code: def precision_calculation(model, df, y):
      output = model.predict(df["test"])
      average_value = (
          "binary" if len(np.unique(y["test"])) == 2 else "macro"
      )
  
      return float(
          precision_score(
              y["test"],
              output,
              average=average_value,
              labels=np.unique(output),
          )
      )
  
file_path: nylon/nylon/analysis/analysis.py
imports: from sklearn.metrics import accuracy_score
  from sklearn.metrics import precision_score, recall_score
  from sklearn.metrics import confusion_matrix
  from sklearn.model_selection import cross_val_score
  import numpy
label_desc: Use image node_id 5 for calling a global function with example usage: precision_calculation(model, df, y) and returns: float