Time Series data is a sequence of data points that are measured at regular intervals over time. Plotting time series data is a useful way to visualize trends and patterns over time. Highcharter is an R package that provides an interface to the Highcharts JavaScript charting library. Highcharts is a popular web application library for creating interactive charts and graphs. In this article, we will explore how to use Highcharter to plot time series data in R.Before we can use Highcharter, we need to install it. We can do this using the install.packages() function in R Programming Language:We will use the AirPassengers dataset, which contains monthly totals of international airline passengers from January 1949 to December 1960. This dataset is included with the base R installation and can be loaded using the data() function:Output:To create a basic time series plot using Highcharter, we need to first convert our data into a format that Highcharter can understand. We will use the xts package to convert our data into a time series object, and then use the hchart() function in Highcharter to create the plot:Output:Basic time series plot using highcharter libraryHighcharter provides many options for customizing the appearance of the plot. Here are a few examples:Output:Added plot options in the time series plothighcharter provides many options for customizing time series plots. Here, we will demonstrate some of the commonly used customizations.We can add a title and subtitle to our plot using the hc_titel( ) and hc_subtitle( ) functions. These functions take similar arguments and have similar functionality. Here are the main arguments that both functions take:Output:Adding Title and Subtitle Label to the high charter plotsObserve in the above graph, Title “Average Monthly Temperatures in Nottingham, England” and the subtitle “1920-1939” have been added to the basic timeseries plot.We can change the x-axis and y-axis labels using the hc_xAxis( ) and hc_yAxis( ) functions respectively. hc_xAxis() is used to modify the properties of the X-axis. It takes several arguments, including:ParameterDescription`title``type``categories``labels`hc_yAxis() is used to modify the properties of the Y axis. It takes similar arguments to hc_xAxis(), including:ParameterDescription`title``type``max``min``opposite`Output:Adding Axis Label to the high charter plotsObserve we have changed the Y-axis label (“Temperature (F)) as compared to our previous time-series plot. The hc_tooltip() function is used to customize the tooltip of the Highcharts object. The tooltip is a floating box that appears when the user hovers over a point on the chart. The hc_tooltip() function takes several arguments that can be used to customize the tooltip, including:ParameterDescription`formatter``enabled``useHTML``headerFormat``pointFormat``footerFormat``valueDecimals`The other arguments taken by this function are “valuePrefix”, “valueSuffix”, “backgroundColor”, “borderColor”, “borderRadius”, “borderWidth” and “style”.Output:Adding Data Label to the high charter plotsObserve the data label displayed as we hover the cursor on the plot. We can customize the data label elements as per the requirement.We can add annotations to our plot using the hc_annotations( ) function. Annotations are graphical elements that can be added to a chart to provide additional information or highlight specific data points. The main arguments of the hc_annotations() function are:Output:Adding annotation to the high charter plotsObserve the annotation added on the y-axis for the temperature of the month of July 1934 which is the month with the highest temperature.In conclusion, Highcharter is a powerful R library for creating interactive and dynamic time series visualizations. With its intuitive syntax and easy-to-use functions, Highcharter makes it easy to create professional-looking charts and graphs with minimal effort. In this article, we covered the basics of creating time series plots using Highcharter, including how to set up data, create charts, and customize the appearance of the plot. We also showed some advanced features such as adding annotations, changing the plot type, and adding multiple series. Overall, Highcharter is a great tool for anyone looking to create high-quality time series visualizations quickly and easily.