diff --git a/data_ingest.py b/data_ingest.py
index 9beb070..a8db4ed 100644
--- a/data_ingest.py
+++ b/data_ingest.py
@@ -84,6 +84,9 @@ def read_data() -> pd.DataFrame:
 
     # Fill in Vuositulot as 12.5 * Kk-tulot if empty
     df["Vuositulot"] = df.apply(map_vuositulot, axis=1)
+
+    # Synthesize kk-tulot from Vuositulot
+    df["Kk-tulot"] = pd.to_numeric(df["Vuositulot"], errors="coerce") / 12
     return df
 
 
@@ -93,6 +96,16 @@ def force_tulot_numeric(df):
     return df
 
 
+def force_age_numeric(df):
+    age_map = {}
+    for cat in df["Ikä"].cat.categories:
+        m = re.match("^(\d+)-(\d+) v", cat)
+        if m:
+            age_map[cat] = int(round(float(m.group(1)) + float(m.group(2)) / 2))
+    df["Ikä"] = df["Ikä"].apply(lambda r: age_map.get(r, r))
+    return df
+
+
 def main():
     pd.set_option("display.max_column", None)
     pd.set_option("display.max_rows", None)
diff --git a/generate_profiling.py b/generate_profiling.py
index a751276..792150e 100644
--- a/generate_profiling.py
+++ b/generate_profiling.py
@@ -1,10 +1,11 @@
-from data_ingest import read_data, force_tulot_numeric
+from data_ingest import read_data, force_tulot_numeric, force_age_numeric
 from pandas_profiling import ProfileReport
 
 
 def main():
     df = read_data()
     df = force_tulot_numeric(df)
+    df = force_age_numeric(df)
     profile = ProfileReport(df)
     profile.to_file("out/profiling_report.html")