I have a large spreadsheet file (.xlsx) that I'm processing using python pandas. It happens that I need data from two tabs in that large file. One of the tabs has a ton of data and the other is just a few square cells.
When I use pd.read_excel() on any worksheet, it looks to me like the whole file is loaded (not just the worksheet I'm interested in). So when I use the method twice (once for each sheet), I effectively have to suffer the whole workbook being read in twice (even though we're only using the specified sheet).
Am I using it wrong or is it just limited in this way?
Thank you!
Try pd.ExcelFile
:
xls = pd.ExcelFile('path_to_file.xls')
df1 = pd.read_excel(xls, 'Sheet1')
df2 = pd.read_excel(xls, 'Sheet2')
As noted by @HaPsantran, the entire Excel file is read in during the ExcelFile()
call (there doesn't appear to be a way around this). This merely saves you from having to read the same file in each time you want to access a new sheet.
Note that the sheet_name
argument to pd.read_excel()
can be the name of the sheet (as above), an integer specifying the sheet number (eg 0, 1, etc), a list of sheet names or indices, or None
. If a list is provided, it returns a dictionary where the keys are the sheet names/indices and the values are the data frames. The default is to simply return the first sheet (ie, sheet_name=0
).
If None
is specified, all sheets are returned, as a {sheet_name:dataframe}
dictionary.