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r_programming_gl [2014/11/21 20:44] glaroc |
r_programming_gl [2014/11/21 21:31] (current) glaroc old revision restored (2014/11/21 15:54) |
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| + | ====== Knitr ====== | ||
| + | Knitr is a package that can be used to generate dynamic reports or web pages from R code. The code is evaluated at the moment the report is generated. | ||
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| + | Code can be easily written in RStudio use the Markdown language. View this page in Markdown language, and view the resulting web page. | ||
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| ====== Data Table ====== | ====== Data Table ====== | ||
| Data table is a very useful package in R which allows to facilitate and to improve the efficiency of certain operations in R. Data tables are just like data frames. You can even create them from data frames. | Data table is a very useful package in R which allows to facilitate and to improve the efficiency of certain operations in R. Data tables are just like data frames. You can even create them from data frames. | ||
| Line 27: | Line 33: | ||
| <file rsplus> | <file rsplus> | ||
| mydt['F'] | mydt['F'] | ||
| - | </file | + | </file> |
| Gives the mean value of column b for each letter in column a. | Gives the mean value of column b for each letter in column a. | ||
| Line 39: | Line 45: | ||
| </file> | </file> | ||
| - | With tapply() | + | **With tapply()** |
| <file rsplus> | <file rsplus> | ||
| system.time(t2<-tapply(mydf$b,mydf$a,mean)) | system.time(t2<-tapply(mydf$b,mydf$a,mean)) | ||
| </file> | </file> | ||
| - | With reshape2 | + | **With reshape2** |
| <file rsplus> | <file rsplus> | ||
| library(reshape2) | library(reshape2) | ||
| Line 51: | Line 57: | ||
| </file> | </file> | ||
| - | With plyr | + | **With plyr** |
| <file rsplus> | <file rsplus> | ||
| library(plyr) | library(plyr) | ||
| Line 57: | Line 63: | ||
| </file> | </file> | ||
| - | With sqldf. This package allows one to write Structured Query Language commands to perfom queries on a data frame. | + | **With sqldf**. This package allows one to write Structured Query Language commands to perfom queries on a data frame. |
| <file rsplus> | <file rsplus> | ||
| library(sqldf) | library(sqldf) | ||
| Line 63: | Line 69: | ||
| </file> | </file> | ||
| - | With a basic FOR loop | + | **With a basic FOR loop** |
| <file rsplus> | <file rsplus> | ||
| ti1<-proc.time() | ti1<-proc.time() | ||
| Line 74: | Line 80: | ||
| </file> | </file> | ||
| - | ### With a parallelized FOR loop | + | **With a parallelized FOR loop** |
| <file rsplus> | <file rsplus> | ||
| library(foreach) | library(foreach) | ||
| Line 92: | Line 98: | ||
| <file rsplus> | <file rsplus> | ||
| library(RgoogleMaps) | library(RgoogleMaps) | ||
| - | myhome=getGeoCode('McGill Biology Department'); | + | myhome=getGeoCode('Olympic stadium, Montreal'); |
| mymap<-GetMap(center=myhome, zoom=14) | mymap<-GetMap(center=myhome, zoom=14) | ||
| PlotOnStaticMap(mymap,lat=myhome['lat'],lon=myhome['lon'],cex=5,pch=10,lwd=3,col=c('red')); | PlotOnStaticMap(mymap,lat=myhome['lat'],lon=myhome['lon'],cex=5,pch=10,lwd=3,col=c('red')); | ||
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| dc[,c('toponymName')] | dc[,c('toponymName')] | ||
| </file> | </file> | ||
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