`client.context.item`

trendminer_interface._client.context.item.ContextItemFacade

Facade for managing context items in TrendMiner

Context items are always represented as a pandas DataFrame, where each row corresponds to a context item.

create(items: DataFrame) -> None

Create new context items from a valid DataFrame.

Parameters:

Name	Type	Description	Default
`items`	`DataFrame`	Input DataFrame with a pandas.IntervalIndex and the following structure: Index: The index will be a pandas.IntervalIndex, with `index.left` and `index.right` the timestamps of the context item start and end events, respectively. Required columns: - type (ContextType): context type of each item - component (Tag or Asset or Attribute): component to which the item will be attached Optional columns: - open (bool): whether the context item is open-ended (no end state). Default behavior is closed. - keywords (list[str]): the keywords to attach to the context item - description (str): the context item description Event columns: Additional pandas.Timestamp values will be considered additional states (events) with the column name as the state name. Field columns: Any remaining numeric or string values will be considered context fields with the column name as the key. The following metadata columns will be ignored: key, identifier, identifier_external, created_by, created_at, last_modified.	required

Returns:

Type	Description
`None`	No output is returned. To load the created context items (with their metadata such as identifiers), use `get_items` on a `ContextHubViewDefinition` with appropriate filters.

Notes

If a DataFrame of existing context items is passed, copies of these context items will be created.

update(items: DataFrame) -> None

Update existing context items to a new state

Parameters:

Name	Type	Description	Default
`items`	`DataFrame`	Input DataFrame with a pandas.IntervalIndex and the following structure: Index: The index will be a pandas.IntervalIndex, with `index.left` and `index.right` the timestamps of the context item start and end events, respectively. Required columns: - identifier (str): identifier of the existing context item - type (ContextType): context type of each item - component (Tag or Asset or Attribute): component to which the item will be attached Optional columns: - open (bool): whether the context item is open-ended (no end state). Default behavior is closed. - keywords (list[str]): the keywords to attach to the context item - description (str): the context item description Event columns: Additional pandas.Timestamp values will be considered additional states (events) with the column name as the state name. Field columns: Any remaining numeric or string values will be considered context fields with the column name as the key. The following metadata columns will be ignored: key, identifier_external, created_by, created_at, last_modified.	required

Returns:

Type	Description
`None`

delete(items: DataFrame) -> None

Permanently delete all context items in the DataFrame