diff options
| -rw-r--r-- | R/load_bloomberg_data.R | 1 | ||||
| -rw-r--r-- | python/load_bloomberg_data.py | 5 |
2 files changed, 3 insertions, 3 deletions
diff --git a/R/load_bloomberg_data.R b/R/load_bloomberg_data.R index 6b7e36f5..1b7d5eaa 100644 --- a/R/load_bloomberg_data.R +++ b/R/load_bloomberg_data.R @@ -16,6 +16,7 @@ fields.corp <- c("PX_LAST","LAST_UPDATE_DT","ISSUER","MATURITY","CPN","CPN_TYP", corpcusips <- scan(file = file.path(root.dir, "data", "bbgcusips.txt"), what="char")
+corpcusips <- unique(corpcusips)
secCorp <- paste(corpcusips, "Corp")
dataCorp <- bdp(bbgCon, secCorp, fields.corp)
corpcusips <- substr(rownames(dataCorp[which(!is.na(dataCorp$ISSUER)),]),1,9)
diff --git a/python/load_bloomberg_data.py b/python/load_bloomberg_data.py index 1bca78bf..fcd4bed4 100644 --- a/python/load_bloomberg_data.py +++ b/python/load_bloomberg_data.py @@ -4,7 +4,6 @@ import datetime from datetime import date
import csv
import common
-import pdb
def convertToNone(s):
return None if (s=='' or s=='NA') else s
@@ -25,8 +24,8 @@ for filename in os.listdir(root): if "datacorp" in filename:
for line in dr:
if line["LAST_UPDATE_DT"] != 'NA':
- line["LAST_UPDATE_DT"] = \
- datetime.datetime.strptime(line["LAST_UPDATE_DT"], '%Y-%m-%d').date()
+ line["LAST_UPDATE_DT"] = \
+ datetime.datetime.strptime(line["LAST_UPDATE_DT"], '%Y-%m-%d').date()
else:
line["LAST_UPDATE_DT"] = \
datetime.datetime.strptime(filename.split("_")[2].split(".")[0], '%Y-%m-%d').date()
|