code: def describe(df: "DataFrame", ddof=1, unbiased=False):
      stat_metrics = dict()
      stat_metrics["sum"] = sum(df)
      stat_metrics["min"] = min(df)
      stat_metrics["max"] = max(df)
      stat_metrics["mean"] = mean(df)
      stat_metrics["std"] = std(df, ddof=ddof)
      stat_metrics["var"] = var(df, ddof=ddof)
      stat_metrics["variation"] = variation(df, ddof=ddof)
      stat_metrics["skew"] = skew(df, unbiased=unbiased)
      stat_metrics["kurt"] = kurt(df, unbiased=unbiased)
      stat_metrics["na_count"] = df.isna().sum()
  
      return pd.DataFrame(stat_metrics)
  
file_path: FATE/python/fate/arch/dataframe/ops/_stat.py
imports: import functools
  import numpy
  import pandas
  import torch
  from .._dataframe import DataFrame
  from ..manager import DataManager
label_desc: Use image node_id 10 for calling a global function with example usage: describe(df, ddof, unbiased) and returns: pd