Short toy example to show hot to build a parent report with subreports (child reports) repeated on subsamples of the data within a loop. We first describe the Iris dataset. Then for each of the 4 variables measured we perform the same analysis and plots repeated. these analyses are performed in a subreport_child.Rmd file on the disc, compiled by the knitr function knit_child() and then inserted in the parent report/document. Then we continue with a few analyses/info on the main parent report (scatterplot matrix, Info Session).
Dataset for 3 Iris species (Iris virginica, Iris setosa, Iris versicolor) with 4 morphological variables measured :
Random sample :
| Sepal.Length | Sepal.Width | Petal.Length | Petal.Width | Species | |
|---|---|---|---|---|---|
| 141 | 6.7 | 3.1 | 5.6 | 2.4 | virginica |
| 104 | 6.3 | 2.9 | 5.6 | 1.8 | virginica |
| 93 | 5.8 | 2.6 | 4 | 1.2 | versicolor |
| 19 | 5.7 | 3.8 | 1.7 | 0.3 | setosa |
| 24 | 5.1 | 3.3 | 1.7 | 0.5 | setosa |
Summary :
| Sepal.Length | Sepal.Width | Petal.Length | Petal.Width | Species |
|---|---|---|---|---|
| Min. :4.300 | Min. :2.000 | Min. :1.000 | Min. :0.100 | setosa :50 |
| 1st Qu.:5.100 | 1st Qu.:2.800 | 1st Qu.:1.600 | 1st Qu.:0.300 | versicolor:50 |
| Median :5.800 | Median :3.000 | Median :4.350 | Median :1.300 | virginica :50 |
| Mean :5.843 | Mean :3.057 | Mean :3.758 | Mean :1.199 | NA |
| 3rd Qu.:6.400 | 3rd Qu.:3.300 | 3rd Qu.:5.100 | 3rd Qu.:1.800 | NA |
| Max. :7.900 | Max. :4.400 | Max. :6.900 | Max. :2.500 | NA |
Structure :
## 'data.frame': 150 obs. of 5 variables:
## $ Sepal.Length: num 5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...
## $ Sepal.Width : num 3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...
## $ Petal.Length: num 1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 1.4 1.5 ...
## $ Petal.Width : num 0.2 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 ...
## $ Species : Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ...The mean Sepal.Length is 5.8433333 cm.
| Min. | 1st Qu. | Median | Mean | 3rd Qu. | Max. |
|---|---|---|---|---|---|
| 4.3 | 5.1 | 5.8 | 5.843 | 6.4 | 7.9 |
The mean Sepal.Width is 3.0573333 cm.
| Min. | 1st Qu. | Median | Mean | 3rd Qu. | Max. |
|---|---|---|---|---|---|
| 2 | 2.8 | 3 | 3.057 | 3.3 | 4.4 |
The mean Petal.Length is 3.758 cm.
| Min. | 1st Qu. | Median | Mean | 3rd Qu. | Max. |
|---|---|---|---|---|---|
| 1 | 1.6 | 4.35 | 3.758 | 5.1 | 6.9 |
The mean Petal.Width is 1.1993333 cm.
| Min. | 1st Qu. | Median | Mean | 3rd Qu. | Max. |
|---|---|---|---|---|---|
| 0.1 | 0.3 | 1.3 | 1.199 | 1.8 | 2.5 |
## R version 3.2.5 (2016-04-14)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu precise (12.04.5 LTS)
##
## locale:
## [1] LC_CTYPE=en_GB.UTF-8 LC_NUMERIC=C LC_TIME=en_GB.UTF-8
## [4] LC_COLLATE=en_GB.UTF-8 LC_MONETARY=en_GB.UTF-8 LC_MESSAGES=fr_BE.UTF-8
## [7] LC_PAPER=fr_BE.UTF-8 LC_NAME=C LC_ADDRESS=C
## [10] LC_TELEPHONE=C LC_MEASUREMENT=fr_BE.UTF-8 LC_IDENTIFICATION=C
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] pander_0.6.0 knitr_1.13
##
## loaded via a namespace (and not attached):
## [1] magrittr_1.5 formatR_1.4 tools_3.2.5 Rcpp_0.12.5 stringi_1.0-1 digest_0.6.9 stringr_1.0.0
## [8] evaluate_0.9