BUG: df[col].replace(dict, inplace=True) is brutally slow, while .apply which does the same is blazing fast

[Liquidmasl]

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Reproducible Example

# create somewhat large dataframe, partition it into ~25 parts

df = pd.DataFrame({
    'val': np.random.randint(1, 10001, size=20_000_000)
})

unique = orig_with_hashes['df'].unique()
hash_map = {hash_: i for i, hash_ in enumerate(unique_hashes)}

# fast:
# df['val'] = df['val'].apply(lambda x: hash_map[x])

# slow:
df['val'].replace(hash_map, in_place=True)

Issue Description

replace method seams unreasonably slow.

Expected Behavior

should be faster

Error Logs

Replace this line with the error backtrace (if applicable).

Installed Versions

INSTALLED VERSIONS

commit : 52fca1c
python : 3.11.9.final.0
python-bits : 64
OS : Linux
OS-release : 6.8.0-40-generic
Version : #40~22.04.3-Ubuntu SMP PREEMPT_DYNAMIC Tue Jul 30 17:30:19 UTC 2
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
Modin dependencies

modin : 0.30.1
ray : 2.24.0
dask : 2024.6.0
distributed : 2024.6.0
hdk : None
pandas dependencies

pandas : 2.2.2
numpy : 1.26.3
pytz : 2024.1
dateutil : 2.9.0.post0
setuptools : 69.5.1
pip : 24.1.2
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.3
IPython : 8.25.0
pandas_datareader : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.12.3
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : 2024.2.0
gcsfs : None
matplotlib : 3.8.4
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 16.1.0
pyreadstat : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : 1.14.0
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
zstandard : None
tzdata : 2024.1
qtpy : None
pyqt5 : None