Learn more about computerscience with this collection
Understanding machine learning models
Improving data analysis and decision-making
How Google uses logic in machine learning
The main difference between R and Python
They approach data science differently:
- R is used for statistical analysis.
- Python provides a more general approach to data.
- R is built by statisticians and leans heavily into statistical models and specialised analytics.
- Python is a multipurpose language that can provide data analysis or machine learning in scalable production environments.
- You might use R for customer behaviour analysis or genomics research.
- You might use Python for developing a machine learning application.
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Other key differences
Data collection
- Python supports all kinds of data formats.
- R is designed for data analysts to import data from Excel, CSV and text files.
Data exploration
- In Python, you ...
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Python
- Python is a general-purpose, object-oriented programming language.
- It emphasises code readability by using white space.
- It is easy to learn.
- It is a f...
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Python vs. R: which one to choose
The language to choose depends on your situation.
Points to consider:
- Do you have programming experience? Python has a learning curve that's linear and smooth. With R, novices can Run data analysis tasks in minutes, but it takes longer to de...
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R
- R is also is an open-source programming language.
- It's optimised for statistical analysis and data visualisation.
- R has a rich ecosystem with complex data mode...
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Python data processing with pandas
Pandas is a Python language package, which is used for data processing. This is a very common basic programming library when we use Python language for machine learning programming. This article is an introductory tutorial to it. Pandas provide fast, flexible and expressive data structures with t...
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