aggregations¶
This module contains all possible aggregations to be used with
Multirel
,
FastProp
,
Mapping
.
Refer to the feature learning section in the user guide for details about how these aggregations are used in the context of feature learning.
Functions
|
Returns a new subclass of tuple with named fields. |
Attributes
Average value of a given numerical column. |
|
Number of rows in a given column. |
|
Counts the number of values strictly greater than the mean. |
|
Counts the number of values strictly smaller than the mean. |
|
Count function with distinct clause. |
|
COUNT DISTINCT divided by COUNT. |
|
Counts minus counts distinct. |
|
Exponentially weighted moving average with an half-life of 1 second. |
|
Exponentially weighted moving average with an half-life of 1 minute. |
|
Exponentially weighted moving average with an half-life of 1 hour. |
|
Exponentially weighted moving average with an half-life of 1 day. |
|
Exponentially weighted moving average with an half-life of 7 days. |
|
Exponentially weighted moving average with an half-life of 30 days. |
|
Exponentially weighted moving average with an half-life of 90 days. |
|
Exponentially weighted moving average with an half-life of 365 days. |
|
First value of a given column, when ordered by the time stamp. |
|
The kurtosis of a given column. |
|
Last value of a given column, when ordered by the time stamp. |
|
Largest value of a given column. |
|
Median of a given column |
|
Smallest value of a given column. |
|
Most frequent value of a given column. |
|
The number of times we observe the maximum value. |
|
The number of times we observe the minimum value. |
|
The 1%-quantile. |
|
The 5%-quantile. |
|
The 10%-quantile. |
|
The 25%-quantile. |
|
The 75%-quantile. |
|
The 90%-quantile. |
|
The 95%-quantile. |
|
The 99%-quantile. |
|
Skewness of a given column. |
|
Standard deviation of a given column. |
|
Total sum of a given numerical column. |
|
The time difference between the first time we see the maximum value and the time stamp in the population table. |
|
The time difference between the first time we see the minimum value and the time stamp in the population table. |
|
The time difference between the last time we see the maximum value and the time stamp in the population table. |
|
The time difference between the last time we see the minimum value and the time stamp in the population table. |
|
Extracts a linear trend from a variable over time and extrapolates this trend to the current time stamp. |
|
Statistical variance of a given numerical column. |
|
VAR divided by MEAN. |
|
Set of default aggregations for |
|
Set of default aggregations for |
|
Set of default aggregations for |