What is the best way to read Excel (XLS) files with Python (not CSV files).

Is there a built-in package which is supported by default in Python to do this task?

I highly recommend xlrd for reading .xls files. But there are some limitations(refer to xlrd github page):


This library will no longer read anything other than .xls files. For
alternatives that read newer file formats, please see

The following are also not supported but will safely and reliably be

- Charts, Macros, Pictures, any other embedded object, including embedded worksheets.
- VBA modules
- Formulas, but results of formula calculations are extracted.
- Comments
- Hyperlinks
- Autofilters, advanced filters, pivot tables, conditional formatting, data validation

Password-protected files are not supported and cannot be read by this

voyager mentioned the use of COM automation. Having done this myself a few years ago, be warned that doing this is a real PITA. The number of caveats is huge and the documentation is lacking and annoying. I ran into many weird bugs and gotchas, some of which took many hours to figure out.

UPDATE: For newer .xlsx files, the recommended library for reading and writing appears to be openpyxl (thanks, Ikar Pohorský).

Using pandas:

import pandas as pd

xls = pd.ExcelFile(r"yourfilename.xls") #use r before absolute file path 

sheetX = xls.parse(2) #2 is the sheet number+1 thus if the file has only 1 sheet write 0 in paranthesis

var1 = sheetX['ColumnName']

print(var1[1]) #1 is the row number...

You can choose any one of them http://www.python-excel.org/
I would recommended python xlrd library.

install it using

pip install xlrd

import using

import xlrd

to open a workbook

workbook = xlrd.open_workbook('your_file_name.xlsx')

open sheet by name

worksheet = workbook.sheet_by_name('Name of the Sheet')

open sheet by index

worksheet = workbook.sheet_by_index(0)

read cell value

worksheet.cell(0, 0).value    

I think Pandas is the best way to go. There is already one answer here with Pandas using ExcelFile function, but it did not work properly for me. From here I found the read_excel function which works just fine:

import pandas as pd
dfs = pd.read_excel("your_file_name.xlsx", sheet_name="your_sheet_name")

P.S. You need to have the xlrd installed for read_excel function to work

Update 21-03-2020: As you may see here, there are issues with the xlrd engine and it is going to be deprecated. The openpyxl is the best replacement. So as described here, the canonical syntax should be:

dfs = pd.read_excel("your_file_name.xlsx", sheet_name="your_sheet_name", engine="openpyxl")

For xlsx I like the solution posted earlier as https://web.archive.org/web/20180216070531/https://stackoverflow.com/questions/4371163/reading-xlsx-files-using-python. I uses modules from the standard library only.

def xlsx(fname):
    import zipfile
    from xml.etree.ElementTree import iterparse
    z = zipfile.ZipFile(fname)
    strings = [el.text for e, el in iterparse(z.open('xl/sharedStrings.xml')) if el.tag.endswith('}t')]
    rows = []
    row = {}
    for e, el in iterparse(z.open('xl/worksheets/sheet1.xml')):
        if el.tag.endswith('}v'):  # Example: <v>84</v>                            
            value = el.text
        if el.tag.endswith('}c'):  # Example: <c r="A3" t="s"><v>84</v></c>                                 
            if el.attrib.get('t') == 's':
                value = strings[int(value)]
            letter = el.attrib['r']  # Example: AZ22                         
            while letter[-1].isdigit():
                letter = letter[:-1]
            row[letter] = value
        if el.tag.endswith('}row'):
            row = {}
    return rows

Improvements added are fetching content by sheet name, using re to get the column and checking if sharedstrings are used.

def xlsx(fname,sheet):
    import zipfile
    from xml.etree.ElementTree import iterparse
    import re
    z = zipfile.ZipFile(fname)
    if 'xl/sharedStrings.xml' in z.namelist():
        # Get shared strings
        strings = [element.text for event, element
                   in iterparse(z.open('xl/sharedStrings.xml')) 
                   if element.tag.endswith('}t')]
    sheetdict = { element.attrib['name']:element.attrib['sheetId'] for event,element in iterparse(z.open('xl/workbook.xml'))
                                      if element.tag.endswith('}sheet') }
    rows = []
    row = {}

    if sheet in sheets:
    for event, element in iterparse(z.open(sheetfile)):
        # get value or index to shared strings
        if element.tag.endswith('}v') or element.tag.endswith('}t'):
            value = element.text
        # If value is a shared string, use value as an index
        if element.tag.endswith('}c'):
            if element.attrib.get('t') == 's':
                value = strings[int(value)]
            # split the row/col information so that the row leter(s) can be separate
            letter = re.sub('\d','',element.attrib['r'])
            row[letter] = value
        if element.tag.endswith('}row'):
            row = {}

    return rows

If you need old XLS format. Below code for ansii ‘cp1251’.

import xlrd


    book = xlrd.open_workbook(file,encoding_override="cp1251")  
    book = xlrd.open_workbook(file)
print("The number of worksheets is {0}".format(book.nsheets))
print("Worksheet name(s): {0}".format(book.sheet_names()))
sh = book.sheet_by_index(0)
print("{0} {1} {2}".format(sh.name, sh.nrows, sh.ncols))
print("Cell D30 is {0}".format(sh.cell_value(rowx=29, colx=3)))
for rx in range(sh.nrows):

For older .xls files, you can use xlrd

either you can use xlrd directly by importing it. Like below

import xlrd
wb = xlrd.open_workbook(file_name)

Or you can also use pandas pd.read_excel() method, but do not forget to specify the engine, though the default is xlrd, it has to be specified.

pd.read_excel(file_name, engine = xlrd)

Both of them work for older .xls file formats.
Infact I came across this when I used OpenPyXL, i got the below error

InvalidFileException: openpyxl does not support the old .xls file format, please use xlrd to read this file, or convert it to the more recent .xlsx file format.

You can use any of the libraries listed here (like Pyxlreader that is based on JExcelApi, or xlwt), plus COM automation to use Excel itself for the reading of the files, but for that you are introducing Office as a dependency of your software, which might not be always an option.

Python Excelerator handles this task as well. http://ghantoos.org/2007/10/25/python-pyexcelerator-small-howto/

It’s also available in Debian and Ubuntu:

 sudo apt-get install python-excelerator

You might also consider running the (non-python) program xls2csv. Feed it an xls file, and you should get back a csv.

For older Excel files there is the OleFileIO_PL module that can read the OLE structured storage format used.

    with open(csv_filename) as file:
        data = file.read()

    with open(xl_file_name, 'w') as file:

You can turn CSV to excel like above with inbuilt packages. CSV can be handled with an inbuilt package of dictreader and dictwriter which will work the same way as python dictionary works. which makes it a ton easy
I am currently unaware of any inbuilt packages for excel but I had come across openpyxl. It was also pretty straight forward and simple You can see the code snippet below hope this helps

    import openpyxl
    book = openpyxl.load_workbook(filename)
    sheet = book.active 
    result =sheet['AP2']

If the file is really an old .xls, this works for me on python3 just using base open() and pandas:

df = pandas.read_csv(open(f, encoding = 'UTF-8'), sep='\t')

Note that the file I’m using is tab delimited. less or a text editor should be able to read .xls so that you can sniff out the delimiter.

I did not have a lot of luck with xlrd because of – I think – UTF-8 issues.