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Chart macroeconomic time series from mini-kep dataset
Replicate correlations from Prescot artice, see https://github.com/epogrebnyak/cmf-comovement-tables.
import pandas as pd
URL = {'a': 'http://mini-kep.herokuapp.com/annual',
'q': 'http://mini-kep.herokuapp.com/quarterly',
'm': 'http://mini-kep.herokuapp.com/monthly'}
def read_csv(source):
return pd.read_csv(source, converters={0: pd.to_datetime}, index_col=0)
dfa, dfq, dfm = (read_csv(URL[freq]) for freq in 'aqm')
As a simple approximation of the task - in a dataset I have some highly seasonal time sereis like these ones:
Can look up these in macrodash
As well as some time series where the seasonlaity is not apparent, but you also want to have it removed, as in GDP
Basically, I would like to store one or several seasonally adjusted versions for the indicator
and deliver it in API with sa parameter
http://minikep-db.herokuapp.com/all/series/TRANSPORT_FREIGHT_bln_tkm/m/sa (example, not working)
also sa can contain a verson like sa:x13
, sa:something
a problem for me is that my code is python and most seasonal adjustment is in R
my own little snippet of R code
@alexeyzakharenkov made an attempt to chart CPI retail sales from FRED for US and mini-kep
fro Russian, here are two notebooks: https://github.com/alexeyzakharenkov/mini-kep-chart
It is good for the start, but I think several things can be done:
@ravshansk - maybe you can look at this?
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