Pandas.read_excel reads date into timestamp, I want a string

Question

I read a large Excel file into pandas using .read_excel, and the file has date columns. When read into pandas, the dates default to a timestamp. Since the file is large, I would like to read the dates as a string.

If that is not possible, then I would at least like to export the date back to Excel in the same format as it is in the original file (e.g. "8/18/2009").

My two questions are:

1. Can I avoid converting the Excel date into a timestamp in pandas?
2. If not possible, how can I write back the date in the original format efficiently?

Answer 1

1. I am not sure how to read the date and not convert into timestamp using read_excel.
2. Because the date is already converted into datetime while reading it into a dataframe, here is how the date can be printed in the original format - I have used 'mm/dd/yyyy'.

import pandas as pd

df = pd.read_excel(
    "file_to_read.xlsx",
    sheet_name="sheetname",
)
writer = pd.ExcelWriter(
    "file_to_write.xlsx",
    engine="xlsxwriter",
    datetime_format="mm/dd/yyyy",
)
df.to_excel(
    writer,
    index=False,
    header=True,
    sheet_name="sheetname",
)

Answer 2

this is similar as issue here. Leave dates as strings using read_excel function from pandas in python

check the answers:

• Using converters{'Date': str} option inside the pandas.read_excel which helps.
  pandas.read_excel(xlsx, sheet, converters={'Date': str})
• you can try convert your timestamp back to the original format
  df['Date'][0].strftime('%Y/%m/%d')