Overview: Series: Iterator

Detail: Series: Iterator

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Series.iter_element()

Iterator of elements.

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Series.iter_element().apply(func, *, dtype, name, index_constructor)

Apply a function to each value. Returns a new container. Args: func: A function…

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Series.iter_element().apply_iter(func)

Apply a function to each value. A generator of resulting values. Args: func: A f…

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Series.iter_element().apply_iter_items(func)

Apply a function to each value. A generator of resulting key, value pairs. Args:…

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Series.iter_element().apply_pool(func, *, dtype, name, index_constructor, max_workers, chunksize, use_threads)

Apply a function to each value. Employ parallel processing with either the Proce…

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Series.iter_element().map_all(mapping, *, dtype, name, index_constructor)

Apply a mapping; for values not in the mapping, an Exception is raised. Returns…

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Series.iter_element().map_all_iter(mapping)

Apply a mapping; for values not in the mapping, an Exception is raised. A genera…

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Series.iter_element().map_all_iter_items(mapping)

Apply a mapping; for values not in the mapping, an Exception is raised. A genera…

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Series.iter_element().map_any(mapping, *, dtype, name, index_constructor)

Apply a mapping; for values not in the mapping, the value is returned. Returns a…

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Series.iter_element().map_any_iter(mapping)

Apply a mapping; for values not in the mapping, the value is returned. A generat…

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Series.iter_element().map_any_iter_items(mapping)

Apply a mapping; for values not in the mapping, the value is returned. A generat…

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Series.iter_element().map_fill(mapping, *, fill_value, dtype, name, index_constructor)

Apply a mapping; for values not in the mapping, the fill_value is returned. Retu…

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Series.iter_element().map_fill_iter(mapping, *, fill_value)

Apply a mapping; for values not in the mapping, the fill_value is returned. A ge…

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Series.iter_element().map_fill_iter_items(mapping, *, fill_value)

Apply a mapping; for values not in the mapping, the fill_value is returned. A ge…

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Series.iter_element_items()

Iterator of label, element pairs.

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Series.iter_element_items().apply(func, *, dtype, name, index_constructor)

Apply a function to each value. Returns a new container. Args: func: A function…

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Series.iter_element_items().apply_iter(func)

Apply a function to each value. A generator of resulting values. Args: func: A f…

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Series.iter_element_items().apply_iter_items(func)

Apply a function to each value. A generator of resulting key, value pairs. Args:…

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Series.iter_element_items().apply_pool(func, *, dtype, name, index_constructor, max_workers, chunksize, use_threads)

Apply a function to each value. Employ parallel processing with either the Proce…

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Series.iter_element_items().map_all(mapping, *, dtype, name, index_constructor)

Apply a mapping; for values not in the mapping, an Exception is raised. Returns…

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Series.iter_element_items().map_all_iter(mapping)

Apply a mapping; for values not in the mapping, an Exception is raised. A genera…

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Series.iter_element_items().map_all_iter_items(mapping)

Apply a mapping; for values not in the mapping, an Exception is raised. A genera…

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Series.iter_element_items().map_any(mapping, *, dtype, name, index_constructor)

Apply a mapping; for values not in the mapping, the value is returned. Returns a…

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Series.iter_element_items().map_any_iter(mapping)

Apply a mapping; for values not in the mapping, the value is returned. A generat…

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Series.iter_element_items().map_any_iter_items(mapping)

Apply a mapping; for values not in the mapping, the value is returned. A generat…

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Series.iter_element_items().map_fill(mapping, *, fill_value, dtype, name, index_constructor)

Apply a mapping; for values not in the mapping, the fill_value is returned. Retu…

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Series.iter_element_items().map_fill_iter(mapping, *, fill_value)

Apply a mapping; for values not in the mapping, the fill_value is returned. A ge…

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Series.iter_element_items().map_fill_iter_items(mapping, *, fill_value)

Apply a mapping; for values not in the mapping, the fill_value is returned. A ge…

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Series.iter_group(*, axis)

Iterator of Series, where each Series matches unique values.

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Series.iter_group(*, axis).apply(func, *, dtype, name, index_constructor)

Apply a function to each value. Returns a new container. Args: func: A function…

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Series.iter_group(*, axis).apply_iter(func)

Apply a function to each value. A generator of resulting values. Args: func: A f…

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Series.iter_group(*, axis).apply_iter_items(func)

Apply a function to each value. A generator of resulting key, value pairs. Args:…

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Series.iter_group(*, axis).apply_pool(func, *, dtype, name, index_constructor, max_workers, chunksize, use_threads)

Apply a function to each value. Employ parallel processing with either the Proce…

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Series.iter_group_array(*, axis)

Iterator of Series, where each Series matches unique values.

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Series.iter_group_array(*, axis).apply(func, *, dtype, name, index_constructor)

Apply a function to each value. Returns a new container. Args: func: A function…

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Series.iter_group_array(*, axis).apply_iter(func)

Apply a function to each value. A generator of resulting values. Args: func: A f…

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Series.iter_group_array(*, axis).apply_iter_items(func)

Apply a function to each value. A generator of resulting key, value pairs. Args:…

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Series.iter_group_array(*, axis).apply_pool(func, *, dtype, name, index_constructor, max_workers, chunksize, use_threads)

Apply a function to each value. Employ parallel processing with either the Proce…

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Series.iter_group_array_items(*, axis)

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Series.iter_group_array_items(*, axis).apply(func, *, dtype, name, index_constructor)

Apply a function to each value. Returns a new container. Args: func: A function…

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Series.iter_group_array_items(*, axis).apply_iter(func)

Apply a function to each value. A generator of resulting values. Args: func: A f…

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Series.iter_group_array_items(*, axis).apply_iter_items(func)

Apply a function to each value. A generator of resulting key, value pairs. Args:…

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Series.iter_group_array_items(*, axis).apply_pool(func, *, dtype, name, index_constructor, max_workers, chunksize, use_threads)

Apply a function to each value. Employ parallel processing with either the Proce…

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Series.iter_group_items(*, axis)

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Series.iter_group_items(*, axis).apply(func, *, dtype, name, index_constructor)

Apply a function to each value. Returns a new container. Args: func: A function…

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Series.iter_group_items(*, axis).apply_iter(func)

Apply a function to each value. A generator of resulting values. Args: func: A f…

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Series.iter_group_items(*, axis).apply_iter_items(func)

Apply a function to each value. A generator of resulting key, value pairs. Args:…

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Series.iter_group_items(*, axis).apply_pool(func, *, dtype, name, index_constructor, max_workers, chunksize, use_threads)

Apply a function to each value. Employ parallel processing with either the Proce…

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Series.iter_group_labels(depth_level)

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Series.iter_group_labels(depth_level).apply(func, *, dtype, name, index_constructor)

Apply a function to each value. Returns a new container. Args: func: A function…

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Series.iter_group_labels(depth_level).apply_iter(func)

Apply a function to each value. A generator of resulting values. Args: func: A f…

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Series.iter_group_labels(depth_level).apply_iter_items(func)

Apply a function to each value. A generator of resulting key, value pairs. Args:…

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Series.iter_group_labels(depth_level).apply_pool(func, *, dtype, name, index_constructor, max_workers, chunksize, use_threads)

Apply a function to each value. Employ parallel processing with either the Proce…

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Series.iter_group_labels_array(depth_level)

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Series.iter_group_labels_array(depth_level).apply(func, *, dtype, name, index_constructor)

Apply a function to each value. Returns a new container. Args: func: A function…

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Series.iter_group_labels_array(depth_level).apply_iter(func)

Apply a function to each value. A generator of resulting values. Args: func: A f…

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Series.iter_group_labels_array(depth_level).apply_iter_items(func)

Apply a function to each value. A generator of resulting key, value pairs. Args:…

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Series.iter_group_labels_array(depth_level).apply_pool(func, *, dtype, name, index_constructor, max_workers, chunksize, use_threads)

Apply a function to each value. Employ parallel processing with either the Proce…

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Series.iter_group_labels_array_items(depth_level)

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Series.iter_group_labels_array_items(depth_level).apply(func, *, dtype, name, index_constructor)

Apply a function to each value. Returns a new container. Args: func: A function…

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Series.iter_group_labels_array_items(depth_level).apply_iter(func)

Apply a function to each value. A generator of resulting values. Args: func: A f…

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Series.iter_group_labels_array_items(depth_level).apply_iter_items(func)

Apply a function to each value. A generator of resulting key, value pairs. Args:…

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Series.iter_group_labels_array_items(depth_level).apply_pool(func, *, dtype, name, index_constructor, max_workers, chunksize, use_threads)

Apply a function to each value. Employ parallel processing with either the Proce…

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Series.iter_group_labels_items(depth_level)

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Series.iter_group_labels_items(depth_level).apply(func, *, dtype, name, index_constructor)

Apply a function to each value. Returns a new container. Args: func: A function…

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Series.iter_group_labels_items(depth_level).apply_iter(func)

Apply a function to each value. A generator of resulting values. Args: func: A f…

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Series.iter_group_labels_items(depth_level).apply_iter_items(func)

Apply a function to each value. A generator of resulting key, value pairs. Args:…

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Series.iter_group_labels_items(depth_level).apply_pool(func, *, dtype, name, index_constructor, max_workers, chunksize, use_threads)

Apply a function to each value. Employ parallel processing with either the Proce…

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Series.iter_group_other(other, *, fill_value, axis)

Iterator of Series, grouped by unique values found in the passed container.

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Series.iter_group_other(other, *, fill_value, axis).apply(func, *, dtype, name, index_constructor)

Apply a function to each value. Returns a new container. Args: func: A function…

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Series.iter_group_other(other, *, fill_value, axis).apply_iter(func)

Apply a function to each value. A generator of resulting values. Args: func: A f…

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Series.iter_group_other(other, *, fill_value, axis).apply_iter_items(func)

Apply a function to each value. A generator of resulting key, value pairs. Args:…

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Series.iter_group_other(other, *, fill_value, axis).apply_pool(func, *, dtype, name, index_constructor, max_workers, chunksize, use_threads)

Apply a function to each value. Employ parallel processing with either the Proce…

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Series.iter_group_other_array(other, *, fill_value, axis)

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Series.iter_group_other_array(other, *, fill_value, axis).apply(func, *, dtype, name, index_constructor)

Apply a function to each value. Returns a new container. Args: func: A function…

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Series.iter_group_other_array(other, *, fill_value, axis).apply_iter(func)

Apply a function to each value. A generator of resulting values. Args: func: A f…

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Series.iter_group_other_array(other, *, fill_value, axis).apply_iter_items(func)

Apply a function to each value. A generator of resulting key, value pairs. Args:…

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Series.iter_group_other_array(other, *, fill_value, axis).apply_pool(func, *, dtype, name, index_constructor, max_workers, chunksize, use_threads)

Apply a function to each value. Employ parallel processing with either the Proce…

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Series.iter_group_other_array_items(other, *, fill_value, axis)

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Series.iter_group_other_array_items(other, *, fill_value, axis).apply(func, *, dtype, name, index_constructor)

Apply a function to each value. Returns a new container. Args: func: A function…

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Series.iter_group_other_array_items(other, *, fill_value, axis).apply_iter(func)

Apply a function to each value. A generator of resulting values. Args: func: A f…

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Series.iter_group_other_array_items(other, *, fill_value, axis).apply_iter_items(func)

Apply a function to each value. A generator of resulting key, value pairs. Args:…

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Series.iter_group_other_array_items(other, *, fill_value, axis).apply_pool(func, *, dtype, name, index_constructor, max_workers, chunksize, use_threads)

Apply a function to each value. Employ parallel processing with either the Proce…

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Series.iter_group_other_items(other, *, fill_value, axis)

Iterator of pairs of label, Series, grouped by unique values found in the passed…

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Series.iter_group_other_items(other, *, fill_value, axis).apply(func, *, dtype, name, index_constructor)

Apply a function to each value. Returns a new container. Args: func: A function…

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Series.iter_group_other_items(other, *, fill_value, axis).apply_iter(func)

Apply a function to each value. A generator of resulting values. Args: func: A f…

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Series.iter_group_other_items(other, *, fill_value, axis).apply_iter_items(func)

Apply a function to each value. A generator of resulting key, value pairs. Args:…

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Series.iter_group_other_items(other, *, fill_value, axis).apply_pool(func, *, dtype, name, index_constructor, max_workers, chunksize, use_threads)

Apply a function to each value. Employ parallel processing with either the Proce…

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Series.iter_window(*, size, axis, step, window_sized, window_func, window_valid, label_shift, start_shift, size_increment)

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Series.iter_window(*, size, axis, step, window_sized, window_func, window_valid, label_shift, start_shift, size_increment).apply(func, *, dtype, name, index_constructor)

Apply a function to each value. Returns a new container. Args: func: A function…

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Series.iter_window(*, size, axis, step, window_sized, window_func, window_valid, label_shift, start_shift, size_increment).apply_iter(func)

Apply a function to each value. A generator of resulting values. Args: func: A f…

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Series.iter_window(*, size, axis, step, window_sized, window_func, window_valid, label_shift, start_shift, size_increment).apply_iter_items(func)

Apply a function to each value. A generator of resulting key, value pairs. Args:…

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Series.iter_window(*, size, axis, step, window_sized, window_func, window_valid, label_shift, start_shift, size_increment).apply_pool(func, *, dtype, name, index_constructor, max_workers, chunksize, use_threads)

Apply a function to each value. Employ parallel processing with either the Proce…

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Series.iter_window_array(*, size, axis, step, window_sized, window_func, window_valid, label_shift, start_shift, size_increment)

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Series.iter_window_array(*, size, axis, step, window_sized, window_func, window_valid, label_shift, start_shift, size_increment).apply(func, *, dtype, name, index_constructor)

Apply a function to each value. Returns a new container. Args: func: A function…

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Series.iter_window_array(*, size, axis, step, window_sized, window_func, window_valid, label_shift, start_shift, size_increment).apply_iter(func)

Apply a function to each value. A generator of resulting values. Args: func: A f…

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Series.iter_window_array(*, size, axis, step, window_sized, window_func, window_valid, label_shift, start_shift, size_increment).apply_iter_items(func)

Apply a function to each value. A generator of resulting key, value pairs. Args:…

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Series.iter_window_array(*, size, axis, step, window_sized, window_func, window_valid, label_shift, start_shift, size_increment).apply_pool(func, *, dtype, name, index_constructor, max_workers, chunksize, use_threads)

Apply a function to each value. Employ parallel processing with either the Proce…

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Series.iter_window_array_items(*, size, axis, step, window_sized, window_func, window_valid, label_shift, start_shift, size_increment)

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Series.iter_window_array_items(*, size, axis, step, window_sized, window_func, window_valid, label_shift, start_shift, size_increment).apply(func, *, dtype, name, index_constructor)

Apply a function to each value. Returns a new container. Args: func: A function…

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Series.iter_window_array_items(*, size, axis, step, window_sized, window_func, window_valid, label_shift, start_shift, size_increment).apply_iter(func)

Apply a function to each value. A generator of resulting values. Args: func: A f…

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Series.iter_window_array_items(*, size, axis, step, window_sized, window_func, window_valid, label_shift, start_shift, size_increment).apply_iter_items(func)

Apply a function to each value. A generator of resulting key, value pairs. Args:…

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Series.iter_window_array_items(*, size, axis, step, window_sized, window_func, window_valid, label_shift, start_shift, size_increment).apply_pool(func, *, dtype, name, index_constructor, max_workers, chunksize, use_threads)

Apply a function to each value. Employ parallel processing with either the Proce…

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Series.iter_window_items(*, size, axis, step, window_sized, window_func, window_valid, label_shift, start_shift, size_increment)

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Series.iter_window_items(*, size, axis, step, window_sized, window_func, window_valid, label_shift, start_shift, size_increment).apply(func, *, dtype, name, index_constructor)

Apply a function to each value. Returns a new container. Args: func: A function…

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Series.iter_window_items(*, size, axis, step, window_sized, window_func, window_valid, label_shift, start_shift, size_increment).apply_iter(func)

Apply a function to each value. A generator of resulting values. Args: func: A f…

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Series.iter_window_items(*, size, axis, step, window_sized, window_func, window_valid, label_shift, start_shift, size_increment).apply_iter_items(func)

Apply a function to each value. A generator of resulting key, value pairs. Args:…

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Series.iter_window_items(*, size, axis, step, window_sized, window_func, window_valid, label_shift, start_shift, size_increment).apply_pool(func, *, dtype, name, index_constructor, max_workers, chunksize, use_threads)

Apply a function to each value. Employ parallel processing with either the Proce…

Series: Constructor | Exporter | Attribute | Method | Dictionary-Like | Display | Assignment | Selector | Iterator | Operator Binary | Operator Unary | Accessor Values | Accessor Datetime | Accessor String | Accessor Fill Value | Accessor Regular Expression | Accessor Hashlib