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