Repository: modin-project/modin

Issue:
BUG: converting string columns to interchange protocol changes values to NaN
### Modin version checks

- [X] I have checked that this issue has not already been reported.

- [X] I have confirmed this bug exists on the latest released version of Modin.

- [X] I have confirmed this bug exists on the main branch of Modin. (In order to do this you can follow [this guide](https://modin.readthedocs.io/en/stable/getting_started/installation.html#installing-from-the-github-master-branch).)


### Reproducible Example

```python
import pandas
import modin.pandas as pd

print(pandas.api.interchange.from_dataframe(pd.DataFrame({'fips': ['01001']}).__dataframe__()))
```


### Issue Description

BUG: converting string columns to interchange protocol changes values to NaN

### Expected Behavior

Should convert to strings, as pandas would

### Error Logs

N/A

### Installed Versions

<details>

```

INSTALLED VERSIONS
------------------
commit           : 38110bb65643babc748e9ed59f6e7780d80c539e
python           : 3.8.16.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 22.5.0
Version          : Darwin Kernel Version 22.5.0: Mon Apr 24 20:51:50 PDT 2023; root:xnu-8796.121.2~5/RELEASE_X86_64
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

Modin dependencies
------------------
modin            : 0.23.0+67.g38110bb65
ray              : 2.4.0
dask             : 2023.4.1
distributed      : 2023.4.1
hdk              : None

pandas dependencies
-------------------
pandas           : 2.0.2
numpy            : 1.24.3
pytz             : 2023.3
dateutil         : 2.8.2
setuptools       : 66.0.0
pip              : 23.0.1
Cython           : 0.29.34
pytest           : 7.3.1
hypothesis       : None
sphinx           : 7.0.0
blosc            : None
feather          : 0.4.1
xlsxwriter       : None
lxml.etree       : 4.9.2
html5lib         : None
pymysql          : None
psycopg2         : 2.9.6
jinja2           : 3.1.2
IPython          : 8.12.1
pandas_datareader: None
bs4              : 4.12.2
bottleneck       : None
brotli           : 1.0.9
fastparquet      : 2022.12.0
fsspec           : 2023.4.0
gcsfs            : None
matplotlib       : 3.7.1
numba            : None
numexpr          : 2.8.4
odfpy            : None
openpyxl         : 3.0.10
pandas_gbq       : 0.19.1
pyarrow          : 11.0.0
pyreadstat       : None
pyxlsb           : None
s3fs             : 0.4.2
scipy            : 1.10.1
snappy           : None
sqlalchemy       : 1.4.45
tables           : 3.8.0
tabulate         : None
xarray           : 2023.1.0
xlrd             : 2.0.1
zstandard        : None
tzdata           : 2023.3
qtpy             : None
pyqt5            : None
```

</details>



Discussion:

Resolving patch:
diff --git a/modin/core/dataframe/pandas/interchange/dataframe_protocol/column.py b/modin/core/dataframe/pandas/interchange/dataframe_protocol/column.py
--- a/modin/core/dataframe/pandas/interchange/dataframe_protocol/column.py
+++ b/modin/core/dataframe/pandas/interchange/dataframe_protocol/column.py
@@ -411,15 +411,18 @@ def _get_validity_buffer(self) -> Tuple[PandasProtocolBuffer, Any]:
             buf = self._col.to_numpy().flatten()
 
             # Determine the encoding for valid values
-            valid = 1 if invalid == 0 else 0
+            valid = invalid == 0
+            invalid = not valid
 
-            mask = [valid if type(buf[i]) is str else invalid for i in range(buf.size)]
+            mask = np.empty(shape=(len(buf),), dtype=np.bool_)
+            for i, obj in enumerate(buf):
+                mask[i] = valid if isinstance(obj, str) else invalid
 
             # Convert the mask array to a Pandas "buffer" using a NumPy array as the backing store
-            buffer = PandasProtocolBuffer(np.asarray(mask, dtype="uint8"))
+            buffer = PandasProtocolBuffer(mask)
 
             # Define the dtype of the returned buffer
-            dtype = (DTypeKind.UINT, 8, "C", "=")
+            dtype = (DTypeKind.BOOL, 8, "b", "=")
 
             self._validity_buffer_cache = (buffer, dtype)
             return self._validity_buffer_cache


Test patch:
diff --git a/modin/test/interchange/dataframe_protocol/pandas/test_protocol.py b/modin/test/interchange/dataframe_protocol/pandas/test_protocol.py
--- a/modin/test/interchange/dataframe_protocol/pandas/test_protocol.py
+++ b/modin/test/interchange/dataframe_protocol/pandas/test_protocol.py
@@ -13,6 +13,8 @@
 
 """Dataframe exchange protocol tests that are specific for pandas storage format implementation."""
 
+import pandas
+
 import modin.pandas as pd
 from modin.pandas.utils import from_dataframe
 from modin.pandas.test.utils import df_equals, test_data
@@ -60,3 +62,9 @@ def test_from_dataframe_with_empty_dataframe():
     modin_df = pd.DataFrame({"foo_col": pd.Series([], dtype="int64")})
     with warns_that_defaulting_to_pandas():
         eval_df_protocol(modin_df)
+
+
+def test_interchange_with_pandas_string():
+    modin_df = pd.DataFrame({"fips": ["01001"]})
+    pandas_df = pandas.api.interchange.from_dataframe(modin_df.__dataframe__())
+    df_equals(modin_df, pandas_df)