A Python library for working with time series data. It comes with common financial functions built-in.
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import pandas
from fincal.fincal import TimeSeries
dfd = pandas.read_csv('test_files/nav_history_daily - Copy.csv')
dfm = pandas.read_csv('test_files/nav_history_monthly.csv')
data_d = [(i.date, i.nav) for i in dfd.itertuples() if i.amfi_code == 118825]
data_d.sort()
data_m = [{'date': i.date, 'value': i.nav} for i in dfm.itertuples()]
tsd = TimeSeries(data_d, frequency='D')
md = dict(data_d)
counter = 1
for i in iter(md):
print(i)
counter += 1
if counter >= 5: break
print('\n')
counter = 1
for i in reversed(md):
print('rev', i)
counter += 1
if counter >= 5: break
x = [next(i) for i in iter(md)]
print(x)