input: Write a python function to create a pandas DataFrame from a list of car data and column names.
  assert df_equals([["Toyota", "Camry", 23000, 28], ["Honda", "Accord", 21000, 30]], ["make", "model", "price", "mpg"], pd.DataFrame([["Toyota", "Camry", 23000, 28], ["Honda", "Accord", 21000, 30]], columns=["make", "model", "price", "mpg"]))
  assert df_equals([["Ford", "Ecosport", 20000, 25], ["Hyundai", "Elantra", 22000, 27]], ["make", "model", "price", "mpg"], pd.DataFrame([["Ford", "Ecosport", 20000, 25], ["Hyundai", "Elantra", 22000, 27]], columns=["make", "model", "price", "mpg"]))
  assert df_equals([["Toyota", "Corolla", 18000, 35], ["Honda", "Civic", 19000, 32]], ["make", "model", "price", "mpg"], pd.DataFrame([["Toyota", "Corolla", 18000, 35], ["Honda", "Civic", 19000, 32]], columns=["make", "model", "price", "mpg"]))
output: import pandas as pd
  
  def df_equals(data, columns, expected_df):
      df = pd.DataFrame(data, columns=columns)
      return df.equals(expected_df)