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BUG: Fixed encoding of pd.NA with to_json #31748

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Merged
merged 4 commits into from
Feb 8, 2020
Merged

BUG: Fixed encoding of pd.NA with to_json #31748

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715118e
BUG: Fixed encoding of pd.NA with to_json GH31615
ArtificialQualia Feb 6, 2020
c472a3a
DOC/TST: Update tests and docs for np.NA fix
ArtificialQualia Feb 6, 2020
cda6f07
DOC/TST: Fixes for PR
ArtificialQualia Feb 7, 2020
2f3853e
TST: remove label tests
ArtificialQualia Feb 7, 2020
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5 changes: 3 additions & 2 deletions doc/source/whatsnew/v1.0.2.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -25,8 +25,9 @@ Fixed regressions
Bug fixes
~~~~~~~~~

-
-
**I/O**
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Thanks @ArtificialQualia

This should be

I/O
^^^

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@MarcoGorelli I've updated that to the correct format.

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The original was actually fine, to be consistent with the v1.0.1 file

(sorry for the conflicting comments)

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My mistake, sorry, I'd taken that from v1.1.0 where we go back to

I/O
^^^

, will be more careful in the future

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@MarcoGorelli no problem! It's also inconsistent between the different files .. (for the bug fix releases, the list of bugs is much smaller, so less worth it to make subsections. At least, that is what we just did for the v1.0.1 file)

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Reverted to original format


- Using ``pd.NA`` with :meth:`DataFrame.to_json` now correctly outputs a null value instead of an empty object (:issue:`31615`)

.. ---------------------------------------------------------------------------

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12 changes: 12 additions & 0 deletions pandas/_libs/src/ujson/python/objToJSON.c
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Expand Up @@ -53,6 +53,7 @@ static PyTypeObject *cls_dataframe;
static PyTypeObject *cls_series;
static PyTypeObject *cls_index;
static PyTypeObject *cls_nat;
static PyTypeObject *cls_na;
PyObject *cls_timedelta;

npy_int64 get_nat(void) { return NPY_MIN_INT64; }
Expand Down Expand Up @@ -149,6 +150,7 @@ int PdBlock_iterNext(JSOBJ, JSONTypeContext *);
void *initObjToJSON(void) {
PyObject *mod_pandas;
PyObject *mod_nattype;
PyObject *mod_natype;
PyObject *mod_decimal = PyImport_ImportModule("decimal");
type_decimal =
(PyTypeObject *)PyObject_GetAttrString(mod_decimal, "Decimal");
Expand All @@ -174,6 +176,12 @@ void *initObjToJSON(void) {
Py_DECREF(mod_nattype);
}

mod_natype = PyImport_ImportModule("pandas._libs.missing");
if (mod_natype) {
cls_na = (PyTypeObject *)PyObject_GetAttrString(mod_natype, "NAType");
Py_DECREF(mod_natype);
}

/* Initialise numpy API */
import_array();
// GH 31463
Expand Down Expand Up @@ -1789,6 +1797,10 @@ void Object_beginTypeContext(JSOBJ _obj, JSONTypeContext *tc) {
"%R (0d array) is not JSON serializable at the moment",
obj);
goto INVALID;
} else if (PyObject_TypeCheck(obj, cls_na)) {
PRINTMARK();
tc->type = JT_NULL;
return;
}

ISITERABLE:
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8 changes: 8 additions & 0 deletions pandas/tests/io/json/test_pandas.py
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Expand Up @@ -1671,3 +1671,11 @@ def test_to_s3(self, s3_resource):
assert target_file in (
obj.key for obj in s3_resource.Bucket("pandas-test").objects.all()
)

@pytest.mark.parametrize(
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I think the comment around parametrization got lost in GH comments but in any case would rather parametrize on nulls_fixture + pd.NA if we don't think we can add pd.NA to the former for now

I don't think the current parametrization is super useful, so OK to just take the first case and put it in the body of the test

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parametrize on nulls_fixture + pd.NA

+1

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Couldn't find a way to add pd.NA to a pytest fixture without recreating the contents of the fixture entirely, so I've added them as separate tests. Let me know if you were thinking of something else.

Note that pd.NaT is the only object that doesn't use its string representation when encoded from a label.

"dataframe,expected", [(pd.DataFrame([[pd.NA]]), '{"0":{"0":null}}',)],
)
def test_json_pandas_na(self, dataframe, expected):
# GH 31615
result = dataframe.to_json()
assert result == expected