本文整理匯總了Python中influxdb.influxdb08.DataFrameClient.delete_series方法的典型用法代碼示例。如果您正苦於以下問題：Python DataFrameClient.delete_series方法的具體用法？Python DataFrameClient.delete_series怎麽用？Python DataFrameClient.delete_series使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類influxdb.influxdb08.DataFrameClient的用法示例。
在下文中一共展示了DataFrameClient.delete_series方法的2個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: DataFrameClient
# 需要導入模塊: from influxdb.influxdb08 import DataFrameClient [as 別名]
# 或者: from influxdb.influxdb08.DataFrameClient import delete_series [as 別名]
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
start = timeit.default_timer()
influx_Econ = InfluxDB(db_name='Econ')
for item in processed_list:
if item[0] in df.get_list_series():
df.delete_series(item[0])
results = influx_Econ.interpret(item[1])
results = results.replace(to_replace='NaN',value='.')示例2: QuandlAPI
# 需要導入模塊: from influxdb.influxdb08 import DataFrameClient [as 別名]
# 或者: from influxdb.influxdb08.DataFrameClient import delete_series [as 別名]
'''
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)