code: def lalonde_dataset() -> pd.DataFrame:
      """Downloads and returns the Lalonde dataset from https://users.nber.org/~rdehejia/nswdata2.html"""
      # The following code for loading the Lalonde dataset was copied from
      # https://github.com/wayfair/pylift/blob/5afc9088e96f25672423663f5c9b4bb889b4dfc0/examples/Lalonde/Lalonde_sample.ipynb?short_path=b1d451f#L94-L99).
      #
      # Copyright 2018, Wayfair, Inc.
      #
      # Redistribution and use in source and binary forms, with or without modification, are permitted provided that
      # the following conditions are met:
      #
      # 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the
      #    following disclaimer.
      #
      # 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the
      #    following disclaimer in the documentation and/or other materials provided with the distribution.
      #
      # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED
      # WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A
      # PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY
      # DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
      # PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
      # CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
      # OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH
      # DAMAGE.
      cols = [
          "treat",
          "age",
          "educ",
          "black",
          "hisp",
          "married",
          "nodegr",
          "re74",
          "re75",
          "re78",
      ]
      control = pd.read_csv(
          "https://www.nber.org/~rdehejia/data/nswre74_control.txt",
          sep="\\s+",
          header=None,
          names=cols,
      )
      treated = pd.read_csv(
          "https://www.nber.org/~rdehejia/data/nswre74_treated.txt",
          sep="\\s+",
          header=None,
          names=cols,
      )
      lalonde = pd.concat([control, treated], ignore_index=True).astype(
          {"treat": "bool"}, copy=False
      )
      lalonde["u74"] = np.where(lalonde["re74"] == 0, 1.0, 0.0)
      lalonde["u75"] = np.where(lalonde["re75"] == 0, 1.0, 0.0)
      return lalonde
  
imports: import math
  import string
  import networkx
  import numpy
  import pandas
  import scipy.stats
  from numpy.random import choice
  from scipy.stats import bernoulli, halfnorm, poisson, uniform
  from sklearn.neural_network import MLPRegressor
  from dowhy.utils.graph_operations import add_edge, del_edge, get_random_node_pair, get_simple_ordered_tree
label_desc: Use image node_id 16 for calling a global function with example usage: lalonde_dataset() and returns: lalonde