fix: prevent DataFrame mutation in prepare_data() causing indication charts to fail

prepare_data() mapped Provider Code → Name in-place. When called for directory
charts first, then indication charts, the second call re-mapped already-mapped
values to NaN, silently dropping all data. Added df.copy() to prevent mutation.

Also fixes directory charts only generating data for the first date filter.

Results: 3,633 pathway nodes now generated (1,101 directory + 2,532 indication)
across all 12 datasets (6 date filters × 2 chart types).

analysis/pathway_analyzer.py

@@ -53,6 +53,10 @@ def prepare_data(
     if paths is None:
         paths = default_paths
 
+    # Work on a copy to avoid mutating the caller's DataFrame
+    # (Provider Code mapping is destructive — second call would map names to NaN)
+    df = df.copy()
+
     df["UPIDTreatment"] = df["UPID"] + df["Drug Name"]
 
     org_codes = pd.read_csv(paths.org_codes_csv, index_col=1)