Handling Variable Number of Columns with Pandas – Python
I have a data set that looks like this (at most 5 columns – but can be less)
I have a data set that looks like this (at most 5 columns – but can be less)
I have a dataframe with over 200 columns. The issue is as they were generated the order is ['Q1.3','Q6.1','Q1.2','Q1.1',……] I need to sort the columns as follows: ['Q1.1','Q1.2','Q1.3',…..'Q6.1',……] Is there some way for me to do this within Python? Answers: Thank you for visiting the Q&A section on Magenaut. Please note that all the answers … Read more
I would like to shift a column in a Pandas DataFrame, but I haven’t been able to find a method to do it from the documentation without rewriting the whole DF. Does anyone know how to do it?
DataFrame:
I am new to Python and Pandas. I am trying to convert a Pandas Dataframe to a nested JSON. The function .to_json() doens’t give me enough flexibility for my aim.
I want to group my dataframe by two columns and then sort the aggregated results within the groups.
I have manipulated some data using pandas and now I want to carry out a batch save back to the database. This requires me to convert the dataframe into an array of tuples, with each tuple corresponding to a “row” of the dataframe.
I have a 14MB Excel file with five worksheets that I’m reading into a Pandas dataframe, and although the code below works, it takes 9 minutes!
I am reading contents of a spreadsheet into pandas. DataNitro has a method that returns a rectangular selection of cells as a list of lists. So
consider the list of lists l
If I import or create a pandas column that contains no spaces, I can access it as such: