If:
Then, you can pass a list of worksheet names. Which you could populate manually:
import pandas as pd
path = "C:\\Path\\To\\Your\\Data\\"
file = "data.xlsx"
sheet_lst_wanted = ["01_SomeName","05_SomeName","12_SomeName"] # tab names from Excel
### import and compile data ###
# read all sheets from list into an ordered dictionary
dict_temp = pd.read_excel(path+file, sheet_name= sheet_lst_wanted)
# concatenate the ordered dict items into a dataframe
df = pd.concat(dict_temp, axis=0, ignore_index=True)
OR
A bit of automation is possible if your desired worksheets have a common naming convention that also allows you to differentiate from unwanted sheets:
# substitute following block for the sheet_lst_wanted line in above block
import xlrd
# string common to only worksheets you want
str_like = "SomeName"
### create list of sheet names in Excel file ###
xls = xlrd.open_workbook(path+file, on_demand=True)
sheet_lst = xls.sheet_names()
### create list of sheets meeting criteria ###
sheet_lst_wanted = []
for s in sheet_lst:
# note: following conditional statement based on my sheets ending with the string defined in sheet_like
if s[-len(str_like):] == str_like:
sheet_lst_wanted.append(s)
else:
pass