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python – Read Excel XML .xls file with pandas

Posted by: admin March 9, 2020 Leave a comment

Questions:

I’m aware of a number of previously asked questions, but none of the solutions given work on the reproducible example that I provide below.

I am trying to read in .xls files from http://www.eia.gov/coal/data.cfm#production — specifically the Historical detailed coal production data (1983-2013) coalpublic2012.xls file that’s freely available via the dropdown. Pandas cannot read it.

In contrast, the file for the most recent year available, 2013, coalpublic2013.xls file, works without a problem:

import pandas as pd
df1 = pd.read_excel("coalpublic2013.xls")

but the next decade of .xls files (2004-2012) do not load. I have looked at these files with Excel, and they open, and are not corrupted.

The error that I get from pandas is:

---------------------------------------------------------------------------
XLRDError                                 Traceback (most recent call last)
<ipython-input-28-0da33766e9d2> in <module>()
----> 1 df = pd.read_excel("coalpublic2012.xlsx")

/Users/jonathan/anaconda/lib/python2.7/site-packages/pandas/io/excel.pyc in read_excel(io, sheetname, header, skiprows, skip_footer, index_col, parse_cols, parse_dates, date_parser, na_values, thousands, convert_float, has_index_names, converters, engine, **kwds)
    161 
    162     if not isinstance(io, ExcelFile):
--> 163         io = ExcelFile(io, engine=engine)
    164 
    165     return io._parse_excel(

/Users/jonathan/anaconda/lib/python2.7/site-packages/pandas/io/excel.pyc in __init__(self, io, **kwds)
    204                 self.book = xlrd.open_workbook(file_contents=data)
    205             else:
--> 206                 self.book = xlrd.open_workbook(io)
    207         elif engine == 'xlrd' and isinstance(io, xlrd.Book):
    208             self.book = io

/Users/jonathan/anaconda/lib/python2.7/site-packages/xlrd/__init__.pyc in open_workbook(filename, logfile, verbosity, use_mmap, file_contents, encoding_override, formatting_info, on_demand, ragged_rows)
    433         formatting_info=formatting_info,
    434         on_demand=on_demand,
--> 435         ragged_rows=ragged_rows,
    436         )
    437     return bk

/Users/jonathan/anaconda/lib/python2.7/site-packages/xlrd/book.pyc in open_workbook_xls(filename, logfile, verbosity, use_mmap, file_contents, encoding_override, formatting_info, on_demand, ragged_rows)
     89         t1 = time.clock()
     90         bk.load_time_stage_1 = t1 - t0
---> 91         biff_version = bk.getbof(XL_WORKBOOK_GLOBALS)
     92         if not biff_version:
     93             raise XLRDError("Can't determine file's BIFF version")

/Users/jonathan/anaconda/lib/python2.7/site-packages/xlrd/book.pyc in getbof(self, rqd_stream)
   1228             bof_error('Expected BOF record; met end of file')
   1229         if opcode not in bofcodes:
-> 1230             bof_error('Expected BOF record; found %r' % self.mem[savpos:savpos+8])
   1231         length = self.get2bytes()
   1232         if length == MY_EOF:

/Users/jonathan/anaconda/lib/python2.7/site-packages/xlrd/book.pyc in bof_error(msg)
   1222         if DEBUG: print("reqd: 0x%04x" % rqd_stream, file=self.logfile)
   1223         def bof_error(msg):
-> 1224             raise XLRDError('Unsupported format, or corrupt file: ' + msg)
   1225         savpos = self._position
   1226         opcode = self.get2bytes()

XLRDError: Unsupported format, or corrupt file: Expected BOF record; found '<?xml ve'

And I have tried various other things:

df = pd.ExcelFile("coalpublic2012.xls", encoding_override='cp1252')
import xlrd
wb = xlrd.open_workbook("coalpublic2012.xls")

to no avail. My pandas version: 0.17.0

I’ve also submitted this as a bug to the pandas github issues list.

How to&Answers:

You can convert this Excel XML file programmatically. Requirement: only python and pandas.

import pandas as pd
from xml.sax import ContentHandler, parse

# Reference https://goo.gl/KaOBG3
class ExcelHandler(ContentHandler):
    def __init__(self):
        self.chars = [  ]
        self.cells = [  ]
        self.rows = [  ]
        self.tables = [  ]
    def characters(self, content):
        self.chars.append(content)
    def startElement(self, name, atts):
        if name=="Cell":
            self.chars = [  ]
        elif name=="Row":
            self.cells=[  ]
        elif name=="Table":
            self.rows = [  ]
    def endElement(self, name):
        if name=="Cell":
            self.cells.append(''.join(self.chars))
        elif name=="Row":
            self.rows.append(self.cells)
        elif name=="Table":
            self.tables.append(self.rows)

excelHandler = ExcelHandler()
parse('coalpublic2012.xls', excelHandler)
df1 = pd.DataFrame(excelHandler.tables[0][4:], columns=excelHandler.tables[0][3])

Answer:

You can convert this Excel XML file programmatically.
Requirement: Windows, Office installed.

1.Create in Notepad ExcelToCsv.vbs script:

if WScript.Arguments.Count < 3 Then
    WScript.Echo "Please specify the source and the destination files. Usage: ExcelToCsv <xls/xlsx source file> <csv destination file> <worksheet number (starts at 1)>"
    Wscript.Quit
End If

csv_format = 6

Set objFSO = CreateObject("Scripting.FileSystemObject")

src_file = objFSO.GetAbsolutePathName(Wscript.Arguments.Item(0))
dest_file = objFSO.GetAbsolutePathName(WScript.Arguments.Item(1))
worksheet_number = CInt(WScript.Arguments.Item(2))

Dim oExcel
Set oExcel = CreateObject("Excel.Application")

Dim oBook
Set oBook = oExcel.Workbooks.Open(src_file)
oBook.Worksheets(worksheet_number).Activate

oBook.SaveAs dest_file, csv_format

oBook.Close False
oExcel.Quit
  1. Convert the Excel XML file in CSV:

$ cscript ExcelToCsv.vbs coalpublic2012.xls coalpublic2012.csv 1

  1. Open the CSV file with pandas

>>> df1 = pd.read_csv('coalpublic2012.csv', skiprows=3)

Reference: Faster way to read Excel files to pandas dataframe

Answer:

The problem is that while the 2013 data is an actual Excel file, the 2012 data is an XML document, something which seems to not be supported in Python. I would say your best bet is to open it in Excel, and save a copy as either a proper Excel file, or as a CSV.

Answer:

@JBWhitmore I have run the following code:

import pandas as pd
#Read and write to excel
dataFileUrl = r"/Users/stutiverma/Downloads/coalpublic2012.xls"
data = pd.read_table(dataFileUrl)

This reads the file successfully without giving any error. But, it gives all the data in the exact format as mentioned. So, you may have to do extra efforts in order to process the data after reading it successfully.