input: Write a python function to encode categorical data using LabelEncoder from sklearn and apply it to a specific column in a pandas DataFrame.
  assert encode_gender(pd.DataFrame({"Gender": ["Male", "Female", "Female", "Male"]}), "Gender")["Gender"].tolist() == [1, 0, 0, 1]
  assert encode_gender(pd.DataFrame({"Gender": ["Female", "Female", "Male"]}), "Gender")["Gender"].tolist() == [0, 0, 1]
  assert encode_gender(pd.DataFrame({"Gender": ["Male"]}), "Gender")["Gender"].tolist() == [0]
output: def encode_gender(df, column):
      from sklearn.preprocessing import LabelEncoder
      le = LabelEncoder()
      df[column] = le.fit_transform(df[column])
      return df