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R data manipulation, formats, and database packages. Use for data wrangling with dplyr/data.table, reading files (CSV, Excel, JSON, Arrow), and database connections (SQL, MongoDB, Redis).
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SOC 職業分類に基づく
| name | r-data |
| description | R data manipulation, formats, and database packages. Use for data wrangling with dplyr/data.table, reading files (CSV, Excel, JSON, Arrow), and database connections (SQL, MongoDB, Redis). |
| Sub-skill | Description |
|---|---|
| r-data-manipulation | dplyr, data.table, tidyr |
| r-data-formats | CSV, Excel, JSON, Arrow, Parquet |
| r-data-database | SQL, MongoDB, Redis connections |
Data manipulation, formats, and database management in R.
| Package | Description |
|---|---|
| dplyr ★ | Fast data frames manipulation and database query |
| data.table ★ | Fast manipulation with concise syntax |
| tidyr | Tidy messy data with spread/gather |
| reshape2 ★ | Flexible reshape and aggregate |
| broom ★ | Convert models to tidy data frames |
| tidyverse | Meta-package for data science |
| lubridate | Date/time manipulation |
| stringr ★ | Consistent string processing |
| stringi ★ | ICU-based string processing |
| fuzzyjoin | Join on inexact matching |
| rlist | Non-tabular data manipulation |
| bigmemory | Shared memory matrices |
| snakecase | Case conversion |
| DataExplorer | Fast EDA with minimum code |
| Package | Description |
|---|---|
| arrow ★ | Apache Arrow interface |
| fst ★ | Lightning fast serialization |
| feather ★ | Fast binary data frame storage |
| readr ★ | Fast tabular data reading |
| readxl ★ | Read Excel files |
| haven | Read SPSS, Stata, SAS |
| jsonlite | JSON parsing |
| vroom | Fast delimited file reading |
| rio | Swiss-Army Knife for Data I/O |
| qs | Quick serialization |
| writexl | Write Excel files |
| yaml | YAML conversion |
| readODS | Read OpenDocument Spreadsheets |
| RcppTOML | TOML file parsing |
| Package | Description |
|---|---|
| DBI | Common database interface |
| odbc | ODBC connections (DBI interface) |
| RSQLite | SQLite interface |
| RPostgres | PostgreSQL (DBI-compliant) |
| RMariaDB | MariaDB/MySQL interface |
| RMySQL | MySQL interface |
| ROracle | Oracle database interface |
| RODBC | ODBC database access |
| RJDBC | JDBC interface |
| mongolite | MongoDB streaming client |
| rmongodb | MongoDB driver |
| redux | Redis client |
| elastic | Elasticsearch HTTP API |
| RNeo4j | Neo4j graph database |
| RCassandra | Apache Cassandra interface |
| RHive | Apache Hive integration |
| rpostgis | PostGIS spatial interface |
# dplyr pipeline
library(dplyr)
df %>%
filter(x > 10) %>%
select(a, b) %>%
mutate(c = a + b) %>%
group_by(category) %>%
summarise(mean = mean(c))
# data.table
library(data.table)
dt <- as.data.table(df)
dt[x > 10, .(mean = mean(c)), by = category]
# Read various formats
readr::read_csv("data.csv")
readxl::read_excel("data.xlsx")
arrow::read_parquet("data.parquet")
jsonlite::fromJSON("data.json")
# Database query
library(DBI)
con <- dbConnect(RSQLite::SQLite(), "db.sqlite")
dbGetQuery(con, "SELECT * FROM table WHERE x > 10")
dbDisconnect(con)
R language data analysis and visualization skill. Use when user asks to (1) run R scripts or code, (2) install/update R packages, (3) perform data analysis with R, (4) create visualizations with ggplot2/plotly, (5) statistical analysis, (6) data manipulation with tidyverse/dplyr/data.table. Triggers on keywords like "R语言", "R脚本", "ggplot", "tidyverse", "数据分析", "可视化".
R DALEX package for model explanations. Use for explaining complex machine learning models.
R iml package for interpretable ML. Use for model-agnostic interpretability methods.
R lime package for local explanations. Use for explaining individual predictions with local interpretable models.
R packages for ML interpretability. Use for explaining and interpreting machine learning models.
R vip package for variable importance. Use for computing and visualizing variable importance scores.