update dataset card with characters

README.md

@@ -23,6 +23,8 @@ size_categories:
 
 <div align="center">
 
+<img alt="DartLab" src="https://huggingface.co/datasets/eddmpython/dartlab-data/resolve/main/assets/logo.png" width="160">
+
 # DartLab Data
 
 **Structured company data from DART & EDGAR disclosure filings**
@@ -36,6 +38,8 @@ size_categories:
 
 ## What is this?
 
+<img align="right" src="https://huggingface.co/datasets/eddmpython/dartlab-data/resolve/main/assets/avatar-study.png" width="120">
+
 Pre-collected [Parquet](https://parquet.apache.org/) files from [DartLab](https://github.com/eddmpython/dartlab) — a Python library that turns DART (Korea) and EDGAR (US) disclosure filings into one structured company map.
 
 This dataset is the **data layer** behind DartLab. When you run `dartlab.Company("005930")`, the library automatically downloads the relevant parquet from this repo.
@@ -103,6 +107,8 @@ XBRL-based financial data from DART OpenAPI (`fnlttSinglAcntAll`).
 
 ## Usage
 
+<img align="right" src="https://huggingface.co/datasets/eddmpython/dartlab-data/resolve/main/assets/avatar-analyze.png" width="120">
+
 ### With DartLab (recommended)
 
 ```bash
@@ -141,6 +147,8 @@ df = pl.read_parquet(url)
 wget https://huggingface.co/datasets/eddmpython/dartlab-data/resolve/main/dart/finance/005930.parquet
 ```
 
+<img align="right" src="https://huggingface.co/datasets/eddmpython/dartlab-data/resolve/main/assets/avatar-discover.png" width="120">
+
 ## Data Source
 
 - **DART** (Korea): [dart.fss.or.kr](https://dart.fss.or.kr) — Korea's electronic disclosure system operated by the Financial Supervisory Service