df.to_pandas() function converts string to object format instead of string dtype about polars HOT 2 CLOSED

That is pyarrow default behaviour for pandas conversion (which we use for this). If you want a faster and more accurate conversion (including a much-improved string type) you need to opt-in to pandas' newer arrow-backed dtypes, like so:

pd_df = df.to_pandas(use_pyarrow_extension_array=True)
pd_df.dtypes
# ID             int64[pyarrow]
# Name    large_string[pyarrow]
# Age            int64[pyarrow]

Once the pandas ecosystem has more fully adopted the arrow dtypes (which will take a bit of time) this will likely become the default conversion path. For now it requires opt-in.

from polars.

This issue should be closed because it's not a bug - pandas doesn't have a dedicated string dtype when using NumPy arrays as the backing, even if you literally pass it a NumPy string array:

>>> pd.DataFrame({'a': np.array(['a', 'b'], dtype='U1')}).dtypes
a    object
dtype: object

from polars.