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.