Package bigquery (1.7.0)

API documentation for bigquery package.

Packages Functions

array_agg

array_agg(
    obj: groupby.SeriesGroupBy | groupby.DataFrameGroupBy,
) -> series.Series | dataframe.DataFrame

Group data and create arrays from selected columns, omitting NULLs to avoid BigQuery errors (NULLs not allowed in arrays).

Examples:

>>> import bigframes.pandas as bpd
>>> import bigframes.bigquery as bbq
>>> import numpy as np
>>> bpd.options.display.progress_bar = None

For a SeriesGroupBy object:

>>> lst = ['a', 'a', 'b', 'b', 'a']
>>> s = bpd.Series([1, 2, 3, 4, np.nan], index=lst)
>>> bbq.array_agg(s.groupby(level=0))
a    [1. 2.]
b    [3. 4.]
dtype: list<item: double>[pyarrow]

For a DataFrameGroupBy object:

>>> l = [[1, 2, 3], [1, None, 4], [2, 1, 3], [1, 2, 2]]
>>> df = bpd.DataFrame(l, columns=["a", "b", "c"])
>>> bbq.array_agg(df.groupby(by=["b"]))
         a      c
b
1.0    [2]    [3]
2.0  [1 1]  [3 2]
<BLANKLINE>
[2 rows x 2 columns]

Parameter
Name	Description
`obj`	A GroupBy object to be applied the function.

array_length

array_length(series: series.Series) -> series.Series

Compute the length of each array element in the Series.

Examples:

>>> import bigframes.pandas as bpd
>>> import bigframes.bigquery as bbq
>>> bpd.options.display.progress_bar = None

>>> s = bpd.Series([[1, 2, 8, 3], [], [3, 4]])
>>> bbq.array_length(s)
0    4
1    0
2    2
dtype: Int64

You can also apply this function directly to Series.

>>> s.apply(bbq.array_length, by_row=False)
0    4
1    0
2    2
dtype: Int64

Parameter
Name	Description
`series`	A Series with array columns.