outputsize='compact' is giving last 100 days, and outputsize='full' is giving whole history which is too much data. Any idea how to write a code that extract some specific period?
ts=TimeSeries(key='KEY', output_format='pandas')
data, meta_data = ts.get_daily(symbol='MSFT', outputsize='compact')
print(data)
Thanks.
This is how I was able to get the dates to work
ts = TimeSeries (key=api_key, output_format = "pandas")
data_daily, meta_data = ts.get_daily_adjusted(symbol=stock_ticker, outputsize ='full')
start_date = datetime.datetime(2000, 1, 1)
end_date = datetime.datetime(2019, 12, 31)
# Create a filtered dataframe, and change the order it is displayed.
date_filter = data_daily[(data_daily.index > start_date) & (data_daily.index <= end_date)]
date_filter = date_filter.sort_index(ascending=True)
If you want to iterate trough the rows in the new dataframe
for index, row in date_filter.iterrows():
