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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
+25 −2
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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10 changes: 10 additions & 0 deletions pandas/tests/io/json/test_pandas.py
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Expand Up @@ -1671,3 +1671,13 @@ def test_to_s3(self, s3_resource):
assert target_file in (
obj.key for obj in s3_resource.Bucket("pandas-test").objects.all()
)

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

def test_json_pandas_nulls(self, nulls_fixture):
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@simonjayhawkins do you know of an easy way to add pd.NA to nulls_fixture inline during injection? Or would adding another fixture on top be the only way?

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since we already have two nulls_fixtures (nulls_fixture and unique_nulls_fixture), I think adding another could be the simplest way for now.

I think, in general, simpler to skip than to add a extra parameter (although I've not kept up with the latest pytest releases).

There is not a huge number of tests using the nulls_fixture and maybe tests that do should also test for pandas.NA, either now of in the future. So an alternative could be to add pd.NA to the existing nulls fixture and either skip of xfail.

# GH 31615
result = pd.DataFrame([[nulls_fixture]]).to_json()
assert result == '{"0":{"0":null}}'