Hurrrray
I get it now.
I simply need to save a table I need as ned data frame and export it.
I did that:
ddply(NL.Current.data, .(year,hy), summarize, A2TB=mean(A2TB), B1=mean(B1), C1=mean(C1), D1=mean(D1,na.rm=TRUE), E1=mean(E1), F1=mean(F1), G1=mean(G1))
having this in my console:
year hy A2TB B1 C1 D1 E1 F1 G1
1 2017 2 80.02937 91.64464 92.86344 84.05172 92.29075 93.95742 58.46549
2 2018 1 79.39543 91.75817 92.38125 85.85480 91.81370 93.25725 56.78593
3 2018 2 78.93082 91.24738 92.45283 86.92946 91.56184 92.98742 56.06918
then I saved that as df.stats dataframe:
df.stats <- ddply(NL.Current.data, .(year,hy), summarize, A2TB=mean(A2TB), B1=mean(B1), C1=mean(C1), D1=mean(D1,na.rm=TRUE), E1=mean(E1), F1=mean(F1), G1=mean(G1))
and used Adam83's code:
df.stats
write.xlsx(df.stats, "writeStats.xlsx", colNames = TRUE, rowNames=TRUE)
and I've got my Excel table!
Well done and thank you very much!!!
The only issue I have now is exporting CrossTables (generated in my reprex using gmodels library) as a different solution is required I suppose...