Feedback about Clean And Analyze Employee Exit Surveys

I have done the guided project on Clean And Analyze Employee Exit Surveys and would like to receive your valuable feedback especially about my analysis.
Thanks
Clean And Analyze Employee Exit Surveys.ipynb (126.6 KB)

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Hi @jafarinasim, congrats on finishing your project! I like that your started the intro with questions and made sure that you answered them in your conclusion. You also took some time to explain between steps what you were observing to keep the reader’s interest. I would advise making use of Markdown codes for headings to further break up the text into sections. The bold text helps, but the text sizes will make the divisions stand out more easily.

Thanks for sharing with us! Happy learning!

Thanks for your feedback. I have updated my project, the link is below. I appreciate it if you can also share your ideas about my analysis as well.

Clean And Analyze Employee Exit Surveys.ipynb (212.2 KB)

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Thanks for sharing the update! The changes made a big difference in the overall feel of the project. As far as the analysis, I didn’t see anything that was inconsistent with other students’ project. I thought it was interesting that you had a look at the DETE and TAFE datasets separately to see any differences between the two institutes with regard to dissatisfaction. It makes you wonder what each institute was doing to cause the dissatisfaction in one set and not the other! Would you have been able to do this from the already cleaned ‘combined’ dataframe (since we added the ‘institute’ column) instead of cleaning both the individual dete and tafe dataframes a 2nd time?

Thanks for your comments. I have updated the project using the combined data frame.

Clean And Analyze Employee Exit Surveys.ipynb (204.7 KB)

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