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from glob import iglob
import os
import pandas as pd
from itertools import chain
from pandas.tseries.offsets import BDay
import pdb
def daily_reports(fname, years=['2013', '2014', '2015']):
df = pd.DataFrame()
basedir = '/home/share/Daily'
globs = [iglob(os.path.join(basedir, year,
("{0}_*/{0}*/Reports/{1}.csv".
format(year, fname))))
for year in years]
globs.append(iglob(os.path.join(basedir,
'{0}-*/Reports/{1}.csv'.format(years[-1],
fname))))
for f in chain.from_iterable(globs):
try:
date = pd.Timestamp(f.split('/')[6])
except ValueError:
date = pd.Timestamp(f.split('/')[4])
if date>=pd.Timestamp('2013-02-06'):
newdf = pd.read_csv(f, parse_dates=['KnowledgeDate','PeriodEndDate'])
else:
newdf = pd.read_csv(f)
newdf['KnowledgeDate'] = date
newdf['PeriodEndDate'] = date - BDay(1)
if newdf.empty or ('PeriodEndDate' in df and \
not df[df.PeriodEndDate == newdf.PeriodEndDate.iat[0]].empty):
continue
df = df.append(newdf)
del df['AccountingPeriod']
for col in ['Strat','InvCcy','Fund','Port']:
df[col] = df[col].astype('category')
df.to_hdf('globeop.hdf', fname.lower(), format='table', complib='blosc')
if __name__=='__main__':
#daily_reports('Pnl')
daily_reports('Valuation_Report')
df = pd.read_hdf('globeop.hdf', 'valuation_report')
nav = df[df.Fund=='SERCGMAST'].groupby('PeriodEndDate')['EndBookNAV'].sum()
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