This article describes how to create a highstock chart in R using the highcharter R package.
Contents:
Loading required R packages
# Load required R packages
library(dplyr)
library(highcharter)
# Set highcharter options
options(highcharter.theme = hc_theme_smpl(tooltip = list(valueDecimals = 2)))Data preparation
Download exchange rates using the quantmod R package. The function getFX() is used. It returns an object of class xts which can be directly plotted using the highcharter R package.
library(quantmod)
x <- getFX("USD/JPY", auto.assign = FALSE)df <- as.data.frame(x)
head(df)## USD.JPY
## 2019-10-31 108
## 2019-11-01 108
## 2019-11-02 108
## 2019-11-03 108
## 2019-11-04 108
## 2019-11-05 109Visualize quantmod xts data
hc <- hchart(x)hcVisualize quantmod symbols data from different sources
# `xts ohlc` objects
library(quantmod)
y <- getSymbols("SPY", auto.assign = FALSE)hc <- hchart(y)hcCreate highstock chart from a data frame
hc <- highchart(type = "stock") %>%
hc_add_series(df$USD.JPY, type = "line")hcRecommended for you
This section contains best data science and self-development resources to help you on your path.
Coursera - Online Courses and Specialization
Data science
- Course: Machine Learning: Master the Fundamentals by Stanford
- Specialization: Data Science by Johns Hopkins University
- Specialization: Python for Everybody by University of Michigan
- Courses: Build Skills for a Top Job in any Industry by Coursera
- Specialization: Master Machine Learning Fundamentals by University of Washington
- Specialization: Statistics with R by Duke University
- Specialization: Software Development in R by Johns Hopkins University
- Specialization: Genomic Data Science by Johns Hopkins University
Popular Courses Launched in 2020
- Google IT Automation with Python by Google
- AI for Medicine by deeplearning.ai
- Epidemiology in Public Health Practice by Johns Hopkins University
- AWS Fundamentals by Amazon Web Services
Trending Courses
- The Science of Well-Being by Yale University
- Google IT Support Professional by Google
- Python for Everybody by University of Michigan
- IBM Data Science Professional Certificate by IBM
- Business Foundations by University of Pennsylvania
- Introduction to Psychology by Yale University
- Excel Skills for Business by Macquarie University
- Psychological First Aid by Johns Hopkins University
- Graphic Design by Cal Arts
Amazon FBA
Amazing Selling Machine
Books - Data Science
Our Books
- Practical Guide to Cluster Analysis in R by A. Kassambara (Datanovia)
- Practical Guide To Principal Component Methods in R by A. Kassambara (Datanovia)
- Machine Learning Essentials: Practical Guide in R by A. Kassambara (Datanovia)
- R Graphics Essentials for Great Data Visualization by A. Kassambara (Datanovia)
- GGPlot2 Essentials for Great Data Visualization in R by A. Kassambara (Datanovia)
- Network Analysis and Visualization in R by A. Kassambara (Datanovia)
- Practical Statistics in R for Comparing Groups: Numerical Variables by A. Kassambara (Datanovia)
- Inter-Rater Reliability Essentials: Practical Guide in R by A. Kassambara (Datanovia)
Others
- R for Data Science: Import, Tidy, Transform, Visualize, and Model Data by Hadley Wickham & Garrett Grolemund
- Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems by Aurelien Géron
- Practical Statistics for Data Scientists: 50 Essential Concepts by Peter Bruce & Andrew Bruce
- Hands-On Programming with R: Write Your Own Functions And Simulations by Garrett Grolemund & Hadley Wickham
- An Introduction to Statistical Learning: with Applications in R by Gareth James et al.
- Deep Learning with R by François Chollet & J.J. Allaire
- Deep Learning with Python by François Chollet
Version:
Français
No Comments