In Pandas, whats the equivalent of ‘nrows’ from read_csv() to be used in read_excel()?

Want to import only certain range of data from an excel spreadsheet (.xlsm format as it has macros) into a pandas dataframe. Was doing it this way:

data    = pd.read_excel(filepath, header=0,  skiprows=4, nrows= 20, parse_cols = "A:D")

But it seems that nrows works only with read_csv() ? What would be the equivalent for read_excel()?

Answer

If you know the number of rows in your Excel sheet, you can use the skip_footer parameter to read the first n – skip_footer rows of your file, where n is the total number of rows.

http://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_excel.html

Usage:

data = pd.read_excel(filepath, header=0, parse_cols = "A:D", skip_footer=80)

Assuming your excel sheet has 100 rows, this line would parse the first 20 rows.