class_docstr: The class for binary operations of pandas-on-Spark objects with spark type: BooleanType.
class_docstr_tok: ["The","class","for","binary","operations","of","pandas-on-Spark","objects","with","spark","type",":","BooleanType","."]
code: def __and__(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
      _sanitize_list_like(right)
      if isinstance(right, IndexOpsMixin) and isinstance(
          right.dtype, extension_dtypes
      ):
          return right.__and__(left)
      else:
  
          def and_func(
              left: PySparkColumn, right: Any
          ) -> PySparkColumn:
              try:
                  is_null = pd.isna(right)
              except PySparkValueError:
                  # Complaining `PySparkValueError` means that `right` is a Column.
                  is_null = False
  
              right = F.lit(None) if is_null else F.lit(right)
              scol = left & right
              return F.when(scol.isNull(), False).otherwise(scol)
  
          return column_op(and_func)(left, right)
  
imports: import numbers
  from typing import Any, Union
  import pandas
  from pandas.api.types import CategoricalDtype
  from pyspark.pandas.base import column_op, IndexOpsMixin
  from pyspark.pandas._typing import Dtype, IndexOpsLike, SeriesOrIndex
  from pyspark.pandas.data_type_ops.base import DataTypeOps, is_valid_operand_for_numeric_arithmetic, transform_boolean_operand_to_numeric, _as_bool_type, _as_categorical_type, _as_other_type, _sanitize_list_like, _is_valid_for_logical_operator, _is_boolean_type
  from pyspark.pandas.typedef.typehints import as_spark_type, extension_dtypes, pandas_on_spark_type
  from pyspark.sql import functions
  from pyspark.sql.column import Column
  from pyspark.sql.types import BooleanType, StringType
  from pyspark.sql.utils import get_column_class
  from pyspark.errors import PySparkValueError
label_desc: Use image node_id 16 for calling the BooleanOps obj's underlying member method code with example usage: obj.__and__(left, right) and returns: right, column_op, F