I concluded that Python sucks for data wrangling and visualization. Oh boy, where do I start? Maybe my usual venting that python's integer starts from zero? or pandas syntax is pretty much like the worse version of base R? The only thing why I invested my time learning python is, because it's simply popular and pretty much used everywhere. However if I have to recommend whether you should start your data science journey: pick R.
The experience of data wrangling with dplyr is much better and intuitive and it's capable for machine learning too. The only catch? R is considered as a niche language and mostly used by academics. I didn't learn R during my grad school (which I think, was surprising because Hadley Wickham, the founder of R studio was from new zealand), however I picked R last year and have been using it for almost daily basis to the point I am confident I have an intermediate skills in R.
One thing I haven't explored in R though: creating maps and making web-based apps (you can use shiny for that). It's just that I am also fairly proficient in Power BI and I could just create a dashboard with power BI whenever necessary. Shiny requires me to learn a skill of being a web developer which I am not really interested in.
At the moment I am still on my progress completing my Python machine learning course . So far I already finished simple linear regression, multiple linear regression, polynomial regression, and support vector regression. Before I continue further, I think I want to understand how to apply the last two in real-life scenarios. Since I am learning ML in python, honestly, the experience is less pleasant, but I force myself to focus myself in python to ensure I maintain my python proficiency, given that 80% of time I code with R.
The experience of data wrangling with dplyr is much better and intuitive and it's capable for machine learning too. The only catch? R is considered as a niche language and mostly used by academics. I didn't learn R during my grad school (which I think, was surprising because Hadley Wickham, the founder of R studio was from new zealand), however I picked R last year and have been using it for almost daily basis to the point I am confident I have an intermediate skills in R.
One thing I haven't explored in R though: creating maps and making web-based apps (you can use shiny for that). It's just that I am also fairly proficient in Power BI and I could just create a dashboard with power BI whenever necessary. Shiny requires me to learn a skill of being a web developer which I am not really interested in.
At the moment I am still on my progress completing my Python machine learning course . So far I already finished simple linear regression, multiple linear regression, polynomial regression, and support vector regression. Before I continue further, I think I want to understand how to apply the last two in real-life scenarios. Since I am learning ML in python, honestly, the experience is less pleasant, but I force myself to focus myself in python to ensure I maintain my python proficiency, given that 80% of time I code with R.
