Output:
       Apples:       1596.403 +-    10.651
       Oranges:         10.164 +-     0.685
       Bananas:          0.879 +-     0.200
         Pears:          0.006 +-     0.047
 Pears/Bananas:         -0.021 +-     0.101

Output:
Apples       oranges     Bananas
1596.403      10.164      0.879
1467.234      12.345      0.461
1234.456      14.658      0.592
    ....So on and so on.....

import pandas as pd
import numpy as np
import glob

txt_list = [] # empty list
sheet_list = [] # empty list

# a for loop through filenames matching a specified pattern (.txt) in the current directory
for infile in glob.glob("test-1.txt"): 
    outfile = infile.replace('.txt', '') #removing '.txt' for excel sheet names
    sheet_list.append(outfile) #appending for excel sheet name to sheet_list
    txt_list.append(infile) #appending for '...txt' to txtt_list

writer = pd.ExcelWriter('summary.xlsx', engine='xlsxwriter')

# a for loop through all elements in txt_list
for i in range(0, len(txt_list)):
    df = pd.read_csv('%s' % (txt_list[i])) #reading element from txt_list at index = i 
    df.to_excel(writer, sheet_name='%s' % (sheet_list[i]), index=False) #reading element from sheet_list at index = i 

writer.save()