def norgate_defined_start(watchlist, start_date, end_date, frequency):
symbols = norgatedata.watchlist_symbols(watchlist)
df_list = []
for symbol in symbols:
norgate_df = norgatedata.price_timeseries(symbol,
start_date=start_date,
end_date=end_date,
interval=frequency,
format='pandas-dataframe')
# creating a symbol column so that we can identify
# what ticker information we're looking at
norgate_df['Symbol'] = symbol
# appending the dataframes to an empty list to concatenate them after the for loop
df_list.append(norgate_df)
return df_list
import pandas as pd
import norgatedata
from datetime import datetime
lookback_period = 60
end_date = datetime.now()
watchlistname = 'spy_tlt_gld'
symbols = norgatedata.watchlist_symbols(watchlistname)
df_list = []
for symbol in symbols:
norgate_df = norgatedata.price_timeseries(
symbol,
end_date=end_date,
limit=lookback_period,
interval='D',
format='pandas-dataframe')
# creating a symbol column so that we can identify
# what ticker information we're looking at
norgate_df['Symbol'] = symbol
# appending the dataframes to an empty list to concatenate them after the for loop
df_list.append(norgate_df)
# joins the dataframes together for all tickers
def load_index_universe(indexname): watchlist = watchlist_for(indexname) symbols = ng.watchlist_symbols(watchlist) return symbols
def get_symbols_from_norgate_watchlist(watchlist_name):
symbols = norgatedata.watchlist_symbols(watchlist_name)
return symbols