Dear all, I want to realize spatial analysis on rainfall data on a five minute time step. The data has the following format.
Station Stat_01 Stat_02 Stat_03 Stat_04 X 180000 195900 181950 192150 Y 157550 150950 154550 141650 30.04.11 00:05 0 0 0 0 30.04.11 00:10 0 0 0 0 30.04.11 00:15 0 0 0 0 30.04.11 00:20 0 0 0 0 30.04.11 00:25 0.2 0.4 1.2 0 30.04.11 00:30 0 0 0 0 30.04.11 00:35 0 0 0 0 30.04.11 00:40 0 0 0 0 30.04.11 00:45 0 0 0 0 30.04.11 00:50 0 0 0 0 When I convert the data now into SpatialPointsDataFrame I have to assign coordinates(data) < ~X+Y. All examples I saw until now are transposing the data first so that the coordinates are changed to columns. If I follow these examples and convert my data with t(data) I end up with a SpatialPointsDataFrame with a huge amount of columns and have performance problems to do some simple calculations through every object in the dataframe. I'm happy about any help Cheers Fabian _______________________________________________ R-sig-Geo mailing list [email protected] https://stat.ethz.ch/mailman/listinfo/r-sig-geo
