1.4.0

Home

Installation
How to use this guide
Getting started
Support

User Guide

Tutorials
getML suite
Managing projects
Importing data
Annotating data
Data model
Preprocessing
Feature engineering
Predicting
Hyperparameter optimization
Deployment

API Documentation

Python API
- data
- database
- datasets
- engine
- hyperopt
- feature_learning
  - FastProp
  - Multirel
  - Relboost
  - Fastboost
  - RelMT
  - aggregations
    - namedtuple
    - Avg
    - Count
    - CountDistinct
    - CountDistinctOverCount
    - CountMinusCountDistinct
    - EWMA_1s
    - EWMA_1m
    - EWMA_1h
    - EWMA_1d
    - EWMA_7d
    - EWMA_30d
    - EWMA_90d
    - EWMA_365d
    - EWMA_TREND_1s
    - EWMA_TREND_1m
    - EWMA_TREND_1h
    - EWMA_TREND_1d
    - EWMA_TREND_7d
    - EWMA_TREND_30d
    - EWMA_TREND_90d
    - EWMA_TREND_365d
    - First
    - Kurtosis
    - Last
    - Max
    - Median
    - Min
    - Mode
    - NumMax
    - NumMin
    - Q1
    - Q5
    - Q10
    - Q25
    - Q75
    - Q90
    - Q95
    - Q99
    - Skew
    - Stddev
    - Sum
    - TimeSinceFirstMaximum
    - TimeSinceFirstMinimum
    - TimeSinceLastMaximum
    - TimeSinceLastMinimum
    - Trend
    - Var
    - VariationCoefficient
    - fastprop
    - mapping
    - multirel
- project
- preprocessors
- pipeline
- predictors
- sqlite3
- DataFrame
- Pipeline
- set_project
Command line interface

Integration

Fast API

About

getML

Docs »
Python API »
getml.feature_learning »
aggregations »
CountDistinct

CountDistinct¶

getml.feature_learning.aggregations.CountDistinct = 'COUNT DISTINCT'¶: Count function with distinct clause. This only counts unique elements.

© Copyright The SQLNet Company GmbH

Term of Service | Privacy Policy | Imprint | About |