Python for Data Scientists | R or Python for Data Analysis?

Python for Data Scientists

Python and R are the two leading contenders for data scientists, with many statisticians running out to complete an R or Python for data scientists course. However before investing in R or Python training, it is essential that you investigate which of these languages is best for your needs and for data analysis.

Why Python is Great for Data Science:

Since its release in 1989, Python offers many benefits for data scientists such as object-oriented programming, and powerful integrated development environments (IDE’s). Furthermore, there is a significant Python community to answer any questions, Anaconda for effectively managing packages, and libraries such as Panda, that simplifies working with data frames and time series data. 

Although Python was not developed specifically for data scientists, it is a general purpose language that is simple and intuitive with a very flat learning curve, and minimal time needed to write a program. It is possible to create visualisations using Python, however unlike those of R, visualisations done on Python are often more convoluted and less aesthetically pleasing.

Why R is Great for Data Science:

Created in 1992, R was able to learn from Python before its release. Similarly to Python, R offers RStudio, a powerful IDE, and allows for the capabilities of the language to be extended with C++. With the use of CRAN, a network of ftp and web servers around the world that store identical, up-to-date, versions of code and documentation for R, data scientists can utilise a variety of machine learning algorithms and statistical tools. 

R is a brilliant language for visualised data with numerous visualisation packages such as ggplot2, ggvis, googleVis and rCharts. Although R may be slow to run at times and can have a steep learning curve, it was a language developed by data scientists for data scientists and has therefore become the lingua franca of data science. 

Despite not offering an alternative to the hundreds of essential R packages, Python remains a challenger to R as a tool for data science. Although it’s catching up, it’s still unclear if this will make people give up R. JBI offers Python training, for a range of courses such as a regular Python course, a Python (Advanced) course, and a Python for data scientists course. As Python edges closer and closer to overtaking R as the lingua franca of data science, don’t miss your opportunity to do a Python for data scientists course with JBI today!

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