bigframes.bigquery.json_value_array

bigframes.bigquery.json_value_array(input: Series, json_path: str = '$') → Series

Extracts a JSON array of scalar values and converts it to a SQL ARRAY<STRING> value. In addition, this function:

• Removes the outermost quotes and unescapes the values.

• Returns a SQL NULL if the selected value isn’t an array or not an array containing only scalar values.

• Uses double quotes to escape invalid JSON_PATH characters in JSON keys.

Examples:

>>> import bigframes.pandas as bpd
>>> import bigframes.bigquery as bbq

>>> s = bpd.Series(['[1, 2, 3]', '[4, 5]'])
>>> bbq.json_value_array(s)
0    ['1' '2' '3']
1        ['4' '5']
dtype: list<item: string>[pyarrow]

>>> s = bpd.Series([
...   '{"fruits": ["apples", "oranges", "grapes"]',
...   '{"fruits": ["guava", "grapes"]}'
... ])
>>> bbq.json_value_array(s, "$.fruits")
0    ['apples' 'oranges' 'grapes']
1               ['guava' 'grapes']
dtype: list<item: string>[pyarrow]

>>> s = bpd.Series([
...   '{"fruits": {"color": "red",   "names": ["apple","cherry"]}}',
...   '{"fruits": {"color": "green", "names": ["guava", "grapes"]}}'
... ])
>>> bbq.json_value_array(s, "$.fruits.names")
0    ['apple' 'cherry']
1    ['guava' 'grapes']
dtype: list<item: string>[pyarrow]

Parameters:

• input (bigframes.series.Series) – The Series containing JSON data (as native JSON objects or JSON-formatted strings).

• json_path (str) – The JSON path identifying the data that you want to obtain from the input.

Returns:

A new Series with the parsed arrays from the input.

Return type:

bigframes.series.Series