2/n Python was too much like coding. And I came from a business background. My main tool was Excel. Python was unnatural.
A friend of mine recommended me to try #R.
I was instantly surprised at how much more intuitive it was for me given my Excel background. Here's what R had:
A friend of mine recommended me to try #R.
I was instantly surprised at how much more intuitive it was for me given my Excel background. Here's what R had:
4/n
π#R has analytics built-in. I could do correlation and make trendlines with linear regression very easily.
π#R has analytics built-in. I could do correlation and make trendlines with linear regression very easily.
5/n
π#R had the #tidyverse. The tidyverse blew my mind. This toolkit includes data wrangling and visualization libraries that effortlessly worked together.
π#R had the #tidyverse. The tidyverse blew my mind. This toolkit includes data wrangling and visualization libraries that effortlessly worked together.
6/n
π #R had the pipe! If youβve never tried it, the pipe %>% is this amazing operation that allows you to flow your data transformations from one operation to another.
π #R had the pipe! If youβve never tried it, the pipe %>% is this amazing operation that allows you to flow your data transformations from one operation to another.
7/n
π#R has reporting! I was able to make a simple PDF report in minutes versus struggling with Jupyter.
π#R has reporting! I was able to make a simple PDF report in minutes versus struggling with Jupyter.
8/n
So I ended up picking #R and to this day Iβm so happy I did.
Want more information on how to become a data scientist with R?
Iβve consolidated my learnings into 10 secrets that I wished I knew going into data science.
learn.business-science.io
So I ended up picking #R and to this day Iβm so happy I did.
Want more information on how to become a data scientist with R?
Iβve consolidated my learnings into 10 secrets that I wished I knew going into data science.
learn.business-science.io
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