- R Graphs Cookbook Second Edition
- Jaynal Abedin Hrishi V. Mittal
- 254字
- 2021-08-05 17:30:34
Introduction
In this chapter, we will learn about scatter plots in depth by looking at some advanced recipes. Scatter plots are one of the most commonly used type of graphs in data analysis. In the first chapter, we learned how to create a basic scatter plot. Now, we will learn how we can create more enhanced plots by adjusting various arguments and using some new functions.
So far, we have mostly only used the base graphics functions such as plot()
, but in this chapter, we have recipes that use other graph libraries such as lattice
and ggplot2
, which offer more advanced control over graphs. It is possible to create these advanced graphs using the base library too, but the additional libraries give us ways to achieve the same results with less code and often produce better-looking graphs with the least amount of effort.
A lot of new functions will be introduced in this chapter. It is a good practice to look up the help file whenever you encounter a new function. For example, to look up the help file for the plot()
function, you can type ?plot
or help(plot)
in the R command prompt.
As the recipes in this chapter are slightly more advanced than the earlier chapters, you may require some practice with multiple datasets before you are comfortable with using all the functions. Example datasets are used in each recipe, but it is highly recommended that you also work with your own datasets and modify the recipes to suit your own analysis.
- Creating Dynamic UI with Android Fragments
- 施耐德SoMachine控制器應用及編程指南
- INSTANT Wijmo Widgets How-to
- 現代辦公設備使用與維護
- 平衡掌控者:游戲數值經濟設計
- Large Scale Machine Learning with Python
- 嵌入式系統中的模擬電路設計
- 基于Apache Kylin構建大數據分析平臺
- 微軟互聯網信息服務(IIS)最佳實踐 (微軟技術開發者叢書)
- 筆記本電腦維修300問
- 深入理解序列化與反序列化
- Blender Quick Start Guide
- 超大流量分布式系統架構解決方案:人人都是架構師2.0
- 基于PROTEUS的電路設計、仿真與制板
- Hands-On Deep Learning for Images with TensorFlow