df2yaml
The goal of df2yaml is to simplify the process of converting dataframe
to YAML. The dataframe with multiple key columns and one value column
(this column can also contain key-value pair(s)) will be converted to
multi-level hierarchy.
Installation
df2yaml is an R package distributed as part of the
CRAN. To install the package, start R and
enter:
# install via CRAN
install.package("df2yaml")
# install via Github
# install.package("remotes") #In case you have not installed it.
remotes::install_github("showteeth/df2yaml")In general, it is recommended to install from Github repository (update more timely).
Usage
# library
library(df2yaml)
#> Warning: replacing previous import 'lifecycle::last_warnings' by
#> 'rlang::last_warnings' when loading 'tibble'
#> Warning: replacing previous import 'lifecycle::last_warnings' by
#> 'rlang::last_warnings' when loading 'pillar'
# load test file
test_file <- system.file("extdata", "df2yaml_l3.txt", package = "df2yaml")
test_data = read.table(file = test_file, header = T, sep = "\t")
head(test_data)
#> paras subcmd values
#> 1 picard insert_size MINIMUM_PCT: 0.5
#> 2 picard markdup CREATE_INDEX: true; VALIDATION_STRINGENCY: SILENT
#> 3 preseq -r 100 -seg_len 100000000
#> 4 qualimap --java-mem-size=20G -outformat HTML
#> 5 rseqc mapq: 30; percentile-floor: 5; percentile-step: 5
# output yaml string
yaml_res = df2yaml(df = test_data, key_col = c("paras", "subcmd"), val_col = "values")
cat(yaml_res)
#> preseq: -r 100 -seg_len 100000000
#> qualimap: --java-mem-size=20G -outformat HTML
#> rseqc:
#> mapq: 30
#> percentile-floor: 5
#> percentile-step: 5
#> picard:
#> insert_size:
#> MINIMUM_PCT: 0.5
#> markdup:
#> CREATE_INDEX: true
#> VALIDATION_STRINGENCY: SILENTCode of Conduct
Please note that the df2yaml project is released with a Contributor
Code of
Conduct.
By contributing to this project, you agree to abide by its terms.