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enums

class atscale.base.enums.Aggs​

Holds constant string representations for the supported aggregation methods of numerical aggregate features
SUM: Addition
AVG: Average
MAX: Maximum
MIN: Mininum
DISTINCT_COUNT: Distinct-Count (count of unique values)
DISTINCT_COUNT_ESTIMATE: An estimate of the distinct count to save compute
NON_DISTINCT_COUNT: Count of all values
STDDEV_SAMP: standard deviation of the sample
STDDEV_POP: population standard deviation
VAR_SAMP: sample variance
VAR_POP: population variance

class atscale.base.enums.FeatureFormattingType​

How the value of a feature gets formatted before output

class atscale.base.enums.FeatureType​

Used for specifying all features or only numerics or only categorical

class atscale.base.enums.MDXAggs​

Holds constant string representations for the supported MDX aggregation methods
SUM: Addition
STANDARD_DEVIATION: standard deviation of the sample
MEAN: Average
MAX: Maximum
MIN: Mininum

class atscale.base.enums.MappedColumnDataTypes​

Used for specifying data type of mapped column

class atscale.base.enums.MappedColumnFieldTerminator​

Used for specifying mapped column field delimiters

class atscale.base.enums.MappedColumnKeyTerminator​

Used for specifying mapped column key delimiters

class atscale.base.enums.TableExistsAction​

Potential actions to take if a table already exists when trying to write a dataframe to that database table.
APPEND: Append content of the dataframe to existing data or table
OVERWRITE: Overwrite existing data with the content of dataframe
IGNORE: Ignore current write operation if data/ table already exists without any error. This is not valid for pandas dataframes
ERROR: Throw an exception if data or table already exists

class atscale.base.enums.TimeSteps​

Translates the time levels into usable step sizes.