code: def plot_predt(y: np.ndarray, y_predt: np.ndarray, name: str) -> None:
      s = 25
      plt.scatter(
          y[:, 0],
          y[:, 1],
          c="navy",
          s=s,
          edgecolor="black",
          label="data",
      )
      plt.scatter(
          y_predt[:, 0],
          y_predt[:, 1],
          c="cornflowerblue",
          s=s,
          edgecolor="black",
      )
      plt.xlim([-1, 2])
      plt.ylim([-1, 2])
      plt.show()
  
file_path: xgboost/demo/guide-python/multioutput_regression.py
imports: import argparse
  from typing import Dict, List, Tuple
  import numpy
  from matplotlib import pyplot
  import xgboost
label_desc: Use image node_id 1 for calling a global function with example usage: plot_predt(y, y_predt, name) without return types