code: def plot_quantile_statistics_table(factor_data):
      quantile_stats = factor_data.groupby("factor_quantile").agg(
          ["min", "max", "mean", "std", "count"]
      )["factor"]
      quantile_stats["count %"] = (
          quantile_stats["count"]
          / quantile_stats["count"].sum()
          * 100.0
      )
  
      print("Quantiles Statistics")
      utils.print_table(quantile_stats)
  
imports: import numpy
  import pandas
  from scipy import stats
  import statsmodels.api
  import seaborn
  import matplotlib.cm
  import matplotlib.pyplot
  from matplotlib.ticker import ScalarFormatter
  from functools import wraps
  from .None import utils
  from .None import performance
label_desc: Use image node_id 7 for calling a global function with example usage: plot_quantile_statistics_table(factor_data) without return types