

Simply click on the data series line in your graph, and each data point should then be highlighted. Alright, so now we are going to add a trend line to see if there isn't a longer-term signal embedded in the monthly data.Obviously we only plotted 3 years of data, but you should have plotted at least 30 years or more from your datasets so you could look at this issue in your data.


In this case, the seasonal fluctuation is about 30 cm (300 mm). You could even calculate the average seasonal range of sea level from your dataset because you now have the data.This suggests Panama experiences a persistent seasonal sea level change. Looking at our dataset (Figure 4.51 above), it looks like there are annual highs and lows where tides are high for about 8 months (May-December) every year, and are relatively low for 4 months (January-April).In the dataset example used here, remember, we are looking at monthly averages, so the data we downloaded is the 30-day average for each month therefore all tides in a given month are averaged to a single value.In fact you may see trends and patterns that we discussed throughout the module. You will begin to see patterns or trends in the data. At this point, it is a good idea to look at the data and see what is going on with tides.
