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Reproducible Example

import pandas as pd

df = pd.DataFrame({'var1': ['44794724', None]})
df.to_csv('sample.csv', index=False)
df.head

df1 = pd.read_csv('sample.csv', dtype='string[pyarrow]',dtype_backend='pyarrow')
df2 = pd.read_csv('sample.csv', dtype='string[pyarrow]',dtype_backend='pyarrow',engine="pyarrow")

print(df1['var1'].astype(str).str.endswith('.0').sum())
print(df2['var1'].astype(str).str.endswith('.0').sum())

Issue Description

I've encountered an issue with read_csv when using the pyarrow engine. Specifically, when a numeric column with missing values is imported as a string type, each number in the column has ".0" appended to it. This issue occurs when setting the dtype to 'string' or 'string[pyarrow]'. The issue is not observed if at least one of the data rows contains a string, or if the dtype is set to 'object'.

Expected Behavior

Expected the same behavior turning on and off the pyarrow engine. The numeric values should be imported as strings without alteration.

Installed Versions

pandas '2.2.0' and '3.0.0.dev0+171.gd928a5cc22'
pyarrow=14.0.2
python=3.11.7
OS: win11-22H2