
Version: 0.1.1
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| What | kibior is a R package dedicated to ease the pain of data handling in science, and more notably with biological data. |
| Where | kibior is using Elasticsearch as database and search engine. |
| Who | kibior is built for data science and data manipulation, so when any data-related action or need is involved, notably sharing data. It mainly targets bioinformaticians, and more broadly, data scientists. |
| When | Available now from this repository, or CRAN repository. |
| Public instances | Use the $get_kibio_instance() method to connect to Kibio and access known datasets. See Kibio datasets at the end of this document for a complete list. |
| Cite this package | In R session, run citation("kibior") |
| Publication | 10.1093/bioinformatics/btab157 |
This package allows:
Pushing, pulling, joining, sharing and searching tabular data between an R session and one or multiple Elasticsearch instances/clusters. Massive data query and filter with Elasticsearch engine.Multiple living Elasticsearch connections to different addresses.Method autocompletion in proper environments (e.g. R cli, RStudio). Import and export datasets from an to files.Server-side execution for most of operations (i.e. on Elasticsearch instances/clusters).# Get from CRAN
install.packages("kibior")
# or get the latest from Github
devtools::install_github("regisoc/kibior")
# load
library(kibior)
# Get a specific instance
kc <- Kibior$new("server_or_address", port)
# Or try something bigger...
kibio <- Kibior$get_kibio_instance()
kibio$list()
Here is an extract of some of the features proposed by KibioR.
See Introduction vignette for more advanced usage.
push datasets# Push data (R memory -> Elasticsearch)
dplyr::starwars %>% kc$push("sw")
dplyr::storms %>% kc$push("st")
pull datasets# Pull data with columns selection (Elasticsearch -> R memory)
kc$pull("sw", query = "homeworld:(naboo || tatooine)",
columns = c("name", "homeworld", "height", "mass", "species"))
# see vignette for query syntax
copy datasets# Copy dataset (Elasticsearch internal operation)
kc$copy("sw", "sw_copy")
delete datasets
# Delete datasets
kc$delete("sw_copy")
list, match dataset names# List available datasets
kc$list()
# Search for index names starting with "s"
kc$match("s*")
columns names and list unique keys in values# Get columns of all datasets starting with "s"
kc$columns("s*")
# Get unique values of a column
kc$keys("sw", "homeworld")
# Count number of lines in dataset
kc$count("st")
# Count number of lines with query (name of the storm is Anita)
kc$count("st", query = "name:anita")
# Generic stats on two columns
kc$stats("sw", c("height", "mass"))
# Specific descriptive stats with query
kc$avg("sw", c("height", "mass"), query = "homeworld:naboo")
join# Inner join between:
# 1/ a Elasticsearch-based dataset with query ("sw"),
# 2/ and a in-memory R dataset (dplyr::starwars)
kc$inner_join("sw", dplyr::starwars,
left_query = "hair_color:black",
left_columns = c("name", "mass", "height"),
by = "name")
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