I loop through the whole dataframe in my example but you could select specific rows based on the index if you wanted to do so. I've posted a fully reproducible example below, using pandas and fpdf (it also uses numpy to create a sample dataframe). The FPDF library is fairly stragihtforward to use and is what I've used in this example. xlsx file.įor creating the pdf part, there are several options including pydf2, pdfdocument and FPDF. Please see fsspec and urllib for moreĭetails, and for more examples on storage options refer here.If you're just reading from excel and then creating an original pdf, I would recommend just using pandas.read_excel for reading the. starting with “s3://”, and “gcs://”) the key-value pairs areįorwarded to fsspec.open. For HTTP(S) URLs the key-value pairsĪre forwarded to as header options. storage_options dict, optionalĮxtra options that make sense for a particular storage connection, e.g. mode, default ‘w’įile mode to use (write or append). datetime_format str, default Noneįormat string for datetime objects written into Excel files. NOTE: can only be passed as a keywordįormat string for dates written into Excel files (e.g. engine str (optional)Įngine to use for writing. Otherwise, call close() to saveĪnd close any opened file handles. The writer should be used as a context manager. See DataFrame.to_excel for typical usage. ExcelWriter ( path, engine = None, date_format = None, datetime_format = None, mode = 'w', storage_options = None, if_sheet_exists = None, engine_kwargs = None ) #Ĭlass for writing DataFrame objects into excel sheets.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |