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    Class SeriesGroupBy (1.5.0) 

      SeriesGroupBy 
 ( 
 block 
 : 
 bigframes 
 . 
 core 
 . 
 blocks 
 . 
 Block 
 , 
 value_column 
 : 
 str 
 , 
 by_col_ids 
 : 
 typing 
 . 
 Sequence 
 [ 
 str 
 ], 
 value_name 
 : 
 typing 
 . 
 Hashable 
 = 
 None 
 , 
 dropna 
 = 
 True 
 , 
 )

    Class for grouping and aggregating relational data.

    Methods

    agg

      agg 
 ( 
 func 
 = 
 None 
 , 
 ) 
 - 
> typing 
 . 
 Union 
 [ 
 bigframes 
 . 
 dataframe 
 . 
 DataFrame 
 , 
 bigframes 
 . 
 series 
 . 
 Series 
 ]

    Aggregate using one or more operations.

    aggregate

      aggregate 
 ( 
 func 
 = 
 None 
 , 
 ) 
 - 
> typing 
 . 
 Union 
 [ 
 bigframes 
 . 
 dataframe 
 . 
 DataFrame 
 , 
 bigframes 
 . 
 series 
 . 
 Series 
 ]

    API documentation for aggregate method.

    all

      all 
 () 
 - 
> bigframes 
 . 
 series 
 . 
 Series

    Return True if all values in the group are true, else False.

    Returns
    Type
    Description
    Series or DataFrame
    DataFrame or Series of boolean values, where a value is True if all elements are True within its respective group; otherwise False.

    any

      any 
 () 
 - 
> bigframes 
 . 
 series 
 . 
 Series

    Return True if any value in the group is true, else False.

    Returns
    Type
    Description
    Series or DataFrame
    DataFrame or Series of boolean values, where a value is True if any element is True within its respective group; otherwise False.

    count

      count 
 () 
 - 
> bigframes 
 . 
 series 
 . 
 Series

    Compute count of group, excluding missing values.

    Returns
    Type
    Description
    Series or DataFrame
    Count of values within each group.

    cumcount

      cumcount 
 ( 
 * 
 args 
 , 
 ** 
 kwargs 
 ) 
 - 
> bigframes 
 . 
 series 
 . 
 Series

    Number each item in each group from 0 to the length of that group - 1.

    Parameter
    Name
    Description
    ascending
    bool, default True

    If False, number in reverse, from length of group - 1 to 0.

    Returns
    Type
    Description
    Series
    Sequence number of each element within each group.

    cummax

      cummax 
 ( 
 * 
 args 
 , 
 ** 
 kwargs 
 ) 
 - 
> bigframes 
 . 
 series 
 . 
 Series

    Cumulative max for each group.

    Returns
    Type
    Description
    Series or DataFrame
    Cumulative max for each group.

    cummin

      cummin 
 ( 
 * 
 args 
 , 
 ** 
 kwargs 
 ) 
 - 
> bigframes 
 . 
 series 
 . 
 Series

    Cumulative min for each group.

    Returns
    Type
    Description
    Series or DataFrame
    Cumulative min for each group.

    cumprod

      cumprod 
 ( 
 * 
 args 
 , 
 ** 
 kwargs 
 ) 
 - 
> bigframes 
 . 
 series 
 . 
 Series

    Cumulative product for each group.

    Returns
    Type
    Description
    Series or DataFrame
    Cumulative product for each group.

    cumsum

      cumsum 
 ( 
 * 
 args 
 , 
 ** 
 kwargs 
 ) 
 - 
> bigframes 
 . 
 series 
 . 
 Series

    Cumulative sum for each group.

    Returns
    Type
    Description
    Series or DataFrame
    Cumulative sum for each group.

    diff

      diff 
 ( 
 periods 
 = 
 1 
 ) 
 - 
> bigframes 
 . 
 series 
 . 
 Series

    First discrete difference of element. Calculates the difference of each element compared with another element in the group (default is element in previous row).

    Returns
    Type
    Description
    Series or DataFrame
    First differences.

    expanding

      expanding 
 ( 
 min_periods 
 : 
 int 
 = 
 1 
 ) 
 - 
> bigframes 
 . 
 core 
 . 
 window 
 . 
 Window

    Provides expanding functionality.

    Returns
    Type
    Description
    Series or DataFrame
    An expanding grouper, providing expanding functionality per group.

    kurt

      kurt 
 ( 
 * 
 args 
 , 
 ** 
 kwargs 
 ) 
 - 
> bigframes 
 . 
 series 
 . 
 Series

    Return unbiased kurtosis over requested axis.

    Kurtosis obtained using Fisher's definition of kurtosis (kurtosis of normal == 0.0). Normalized by N-1.

    Parameter
    Name
    Description
    numeric_only
    bool, default False

    Include only float , int or boolean data.

    kurtosis

      kurtosis 
 ( 
 * 
 args 
 , 
 ** 
 kwargs 
 ) 
 - 
> bigframes 
 . 
 series 
 . 
 Series

    API documentation for kurtosis method.

    max

      max 
 ( 
 * 
 args 
 ) 
 - 
> bigframes 
 . 
 series 
 . 
 Series

    Compute max of group values.

    Parameters
    Name
    Description
    numeric_only
    bool, default False

    Include only float, int, boolean columns.

    min_count
    int, default 0

    The required number of valid values to perform the operation. If fewer than min_count and non-NA values are present, the result will be NA.

    Returns
    Type
    Description
    Series or DataFrame
    Computed max of values within each group.

    mean

      mean 
 ( 
 * 
 args 
 ) 
 - 
> bigframes 
 . 
 series 
 . 
 Series

    Compute mean of groups, excluding missing values.

    Parameter
    Name
    Description
    numeric_only
    bool, default False

    Include only float, int, boolean columns.

    Returns
    Type
    Description
    pandas.Series or pandas.DataFrame
    Mean of groups.

    median

      median 
 ( 
 * 
 args 
 , 
 exact 
 : 
 bool 
 = 
 True 
 , 
 ** 
 kwargs 
 ) 
 - 
> bigframes 
 . 
 series 
 . 
 Series

    Compute median of groups, excluding missing values.

    Parameters
    Name
    Description
    numeric_only
    bool, default False

    Include only float, int, boolean columns.

    exact
    bool, default True

    Calculate the exact median instead of an approximation.

    Returns
    Type
    Description
    pandas.Series or pandas.DataFrame
    Median of groups.

    min

      min 
 ( 
 * 
 args 
 ) 
 - 
> bigframes 
 . 
 series 
 . 
 Series

    Compute min of group values.

    Parameters
    Name
    Description
    numeric_only
    bool, default False

    Include only float, int, boolean columns.

    min_count
    int, default 0

    The required number of valid values to perform the operation. If fewer than min_count and non-NA values are present, the result will be NA.

    Returns
    Type
    Description
    Series or DataFrame
    Computed min of values within each group.

    nunique

      nunique 
 () 
 - 
> bigframes 
 . 
 series 
 . 
 Series

    Return number of unique elements in the group.

    Returns
    Type
    Description
    Series
    Number of unique values within each group.

    prod

      prod 
 ( 
 * 
 args 
 ) 
 - 
> bigframes 
 . 
 series 
 . 
 Series

    Compute prod of group values.

    Parameters
    Name
    Description
    numeric_only
    bool, default False

    Include only float, int, boolean columns.

    min_count
    int, default 0

    The required number of valid values to perform the operation. If fewer than min_count and non-NA values are present, the result will be NA.

    Returns
    Type
    Description
    Series or DataFrame
    Computed prod of values within each group.

    quantile

      quantile 
 ( 
 q 
 : 
 typing 
 . 
 Union 
 [ 
 float 
 , 
 typing 
 . 
 Sequence 
 [ 
 float 
 ]] 
 = 
 0.5 
 , 
 * 
 , 
 numeric_only 
 : 
 bool 
 = 
 False 
 ) 
 - 
> bigframes 
 . 
 series 
 . 
 Series

    Return group values at the given quantile, a la numpy.percentile.

    Examples:

     >>> import bigframes.pandas as bpd
>>> bpd.options.display.progress_bar = None
>>> df = bpd.DataFrame([
...     ['a', 1], ['a', 2], ['a', 3],
...     ['b', 1], ['b', 3], ['b', 5]
... ], columns=['key', 'val'])
>>> df.groupby('key').quantile()
     val
key
a    2.0
b    3.0
<BLANKLINE>
[2 rows x 1 columns]
    Parameters
    Name
    Description
    q
    float or array-like, default 0.5 (50% quantile)

    Value(s) between 0 and 1 providing the quantile(s) to compute.

    numeric_only
    bool, default False

    Include only float , int or boolean data.

    Returns
    Type
    Description
    Series or DataFrame
    Return type determined by caller of GroupBy object.

    rolling

      rolling 
 ( 
 window 
 : 
 int 
 , 
 min_periods 
 = 
 None 
 ) 
 - 
> bigframes 
 . 
 core 
 . 
 window 
 . 
 Window

    Returns a rolling grouper, providing rolling functionality per group.

    Parameter
    Name
    Description
    min_periods
    int, default None

    Minimum number of observations in window required to have a value; otherwise, result is np.nan . For a window that is specified by an offset, min_periods will default to 1. For a window that is specified by an integer, min_periods will default to the size of the window.

    Returns
    Type
    Description
    Series or DataFrame
    Return a new grouper with our rolling appended.

    shift

      shift 
 ( 
 periods 
 = 
 1 
 ) 
 - 
> bigframes 
 . 
 series 
 . 
 Series

    Shift index by desired number of periods.

    skew

      skew 
 ( 
 * 
 args 
 , 
 ** 
 kwargs 
 ) 
 - 
> bigframes 
 . 
 series 
 . 
 Series

    Return unbiased skew within groups.

    Normalized by N-1.

    Parameter
    Name
    Description
    numeric_only
    bool, default False

    Include only float , int or boolean data.

    std

      std 
 ( 
 * 
 args 
 , 
 ** 
 kwargs 
 ) 
 - 
> bigframes 
 . 
 series 
 . 
 Series

    Compute standard deviation of groups, excluding missing values.

    For multiple groupings, the result index will be a MultiIndex.

    Parameter
    Name
    Description
    numeric_only
    bool, default False

    Include only float , int or boolean data.

    Returns
    Type
    Description
    Series or DataFrame
    Standard deviation of values within each group.

    sum

      sum 
 ( 
 * 
 args 
 ) 
 - 
> bigframes 
 . 
 series 
 . 
 Series

    Compute sum of group values.

    Parameters
    Name
    Description
    numeric_only
    bool, default False

    Include only float, int, boolean columns.

    min_count
    int, default 0

    The required number of valid values to perform the operation. If fewer than min_count and non-NA values are present, the result will be NA.

    Returns
    Type
    Description
    Series or DataFrame
    Computed sum of values within each group.

    var

      var 
 ( 
 * 
 args 
 , 
 ** 
 kwargs 
 ) 
 - 
> bigframes 
 . 
 series 
 . 
 Series

    Compute variance of groups, excluding missing values.

    For multiple groupings, the result index will be a MultiIndex.

    Parameter
    Name
    Description
    numeric_only
    bool, default False

    Include only float , int or boolean data.
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