otp.agg.distinct#
- distinct(keys, key_attrs_only, running=False, bucket_interval=0, bucket_time='end', bucket_units=None, bucket_end_condition=None, boundary_tick_bucket='new', selection='first')#
Outputs all distinct values for a specified set of key fields.
- Parameters
keys (str or list) – Specifies a list of tick attributes for which unique values are found. The ticks in the input time series must contain those attributes.
key_attrs_only (bool) – If set to true, output ticks will contain only key fields. Otherwise, output ticks will contain all fields of an input tick in which a given distinct combination of key values was first encountered.
running (bool, default=False) –
Aggregation will be calculated as sliding window.
running
andbucket_interval
parameters determines when new buckets are created.running
= Trueaggregation will be calculated in a sliding window.
bucket_interval
= N (N > 0)Window size will be N. Output tick will be generated when tick “enter” window (arrival event) and when “exit” window (exit event)
bucket_interval
= 0Left boundary of window will be bound to start time. For each tick aggregation will be calculated in [start_time; tick_t].
running
= Falsebuckets partition the [query start time, query end time) interval into non-overlapping intervals of size
bucket_interval
(with the last interval possibly of a smaller size). Ifbucket_interval
is set to 0 a single bucket for the entire interval is created.Note that in non-running mode OneTick unconditionally divides the whole time interval into specified number of buckets. It means that you will always get this specified number of ticks in the result, even if you have less ticks in the input data.
Default: False
bucket_interval (int or
Operation
orOnetickParameter
orsymbol parameter
or datetime offset object, default=0) –Determines the length of each bucket (units depends on
bucket_units
).If
Operation
of bool type is passed, acts asbucket_end_condition
.Bucket interval can be set via datetime offset objects like
otp.Second
,otp.Minute
,otp.Hour
,otp.Day
,otp.Month
. In this case you could omit settingbucket_units
parameter.Bucket interval can also be set with integer
OnetickParameter
orsymbol parameter
.bucket_time (Literal['start', 'end'], default=end) –
Control output timestamp.
start
the timestamp assigned to the bucket is the start time of the bucket.
end
the timestamp assigned to the bucket is the end time of the bucket.
bucket_units (Optional[Literal['seconds', 'ticks', 'days', 'months', 'flexible']], default=None) –
Set bucket interval units.
By default, if
bucket_units
andbucket_end_condition
not specified, set to seconds. Ifbucket_end_condition
specified, thenbucket_units
set to flexible.If set to flexible then
bucket_end_condition
must be set.Note that seconds bucket unit doesn’t take into account daylight-saving time of the timezone, so you may not get expected results when using, for example, 24 * 60 * 60 seconds as bucket interval. In such case use days bucket unit instead. See example in
onetick.py.agg.sum()
.bucket_end_condition (condition, default=None) –
An expression that is evaluated on every tick. If it evaluates to “True”, then a new bucket is created. This parameter is only used if
bucket_units
is set to “flexible”.Also can be set via
bucket_interval
parameter by passingOperation
object.boundary_tick_bucket (Literal['new', 'previous'], default=new) –
Controls boundary tick ownership.
previous
A tick on which
bucket_end_condition
evaluates to “true” belongs to the bucket being closed.new
tick belongs to the new bucket.
This parameter is only used if
bucket_units
is set to “flexible”selection (Literal['first', 'last'], default=first) – Controls the selection of the respective beginning or trailing part of ticks.
Examples
>>> data = otp.Ticks(dict(x=[1, 3, 1, 5, 3])) >>> d = otp.agg.distinct('x') >>> data = d.apply(data) >>> otp.run(data) Time x 0 2003-12-04 1 1 2003-12-04 3 2 2003-12-04 5
See also
DISTINCT OneTick event processor