bigframes.pandas.api.typing.SeriesGroupBy

class bigframes.pandas.api.typing.SeriesGroupBy(block: Block, value_column: str, by_col_ids: Sequence[str], value_name: Hashable = None, dropna=True, *, by_key_is_singular: bool = False)

Class for grouping and aggregating relational data.

Methods

__init__(block, value_column, by_col_ids[, ...])
agg([func])	Aggregate using one or more operations.
aggregate([func])	Aggregate using one or more operations.
all()	Return True if all values in the group are true, else False.
any()	Return True if any value in the group is true, else False.
count()	Compute count of group, excluding missing values.
cumcount(*args, **kwargs)	Number each item in each group from 0 to the length of that group - 1.
cummax(*args, **kwargs)	Cumulative max for each group.
cummin(*args, **kwargs)	Cumulative min for each group.
cumprod(*args, **kwargs)	Cumulative product for each group.
cumsum(*args, **kwargs)	Cumulative sum for each group.
describe([include])	Generate descriptive statistics.
diff([periods])	First discrete difference of element.
expanding([min_periods])	Provides expanding functionality.
first([numeric_only, min_count])	Compute the first entry of each column within each group.
head([n])	Return last first n rows of each group
kurt(*args, **kwargs)	Return unbiased kurtosis over requested axis.
kurtosis(*args, **kwargs)	Return unbiased kurtosis over requested axis.
last([numeric_only, min_count])	Compute the last entry of each column within each group.
max(*args)	Compute max of group values.
mean(*args)	Compute mean of groups, excluding missing values.
median(*args[, exact])	Compute median of groups, excluding missing values.
min(*args)	Compute min of group values.
nunique()	Return number of unique elements in the group.
prod(*args)	Compute prod of group values.
quantile([q, numeric_only])	Return group values at the given quantile, a la numpy.percentile.
rank([method, ascending, na_option, pct])	Provide the rank of values within each group.
rolling(window[, min_periods, closed])	Returns a rolling grouper, providing rolling functionality per group.
shift([periods])	Shift index by desired number of periods.
size()	Compute group sizes.
skew(*args, **kwargs)	Return unbiased skew within groups.
std(*args, **kwargs)	Compute standard deviation of groups, excluding missing values.
sum(*args)	Compute sum of group values.
value_counts([normalize, sort, ascending, ...])	Return a Series or DataFrame containing counts of unique rows.
var(*args, **kwargs)	Compute variance of groups, excluding missing values.