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Reproducible Example

import pandas as pd

df = pd.DataFrame({"x": [pd.NA, pd.NA], "y": [1.0, 2.0]})
df2 = pd.read_json(df.to_json(orient="table"), orient="table")
print(df.to_json(orient="table"))
print(df.dtypes)
print(df2.dtypes)

Issue Description

When I have a column consisting of pd.NA the data type is initially object. When I call .to_json(orient="table") the schema says that the type is "string" (which is probably OK??)

{"schema":{"fields":[{"name":"index","type":"integer"},{"name":"x","type":"string"},{"name":"y","type":"number"}],"primaryKey":["index"],"pandas_version":"1.4.0"},"data":[{"index":0,"x":null,"y":1.0},{"index":1,"x":null,"y":2.0}]}

When I read the produced json string back using .read_json the data dype in the resulting frame is float64

Full output of the example

{"schema":{"fields":[{"name":"index","type":"integer"},{"name":"x","type":"string"},{"name":"y","type":"number"}],"primaryKey":["index"],"pandas_version":"1.4.0"},"data":[{"index":0,"x":null,"y":1.0},{"index":1,"x":null,"y":2.0}]}
x     object
y    float64
dtype: object
x    float64
y    float64
dtype: object

Expected Behavior

The data types should be preserved when doing a roundtrip with orient="table" on both read and write.

Minor detail: The schema appears to say "pandas_version": 1.4.0 even though the details below says that the install version is 1.5.2. Would expect that 1.5.2 was present in the output.

Installed Versions

INSTALLED VERSIONS ------------------ commit : 8dab54d6573f7186ff0c3b6364d5e4dd635ff3e7 python : 3.10.9.final.0 python-bits : 64 OS : Linux OS-release : 5.10.16.3-microsoft-standard-WSL2 Version : #1 SMP Fri Apr 2 22:23:49 UTC 2021 machine : x86_64 processor : byteorder : little LC_ALL : None LANG : C.UTF-8 LOCALE : en_US.UTF-8 pandas : 1.5.2 numpy : 1.24.1 pytz : 2022.7.1 dateutil : 2.8.2 setuptools : 66.0.0 pip : 22.3.1 Cython : None pytest : 7.2.1 hypothesis : None sphinx : None blosc : None feather : None xlsxwriter : None lxml.etree : None html5lib : None pymysql : None psycopg2 : None jinja2 : 3.1.2 IPython : 8.8.0 pandas_datareader: None bs4 : 4.11.1 bottleneck : 1.3.5 brotli : None fastparquet : None fsspec : None gcsfs : None matplotlib : None numba : None numexpr : 2.8.4 odfpy : None openpyxl : None pandas_gbq : None pyarrow : 10.0.1 pyreadstat : None pyxlsb : None s3fs : None scipy : 1.9.3 snappy : None sqlalchemy : None tables : None tabulate : None xarray : None xlrd : None xlwt : None zstandard : None tzdata : Non

Comment From: phofl

This looks suspicious, but not sure if this is intentional