Update README.md

README.md

@@ -1,3 +1,10 @@
+---
+license: mit
+language:
+- en
+tags:
+- code
+---
 # Filtered StarCoder Dataset Mini
 
 ## Dataset Description
@@ -9,7 +16,11 @@ This dataset contains filtered and processed code samples from 12 popular progra
 - **Cleaned and Filtered Code**: Samples have been processed to remove outliers in terms of line length and code size
 - **Quality Metrics**: Each sample includes metadata about average line length and line count
 - **Multi-language Support**: 12 programming languages represented in separate subsets
-- **Consistent Format**: All samples follow the same JSON structure for easy processing
+- **Consistent Format**: All samples follow the same Parquet structure for easy processing
+
+### Dataset Size
+
+The complete dataset is approximately 14GB in size. Individual language files vary in size, with the largest being C++ (~2GB) and the smallest being Scala (~700MB).
 
 ### Dataset Statistics
 
@@ -30,44 +41,30 @@ This dataset contains filtered and processed code samples from 12 popular progra
 
 ## Dataset Structure
 
-The dataset is organized with separate JSON files for each programming language:
-- `c.json` - C language samples
-- `cpp.json` - C++ language samples
-- `c-sharp.json` - C# language samples
-- `go.json` - Go language samples
-- `java.json` - Java language samples
-- `javascript.json` - JavaScript language samples
-- `kotlin.json` - Kotlin language samples
-- `python.json` - Python language samples
-- `ruby.json` - Ruby language samples
-- `rust.json` - Rust language samples
-- `scala.json` - Scala language samples
-- `typescript.json` - TypeScript language samples
-
-Within each file, data is stored in the following format:
-
-```json
-{
-    "lang_0": {
-        "code": "ENTIRE CODE",
-        "avg_line_length": 35.7,
-        "line_count": 120
-    },
-    "lang_1": {
-        "code": "ANOTHER CODE EXAMPLE",
-        "avg_line_length": 42.3,
-        "line_count": 85
-    },
-    ...
-    "lang_N": {
-        "code": "ENTIRE CODE",
-        "avg_line_length": 28.9,
-        "line_count": 67
-    }
-}
+The dataset is organized with separate Parquet files for each programming language:
+- `c.parquet` - C language samples
+- `cpp.parquet` - C++ language samples
+- `c-sharp.parquet` - C# language samples
+- `go.parquet` - Go language samples
+- `java.parquet` - Java language samples
+- `javascript.parquet` - JavaScript language samples
+- `kotlin.parquet` - Kotlin language samples
+- `python.parquet` - Python language samples
+- `ruby.parquet` - Ruby language samples
+- `rust.parquet` - Rust language samples
+- `scala.parquet` - Scala language samples
+- `typescript.parquet` - TypeScript language samples
+
+Within each file, data is stored with the following schema:
+
+```
+- language: string (the programming language of the code sample)
+- code: string (the complete code content)
+- avg_line_length: float (average character count per line)
+- line_count: integer (total number of lines in the code)
 ```
 
-Each sample is assigned a unique integer ID (0 to N) prefixed with the language identifier.
+Each sample is stored as a row in the Parquet file with these four columns.
 
 ## How to Access the Dataset
 
@@ -81,16 +78,48 @@ This dataset is hosted on the Hugging Face Hub and can be easily accessed using
 pip install datasets
 ```
 
+#### Import Library
+
+```python
+from datasets import load_dataset
+```
+
 #### Load the Entire Dataset
 
 ```python
-TODO
+dataset = load_dataset(
+    "jugalgajjar/Filtered-StarCoder-Dataset-Mini"
+)
 ```
 
 #### Load a Specific Language
 
 ```python
-TODO
+dataset = load_dataset(
+    "jugalgajjar/Filtered-StarCoder-Dataset-Mini",
+    data_files="scala.parquet"
+)
+```
+
+#### Stream Data
+
+```python
+dataset = load_dataset(
+    "jugalgajjar/Filtered-StarCoder-Dataset-Mini",
+    data_files="scala.parquet",
+    streaming=True
+)
+```
+
+#### Access Data Content (After Downloading)
+
+```python
+try:
+    for example in dataset["train"].take(5):
+        print(example)
+        print("-"*25)
+except Exception as e:
+    print(f"An error occurred: {e}")
 ```
 
 ### Manual Download
@@ -99,7 +128,7 @@ You can also manually download specific language files from the Hugging Face rep
 
 1. Visit `https://huggingface.co/datasets/jugalgajjar/Filtered-StarCoder-Dataset-Mini`
 2. Navigate to the "Files" tab
-3. Click on the language file you want to download (e.g., `python.json`)
+3. Click on the language file you want to download (e.g., `python.parquet`)
 4. Use the download button to save the file locally
 
 ## Dataset Creation
@@ -112,6 +141,7 @@ This dataset was created through the following process:
 4. Samples were filtered to remove excessively long or short code examples
 5. Data was normalized and standardized across languages
 6. Metadata (average line length and line count) was calculated for each sample
+7. Final data was serialized in the efficient Parquet format for optimal storage and access speed
 
 The processing pipeline included steps to:
 - Remove code samples with abnormal line lengths (potential formatting issues)