In read_excel parse_date=False is not working

[ajphukan]

Code Sample, a copy-pastable example if possible

import pandas as pd
df = pd.read_file('filename.xlsx', header= None, skiprows=1, parse_dates=False)

Problem description

In read_excel parse_date default value is False , but still it is parsing the date.

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Expected Output

Output of pd.show_versions()

INSTALLED VERSIONS

commit : None
python : 3.6.4.final.0
python-bits : 64
OS : Windows
OS-release : 10
machine : AMD64
processor : Intel64 Family 6 Model 142 Stepping 9, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : None.None

pandas : 0.25.2
numpy : 1.14.4
pytz : 2019.3
dateutil : 2.8.0
pip : 19.3.1
setuptools : 41.4.0
Cython : None
pytest : 5.2.1
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.10.3
IPython : 7.8.0
pandas_datareader: None
bs4 : 4.8.1
bottleneck : None
fastparquet : None
gcsfs : None
lxml.etree : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pytables : None
s3fs : None
scipy : None
sqlalchemy : 1.0.8
tables : None
xarray : None
xlrd : 1.2.0
xlwt : None
xlsxwriter : None

[hwalinga]

Can you maybe share the file (or something we can reproduce this with) that causes this problem?

The parse_dates can only be used in a specific case. Citing the documentation:

But if you have a column of strings that look like dates (but are not actually formatted as dates in excel), ...

So, this can only be used for columns that have strings that might be interpreted as dates, and not for column that are already the date type in excel itself.

[ajphukan]

Input sample you can use combination of date and simple string
`
col

aaaa
12/10/2019
ppp
cc
12/10/2019

`

Output that I am getting:

aaaa
2019-12-10 00:00:00
ppp
cc
2019-12-10 00:00:00

[hwalinga]

I was looking for the actual binary file 'filename.xlsx'.

[gfyoung]

My guess is that the Excel file is defining the data format of those cells as date:

pandas/pandas/io/excel/_xlrd.py

Lines 59 to 83 in bc020f6

	def _parse_cell(cell_contents, cell_typ):
	"""converts the contents of the cell into a pandas
	appropriate object"""
	if cell_typ == XL_CELL_DATE:
	# Use the newer xlrd datetime handling.
	try:
	cell_contents = xldate.xldate_as_datetime(cell_contents, epoch1904)
	except OverflowError:
	return cell_contents
	# Excel doesn't distinguish between dates and time,
	# so we treat dates on the epoch as times only.
	# Also, Excel supports 1900 and 1904 epochs.
	year = (cell_contents.timetuple())[0:3]
	if (not epoch1904 and year == (1899, 12, 31)) or (
	epoch1904 and year == (1904, 1, 1)
	):
	cell_contents = time(
	cell_contents.hour,
	cell_contents.minute,
	cell_contents.second,
	cell_contents.microsecond,
	)

For those types of cells, we are rendering those as date because Excel told us to do so.

The parameter parse_dates, however, applies to entire columns i.e. we convert the entire column of data to date, which doesn't seem to be happening here.

[ajphukan]

@gfyoung Yes the problem is with the microsoft excel, It is detecting the cell type automatically to date, I had to convert it to Text to avoid the auto parsing of cell to date type.

Can we include this Info in the doc so that new users can get the answer without raising issue ..

[gfyoung]

@ajphukan : You are more than welcome to contribute something!

[vishwasshrikhande]

I want to help, how do i start by adding this info to the doc? Any help

[hwalinga]

https://pandas.pydata.org/pandas-docs/stable/development/contributing.html