df["Current Annual Salary"] = [float(s[1:]) for s
in df["Current Annual Salary"]]
df["Year First Hired"] = [int(s.split("/")[-1])
for s in df["Date First Hired"]]
target_column = "Current Annual Salary"
y = df[target_column].values.ravel()
After Change
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
// and carry out some basic preprocessing:
df["Current Annual Salary"] = df["Current Annual Salary"].str.strip("$").astype(
float)df["Date First Hired"] = pd.to_datetime(df["Date First Hired"])
df["Year First Hired"] = df["Date First Hired"].apply(lambda x: x.year)
target_column = "Current Annual Salary"
y = df[target_column].values.ravel()
