I'm working on a project using pandas library, in which I need to read an Excel file which has following columns:

'invoiceid', 'locationid', 'timestamp', 'customerid', 'discount', 'tax','total', 'subtotal', 'productid', 'quantity', 'productprice','productdiscount', 'invoice_products_id', 'producttax','invoice_payments_id', 'paymentmethod', 'paymentdetails', 'amount'

But when I read this file by using the Python code below:

df_full = pd.read_excel('input/invoiced_products_noinvoiceids_inproduct_v2.0.xlsx', sheet_name=0,)
df_full.head()

it returns some rows along with 6 unnamed columns with values as NAN.I don't know why these columns are displaying here?

Below is the link to a sample file as requested:

https://mega.nz/#!0MlXCBYJ!Oim9RF56h6hUitTwqSG1354dIKLZEgIszzPrVpfHas8

Why are these extra columns appearing?

As discussed in comments the problem seems to be that, there is extra data after last named columns. That's why you are getting Unnamed columns.

If you wanna drop these columns this is how you can ignore these columns

df_full = df_full[df_full.filter(regex='^(?!Unnamed)').columns]