class_docstr: _Col class. It refers to a column of a dataframe.
class_docstr_tok: ["_Col","class",".","It","refers","to","a","column","of","a","dataframe","."]
docstr: Check if the value range of the column is valid.
  
  Args:
      df: The dataframe from which to check the column.
  
  Raises:
      ValueError: If the values of the column are not valid.
docstr_tok: ["Check","if","the","value","range","of","the","column","is","valid",".","Args",":","df",":","The","dataframe","from","which","to","check","the","column",".","Raises",":","ValueError",":","If","the","values","of","the","column","are","not","valid","."]
code: def check_col_value(self, df: pd.DataFrame) -> None:
      """Check if the value range of the column is valid.
  
      Args:
          df: The dataframe from which to check the column.
  
      Raises:
          ValueError: If the values of the column are not valid.
      """
      if self.min_value is not None and self.max_value is not None:
          col_value = df[self.colname]
          if not (
              (col_value >= self.min_value).all()
              and (col_value <= self.max_value).all()
          ):
              raise ValueError(
                  "column '{colname}' must be >= {min_value} and <= {max_value}.".format(
                      colname=self.colname,
                      min_value=self.min_value,
                      max_value=self.max_value,
                  )
              )
      elif self.min_value is not None:
          col_value = df[self.colname]
          if not (col_value >= self.min_value).all():
              raise ValueError(
                  "column '{colname}' must be >= {min_value}.".format(
                      colname=self.colname, min_value=self.min_value
                  )
              )
      else:
          pass
  
imports: import warnings
  import numpy
  import pandas
  from typing import Any, Hashable, List, Optional, Tuple, Type, Union
label_desc: Use image node_id 6 for calling the _Col obj's underlying member method code with example usage: obj.check_col_value(df) without return types