# Because of these limitations, I decided to use an IPython Notebook for creating and fitting linear regression models and printing the results to Excel to share for those who use Excel exclusively and those who don't want to bother installing Python and/or using the Notebook (something I run into frequently in my current position). xlsx format, the data is copied in with additional headers and causes the actual column names to shift down one. # The second issue I came across taking data from the Data tab of the Excel workbook and loading it to process with Pandas.
The package xlrd contains an Image object, but it only works on bitmap files. One issue was I wanted to take the plot images generated and copy them into the Excel sheet however, I wasn't able to find a way to accomplish this. # During the process, I ran into several hurdles. # To accomplish this, I used statsmodels, pandas and xlwings. I also wanted to give a nice summary of the model statistics for users to determine the goodness-of-fit of the model.
# After working through a linear regression example using Python, I wanted to see if it was possible to create an Excel front-end and allow users to load their own datasets, set their parameters, fit a model, and get predictions based on the model, without having to code anything.
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