1 files changed, 23 insertions, 2 deletions
diff --git a/python/collateral/jpm.py b/python/collateral/jpm.py
index 8a5123c2..e9f83f47 100644
--- a/python/collateral/jpm.py
+++ b/python/collateral/jpm.py
@@ -3,7 +3,7 @@ import pandas as pd
 from io import BytesIO
 from pikepdf import Pdf
 from . import DAILY_DIR
-from .common import load_pdf
+from .common import load_pdf, get_col, parse_num
 
 
 def load_file(d, fund):
@@ -37,7 +37,28 @@ def load_file(d, fund):
 def get_collateral(d: datetime.date, fund):
     pdf_file = load_file(d, fund)
     collat_page = load_pdf(pdf_file, pages=True)[3]
-    return float(get_col(pomme, 200, 300, 1000, 1100)[0].replace(",", ""))
+    return float(get_col(collat_page, 200, 300, 1000, 1100)[0].replace(",", ""))
+
+
+def load_positions(d: datetime.date, fund):
+    pdf_file = load_file(d, fund)
+    positions_page = load_pdf(pdf_file, pages=True)[4]
+    anchor = next(c for c in positions_page if c.text.startswith("Total Product Group"))
+    bottom = int(anchor["top"])
+    widths = (10, 160, 300, 350, 450, 500, 550, 600, 650, 750, 850, 950, 1000, 1200)
+    cols = [get_col(positions_page, 200, 289, l, r) for l, r in zip(widths, widths[1:])]
+
+    def combine(l):
+        return [f"{l[0]} {l[1]}", *l[2:]]
+
+    cols = [combine(c) if len(c) == 4 else c for c in cols]
+    df = pd.DataFrame({c[0]: c[1:] for c in cols})
+    for col in ["Pay Notional", "Rec Notional", "MTM Amount", "IM Amount"]:
+        df[col] = df[col].apply(parse_num)
+    for col in ["Trade Date", "Maturity Date"]:
+        df[col] = pd.to_datetime(df[col], format="%d-%b-%y")
+    df["Deal ID"] = df["Deal ID"].str.extract(r"[^-]-(.*)")
+    return df
 
 
 def download_files(em, count=20, *, fund="BowdSt", **kwargs):