code: def plot_lift(
      df,
      outcome_col="y",
      treatment_col="w",
      treatment_effect_col="tau",
      random_seed=42,
      n=100,
      figsize=(8, 8),
  ):
      """Plot the lift chart of model estimates in cumulative population.
  
      If the true treatment effect is provided (e.g. in synthetic data), it's calculated
      as the mean of the true treatment effect in each of cumulative population.
      Otherwise, it's calculated as the difference between the mean outcomes of the
      treatment and control groups in each of cumulative population.
  
      For details, see Section 4.1 of Gutierrez and G{\'e}rardy (2016), `Causal Inference
      and Uplift Modeling: A review of the literature`.
  
      For the former, `treatment_effect_col` should be provided. For the latter, both
      `outcome_col` and `treatment_col` should be provided.
  
      Args:
          df (pandas.DataFrame): a data frame with model estimates and actual data as columns
          outcome_col (str, optional): the column name for the actual outcome
          treatment_col (str, optional): the column name for the treatment indicator (0 or 1)
          treatment_effect_col (str, optional): the column name for the true treatment effect
          random_seed (int, optional): random seed for numpy.random.rand()
          n (int, optional): the number of samples to be used for plotting
      """
  
      plot(
          df,
          kind="lift",
          n=n,
          figsize=figsize,
          outcome_col=outcome_col,
          treatment_col=treatment_col,
          treatment_effect_col=treatment_effect_col,
          random_seed=random_seed,
      )
  
imports: from matplotlib import pyplot
  import logging
  import numpy
  import pandas
  import seaborn
  from lightgbm import LGBMRegressor
  from ..inference.meta.tmle import TMLELearner
label_desc: Use image node_id 8 for calling a global function with example usage: plot_lift(df, outcome_col, treatment_col, treatment_effect_col, random_seed, n, figsize) without return types