When I open excel file with .xls format here it is opened faster than in case of .xlsx extension here using Pandas. I am using Pandas 1.0.1 and Python 3.7.6. These files are literally the same, I just renamed file names and first sheet name for the sake of convenience. The files consist of 6 sheets with 49 columns and approximately 1700 rows numeric data in each sheet. As you can see I am just reading only the first sheet here, but the same result holds for any number of sheets and rows. (Almost 4x time difference)
Is this the reason? [From https://windowsfileviewer.com]
"While XLS files use a proprietary binary format, XLSX files use a newer file format referred to as Open XML. The XLS extension is used by Microsoft Excel 2003 and earlier and the XLSX extension is used by Microsoft Excel 2007 and later"
I could not find any information on Panda`s official documentation. I am just wondering why and how this happens.
maybe because XLS files use a proprietary binary format whereas, XLSX use a newer file format known as Open XML
Related
I have large excel files with format .xlsb and .xlsx. I need to read only one sheet from all these files in python. It takes forever to use read_excel on these files. I want to save off that sheet I need as a .csv file and then read it to make it quicker. The only problem is that I have 24 of these excel workbooks and I don't have the time to manually take that sheet for each workbook and save it as .csv. Any suggestions on how I can change the format of just that one sheet?
An .xlsx-file is technically a folder. It is possible to open it as a zip-file and extract the individual sheets. However, I have never attempted to do this using Python, so I do not know how easy it is to do.
I'm trying to fetch tagged data from a .xls file.
I am able to fetch the tagged data from .xlsx file using Openpyxl, like this: [dn for dn in wb.defined_names.definedName]
But openpyxl does not support .xls format and I need to get the defined_names from .xls file as well.
Is there any library that can read .xls and return the defined_names in the file?
check xlrd package.
Here is the relevant part of the docs - Named references, constants, formulas, and macros
I have thousands of .wfs(windows script files) files and I am looking for a solution to help me convert this huge amount of .wfs files into .csv files using Python Anaconda or Spyder.
May I know any IO API similar to pandas where could read wfs files using similar functions like read.excel? or does python read script files?
Or could I convert these script files into Excel read quick (I know how to convert excel files into csv using Python)?
An example .wfs along with the converted csv is contained in the link below:
https://www.dropbox.com/sh/uwbajpubzuxn7g5/AABbD7W4pXFlxiIi1UAlHKTFa?dl=0
I have a results analysing spreadsheet where i need to enter my raw data into a 8x6 cell 'plate' which has formatted cells to produce the output based on a graph created. This .xlsx file is heavily formatted with formulas for the analysis, and it is a commercial spreadsheet so I cannot replicate these formulas.
I am using python 2.7 to obtain the raw results into a list and I have tried using xlwt and xlutils to copy the spreadsheet to enter the results. When I do this it loses all formatting when I save the file. I am wondering whether there is a different way in which I can make a copy of the spreadsheet to enter my results.
Also when I have used xlutils.copy I can only save the file as a .xls file, not an xlsx, is this the reason why it loses formatting?
First:
Apparently xlwt, does not support xlsx.
does xlwt support xlsx Format
Other library to use with format:
https://pypi.python.org/pypi/XlsxWriter
or
http://pythonexcels.com/python-excel-mini-cookbook/
While Destrif is correct, xlutils uses xlwt which doesn't support the .xlsx file format.
However, you will also find that xlsxwritter is unable to write xlrd formatted objects.
Similarly, the python-excel-cookbook he recommends only works if you are running Windows and have excel installed. A better alternative for this would be xlwings as it works for Windows and Mac with Excel installed.
If you are looking for something more platform agnostic, you could try writing your xlsx file using openpyxl.
I have a web application (based on Django 1.5) wherein a user uploads a spreadsheet file.
I've been using xlrd for manipulating xls files and looked into openpyxl which claims to support xlsx/xlsm files.
So is there a common way to read/write both xls and xlsx files?
Another option could be to convert the uploaded file to xls and use xlrd. For this I looked into gnumeric and ssconvert, this would be favorable since all my existing code in written using xlrd and I will not have to change the existing codebase.
So should I change the library I use or go with the conversion solution?
Thanks in advance.
xlrd can read both xlsx and xls files, so it's probably simplest to use that. Support for xlsx isn't as extensive as openpyxl but should be sufficient.
There's a risk of losing information in converting xlsx to xls because xlsx files can be much larger.