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ERR: Fix missing space in warning message #39159

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ERR: Fix missing space in warning message #39159

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07cdef1
DOC: Fix missing space
MicaelJarniac Jan 13, 2021
89e7cd9
Merge branch 'master' into fix-warning-typo
MicaelJarniac Jan 13, 2021
fb3f074
Merge branch 'master' into fix-warning-typo
MicaelJarniac Feb 8, 2021
92e96df
TST: Check if warning message matches
MicaelJarniac Feb 8, 2021
54c2056
TST: Split long message
MicaelJarniac Mar 15, 2021
15808d6
Merge remote-tracking branch 'upstream/master' into fix-warning-typo
MicaelJarniac Mar 15, 2021
83fb047
TST: Use `match` argument
MicaelJarniac Mar 22, 2021
a7c3f5b
TST: Fix missing regex import
MicaelJarniac Mar 22, 2021
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2 changes: 1 addition & 1 deletion pandas/_libs/parsers.pyx
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Original file line number Diff line number Diff line change
Expand Up @@ -1924,7 +1924,7 @@ def _concatenate_chunks(list chunks):
if warning_columns:
warning_names = ','.join(warning_columns)
warning_message = " ".join([
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does removing the join here work instead and just use fstring literal concatenation

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I can't see why that wouldn't work. Technically, the join wasn't even being used anyways, because the strings were getting concatenated inside of the list, so yeah, "officially" removing the join and manually adding the space between the strings sounds perfectly fine I think.
I'll poke around to see how other similar warnings are created, though, because keeping it consistent between them might be a valid reason as to whether or not to have the join.

f"Columns ({warning_names}) have mixed types."
f"Columns ({warning_names}) have mixed types.",
f"Specify dtype option on import or set low_memory=False."
])
warnings.warn(warning_message, DtypeWarning, stacklevel=8)
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7 changes: 6 additions & 1 deletion pandas/tests/io/parser/common/test_chunksize.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,6 +6,7 @@

import numpy as np
import pytest
import regex as re

from pandas.errors import DtypeWarning

Expand Down Expand Up @@ -190,7 +191,11 @@ def test_warn_if_chunks_have_mismatched_type(all_parsers, request):
buf = StringIO(data)

try:
with tm.assert_produces_warning(warning_type):
msg = (
"Columns (0) have mixed types. Specify dtype option on import or "
"set low_memory=False."
)
with tm.assert_produces_warning(warning_type, match=re.escape(msg)):
df = parser.read_csv(buf)
except AssertionError as err:
# 2021-02-21 this occasionally fails on the CI with an unexpected
Expand Down