You will learn how to create an **interactive line plot in R** using the highchart R package.

Contents:

## Loading required R packages

```
# Load required R packages
library(tidyverse)
library(highcharter)
# Set highcharter options
options(highcharter.theme = hc_theme_smpl(tooltip = list(valueDecimals = 2)))
```

## Data preparation

We’ll create two data frames derived from the `ToothGrowth`

datasets.

```
df <- data.frame(dose=c("D0.5", "D1", "D2"),
len=c(4.2, 10, 29.5))
head(df, 4)
```

```
## dose len
## 1 D0.5 4.2
## 2 D1 10.0
## 3 D2 29.5
```

```
df2 <- data.frame(supp=rep(c("VC", "OJ"), each=3),
dose=rep(c("D0.5", "D1", "D2"),2),
len=c(6.8, 15, 33, 4.2, 10, 29.5))
head(df2, 4)
```

```
## supp dose len
## 1 VC D0.5 6.8
## 2 VC D1 15.0
## 3 VC D2 33.0
## 4 OJ D0.5 4.2
```

`len`

: Tooth length`dose`

: Dose in milligrams (0.5, 1, 2)`supp`

: Supplement type (VC or OJ)

## Basic line plots

```
hc <- df %>% hchart(
'line', hcaes(x = dose, y = len),
color = "steelblue"
)
```

`hc`

## Line plot with multiple groups

```
hc <- df2 %>%
hchart(
'line', hcaes(x = dose, y = len, group = supp)
) %>%
hc_colors(c("#999999", "#E69F00"))
```

`hc`

## Line plot with a numeric x-axis

If the variable on x-axis is numeric, it can be useful to treat it as a continuous or a factor variable depending on what you want to do:

```
# Create some data
df3 <- data.frame(supp=rep(c("VC", "OJ"), each=3),
dose=rep(c("0.5", "1", "2"),2),
len=c(6.8, 15, 33, 4.2, 10, 29.5))
head(df3)
```

```
## supp dose len
## 1 VC 0.5 6.8
## 2 VC 1 15.0
## 3 VC 2 33.0
## 4 OJ 0.5 4.2
## 5 OJ 1 10.0
## 6 OJ 2 29.5
```

X axis treated as continuous variable:

```
df3$dose <- as.numeric(as.vector(df3$dose))
hc <- df3 %>%
hchart('line', hcaes(x = dose, y = len, group = supp))
```

`hc`

X axis treated as discrete variable:

```
df3$dose<-as.factor(df3$dose)
hc <- df3 %>%
hchart('line', hcaes(x = dose, y = len, group = supp))
```

`hc`

## Line plot with dates on x-axis: Time series

```
# Economic time series data
# Check automatically if the x column is date class
data(economics_long, package = "ggplot2")
economics_long2 <- economics_long %>%
dplyr::filter(variable %in% c("pop", "uempmed", "unemploy"))
economics_long2
```

```
## # A tibble: 1,722 x 4
## date variable value value01
## <date> <chr> <dbl> <dbl>
## 1 1967-07-01 pop 198712 0
## 2 1967-08-01 pop 198911 0.00164
## 3 1967-09-01 pop 199113 0.00330
## 4 1967-10-01 pop 199311 0.00492
## 5 1967-11-01 pop 199498 0.00646
## 6 1967-12-01 pop 199657 0.00777
## # … with 1,716 more rows
```

```
hc <- hchart(
economics_long2, "line",
hcaes(x = date, y = value01, group = variable)
)
```

`hc`

## Spline: Line with polynomial interpolation

```
# Data preparation
data("diamonds", package = "ggplot2")
df4 <- diamonds %>%
group_by(cut, color)%>%
count()
# Spline Plot
hc <- df4 %>%
hchart('spline', hcaes(x = 'cut', y = 'n', group = "color"))
```

`hc`

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