Looking at the different script inside this repository, some still very raw, you can evaluate how my coding style evolved.
This code is made to analyze Pomodoro Techniques Logs and understand how well Data Science with Python practice is going. The practice could be python working related task,study, no-profit projects, even reading a data science book.
The goal is to reach 10.000 hours to be an expert. It's just a trivial proxy but gives an idea and a direction and it's enough.
The last colab notebook Andrea_Ciufo_Python_Growth takes as input the link on Google Drive where is located the csv file, and then it starts filtering and processing the data.
This is the comparison with an ideal 3h a day allocated to "Python Activity", the comparison is quite tough because is expected to work and practice also during holidays and weekends or when I worked as a building site engineer supervisor or as a General Manager for Papardò
In the oldest script you can find also the forecasts based on three estimators on the remaining time to become an expert:
-Markov's Inequality
-Linear regression (I know that variables are not independently and identically distributed)
-Non-Linear Regression using #Prophet, an open-source library developed by Facebook