Excel files vs. CSV files
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CSV stands for comma-separated values

Excel files have an extension of xlsx or xlx
  while CSV files have an extension of .csv.

For a CSV file, we can use the read.csv() or read.table() functions. 
Thus, this would be one solutio for an Excel if
  1) the size of the Excel file is samll
  2) just one or few sheets
  3) no or few commas

Then, we can replace commas with space or ;
  then export our data to a CSV file. 
  The read.csv() or read.table() functions 
   can be used to retrieve them. 

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Strategies for Excel files
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To deal with Excel files, we recommend the following four strategies. 

Strategy #1: Seeing is believing; launch your Excel file and look at the data
      sets for the header, starting cell, any missing code, number of sheets, 
      and the first few observations. Note that if saving your data as a CSV 
      file, consider the impact of the commas inside your data. 

Strategy #2: for a small data set, launch your Excel and export or save your 
      data set as a CSV file. Then, use the read.csv() or read.table() functions
      to retrieve the data. 

Strategy #3: Focusing on one R package for Excel files. If this one is not 
      functioning correctly, switch to another package. 

Strategy #4: Always compare your inputted data (using R) with your raw data, 
      such as the number of observations, the first few lines, and maximum, 
      mean, and minimum values. 

Strategy #5: If your function does not support reading a remote file, 
       then download it first. 
       download.file(remoteExcelFile,outfile,'wb')

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Replacing comma with semi-colon   
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For a small data set contained within an Excel file, 
   we can export it to a CSV file. 

However, when comma is part of data, we have to replace
   them with another symbol such as a semi-colon.

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