Varying skiprows argument for individual worksheets when using pd.read

I have an excel-workbook with two worksheets which I want to import using pandas. I would like to use the skiprows argument, with 5 rows for the first sheet and 10 rows for the second sheet. pd.read_excel() returns a dictionary in case the excel file has several worksheets. Can I pass the skiprows argument as a list or similar to make it apply varying values for the individual sheets? I've tried this:

ret = pd.read_excel(file, skiprows=[5, 10], sheet_name=None)

It looks like the skiprows-argument is simply ignored in this case. Can I make it work somehow?

If yes, this can hopefully be generalized to other arguments too.

CodePudding user response：

It's complicated to generalize to all arguments. You have to iterate on each sheets.

A possible solution:

sheets = {
    'Sheet1': {'skiprows': 5},   # add other parameters
    'Sheet2': {'skiprows': 10},  # according the documentation
}

def read_excel_sheets(filename, sheets):
    dfs = {}
    with pd.ExcelFile(filename) as xlsx:
        for sheet_name, params in sheets.items():
            dfs[sheet_name] = xlsx.parse(sheet_name=sheet_name, **params)
    return dfs

# The output is the same as pd.read_excel(filename, sheets=None)
dfs = read_excel_sheets('data.xlsx', sheets)