R and Python have differences as many as simiralities. Through their comparisons, we can understand both languages better and use them effectively. I will take a look at some examples from de facto standard packages such as tidyverse and pandas for data munging tasks, and ggplot2 and matplotlib (and seaborn) for data visualisation.

  1. Differences between R and Python as Language

    • Procedural and object-oriented programming
    • Specific and general purpose
  2. Data Wrangling

    • tidyverse
    • pandas
  3. Data Visualisation

    • ggplot2
    • matplotlib
    • plotly
  4. Some Other Cases (depending on time and interest)

    • Machine learning
    • Deep learning
    • Big data (distributed data processing)
    • Natural language processing
  5. Conclusion

    • To be bilingual

Yuta Kanzawa

Affiliation: Janssen Pharmaceutical K.K., Tokyo; Johnson & Johnson

Data Scientist at Janssen Pharmaceutical K.K., a family company of Johnson & Johnson in Tokyo. I have more than 6 years of experience and have worked at Janssen for 3 years collaborating successfully with commercial colleagues and senior management to deliver strategic insights through data science.

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