segment_extractor

segment_extractor

SegmentExtractor

SegmentExtractor(
    dataframe: DataFrame, column_name: str = "systime"
)

Bases: Base

Extract time ranges from a categorical signal that changes over time.

Given a signal UUID (e.g. order number or part number) whose value changes over time, detects transitions and produces one row per contiguous segment with its start time, end time, and active value.

Methods: - extract_time_ranges: Detect value changes and return time range segments.

extract_time_ranges classmethod

extract_time_ranges(
    dataframe: DataFrame,
    segment_uuid: str,
    uuid_column: str = "uuid",
    value_column: str = "value_string",
    time_column: str = "systime",
    min_duration: Optional[str] = None,
) -> pd.DataFrame

Detect value transitions and extract time ranges per segment.

Parameters:

Name	Type	Description	Default
dataframe	DataFrame	Input DataFrame in long format.	required
segment_uuid	str	The UUID of the categorical signal to segment by (e.g. 'order_number', 'part_number').	required
uuid_column	str	Column identifying each timeseries.	'uuid'
value_column	str	Column containing the categorical values. Use 'value_string' for string signals, 'value_integer' for integer signals, etc.	'value_string'
time_column	str	Column containing timestamps.	'systime'
min_duration	Optional[str]	Optional minimum segment duration (e.g. '10s', '1min'). Segments shorter than this are dropped.	None

Returns:

Type	Description
DataFrame	DataFrame with columns:
DataFrame	segment_value: The active value during this range.
DataFrame	segment_start: Start timestamp of the range.
DataFrame	segment_end: End timestamp of the range.
DataFrame	segment_duration: Duration as Timedelta.
DataFrame	segment_index: Sequential index of the segment.