Different data analysis tools: R vs Python vs Excel
Different data analysis tools
Source: fast campus (https://www.fastcampus.co.kr/)
- There are many tools for data analysis.
- Each tool has its own strength so that acknowledging the difference and smartly using different tools depending on situations is important for analysists.
R
- R has long been used for statistical analysis and visualization.
- R provides abundant statistics functions.
- Yet, as it is specialized in statistics, R is difficult to extend to other systems.
- Relatively slow.
Python
-
Not only for analysis, but also extensible to different systems for example using APIs.
-
Python has gotten great attention for its performance on deep learning (recently python usage has overtaken R usage).
-
Faster than R (but slower than Java or C).
-
Yet, Python is general purpose language in comparison with R which has clearer focus on statistics computation.
Excel
-
Conventional spreadsheet program.
-
Easy to make reports clicking button.
-
Yet, data should be structured and the size of data matters.
Then, which suits best for us?
-
R when you have a project in which statistical accuracy greatly matters.
-
Python if you need fast performance and you want various links with other systems.
-
Excel if you need a quick report by using relatively less large and structured data.
More to read
- Python or R: Which Is A Better Choice For Data Science? (https://habr.com/en/post/482500/)
- Python vs R for Data Science (https://towardsdatascience.com/python-vs-r-for-data-science-6a83e4541000)
Reference
- 패스트캠퍼스 데이터 분석 입문 올인원 패키지 강의