![]() ![]() Live with it"įlask-Excel is based on pyexcel and makes Surely, it must be in an excel format."ĭeveloper: "OK. "but your application says un-supported file format"ĭeveloper: "Did you upload an xlsx file or a csv file?" Here is a typical conversation between the developer and the user: User: "I have uploaded an excel file" Known constraintsįonts, colors and charts are not supported. With your financial support, I will be able to investĪ little bit more time in coding, documentation and writing interesting posts. As a patreon, you will receiveĮarly access to pyexcel related contents. If you are an individual, you are welcome to support me too on patreon and for however long Maintain the project and develop it further. ![]() If you want to save multiple dataframes into the same Excel file, check out this post here.If your company has embedded pyexcel and its components into a revenue generating Note this short post talks about how to save one dataframe into an Excel file. Just want to point out a minor difference, but this is really a difference between Excel and CSV file.ĬSV file is basically a text file, it contains only 1 sheet, so we can’t rename the sheet. The arguments are similar to to_excel() so I won’t repeat them here. We can save the same dataframe to a csv file by using df.to_csv(). I normally don’t use this, as I drop the columns in the dataframe before saving to file. columns: choose the columns you want to output.However, if your dataframe contains numbers, you might want to set this to np_rep = 0 instead. na_rep: value to replace the “Null” values in the dataframe, by default this is an empty string “”.sheet_name: you can name the sheet if you don’t like “Sheet1” by default.We can remove that list from our Excel output file by: df.to_excel('saved_file.xlsx', index = False) Other useful optional arguments to_excel() method provides an optional argument index, which is for controlling that list we just saw. ![]() But for me, that column always bothers me when I look at my files, I have to get rid of it… Removing the starting index when saving an Excel file using pandas If you are okay with leaving it there, fine. We immediately notice something weird… column A contains something looks like a list starting from 0. Let’s open up the file and see if it has the same data inside. import pandas as pdĭf.to_excel('saved_file.xlsx') Python saves an Excel fileĪfter executing the above code, we’ll have a new file called “saved_file.xlsx”, which was created by Python. We’ll use the same file used for the read_excel() example. Let’s look at an example, first we need to have a dataframe ready for saving. We will look at only a few of the arguments here, if you want to learn the full list of arguments, I suggest you read the pandas official documentation. Similar to df.read_excel(), this to_excel() method also has many optional arguments. The simplest way is like this: df.to_excel(), which saves the dataframe into an Excel file. Saving data to Excel file is also easy using pandas. But, we can use another language to make our jobs easier □ Save data to an Excel file Why Excel again? Well, because we are office workers and most our managers and coworkers only know Excel, we have to speak their language. Another important thing to know is how to save data back into Excel file using Python. We have already learned how to read data from Excel files. ![]()
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