Just wanted to share my exit survey and get some feedback. Analyzed the resignation data along the lines of tenure and age. I know that I didn’t do a conclusion, as I was focused on figuring out the code.
This is a very brillaint move and be assured you’ve accomplished a big step towards professionalism as we all are striving to.
A few observations here:
A very good project flow you followed and it is commendable. I love your visualizations as charts were explanatory.
One very vital part I discovered is missisng in your presentation was adding “comments” above your codes. Comments beginning with ‘#’ above your codes help inform the reader of what to expect or what you are about to do in the lines below and then you too, in the case you return to the project days, weeks or even years after, you understand what’s going on in the project. We all(humans) forget things a lot.
It is good practice to import all modules you intend applying at the beginning of every project like in cell  as againt your “numpy” import in cell  like so:
#importing modules for the project import pandas as pd import numpy as np import matplotlib.pyplot as plt %matplotlib inline
- It is also good practice to include a “Conclusion” sub-heading as a summary the insights you have discovered and what next could be done to further improve your analysis.
A nice job. Well done.
- Line 14 of your code, I suppose you wanted to print results , but put # so your line code became just a comment.
- You have a lot of print() function, you can see output without this function in table format. May be, you want to see all columns , then you can use option pd.options.display.max_columns . Here is the link on documentation Options and settings — pandas 1.4.3 documentation