`"N/A"` cannot be converted by `.astype(float)` — it will raise a `ValueError`. Use `pd.to_numeric()` with `errors="coerce"` instead: ```python df["revenue"] = df["revenue"].str.replace("$", "", regex=False) df["revenue"] = df["revenue"].str.replace(",", "", regex=False) df["revenue"] = pd.to_numeri