class_docstr: List methods for Series
class_docstr_tok: ["List","methods","for","Series"]
docstr: For a column with at least one level of nesting, concatenate the
  lists in each row.
  
  Parameters
  ----------
  dropna: bool, optional
      If True (default), ignores top-level null elements in each row.
      If False, and top-level null elements are present, the resulting
      row in the output is null.
  
  Returns
  -------
  Series or Index
  
  Examples
  --------
  >>> s1
  0      [[1.0, 2.0], [3.0, 4.0, 5.0]]
  1    [[6.0, None], [7.0], [8.0, 9.0]]
  dtype: list
  >>> s1.list.concat()
  0    [1.0, 2.0, 3.0, 4.0, 5.0]
  1    [6.0, None, 7.0, 8.0, 9.0]
  dtype: list
  
  Null values at the top-level in each row are dropped by default:
  
  >>> s2
  0    [[1.0, 2.0], None, [3.0, 4.0, 5.0]]
  1        [[6.0, None], [7.0], [8.0, 9.0]]
  dtype: list
  >>> s2.list.concat()
  0    [1.0, 2.0, 3.0, 4.0, 5.0]
  1    [6.0, None, 7.0, 8.0, 9.0]
  dtype: list
  
  Use ``dropna=False`` to produce a null instead:
  
  >>> s2.list.concat(dropna=False)
  0                         None
  1    [6.0, nan, 7.0, 8.0, 9.0]
  dtype: list
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code: def concat(self, dropna=True) -> ParentType:
      """
      For a column with at least one level of nesting, concatenate the
      lists in each row.
  
      Parameters
      ----------
      dropna: bool, optional
          If True (default), ignores top-level null elements in each row.
          If False, and top-level null elements are present, the resulting
          row in the output is null.
  
      Returns
      -------
      Series or Index
  
      Examples
      --------
      >>> s1
      0      [[1.0, 2.0], [3.0, 4.0, 5.0]]
      1    [[6.0, None], [7.0], [8.0, 9.0]]
      dtype: list
      >>> s1.list.concat()
      0    [1.0, 2.0, 3.0, 4.0, 5.0]
      1    [6.0, None, 7.0, 8.0, 9.0]
      dtype: list
  
      Null values at the top-level in each row are dropped by default:
  
      >>> s2
      0    [[1.0, 2.0], None, [3.0, 4.0, 5.0]]
      1        [[6.0, None], [7.0], [8.0, 9.0]]
      dtype: list
      >>> s2.list.concat()
      0    [1.0, 2.0, 3.0, 4.0, 5.0]
      1    [6.0, None, 7.0, 8.0, 9.0]
      dtype: list
  
      Use ``dropna=False`` to produce a null instead:
  
      >>> s2.list.concat(dropna=False)
      0                         None
      1    [6.0, nan, 7.0, 8.0, 9.0]
      dtype: list
      """
      return self._return_or_inplace(
          concatenate_list_elements(self._column, dropna=dropna)
      )
  
imports: from __future__ import annotations
  from functools import cached_property
  from typing import List, Optional, Sequence, Tuple, Union
  import numpy
  import pyarrow
  from typing_extensions import Self
  import cudf
  from cudf._lib.copying import segmented_gather
  from cudf._lib.lists import concatenate_list_elements, concatenate_rows, contains_scalar, count_elements, distinct, extract_element_column, extract_element_scalar, index_of_column, index_of_scalar, sort_lists
  from cudf._lib.strings.convert.convert_lists import format_list_column
  from cudf._lib.types import size_type_dtype
  from cudf._typing import ColumnBinaryOperand, ColumnLike, Dtype, ScalarLike
  from cudf.api.types import _is_non_decimal_numeric_dtype, is_scalar
  from cudf.core.column import ColumnBase, as_column, column
  from cudf.core.column.methods import ColumnMethods, ParentType
  from cudf.core.dtypes import ListDtype
  from cudf.core.missing import NA
label_desc: Use image node_id 10 for calling the ListMethods obj's underlying member method code with example usage: obj.concat(dropna) and returns: self