Append diff between empty and na.

Add warning if note > bareme

notes_tools/tools/df_marks_manip.py

@@ -7,6 +7,9 @@ from math import ceil, floor
 import logging
 logger = logging.getLogger(__name__)
 
+NOANSWER = "na"
+NORATED = ""
+
 # Values manipulations
 
 def round_half_point(val):
@@ -49,7 +52,7 @@ def note_to_rep(x):
     '\\RepU'
     """
     if x["Niveau"]:
-        if pd.isnull(x["Note"]):
+        if x["Note"] == NOANSWER:
             return latex_caract[0]
         elif x["Note"] in range(4):
             return latex_caract[int(x["Note"])+1]
@@ -78,7 +81,12 @@ def note_to_mark(x):
     """
 
     if x["Niveau"]:
+        if x["Note"] == NOANSWER:
+            return 0
         return x["Note"] * x["Bareme"] / 3
+
+    if x["Note"] > x["Bareme"]:
+        logger.warning(f"The note ({x['Note']}) is greated than the rating scale ({x['Bareme']}) at {x}")
     return x["Note"]
 
 def note_to_level(x):
@@ -112,8 +120,7 @@ def note_to_level(x):
     >>> note_to_level(df.loc[10])
     2
     """
-
-    if pd.isnull(x["Note"]):
+    if x["Note"] == NOANSWER:
         return "na"
 
     if pd.isnull(x["Bareme"]) or x["Bareme"] == 0:
@@ -468,8 +475,8 @@ def digest_flat_df(flat_df):
     2      0    E1  N2         1     4.0  01/10/2016   3.0        0.75
     3      1    E2  N2         1     4.0  01/10/2016   NaN         NaN
     """
-    # Remove data with "nn" (non notés)
-    df = flat_df.copy()[flat_df["Note"].astype("object") != "nn"]
+    df = flat_df.dropna(subset=["Note"])
+
     df["Mark"] = compute_marks(df)
     df["Level"] = compute_level(df)
     df["Latex_rep"] = compute_latex_rep(df)