As a data analyst, there will be a need for python as many companies require the knowledge of python. I embarked on 30 days of strict python with many hours of work each day to ground myself in python knowledge. It was a very stressful but rewarding exercise as it improved my skills and also laid a background for the rest of my data journey. Though O had a teacher, I also self-learned some aspects with exercises to buttress understanding. From simple arithmetic, data types, conditional statement (if and else), loops (for and while loop), pandas, NumPy, matplotlib, seaborne, etc. Data preprocessing was done as it is an essential part of data analysis. You cannot model or visualize dirty data hence, cleaning and preprocessing are done depending on what you need the data for. In this case, the data is processed for a machine-learning algorithm. Machine learning does not work with categorical data and Boolean hence, all Boolean values had to be converted to 1 and 0 for easy understanding.