I can pass a StringIO object to pd.to_csv() just fine:
io = StringIO.StringIO()
pd.DataFrame().to_csv(io)
But when using the excel writer, I am having a lot more trouble.
io = StringIO.StringIO()
writer = pd.ExcelWriter(io)
pd.DataFrame().to_excel(writer,"sheet name")
writer.save()
Returns an
AttributeError: StringIO instance has no attribute 'rfind'
I'm trying to create an ExcelWriter
object without calling pd.ExcelWriter()
but am having some trouble. This is what I've tried so far:
from xlsxwriter.workbook import Workbook
writer = Workbook(io)
pd.DataFrame().to_excel(writer,"sheet name")
writer.save()
But now I am getting an AttributeError: 'Workbook' object has no attribute 'write_cells'
How can I save a pandas dataframe in excel format to a StringIO
object?
One can read a text file (txt) by using the pandas read_fwf() function, fwf stands for fixed-width lines, you can use this to read fixed length or variable length text files. Alternatively, you can also read txt file with pandas read_csv() function.
Use pandas to_excel() function to write a DataFrame to an excel sheet with extension . xlsx. By default it writes a single DataFrame to an excel file, you can also write multiple sheets by using an ExcelWriter object with a target file name, and sheet name to write to.
Launch a . data file, or any other file on your PC, by double-clicking it. If your file associations are set up correctly, the application that's meant to open your . data file will open it.
Pandas expects a filename path to the ExcelWriter constructors although each of the writer engines support StringIO
. Perhaps that should be raised as a bug/feature request in Pandas.
In the meantime here is a workaround example using the Pandas xlsxwriter
engine:
import pandas as pd
import StringIO
io = StringIO.StringIO()
# Use a temp filename to keep pandas happy.
writer = pd.ExcelWriter('temp.xlsx', engine='xlsxwriter')
# Set the filename/file handle in the xlsxwriter.workbook object.
writer.book.filename = io
# Write the data frame to the StringIO object.
pd.DataFrame().to_excel(writer, sheet_name='Sheet1')
writer.save()
xlsx_data = io.getvalue()
Update: As of Pandas 0.17 it is now possible to do this more directly:
# Note, Python 2 example. For Python 3 use: output = io.BytesIO().
output = StringIO.StringIO()
# Use the StringIO object as the filehandle.
writer = pd.ExcelWriter(output, engine='xlsxwriter')
See also Saving the Dataframe output to a string in the XlsxWriter docs.
None of these were working from me. I had a view I wanted to return an excel workbook from in Django. I found my solution from the pandas documentation.
import io
bio = io.BytesIO()
writer = pd.ExcelWriter(bio, engine='xlsxwriter')
df.to_excel(writer, sheet_name='Sheet1')
writer.save()
bio.seek(0)
# BONUS CONTENT
# .. because I wanted to return from an api
response = HttpResponse(bio, content_type='application/vnd.openxmlformats-officedocument.spreadsheetml.sheet')
response['Content-Disposition'] = 'attachment; filename=myfile.xlsx'
return response # returned from a view here
Note, I used that value for content type because it was the mime type according to the mozzilla docs. From ".xlsx" in the following link. Replace as needed. https://developer.mozilla.org/en-US/docs/Web/HTTP/Basics_of_HTTP/MIME_types/Common_types
Glancing at the pandas.io.excel source looks like it shouldn't be too much of a problem if you don't mind using xlwt as your writer. The other engines may not be all that difficult either but xlwt jumps out as easy since its save method takes a stream or a filepath.
You need to initially pass in a filename just to make pandas happy as it checks the filename extension against the engine to make sure it's a supported format. But in the case of the xlwt engine, it just stuffs the filename into the object's path attribute and then uses it in the save method. If you change the path attribute to your stream, it'll happily save to that stream when you call the save method.
Here's an example:
import pandas as pd
import StringIO
import base64
df = pd.DataFrame.from_csv('http://moz.com/top500/domains/csv')
xlwt_writer = pd.io.excel.get_writer('xlwt')
my_writer = xlwt_writer('whatever.xls') #make pandas happy
xl_out = StringIO.StringIO()
my_writer.path = xl_out
df.to_excel(my_writer)
my_writer.save()
print base64.b64encode(xl_out.getvalue())
That's the quick, easy and slightly dirty way to do it. BTW... a cleaner way to do it is to subclass ExcelWriter (or one of it's existing subclasses, e.g. _XlwtWriter) -- but honestly there's so little involved in updating the path attribute, I voted to show you the easy way rather than go the slightly longer route.
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