Version: 0.1.1
| | |
|-|-|
| 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 $get_kibio_instance()
method to connect to Kibio
and access known datasets. See Kibio datasets
at the end of this document for a complete list. |
| Cite this package | In R session, run citation("kibior")
|
| Publication | coming soon
. |
This package allows:
Pushing
, pulling
, joining
, sharing
and searching
tabular data between an R session and one or multiple Elasticsearch instances/clusters. Massive data query and filter
with Elasticsearch engine.Multiple living Elasticsearch connections
to different addresses.Method autocompletion
in proper environments (e.g. R cli, RStudio). Import and export datasets
from an to files.Server-side execution
for most of operations (i.e. on Elasticsearch instances/clusters).# Get from CRAN
install.packages("kibior")
# or get the latest from Github
devtools::install_github("regisoc/kibior")
# load
library(kibior)
# Get a specific instance
kc <- Kibior$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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