diff options
Diffstat (limited to 'python')
| -rw-r--r-- | python/load_globeop_report.py | 11 |
1 files changed, 6 insertions, 5 deletions
diff --git a/python/load_globeop_report.py b/python/load_globeop_report.py index 5ea765a7..01ffb5a7 100644 --- a/python/load_globeop_report.py +++ b/python/load_globeop_report.py @@ -21,7 +21,7 @@ def get_globs(fname, years=['2013', '2014', '2015', '2016', '2017']): def read_valuation_report(f): date = pd.Timestamp(f.rsplit('/', 3)[1]) if date >= pd.Timestamp('2013-02-06'): - df = pd.read_csv(f, parse_dates=['KnowledgeDate','PeriodEndDate']) + df = pd.read_csv(f, parse_dates=['KnowledgeDate', 'PeriodEndDate']) else: df = pd.read_csv(f) df['KnowledgeDate'] = date @@ -81,8 +81,9 @@ def read_cds_report(f, old_report=False): 'Last Modified Date', 'Fund Long Name', 'Instrument Sub Type', 'Netting Id', 'Client', 'Trade Status', 'Position Status', 'Clearing Broker', 'Settle Mode', 'Off Price', 'On Price', - 'Price Ccy', 'VAT', 'SEC Fee', 'Clearing Fee', 'Remaining Notional', - 'Trading Notional'], axis=1, errors='ignore') + 'Price Ccy', 'VAT', 'SEC Fee', 'Clearing Fee', + 'Remaining Notional', 'Trading Notional', 'BBGID'], + axis=1, errors='ignore') df.columns = df.columns.str.lower().str.replace(" ", "_") if old_report: df.calendar = df.calendar.str.replace(" ", "") @@ -90,14 +91,14 @@ def read_cds_report(f, old_report=False): df.roll_convention = df.roll_convention.str.title() df = df[df.strategy != 'SER_TEST'] df.loc[df.strategy == 'SERCGMAST__MBSCDS', 'strategy'] = 'MBSCDS' - df.strategy = df.strategy.str.replace("SER_","") + df.strategy = df.strategy.str.replace("SER_", "") df['buy/sell'] = df['buy/sell'].astype('category') df['buy/sell'].cat.categories = ['Buyer', 'Seller'] df.prime_broker = df.prime_broker.where(df.prime_broker != 'NONE') df.loc[df.executing_broker.isnull(),'executing_broker'] = df[df.executing_broker.isnull()].counterparty del df['counterparty'] df = df.rename(columns={'executing_broker': 'counterparty', - 'independent_%':'independent_perc'}) + 'independent_%': 'independent_perc'}) return df def cds_reports(): |