python - Wrong rows and columns imported into a data frame from Excel

Question

While importing data from an Excel file into a data frame via

df = pd.read_excel('df.xlsx', skiprows = 8, usecols = 'B:AX'),

the number of skipped rows is actually 9 (therefore columns' names from row 8 are not imported) and the data frame starts with data from column C instead of B (looks like rows and columns are somehow "indexed" from 0, making 0-8 ignored while importing). Also, a column which contains "+" in its name ("Name + Code") is imported into pandas with a minus sign instead ("Name - Code"). What could be causing this kind of behavior (if there's only one cause for these)?

The computer I'm working on has Python (3.8.6) freshly installed, together with pandas and openpyxl (via pip install). The same code on my other computer works perfectly fine (8 rows are skipped, data from columns B:AX is imported correctly, "+" stays "+" in all df.columns).

question from:https://stackoverflow.com/questions/65901806/wrong-rows-and-columns-imported-into-a-data-frame-from-excel

Answer 1

Waitting for answers