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Python Rgonomics | Emily Riederer

emilyriederer.com

Switching languages is about switching mindsets - not just syntax. New developments in python data science toolings, like polars and seaborn’s object interface, can capture the ‘feel’ that converts from R/tidyverse love while opening the door to truly pythonic workflows

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Comparing dplyr with polars

Data manipulation is one of the most common and essential tasks in data analysis. Whether you are working with tabular data, time series, spatial data, or any other kind of data, you need to be able to perform operations such as filtering, grouping, aggregating, joining, reshaping, and more. In the R world, the dplyr package is one of the most popular and powerful tools for data manipulation. It provides a consistent and expressive syntax based on the tidyverse principles, which make it easy to write readable and maintainable code. Many other packages extend its functionality, allowing you to work with large and diverse data sources.

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