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https://csc-ubc-okanagan.github.io/csc-data-blog/p/python-vs-r-how-to-decide

Python vs R - How To Decide?

Python and R are both very useful tools in academia, research, industry, and everywhere! They have a lot of similarities, but there are also many differences.\nThe purpose of this post is to help students to decide which language to learn first, according to their differences, similarities, and departmental practices.\nFirst, let’s introduce each, and talk about their main purposes.\nIntroducing Python Python is a general-purpose, object-oriented programming language. It was created in 1991, and it has a community of people who contribute to regularly updating libraries and improving efficiencies. It happens to be one of the most popular programming languages in the world. Some of the most common libraries for data-related tasks include NumPy (for arrays), Pandas (for data analysis and manipulation), and MatPlotLib (for data visualizations). Python is a powerful tool used for machine learning, deep learning, and modelling. Jupyter Notebook is a useful interface to pair with Python because it allows for clean, readable layouts to be shared with peers and users. Note that Jupyter Notebook also supports R.\n



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Python vs R - How To Decide?

https://csc-ubc-okanagan.github.io/csc-data-blog/p/python-vs-r-how-to-decide

Python and R are both very useful tools in academia, research, industry, and everywhere! They have a lot of similarities, but there are also many differences.\nThe purpose of this post is to help students to decide which language to learn first, according to their differences, similarities, and departmental practices.\nFirst, let’s introduce each, and talk about their main purposes.\nIntroducing Python Python is a general-purpose, object-oriented programming language. It was created in 1991, and it has a community of people who contribute to regularly updating libraries and improving efficiencies. It happens to be one of the most popular programming languages in the world. Some of the most common libraries for data-related tasks include NumPy (for arrays), Pandas (for data analysis and manipulation), and MatPlotLib (for data visualizations). Python is a powerful tool used for machine learning, deep learning, and modelling. Jupyter Notebook is a useful interface to pair with Python because it allows for clean, readable layouts to be shared with peers and users. Note that Jupyter Notebook also supports R.\n



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https://csc-ubc-okanagan.github.io/csc-data-blog/p/python-vs-r-how-to-decide

Python vs R - How To Decide?

Python and R are both very useful tools in academia, research, industry, and everywhere! They have a lot of similarities, but there are also many differences.\nThe purpose of this post is to help students to decide which language to learn first, according to their differences, similarities, and departmental practices.\nFirst, let’s introduce each, and talk about their main purposes.\nIntroducing Python Python is a general-purpose, object-oriented programming language. It was created in 1991, and it has a community of people who contribute to regularly updating libraries and improving efficiencies. It happens to be one of the most popular programming languages in the world. Some of the most common libraries for data-related tasks include NumPy (for arrays), Pandas (for data analysis and manipulation), and MatPlotLib (for data visualizations). Python is a powerful tool used for machine learning, deep learning, and modelling. Jupyter Notebook is a useful interface to pair with Python because it allows for clean, readable layouts to be shared with peers and users. Note that Jupyter Notebook also supports R.\n

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      Python and R are both very useful tools in academia, research, industry, and everywhere! They have a lot of similarities, but there are also many differences.\nThe purpose of this post is to help students to decide which language to learn first, according to their differences, similarities, and departmental practices.\nFirst, let’s introduce each, and talk about their main purposes.\nIntroducing Python Python is a general-purpose, object-oriented programming language. It was created in 1991, and it has a community of people who contribute to regularly updating libraries and improving efficiencies. It happens to be one of the most popular programming languages in the world. Some of the most common libraries for data-related tasks include NumPy (for arrays), Pandas (for data analysis and manipulation), and MatPlotLib (for data visualizations). Python is a powerful tool used for machine learning, deep learning, and modelling. Jupyter Notebook is a useful interface to pair with Python because it allows for clean, readable layouts to be shared with peers and users. Note that Jupyter Notebook also supports R.\n
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      Python and R are both very useful tools in academia, research, industry, and everywhere! They have a lot of similarities, but there are also many differences.\nThe purpose of this post is to help students to decide which language to learn first, according to their differences, similarities, and departmental practices.\nFirst, let’s introduce each, and talk about their main purposes.\nIntroducing Python Python is a general-purpose, object-oriented programming language. It was created in 1991, and it has a community of people who contribute to regularly updating libraries and improving efficiencies. It happens to be one of the most popular programming languages in the world. Some of the most common libraries for data-related tasks include NumPy (for arrays), Pandas (for data analysis and manipulation), and MatPlotLib (for data visualizations). Python is a powerful tool used for machine learning, deep learning, and modelling. Jupyter Notebook is a useful interface to pair with Python because it allows for clean, readable layouts to be shared with peers and users. Note that Jupyter Notebook also supports R.\n
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      Python and R are both very useful tools in academia, research, industry, and everywhere! They have a lot of similarities, but there are also many differences.\nThe purpose of this post is to help students to decide which language to learn first, according to their differences, similarities, and departmental practices.\nFirst, let’s introduce each, and talk about their main purposes.\nIntroducing Python Python is a general-purpose, object-oriented programming language. It was created in 1991, and it has a community of people who contribute to regularly updating libraries and improving efficiencies. It happens to be one of the most popular programming languages in the world. Some of the most common libraries for data-related tasks include NumPy (for arrays), Pandas (for data analysis and manipulation), and MatPlotLib (for data visualizations). Python is a powerful tool used for machine learning, deep learning, and modelling. Jupyter Notebook is a useful interface to pair with Python because it allows for clean, readable layouts to be shared with peers and users. Note that Jupyter Notebook also supports R.\n

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