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Fix #21356: JSON nested_to_record Silently Drops Top-Level None Values #21363

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Merged
merged 13 commits into from
Jun 8, 2018
Merged

Fix #21356: JSON nested_to_record Silently Drops Top-Level None Values #21363

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2dbf9f2
Fix #21356: JSON nested_to_record Silently Drops Top-Level None Values
daminisatya Jun 7, 2018
2ac19b5
Added bugfix #21356 to whatsnew doc under 0.24v
daminisatya Jun 7, 2018
0de0cd4
changes requested
daminisatya Jun 8, 2018
832cc56
DOC: move whatsnew file for #21116 (index droplevel) (#21367)
jorisvandenbossche Jun 7, 2018
a1858c2
DOC: clean-up 0.23.1 whatsnew (#21368)
jorisvandenbossche Jun 7, 2018
e64acdf
BUG: Fixed concat warning message (#21362)
TomAugspurger Jun 7, 2018
2fa7818
Revert "enable multivalues insert (#19664)" (#21355)
jorisvandenbossche Jun 7, 2018
f3f7eb9
BUG: dropna incorrect with categoricals in pivot_table (#21252)
jreback Jun 7, 2018
7471f3e
Sharey keyword for boxplot (#20968)
Jun 8, 2018
1027a1c
BUG: Series.combine() fails with ExtensionArray inside of Series (#21…
Dr-Irv Jun 8, 2018
7bc2124
requested changes added
daminisatya Jun 8, 2018
e7f787e
Merge branch 'master' into master
WillAyd Jun 8, 2018
b7bda86
Update v0.23.1.txt
WillAyd Jun 8, 2018
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2 changes: 2 additions & 0 deletions doc/source/whatsnew/v0.24.0.txt
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Expand Up @@ -80,6 +80,8 @@ Documentation Changes
Bug Fixes
~~~~~~~~~

- The top level None value is not dropped but rather preserved along with lower levels for consistency (:issue:`21356`)
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Added the bugfix in the whats new note.

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Change of plans here - can you add to the "Fixed Regressions" section in v0.23.1 introduced via #21368?

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this also needs to mention json_normalize, add double backticks on None.

finally, as a user this is not really clear on what has changed, can you re-word a bit.


Categorical
^^^^^^^^^^^

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2 changes: 0 additions & 2 deletions pandas/io/json/normalize.py
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Expand Up @@ -80,8 +80,6 @@ def nested_to_record(ds, prefix="", sep=".", level=0):
if level != 0: # so we skip copying for top level, common case
v = new_d.pop(k)
new_d[newkey] = v
elif v is None: # pop the key if the value is None
new_d.pop(k)
continue
else:
v = new_d.pop(k)
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19 changes: 11 additions & 8 deletions pandas/tests/io/json/test_normalize.py
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Expand Up @@ -238,15 +238,16 @@ def test_non_ascii_key(self):
tm.assert_frame_equal(result, expected)

def test_missing_field(self, author_missing_data):
# GH20030: Checks for robustness of json_normalize - should
# unnest records where only the first record has a None value
# GH20030: Checks for robustness of json_normalize
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@WillAyd Can you verify this comment once again.

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Just the GH issue number is sufficient (like you have below)

result = json_normalize(author_missing_data)
ex_data = [
{'author_name.first': np.nan,
{'info': np.nan,
'author_name.first': np.nan,
'author_name.last_name': np.nan,
'info.created_at': np.nan,
'info.last_updated': np.nan},
{'author_name.first': 'Jane',
{'info': None,
'author_name.first': 'Jane',
'author_name.last_name': 'Doe',
'info.created_at': '11/08/1993',
'info.last_updated': '26/05/2012'}
Expand Down Expand Up @@ -351,9 +352,8 @@ def test_json_normalize_errors(self):
errors='raise'
)

def test_nonetype_dropping(self):
# GH20030: Checks that None values are dropped in nested_to_record
# to prevent additional columns of nans when passed to DataFrame
def test_nonetype(self):
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can you make this test name more informative

# GH21356
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Here, i just added the issue number.

data = [
{'info': None,
'author_name':
Expand All @@ -367,7 +367,8 @@ def test_nonetype_dropping(self):
]
result = nested_to_record(data)
expected = [
{'author_name.first': 'Smith',
{'info': None,
'author_name.first': 'Smith',
'author_name.last_name': 'Appleseed'},
{'author_name.first': 'Jane',
'author_name.last_name': 'Doe',
Expand Down Expand Up @@ -395,6 +396,7 @@ def test_nonetype_top_level_bottom_level(self):
}
result = nested_to_record(data)
expected = {
'id': None,
'location.country.state.id': None,
'location.country.state.town.info.id': None,
'location.country.state.town.info.region': None,
Expand Down Expand Up @@ -423,6 +425,7 @@ def test_nonetype_multiple_levels(self):
}
result = nested_to_record(data)
expected = {
'id': None,
'location.id': None,
'location.country.id': None,
'location.country.state.id': None,
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