFrameClient.create_database方法的典型用法代码示例。如果您正苦于以下问题：Python DataFrameClient.create_database方法的具体用法？Python DataFrameClient.create_database怎么用？Python DataFrameClient.create_database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influxdb.influxdb08.DataFrameClient的用法示例。
在下文中一共展示了DataFrameClient.create_database方法的3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: QuandlAPI
# 需要导入模块: from influxdb.influxdb08 import DataFrameClient [as 别名]
# 或者: from influxdb.influxdb08.DataFrameClient import create_database [as 别名]
'''
Created on Jul 8, 2015
@author: shaunz
'''
from QuandlAPI import QuandlAPI
from influxdb.influxdb08 import DataFrameClient
from QuandlTicker import Quandl_ticker_list
import timeit
quandl = QuandlAPI()
df = DataFrameClient('localhost', 8086, 'root', 'root')
if({'name':'Quandl'} not in df.get_list_database()):
df.create_database('Quandl')
df.switch_database('Quandl')
for series in df.get_list_series():
df.delete_series(series)
start = timeit.default_timer()
for item in Quandl_ticker_list:
results = quandl.get_series(item[1],item[2],item[3])
results = results.replace(to_replace='NaN',value='.')
print item
df.write_points({item[0]:results})
print 'total time in seconds: %.2f' % (timeit.default_timer() - start)示例2: DataFrameClient
# 需要导入模块: from influxdb.influxdb08 import DataFrameClient [as 别名]
# 或者: from influxdb.influxdb08.DataFrameClient import create_database [as 别名]
[ 'wage_us_yoy', '(wage_us_weekly_nonsupervisory/lag(wage_us_weekly_nonsupervisory,12)-1)*100' ],
[ 'wti_yoy', '(avg(wti_spot,M)/lag(avg(wti_spot,M),12)-1)*100' ],
[ 'zillow_median_sale_price_yoy', '(zillow_median_sale_price/lag(zillow_median_sale_price,12)-1)*100' ],
[ 'ng_yoy', '(ng_hh_spot/lag(ng_hh_spot,12)-1)*100' ],
[ 'gdp_us_yoy', '(gdp_us/lag(gdp_us,4)-1)*100' ],
]
processed_list = [
[ 'wage_lag_15m', 'mlag(wage_us_yoy,15)' ],
[ 'zillow_median_sale_price_15m', 'mlag(zillow_median_sale_price_yoy,15)' ],
]
df = DataFrameClient('localhost',8086,'root','root')
if({'name':'Econ'} not in df.get_list_database()):
df.create_database('Econ')
df.switch_database('Econ')
#add all items in interested list
start = timeit.default_timer()
for item in interest_list:
if item[0] in df.get_list_series():
df.delete_series(item[0])
results = influx_Fred.interpret(item[1])
results = results.replace(to_replace='NaN',value='.')
results = DataFrame({'value':results['value']})
df.write_points({item[0]:results})
print item
print 'total time in seconds: %.2f' % (timeit.default_timer() - start)
#add all items in processed list示例3: FredLink
# 需要导入模块: from influxdb.influxdb08 import DataFrameClient [as 别名]
# 或者: from influxdb.influxdb08.DataFrameClient import create_database [as 别名]
'''
Created on Jul 2, 2015
@author: shaunz
'''
from influxdb.influxdb08 import DataFrameClient
from pandas import DataFrame
from FredAPI import FredLink
from FredLink.FredTicker import Fred_ticker_list
import timeit
fred = FredLink()
df = DataFrameClient('localhost', 8086, 'root', 'root')
if({'name':'FRED'} not in df.get_list_database()):
df.create_database('FRED')
df.switch_database('FRED')
for series in df.get_list_series():
df.delete_series(series)
start = timeit.default_timer()
for item in Fred_ticker_list:
results = fred.get_series(item[1])
results = results.replace(to_replace='NaN',value='.')
data = DataFrame({'value': results})
print item
df.write_points({item[0]:data})
print 'total time in seconds: %.2f' % (timeit.default_timer() - start)