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dflib

(★ 321)

In-memory Java DataFrame library

파일 탐색기

최종 버전 다운로드 (.zip)

- - maven.yml
  - maven_settings.xml
  - release.yml
- pom.xml
- pom.xml
- pom.xml
- README.md
- pom.xml
- pom.xml
- pom.xml
- pom.xml
- .DS_Store
- pom.xml
- pom.xml
- pom.xml
- pom.xml
- pom.xml
.gitattributes
.gitignore
LICENSE
NOTICE.txt
pom.xml
README.md
RELEASE-NOTES.md
UPGRADE-1x.md
UPGRADE.md

# 설치 가이드

1. 코드 내려받기

git clone https://github.com/dflib/dflib

깃허브에서 프로젝트 코드 전체를 내 컴퓨터로 내려받습니다.

cd dflib

방금 내려받은 프로젝트 폴더 안으로 이동합니다.

2. Maven (Java)

보통 추천

사전 준비물

Git GitHub에서 프로젝트 코드를 내려받으려면 필요합니다.
JDK (Java) Java 프로젝트를 빌드/실행하려면 필요합니다.
Maven mvn 명령어를 쓰기 위한 빌드 도구입니다.

cd dflib-avro

이 프로젝트의 관련 파일이 하위 폴더 안에 있어서, 먼저 그 폴더로 이동합니다.

mvn clean install

Maven으로 의존성 설치와 빌드를 진행합니다.

✅ BUILD SUCCESS 메시지가 뜨면 성공입니다. target/ 폴더에 결과물이 생성됩니다.

// repository documentation

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# DFLib

DFLib ("DataFrame Library") is a lightweight pure Java implementation of a common `DataFrame` data structure. 
DataFrames exist in Python (pandas), R, Spark and other languages and frameworks. DFLib's DataFrame is specifically 
intended for Java and JVM languages.

With DataFrame API, you get essentially the same data manipulation capabilities you may be used to in SQL (such as 
joins, etc.), only you apply them in-memory and over dynamically defined "table" objects. While SQL is "declarative", 
`DataFrame` allows step-by-step transformations that are somewhat easier to understand and much easier to compose.

`DataFrame` is extremely versatile and can be used to model a variety of data tasks. ETL, log analysis, spreadsheets 
processing are just some of the examples. DFLib comes with connectors for many data formats: 
CSV, Excel, RDBMS, Avro, Parquet, JSON and can be easily adapted to other formats (e.g. web-based ones like 
Google Sheets, etc.)

While DFLib can be used in any Java application, there is a [special integration](https://dflib.org/dflib/docs/2.x/#jupyter) 
with [Jupyter Notebook](https://jupyter.org/), a browser-based interactive environment for data exploration and analysis popular 
among data scientists and engineers. In fact, our community maintains a [Java "kernel" for Jupyter](https://github.com/dflib/jjava), which is a 
sister project of DFLib.

DFLib provides integration with Apache ECharts to visualize DataFrame data. Charts are generated in a form of
HTML/JavaScript code and work in Jupyter as well as regular web applications. A few examples of charts made with DFLib:

![dflib-stocks-candlestick-bar-chart](https://dflib.org/images/charts/dflib-stocks_candlestick_bar_v2.svg)
![dflib-player-weights-scatter-chart](https://dflib.org/images/charts/dflib-player-weights_scatter_v2.svg)
![dflib-github-activity-heatmap-chart](https://dflib.org/images/charts/dflib-github-activity_heatmap_v6.svg)

## Project Links

* [Website](https://dflib.org/)
* [Getting Started](https://dflib.org/dflib/docs/1.x/#_get_started_with_dflib)
* [Documentation](https://dflib.org/docs/)
* [Discussions and Support Forum](https://github.com/dflib/dflib/discussions)

## Presentation Videos

* [DataFrame, a Swiss Army Knife of Java Data Processing](https://youtu.be/1P1UtWxwdYM?t=548), JUG Milano, Italy 09/2024
* [Data visualization with Apache ECharts and DFLib](https://www.youtube.com/live/IWLwcxqkYDM), New York Java SIG, 07/2024