From the course: Python vs. R for Data Science
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Data visualization in Python vs. R
From the course: Python vs. R for Data Science
Data visualization in Python vs. R
- One of the best parts of working with data is building visualizations. Visualizing data is crucial in any data science project as it helps you recognize trends, or patterns in the data. If you're working in Python, the Matplotlib and Seaborn libraries are powerful tools for plotting data. On the other hand, if you're working in R the foundational graphing tools are built into the base of R, and the more advanced graphing tools are available through the ggplot2 package. To demonstrate how visualizing data looks like in Python versus R let me walk you through an example. Let's say you have a dataset containing students' exam grades in a particular class loaded into a program. To visualize a distribution of the exam grades, you could create a histogram. In Python, you could accomplish this using Matplotlib on its own, or a combination of Matplotlib and Seaborn. Note that Seaborn is built on top of Matplotlib. First, I…
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