BUG: Datatypes not preserved on pd.read_excel

[vignesh14052002]

Pandas version checks

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• I have confirmed this bug exists on the latest version of pandas.

• I have confirmed this bug exists on the main branch of pandas.

Reproducible Example

import pandas as pd
pd.read_excel("./preserve_data.xlsx")

Issue Description

Input data

Datatype is preserved, but values are modified

TRUE -> 1

values are modified, even if i read as string

TRUE <-> 1

additionally, I want TRUE in uppercase, if it is changed to True, i can't find difference if user has 'True in a cell

Expected Behavior

There should be a way to preserve values and datatypes as it is

Installed Versions

INSTALLED VERSIONS

commit : d9cdd2e
python : 3.11.3.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19045
machine : AMD64
processor : Intel64 Family 6 Model 142 Stepping 12, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_India.1252

pandas : 2.2.2
numpy : 1.26.2
pytz : 2024.1
dateutil : 2.8.2
setuptools : 69.0.2
pip : 23.1.2
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.4
IPython : 8.18.1
pandas_datareader : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.12.3
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : 2024.9.0
gcsfs : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : 3.1.5
pandas_gbq : None
pyarrow : None
pyreadstat : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : 1.12.0
sqlalchemy : 2.0.23
tables : None
tabulate : None
xarray : None
xlrd : None
zstandard : None
tzdata : 2024.1
qtpy : None
pyqt5 : None

[ZKaoChi]

I think this is worth changing, can I take it ?

[ZKaoChi]

Hello, I tested excel and found that as long as there is only true in the table, it will be converted to TRUE, which is a keyword in excel. So maybe user will not have True in a cell.

[ZKaoChi]

But TRUE is parsed as True in the first column and 1 in the back, which I think is worth changing.Maybe we should make the default values the same for different columns

[ZKaoChi]

I created a excel to test it. The data is:

      a     b     c     d     e     f     g  h     i
0  True     1  True  True     1     1  True  1  True
1  True  True     1  True     1  True     1  1  True
2  True  True  True     1  True     1     1  1  True

If we read it directly, the result is：

>>> pd.read_excel("./123.xlsx")
      a  b  c  d  e  f  g  h     i
0  True  1  1  1  1  1  1  1  True
1  True  1  1  1  1  1  1  1  True
2  True  1  1  1  1  1  1  1  True

If we read it with dtype = str, the result is:

>>> pd.read_excel("./123.xlsx",dtype=str)
      a  b     c     d  e  f     g  h     i
0  True  1  True  True  1  1  True  1  True
1  True  1  True  True  1  1  True  1  True
2  True  1  True  True  1  1  True  1  True

I think it has something to do with the way the data is created.

[rhshadrach]

As the docstring states, use dtype=object if you do not want pandas to do any inference on the dtype.

I checked both calamine and openpyxl, both readers are reading integer or Boolean values instead of e.g. TRUE. You can see this for openpyxl with:

from openpyxl import load_workbook
wb = load_workbook('test.xlsx', data_only=True)
for row in wb.worksheets[0].rows:
    for cell in row:
        print(cell, cell.value, cell.internal_value, cell.data_type)

As pandas only gets values through third-party libraries, they would need to support this first. It is likely there is a technical limitation in the Excel spec that prevents this, but I'm not certain.

As there is nothing pandas can do here, closing this issue.