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BUG: DataFrame#to_json in pandas 2.2.0 outputs Int64 values containing NA as floats #57224

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Closed
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skatsuta opened this issue Feb 3, 2024 · 0 comments · Fixed by #57232
Closed
2 of 3 tasks
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IO JSON read_json, to_json, json_normalize Regression Functionality that used to work in a prior pandas version
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@skatsuta
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skatsuta commented Feb 3, 2024

Pandas version checks

  • I have checked that this issue has not already been reported.
  • I have confirmed this bug exists on the latest version of pandas.
  • I have confirmed this bug exists on the main branch of pandas.

Reproducible Example

import pandas as pd

df = pd.DataFrame({"a": [1, pd.NA]}, dtype="Int64")
json = df.to_json(orient="records", lines=True)
print(json)

# Output:
#   {"a":1.0} <- float!
#   {"a":null}

Issue Description

In pandas 2.1.4, DataFrame#to_json outputs Int64 integers as JSON integers even if the column contains NA, as shown below. This is an expected behavior.

# pandas 2.1.4
import pandas as pd

df = pd.DataFrame({"a": [1, pd.NA]}, dtype="Int64")
json = df.to_json(orient="records", lines=True)
print(json)

# Output:
#   {"a":1} <- int
#   {"a":null}

However, in pandas 2.2.0, DataFrame#to_json outputs Int64 integers as JSON floats for columns containing NA, as shown below.

# pandas 2.2.0
import pandas as pd

df = pd.DataFrame({"a": [1, pd.NA]}, dtype="Int64")
json = df.to_json(orient="records", lines=True)
print(json)

# Output:
#   {"a":1.0} <- float!
#   {"a":null}

Note that even in 2.2.0, Int64 column values that do not contain any NA are output as JSON integers as expected.

# pandas 2.2.0
import pandas as pd

df = pd.DataFrame({"a": [1, 2]}, dtype="Int64")
json = df.to_json(orient="records", lines=True)
print(json)

# Output:
#   {"a":1} <- int
#   {"a":2} <- int

This problem also occurs in Series as follows.

s = pd.Series([1, pd.NA], dtype="Int64")
print(s.to_json(orient="records"))

# Output:
#   [1.0,null]
#     ^
#   float

Expected Behavior

As in pandas 2.1.4, Int64 column values should be output as JSON integers even if they contain NA.

import pandas as pd

df = pd.DataFrame({"a": [1, pd.NA]}, dtype="Int64")
json = df.to_json(orient="records", lines=True)
print(json)

# Expected output:
#   {"a":1} <- int
#   {"a":null}

Installed Versions

INSTALLED VERSIONS
------------------
commit                : fd3f57170aa1af588ba877e8e28c158a20a4886d
python                : 3.12.1.final.0
python-bits           : 64
OS                    : Darwin
OS-release            : 22.6.0
Version               : Darwin Kernel Version 22.6.0: Sun Dec 17 22:12:45 PST 2023; root:xnu-8796.141.3.703.2~2/RELEASE_ARM64_T6000
machine               : arm64
processor             : arm
byteorder             : little
LC_ALL                : en_US.UTF-8
LANG                  : en_US.UTF-8
LOCALE                : en_US.UTF-8

pandas                : 2.2.0
numpy                 : 1.26.3
pytz                  : 2024.1
dateutil              : 2.8.2
setuptools            : 69.0.3
pip                   : 23.3.1
Cython                : None
pytest                : 7.4.4
hypothesis            : None
sphinx                : None
blosc                 : None
feather               : None
xlsxwriter            : None
lxml.etree            : None
html5lib              : None
pymysql               : None
psycopg2              : None
jinja2                : None
IPython               : None
pandas_datareader     : None
adbc-driver-postgresql: None
adbc-driver-sqlite    : None
bs4                   : None
bottleneck            : None
dataframe-api-compat  : None
fastparquet           : None
fsspec                : 2023.12.2
gcsfs                 : 2023.12.2post1
matplotlib            : None
numba                 : None
numexpr               : None
odfpy                 : None
openpyxl              : None
pandas_gbq            : 0.20.0
pyarrow               : 15.0.0
pyreadstat            : None
python-calamine       : None
pyxlsb                : None
s3fs                  : None
scipy                 : 1.12.0
sqlalchemy            : None
tables                : None
tabulate              : None
xarray                : None
xlrd                  : None
zstandard             : None
tzdata                : 2023.4
qtpy                  : None
pyqt5                 : None
@skatsuta skatsuta added Bug Needs Triage Issue that has not been reviewed by a pandas team member labels Feb 3, 2024
@simonjayhawkins simonjayhawkins added Regression Functionality that used to work in a prior pandas version IO JSON read_json, to_json, json_normalize and removed Bug Needs Triage Issue that has not been reviewed by a pandas team member labels Feb 4, 2024
@simonjayhawkins simonjayhawkins added this to the 2.2.1 milestone Feb 4, 2024
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Labels
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