This is an example of how to use knitr for producing reports on data stored in Opal.
The requirement on client side is to have opal package installed:
install.packages("opal", repos = c(getOption("repos"), "http://cran.obiba.org"),
dependencies = TRUE)
The requirements on server side is:
The procedure is then the following:
Load the required libraries on client side and login in Opal (credentials and output are hidden)…
Assign some variables into a data.frame with associated D symbol in R on Opal server side:
opal.assign(o, "D", "mica_demo.FNAC", variables = c("SVUOSI", "SUKUP", "PITUUS",
"PAINO"))
Preview the assigned data.frame:
opal.execute(o, "head(D)")
## SVUOSI SUKUP PITUUS PAINO
## 1000502517535681229 1956 2 1.718 50.60
## 1007286407843912597 1972 1 1.625 68.67
## 1007294810171882184 1975 2 1.691 77.93
## 1008306342245432754 1958 1 1.666 78.29
## 1008983561370747969 1960 1 1.661 87.72
## 1011258566350785406 1969 2 1.744 55.51
Summary of the assigned data.frame:
opal.execute(o, "summary(D)")
## SVUOSI SUKUP PITUUS PAINO
## Min. :1933 1:1512 Min. :1.372 Min. : 40.10
## 1st Qu.:1944 2:1488 1st Qu.:1.624 1st Qu.: 67.08
## Median :1957 Median :1.683 Median : 77.40
## Mean :1957 Mean :1.684 Mean : 77.87
## 3rd Qu.:1970 3rd Qu.:1.747 3rd Qu.: 88.74
## Max. :1982 Max. :2.009 Max. :137.41
Histogram figure of the PITUUS variable:
plot(opal.execute(o, "hist(D$PITUUS)"))
Loading ggplot2 library in R on Opal server side… This will fail if ggplot2 is not installed in R server environment.
Plot PITUUS vs. PAINO with “lm” smoothing:
opal.execute(o, "qplot(PITUUS,PAINO, data=D) + geom_smooth(method=\"lm\")")
Cleaning the resources on Opal server side…