Description
Pandas version checks
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I have checked that this issue has not already been reported.
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I have confirmed this bug exists on the latest version of pandas.
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I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
import pandas as pd
path = "~/Downloads/test-from-gsheets.xlsx"
pd.read_excel(path)Issue Description
It seems like Pandas behaves differently with Excel files downloaded from Google Sheets than with those created in Excel. Namely, with files from Google Sheets, I get .0 decimal points for columns with mixed data types (which does not happen in regular Excel files).
To reproduce: Create a new spreadsheet file in Google Drive and download as Excel. Can be as simple as one column, as long as it has numeric and string-like values:
| Test |
|---|
| ABC123 |
| 234 |
When reading this file with pd.read_excel, you get the following output (with the added .0 in the string):
| Test |
|---|
| ABC123 |
| 234.0 |
Funnily enough, when I create the same file directly in Excel, I don't get the added .0 and it works fine. I was even able to fix the behaviour by opening the downloaded file in Excel and saving it again.
test-from-local.xlsx
test-from-gsheet.xlsx
Expected Behavior
Mixed type columns are read as object type, without trailing .0, independent of whether the Excel file was created in Excel or Google Sheets.
Installed Versions
INSTALLED VERSIONS
commit : 4bfe3d0
python : 3.9.5.final.0
python-bits : 64
OS : Darwin
OS-release : 21.4.0
Version : Darwin Kernel Version 21.4.0: Mon Feb 21 20:36:53 PST 2022; root:xnu-8020.101.4~2/RELEASE_ARM64_T8101
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_GB.UTF-8
LOCALE : en_GB.UTF-8
pandas : 1.4.2
numpy : 1.22.3
pytz : 2022.1
dateutil : 2.8.2
pip : 22.0.4
setuptools : 52.0.0.post20210125
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : None
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
brotli :
fastparquet : None
fsspec : None
gcsfs : None
markupsafe : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : 3.0.9
pandas_gbq : None
pyarrow : None
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : None
snappy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
zstandard : None