In this blog post graphic methods are used to describe tourism time series in Slovenia.

Two types of a line graph could be used to show changes in tourist demand over time. The first displays all three time series (total, domestic and foreign tourists) on a single graph. This graph shows the relative position of time series to each other. However, if the time series levels are disproportional in size then on this graph is difficult to spot patterns in time series.

The second graph displays each series on a separate panel. On such graph any persistent pattern related to trend or seasonal factors should be clearly visible.

Figure 1 shows line graphs of tourists arrival and overnight stay in Slovenia.

From Figure 1 is quite clear that the foreign tourists made a major contribution to total tourists arrival and overnight stay, particularly since 2013. While both total and foreign tourists arrival series show quite similar seasonal patterns, this pattern is not clear for the domestic tourists arrival series because the level of this series is much lower than the levels of the remaining two series on this graph.

Figure 2 shows each tourism time series in Slovenia on separate panels.

On the graphs in Figure 2 the seasonal patterns of total and foreign tourists arrival and overnight stay are very similar. The differences in seasonal patterns between domestic and foreign tourists arrival and overnight stay are prominent. Now it is clear that the domestic tourists arrivals series has quite distinctive seasonal pattern than the other two series. These differences will be further examine on the seasonal plots.

Trends, as another feature of domestic and foreign tourists arrival and overnight stay series are quite different. While domestic tourists time series display oscillation around some constant level until 2014 and increase after that, total and foreign tourists time series show an increasing trend in the whole period. These differences between time series will be further examine after decomposing time series into trend, season and residual series.