title: Why Date column is distorted when read into pandas?
body: <p>I read an excel file from a URL and need to do some cleaning before I can save it. In the original excel file, there are some logos and null entries in the first few rows and then the real data starts. The column date (Unnamed 0:) in excel file appears as date but when read into pandas for some reason it is converted to number. Using astype and pd.to_datetime converts the column to date but incorrect date. Any advice?</p>
  <p>note: although date column appears as date in excel sheet, its type is general. I can go and manually change the type first in the excel file but I do not want to do that because I want to automate the process.
  <a href="https://i.stack.imgur.com/9mNh8.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/9mNh8.png" alt="enter image description here" /></a></p>
  <p>if you want to produce data, here is the code:</p>
  <pre><code>from requests import get
  import pandas as pd
  
  url = 'http://rigcount.bakerhughes.com/static-files/55ff50da-ac65-410d-924c-fe45b23db298'
  # make HTTP request to fetch data
  r = get(url)
  
  # check if request is success
  r.raise_for_status()
  
  # write out byte content to file
  with open('out.xlsb', 'wb') as out_file:
      out_file.write(r.content)
  
  Canada_Oil_Gas = pd.read_excel('out.xlsb', sheet_name='Canada Oil &amp; Gas Split', engine='pyxlsb')
  </code></pre>