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BUG: conversion a JSON field descriptor into pandas type for deprecated offsets frequency 'M' #55581

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Merged
merged 7 commits into from
Oct 24, 2023
Merged

BUG: conversion a JSON field descriptor into pandas type for deprecated offsets frequency 'M' #55581

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a832dcc
correct convert_json_field_to_pandas_type
natmokval Oct 18, 2023
e55001e
fix pre-commit errors
natmokval Oct 18, 2023
e454892
correct def convert_json_field_to_pandas_type in case freq_n>1
natmokval Oct 20, 2023
c0a7ee6
remove print
natmokval Oct 21, 2023
7a98c81
add parameterization to the test
natmokval Oct 21, 2023
e073336
replace the regex with to_offset
natmokval Oct 23, 2023
a298a24
Merge branch 'main' into bug-read-json-table-period-for-depr-freq-M
natmokval Oct 23, 2023
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8 changes: 7 additions & 1 deletion pandas/io/json/_table_schema.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,6 +5,7 @@
"""
from __future__ import annotations

import re
from typing import (
TYPE_CHECKING,
Any,
Expand All @@ -15,6 +16,7 @@
from pandas._libs import lib
from pandas._libs.json import ujson_loads
from pandas._libs.tslibs import timezones
from pandas._libs.tslibs.dtypes import freq_to_period_freqstr
from pandas.util._exceptions import find_stack_level

from pandas.core.dtypes.base import _registry as registry
Expand Down Expand Up @@ -207,8 +209,12 @@ def convert_json_field_to_pandas_type(field) -> str | CategoricalDtype:
if field.get("tz"):
return f"datetime64[ns, {field['tz']}]"
elif field.get("freq"):
# GH#9586 rename frequency M to ME for offsets
freq_name = re.split("[0-9]*", field["freq"], maxsplit=1)[1]
freq_n = field["freq"][: field["freq"].index(freq_name)]
freq = freq_to_period_freqstr(freq_n, freq_name)
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having a regular expression here looks a bit complex - would it work to do

offset = to_offset(field['freq'])
freq_n, freq_name = offset.n, offset.name
freq = freq_to_period_freqstr(freq_n, freq_name)

instead?

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thank you, it works very well. I replaced the regular expression with to_offset and updated my PR.

# GH#47747 using datetime over period to minimize the change surface
return f"period[{field['freq']}]"
return f"period[{freq}]"
else:
return "datetime64[ns]"
elif typ == "any":
Expand Down
10 changes: 10 additions & 0 deletions pandas/tests/io/json/test_json_table_schema.py
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Expand Up @@ -845,3 +845,13 @@ def test_read_json_orient_table_old_schema_version(self):
expected = DataFrame({"a": [1, 2.0, "s"]})
result = pd.read_json(StringIO(df_json), orient="table")
tm.assert_frame_equal(expected, result)

def test_read_json_table_orient_period_depr_freq(self, recwarn):
# GH#9586
df = DataFrame(
{"ints": [1, 2]},
index=pd.PeriodIndex(["2011-01", "2011-08"], freq="2M"),
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could we check it works for both '2M' and 'M'?

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yeah, sure, I added parameterization to the test, for 'M' and '2M'.

)
out = df.to_json(orient="table")
result = pd.read_json(out, orient="table")
tm.assert_frame_equal(df, result)