code: def plot_return_quantiles(
      returns, live_start_date=None, ax=None, **kwargs
  ):
      """
      Creates a box plot of daily, weekly, and monthly return
      distributions.
  
      Parameters
      ----------
      returns : pd.Series
          Daily returns of the strategy, noncumulative.
           - See full explanation in tears.create_full_tear_sheet.
      live_start_date : datetime, optional
          The point in time when the strategy began live trading, after
          its backtest period.
      ax : matplotlib.Axes, optional
          Axes upon which to plot.
      **kwargs, optional
          Passed to seaborn plotting function.
  
      Returns
      -------
      ax : matplotlib.Axes
          The axes that were plotted on.
      """
  
      if ax is None:
          ax = plt.gca()
  
      is_returns = (
          returns
          if live_start_date is None
          else returns.loc[returns.index < live_start_date]
      )
      is_weekly = ep.aggregate_returns(is_returns, "weekly")
      is_monthly = ep.aggregate_returns(is_returns, "monthly")
      sns.boxplot(
          data=[is_returns, is_weekly, is_monthly],
          palette=["#4c72B0", "#55A868", "#CCB974"],
          ax=ax,
          **kwargs,
      )
  
      if live_start_date is not None:
          oos_returns = returns.loc[returns.index >= live_start_date]
          oos_weekly = ep.aggregate_returns(oos_returns, "weekly")
          oos_monthly = ep.aggregate_returns(oos_returns, "monthly")
  
          sns.swarmplot(
              data=[oos_returns, oos_weekly, oos_monthly],
              ax=ax,
              color="red",
              marker="d",
              **kwargs,
          )
          red_dots = matplotlib.lines.Line2D(
              [],
              [],
              color="red",
              marker="d",
              label="Out-of-sample data",
              linestyle="",
          )
          ax.legend(handles=[red_dots], frameon=True, framealpha=0.5)
      ax.set_xticklabels(["Daily", "Weekly", "Monthly"])
      ax.set_title("Return quantiles")
  
      return ax
  
imports: from __future__ import division
  import datetime
  from collections import OrderedDict
  from functools import wraps
  import empyrical
  import matplotlib
  import matplotlib.patches
  import matplotlib.pyplot
  import numpy
  import pandas
  import pytz
  import scipy
  from matplotlib import figure
  from matplotlib.backends.backend_agg import FigureCanvasAgg
  from matplotlib.ticker import FuncFormatter
  from .None import _seaborn
  from .None import capacity
  from .None import pos
  from .None import timeseries
  from .None import txn
  from .None import utils
  from .utils import APPROX_BDAYS_PER_MONTH, MM_DISPLAY_UNIT
label_desc: Use image node_id 23 for calling a global function with example usage: plot_return_quantiles(returns, live_start_date, ax) and returns: ax