class_docstr: NumericalStats contains following basic information:
      - _total_count: total count of values
      - _nan_count: total count of nan values
      - _min: minimum of all values
      - _max: maximum of all values
      - _mean: mean of the values
      - _median: median of the values
      - _sd: standard deviation of the values
      - _histogram: a histogram of value distribution represented by a list of (x_left, x_right, count)
      - _kde: a kernel density estimation curve represented by a list of points
class_docstr_tok: ["NumericalStats","contains","following","basic","information",":","-","_total_count",":","total","count","of","values","-","_nan_count",":","total","count","of","nan","values","-","_min",":","minimum","of","all","values","-","_max",":","maximum","of","all","values","-","_mean",":","mean","of","the","values","-","_median",":","median","of","the","values","-","_sd",":","standard","deviation","of","the","values","-","_histogram",":","a","histogram","of","value","distribution","represented","by","a","list","of","(","x_left",",","x_right",",","count",")","-","_kde",":","a","kernel","density","estimation","curve","represented","by","a","list","of","points"]
code: def __init__(
      self,
      min: Optional[Union[float, int, None]] = None,
      max: Optional[Union[float, int, None]] = None,
      mean: Optional[float] = None,
      median: Optional[Union[float, int, None]] = None,
      sd: Optional[Union[float, int, None]] = None,
      histogram: Optional[
          List[
              Tuple[
                  Union[float, int, None], Union[float, int, None], int
              ]
          ]
      ] = [],
      kde: Optional[
          List[Tuple[Union[float, int, None], Union[float, int, None]]]
      ] = [],
      total_count: Optional[Union[float, int, None]] = 0,
      nan_count: Optional[Union[float, int, None]] = 0,
  ):
      super(NumericalStats).__init__()
      self.total_count = total_count
      self.min = min
      self.max = max
      self.mean = mean
      self.median = median
      self.sd = sd
      self.histogram = histogram
      self.kde = kde
      self.nan_count = nan_count
  
imports: from typing import Dict, List, Tuple, Optional, Union
  from xai.data.abstract_stats import AbstractStats
  from xai.data.constants import STATSKEY
  from xai.data.exceptions import InvalidTypeError, InvalidSizeError
label_desc: Use image node_id 1 to create a new NumericalStats object from inherited base classes: AbstractStats with example: obj = NumericalStats(min, max, mean, median, sd, histogram, kde, total_count, nan_count)