Conditional Sampling
Last updated
Last updated
Do you have exact context that you'd like to include in the synthetic sequences? Using conditional sampling to provide this information.
Do you already know all the context for each sequence? The SDV can factor in the context columns and generate sequences based on them.
Use this function to sample the sequences based on known context columns that do not change.
Parameters
(required) context_columns: A pandas DataFrame that contains the sequence key and all the context columns of your data that do not vary with respect to time. Each row corresponds to a sequence that you want to synthesize.
sequence_length: An integer >0 describing the length of each sequence. If you provide None, the synthesizer will determine the lengths algorithmically, and the length may be different for each sequence. Defaults to None.
Returns A pandas DataFrame object with synthetic data. The synthetic data is based on the referenced, context columns.