DataFrame rename method is extremely slow for dictionary argument

[etrotta]

Checks

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

Reproducible example

import time
import polars as pl
df = pl.DataFrame({f"column_{i}": ['x', 'y', 'z'] for i in range(100_000)})
cols_map = {f"column_{i}": f"renamed_{i}" for i in range(100_000)}
start = time.perf_counter()
_ = df.rename(cols_map)
end = time.perf_counter()
print(f"Time for rename(): {end - start} | Version: {pl.__version__}")

Time for rename(): 117.57077859994024 | Version: 1.0.0

Log output

No response

Issue description

The example code takes around two minutes to run, tested in versions 0.20.31 and 1.0.0

Expected behavior

It shouldn't be that slow.
Passing a function is much faster, even lambda col: cols_map.get(col, col):

import time
import polars as pl
df = pl.DataFrame({f"column_{i}": ['x', 'y', 'z'] for i in range(100_000)})
cols_map = {f"column_{i}": f"renamed_{i}" for i in range(100_000)}
start = time.perf_counter()
_ = df.rename(lambda col: cols_map.get(col, col))
end = time.perf_counter()
print(f"Time for rename(): {end - start} | Version: {pl.__version__}")

Time for rename(): 0.4511210999917239 | Version: 1.0.0

Installed versions

--------Version info---------
Polars:               1.0.0
Index type:           UInt32
Platform:             Windows-11-10.0.22631-SP0
Python:               3.12.0 (tags/v3.12.0:0fb18b0, Oct  2 2023, 13:03:39) [MSC v.1935 64 bit (AMD64)]

----Optional dependencies----
adbc_driver_manager:  <not installed>
cloudpickle:          <not installed>
connectorx:           <not installed>
deltalake:            <not installed>
fastexcel:            0.9.0
fsspec:               <not installed>
gevent:               <not installed>
great_tables:         <not installed>
hvplot:               <not installed>
matplotlib:           3.8.2
nest_asyncio:         <not installed>
numpy:                1.26.4
openpyxl:             3.1.2
pandas:               2.2.2
pyarrow:              15.0.0
pydantic:             2.5.2
pyiceberg:            <not installed>
sqlalchemy:           2.0.29
torch:                <not installed>
xlsx2csv:             <not installed>
xlsxwriter:           <not installed>