code: def get_feature_corr(df, method="spearman"):
      if isinstance(df, pd.DataFrame):
          result = df.corr(method=method).values
      elif callable(method):
          result = method(df)
      elif method == "spearman":
          result = stats.spearmanr(df).correlation
      elif method == "pearson":
          result = np.corrcoef(df)
      else:
          raise ValueError("unsupported correlation method")
      return result
  
imports: import pandas
  import numpy
  import matplotlib.pyplot
  import sklearn
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.ensemble import RandomForestRegressor
  from distutils.version import LooseVersion
  from sklearn.model_selection import cross_val_score
  from sklearn.base import clone
  from sklearn.metrics import r2_score
  from sklearn.metrics import f1_score
  from sklearn.preprocessing import LabelEncoder
  from scipy import stats
  from pandas.api.types import is_numeric_dtype
  from matplotlib.colors import ListedColormap
  from matplotlib.ticker import FormatStrFormatter
  from copy import copy
  import warnings
  import tempfile
  from os import getpid, makedirs
label_desc: Use image node_id 20 for calling a global function with example usage: get_feature_corr(df, method) and returns: result