How to use the Seasonal Graphing in MP-Web
Introduction
Seasonal charts, sometimes called Cyclic Charts, display trends over time and are grouped over set periods. The examples below show rainfall at a weather station over a 10-year period.
The first graph shows the data as a continuous time series bar chart created using the Bar Chart Time Series. This would help establish trends over a linear period, such as how much rainfall had fallen in a given period.
The second graph groups the data monthly, each year a distinct series. This provides better visibility of trends that happen periodically or seasonally instead of over a linear time series.
The third chart further groups all the years to show, in this case, the range grouped by month over the 10 years.
This includes the option to add in multiple Variables.
Chart Type
Users can choose the chart type from either line or bar.
The first is an example of some noise data displayed as a bar. In this example, data is grouped by a day in each series.
This example uses the same data but is represented as a line. Here, each daily series is connected, enabling the user to see a more continuous trend throughout the chosen period than via the bar chart option.
Chart Period
Options to group the data via Day, Weekdays, Month, Weekly and Yearly are provided.
Day - Each series will be a day, and each increment of the x-axis is an hour of the day. This is useful for high-volume data, such as hourly, to observe trends over several days.
Weekdays - Each series will be a week, and each increment of the x-axis will represent a day of the week. This is useful for more periodic data, such as daily, to observe trends over several weeks.
Month - Each series will be a month, and each increment of the x-axis will represent a day of the month. This is useful for more periodic data, such as daily, to observe trends over several months.
Weekly - Each series will be a year, and each increment of the x-axis will represent a week of the year. This is useful for more periodic data, such as daily, to observe trends over several years compared to the weeks of the year.
Yearly - Each series will be a year, and each increment of the x-axis will represent a month of the year. This is useful for more periodic data, such as daily or monthly, to observe trends over several years compared to the months of the year.
Sample Points and Variables
If the Dataset includes multiple Sites/Data Types, the user will first be given the option to choose the appropriate one. Then, users can select the Sample Point(s) and Variables to be plotted. In many use cases, comparisons will be best made with a single Sample Point and Variable. However, the option to include more is provided where applicable.
Below is a yearly plot which includes a single dust location for two years.
Below is a yearly plot which includes multiple dust locations for two years.
Summarisation
Aggregate Across Cycles
Aggregation across cycles combines the values into the x-axis ranges (in the below example, monthly) but does not split them into distinct series (in this example, years are combined). This is useful for examining collective seasonal trends across multiple periods.
The example below is similar, but this example contains multiple Sample Points, and where data spans multiple periods simplifies the plot.
The same concept with three different Variables at a standard Sample Point.
Summary Function
The amount of summarisation that MonitorPro will conduct will depend on the frequency of the underlying data and the Chart Period applied. Users should be sure not to include data frequencies that do not apply to the selected period. Where MonitorPro is summarising data, the user should choose the appropriate summary function. The options are Max, Min, Average, Sum, Standard Deviation, Count, and Most Recent.
The below are the same data but as Max
As Sum
And Avg
Split By
Split By gives the option to refine each series of plots to the distinct Data Source or Sample Type. This gives a range of options to compare data based on indicators such as laboratory, depth, equipment, etc.
Annual plot unsplit
Same data split via Sample Type
Split by Sample Type, including multiple Sample Points.
