class_docstr: Pandas ExtensionArray to represent ragged arrays
  
  Methods not otherwise documented here are inherited from ExtensionArray;
  please see the corresponding method on that class for the docstring
class_docstr_tok: ["Pandas","ExtensionArray","to","represent","ragged","arrays","Methods","not","otherwise","documented","here","are","inherited","from","ExtensionArray",";","please","see","the","corresponding","method","on","that","class","for","the","docstring"]
code: def __getitem__(self, item):
      err_msg = (
          "Only integers, slices and integer or boolean"
          "arrays are valid indices."
      )
      if isinstance(item, Integral):
          if item < -len(self) or item >= len(self):
              raise IndexError(
                  "{item} is out of bounds".format(item=item)
              )
          else:
              # Convert negative item index
              if item < 0:
                  item += len(self)
  
              slice_start = self.start_indices[item]
              slice_end = (
                  self.start_indices[item + 1]
                  if item + 1 <= len(self) - 1
                  else len(self.flat_array)
              )
  
              return (
                  self.flat_array[slice_start:slice_end]
                  if slice_end != slice_start
                  else np.nan
              )
  
      elif type(item) == slice:
          data = []
          selected_indices = np.arange(len(self))[item]
  
          for selected_index in selected_indices:
              data.append(self[selected_index])
  
          return RaggedArray(data, dtype=self.flat_array.dtype)
  
      elif isinstance(item, (np.ndarray, ExtensionArray, list, tuple)):
          if isinstance(item, (np.ndarray, ExtensionArray)):
              # Leave numpy and pandas arrays alone
              kind = item.dtype.kind
          else:
              # Convert others to pandas arrays
              item = pd.array(item)
              kind = item.dtype.kind
  
          if len(item) == 0:
              return self.take([], allow_fill=False)
          elif kind == "b":
              # Check mask length is compatible
              if len(item) != len(self):
                  raise IndexError(
                      "Boolean index has wrong length: {} instead of {}".format(
                          len(item), len(self)
                      )
                  )
  
              # check for NA values
              isna = pd.isna(item)
              if isna.any():
                  if Version(pd.__version__) > Version("1.0.1"):
                      item[isna] = False
                  else:
                      raise ValueError(
                          "Cannot mask with a boolean indexer containing NA values"
                      )
  
              data = []
  
              for i, m in enumerate(item):
                  if m:
                      data.append(self[i])
  
              return RaggedArray(data, dtype=self.flat_array.dtype)
          elif kind in ("i", "u"):
              if any(pd.isna(item)):
                  raise ValueError(
                      "Cannot index with an integer indexer containing NA values"
                  )
              return self.take(item, allow_fill=False)
          else:
              raise IndexError(err_msg)
      else:
          raise IndexError(err_msg)
  
imports: from __future__ import annotations
  import re
  from functools import total_ordering
  from packaging.version import Version
  import numpy
  import pandas
  from numba import jit
  from pandas.api.extensions import ExtensionDtype, ExtensionArray, register_extension_dtype
  from numbers import Integral
  from pandas.api.types import pandas_dtype, is_extension_array_dtype
label_desc: Use image node_id 7 for calling the RaggedArray obj's underlying member method code with example usage: obj.__getitem__(item) and returns: unknown, RaggedArray, self, RaggedArray, self