code: def test_corr_pandas():
      df = pd.DataFrame(
          {
              "x1": [1, 2, 3, 4, 5, 6, 7, 8],
              "x2": [0, 0, 0, 1, 0, 0, 0, 0],
              "y": [2, 3, 4, 6, 6, 7, 8, 9],
          }
      )
  
      mod = Ridge().fit(df[["x1", "x2"]], df["y"])
      assert abs(correlation_score("x1")(mod, df[["x1", "x2"]])) > abs(
          0.99
      )
      assert abs(correlation_score("x2")(mod, df[["x1", "x2"]])) < abs(
          0.02
      )
  
imports: import pandas
  from sklearn.linear_model import Ridge
  from sklego.metrics import correlation_score
label_desc: Use image node_id 1 for calling a global function with example usage: test_corr_pandas() without return types