diff options
Diffstat (limited to 'python/report_ops/wires.py')
| -rw-r--r-- | python/report_ops/wires.py | 23 |
1 files changed, 10 insertions, 13 deletions
diff --git a/python/report_ops/wires.py b/python/report_ops/wires.py index fb0a6120..7fe70940 100644 --- a/python/report_ops/wires.py +++ b/python/report_ops/wires.py @@ -80,11 +80,9 @@ class BNYWireReport(WireReport, custodian="BNY", dtkey="%Y%m%d%H%M%S"): df["Local Amount"] = pd.to_numeric( df["Local Amount"].str.replace(",", "") ) # Not sure how to avoid this with the thousands - df["Wire Details"] = df.apply( - lambda x: x["Transaction Description 1"] - if x["Transaction Type Code"] == "CW" - else x["Transaction Description 2"], - axis=1, + df["Wire Details"] = df["Transaction Description 1"] + df["Wire Details"] = df.where( + df["Transaction Type Code"] == "CW", df["Transaction Description 2"] ) return ( (self.date, self.fund, self.custodian, *t) @@ -110,8 +108,9 @@ class BNYWireReport(WireReport, custodian="BNY", dtkey="%Y%m%d%H%M%S"): class NTWireReport(WireReport, custodian="NT"): def __iter__(self): df = pd.read_csv(self.get_report()) - _ccy_mapping = {"EURO - EUR": "EUR", "U.S. DOLLARS - USD": "USD"} - df["Currency"] = df["N-GL-AC30"].apply(lambda x: _ccy_mapping[x]) + df["Currency"] = df["N-GL-AC30"].map( + {"EURO - EUR": "EUR", "U.S. DOLLARS - USD": "USD"} + ) return ( (self.date, self.fund, self.custodian, *t) for t in df[ @@ -145,9 +144,8 @@ class UMBWireReport(WireReport, custodian="UMB"): def __iter__(self): df = pd.read_excel(self.get_report(), skiprows=3) - df["index"] = df.index - df["Unique Ref"] = df.apply( - lambda x: f'{x["Transaction Date"]}-{x["index"]}', axis=1 + df["Unique Ref"] = ( + df["Transaction Date"].astype("str") + "-" + df.index.astype("str") ) if not df.iloc[0]["Transaction Date"].startswith("No records"): return ( @@ -178,9 +176,8 @@ class UMBWireReport(WireReport, custodian="UMB"): class SCOTIAWireReport(WireReport, custodian="SCOTIA"): def __iter__(self): df = pd.read_excel(self.get_report(), skipfooter=2) - df["Amount"] = df.apply( - lambda x: x["Cr Amount"] if x["Dr/Cr"] == "Cr" else -x["Dr Amount"], axis=1 - ) + df["Amount"] = df["Cr Amount"] + df["Amount"] = df["Amount"].where(df["Dr/Cr"] == "Cr", -df["Amount"]) return ( (self.date, self.fund, self.custodian, *t) for t in df[ |