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BUG: handle none values in json.normalize() #53773

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BUG: handle none values in json.normalize() #53773

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2 changes: 2 additions & 0 deletions pandas/io/json/_normalize.py
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Original file line number Diff line number Diff line change
Expand Up @@ -490,6 +490,8 @@ def _pull_records(js: dict[str, Any], spec: list | str) -> list:
meta_keys = [sep.join(val) for val in _meta]

def _recursive_extract(data, path, seen_meta, level: int = 0) -> None:
if data is None:
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Isn't this generally an issue if data is not list like?

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While running the tests I noticed while passing scalar values must be done in a list as is the expected behavior. But if I have a row of data in my json and one of the field values is null then the normalize() fails by throwing an exception when I instead expect it to ignore the entire row, which this change should do.

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Could you add a test where a nested json value is a scalar like 2 as assert the result?

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Do you mean something like this as my expected value?

expected = DataFrame(
            {
                "nested_field_id": 1,
            }
        )

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hi all, what is the status on this one? Any idea when it could be merged? (original request: #53719)

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@mroeschke Hi. In regard to the previous comment by me, is that what is required in the tests?

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A test where the input has something like "nested_field": [{"nested_field_id": [1]}],

return
if isinstance(data, dict):
data = [data]
if len(path) > 1:
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23 changes: 23 additions & 0 deletions pandas/tests/io/json/test_normalize.py
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Expand Up @@ -582,6 +582,29 @@ def test_top_column_with_leading_underscore(self):

tm.assert_frame_equal(result, expected)

def test_column_with_none(self):
# 53719
data = {
"root": [
{
"id": 1,
"nested_field": [{"nested_field_id": 1}],
},
{"id": 2, "nested_field": None},
]
}
result = json_normalize(
data,
record_path=["root", "nested_field"],
)
expected = DataFrame(
{
"nested_field_id": [1],
}
)

tm.assert_frame_equal(result, expected)


class TestNestedToRecord:
def test_flat_stays_flat(self):
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