How to manipulate strings in both libraries

Textual data does not usually come in a nice and clean format so it requires a lot of preprocessing and manipulation. A substantial amount or raw data is textual so a data analysis library should be able to handle strings very well.

In this article, we will compare two popular libraries in terms of working on strings. The first one is pandas, a data analysis and manipulation library for Python. The other is the tidyverse which is a collection of R packages designed for data science.

We will be using the cities dataframe for the examples in Pandas. I have also created a tibble that contains the same data using the readr package in R.

#python #r #machine-learning #data-science #pandas vs tidyverse on textual data #textual data