Sample rows from this table.
num_rows (int) – Number of rows to sample. If not given the model
will generate as many rows as there were in the
data passed to the fit method.
max_retries (int) – Number of times to retry sampling discarded rows.
Defaults to 100.
max_rows_multiplier (int) – Multiplier to use when computing the maximum number of rows
that can be sampled during the reject-sampling loop.
The maximum number of rows that are sampled at each iteration
will be equal to this number multiplied by the requested num_rows.
Defaults to 10.
conditions (pd.DataFrame, dict or pd.Series) – If this is a dictionary/Series which maps column names to the column
value, then this method generates num_rows samples, all of
which are conditioned on the given variables. If this is a DataFrame,
then it generates an output DataFrame such that each row in the output
is sampled conditional on the corresponding row in the input.
float_rtol (float) – Maximum tolerance when considering a float match. This is the maximum
relative distance at which a float value will be considered a match
when performing reject-sampling based conditioning. Defaults to 0.01.
graceful_reject_sampling (bool) – If False raises a ValueError if not enough valid rows could be sampled
within max_retries trials. If True prints a warning and returns
as many rows as it was able to sample within max_retries.
Defaults to False.
ConstraintsNotMetError – If the conditions are not valid for the given constraints.
ValueError – If any of the following happens:
* any of the conditions’ columns are not valid.
* graceful_reject_sampling is False and not enough valid rows could be
sampled within max_retries trials.
* no rows could be generated.