code: def load_concrete(split=False):
      path = os.path.join(DATA, "concrete", "concrete.csv")
      data = pd.read_csv(path)
  
      X = data[
          [
              "cement",
              "slag",
              "ash",
              "water",
              "splast",
              "coarse",
              "fine",
              "age",
          ]
      ]
      y = data["strength"]
      return _make_dataset(X, y, split)
  
imports: import os
  import argparse
  import numpy
  import pandas
  import matplotlib.pyplot
  from yellowbrick.features import Rank2D, RadViz
  from yellowbrick.model_selection import LearningCurve
  from yellowbrick.cluster import KElbowVisualizer, SilhouetteVisualizer
  from yellowbrick.classifier import ClassificationReport, DiscriminationThreshold
  from yellowbrick.regressor import ResidualsPlot, PredictionError, AlphaSelection
  from collections import namedtuple
  from sklearn.datasets import make_blobs
  from sklearn.naive_bayes import MultinomialNB
  from sklearn.ensemble import RandomForestRegressor
  from sklearn.cluster import MiniBatchKMeans, Birch
  from sklearn.model_selection import train_test_split
  from sklearn.linear_model import LassoCV, RidgeCV, LogisticRegression
label_desc: Use image node_id 3 for calling a global function with example usage: load_concrete(split) and returns: _make_dataset