Give a substantive commdnt on this post: When starting a project for data science the two main platforms are R and Python. R is more geared towards statistical analysis while Python is more of a general-purpose object-oriented language. For me personally, I would use Python for most of my projects since it is the easiest language to learn, and I do not have much experience with any programming language. One of the examples for choosing Python for data science would be data analytics. Python offers packages for data science such as pandas. Pandas allows us to analyze, manipulate, and clean data in Python. This library imports statistical analysis such as max, min, and variance functions. It also makes us be able to use data frames and set up columns and rows using one dimensional arrays that are similar to the vectors we use in R. After learning how to use pandas we can generate tables and compute statistical analysis to manipulate our data and make conclusions based on the data. We can also benefit from using Python with data visualization libraries such as matplotlib. Matplotlib works with pandas and can generate visuals such as a scatterplot or a bar graph. Matplot Development Team. (2023) Matplotlib: Visualization with Python. Matplotlib Visualization with Python