This article describes how to create an **interactive scatter plot in R** using the *highchart* R package.

Contents:

## Loading required R packages

`library(highcharter) `

## Data preparation

Demo dataset: `mtcars`

. The variable `cyl`

is used as grouping variable.

```
# Load data
data("mtcars")
df <- mtcars
# Convert cyl as a grouping variable
df$cyl <- as.factor(df$cyl)
# Inspect the data
head(df[, c("wt", "mpg", "cyl", "qsec")], 4)
```

```
## wt mpg cyl qsec
## Mazda RX4 2.62 21.0 6 16.5
## Mazda RX4 Wag 2.88 21.0 6 17.0
## Datsun 710 2.32 22.8 4 18.6
## Hornet 4 Drive 3.21 21.4 6 19.4
```

## Basic scatter plots

`hc <- df %>% hchart('scatter', hcaes(x = wt, y = mpg))`

`hc`

## Scatter plots with multiple groups

```
# Change color by groups
# Set custom colors
hc <- df %>%
hchart('scatter', hcaes(x = wt, y = mpg, group = cyl)) %>%
hc_colors(c("#00AFBB", "#E7B800", "#FC4E07"))
```

`hc`

## Add regression lines

```
# Fit regression model
library(dplyr)
library(broom)
model <- lm(mpg ~ wt, data = df)
fit <- augment(model) %>% arrange(wt)
# Visualization
hc <- df %>%
hchart('scatter', hcaes(x = wt, y = mpg, group = cyl)) %>%
hc_add_series(
fit, type = "line", hcaes(x = wt, y = .fitted),
name = "Fit", id = "fit"
)
```

`hc`

## Bubble chart

In a bubble chart, points `size`

is controlled by a continuous variable, here `qsec`

.

```
hc <- df %>%
hchart(
'scatter', hcaes(x = wt, y = mpg, size = qsec, group = cyl),
maxSize = "10%"
)
```

`hc`

## Color by a continuous variable

```
hc <- df %>%
hchart('scatter', hcaes(x = wt, y = mpg, color = mpg))
```

`hc`

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