I have an extensive set of code that results in 6 DataFrames per for-loop run. The column names are tailored to what vehicle I have running through the loops so the column names are different but the sizes of the dataframes are the same. I want to print a couple dataframes to the same sheet but I have issues with
Tag: pandas.excelwriter
How can I webscrape information in the html element and save it to an Excel row using Beautifulsoup and any excel writer(Pandas)? [closed]
Closed. This question needs details or clarity. It is not currently accepting answers. Want to improve this question? Add details and clarify the problem by editing this post. Closed last year. Improve this question I’m new to python and I’m doing it for my project. Can someone help me save it to an excel file?. This is needed for multiple
Exporting many excel files based on column value in pandas dataframe while maintaining formatting?
I have a dataframe that I would like to parse to individual files based on unique strings in a column “names.” I can do this with a simple function like: The caveat being that I would like write out these files with conditional formatting. I’ve been able to achieve the desired formatting using ExcelWriter in the following block: Is there
Sort filepaths according to their respective file extensions
I am trying to sort filepaths according to their respective file extensions. I would like to have an output like this: FileType FilePath .h a/b/c/d/xyz.h .h a/b/c/d/xyz1.h .class a/b/c/d/xyz.class .class a/b/c/d/xyz1.class .jar a/b/c/d/xyz.jar .jar a/b/c/d/xyz1.jar But the output I have now is like this: output in excel Below is my code: Could anyone please help me with this. Thanks in
Coloring pivot table pandas dataframe
I have a pivot table created using pandas which looks like below: I want to apply color for the entire column based on account name starts with. Ex: If account name starts with “AA” color=yellow, if starts with “AB” then color = red How can I do that in python and save it into excel file? “Account” has been used