chuuhtetnaing/myanmar-nrc-format-dataset

Myanmar NRC Format Data

This dataset provides cleaned and standardized data for Myanmar National Registration Card (NRC) format references.

Dataset Description

The Myanmar NRC Format Data contains township and state information used in Myanmar's National Registration Card system, including codes and names in both English and Myanmar languages.

Features

• state_code: Numeric code representing the state/region (1-14)
• township_code_en: Township code in English (e.g., "AHGAYA")
• township_code_mm: Township code in Myanmar (e.g., "အဂယ")
• township_en: Township name in English
• township_mm: Township name in Myanmar
• state_en: State/region name in English
• state_mm: State/region name in Myanmar

Loading the Dataset

You can easily load this dataset using the Hugging Face Datasets library:

from datasets import load_dataset

# Load the dataset
dataset = load_dataset("chuuhtetnaing/myanmar-nrc-format-dataset")

# Access the data
nrc_data = dataset["train"]  # The dataset is in the "train" split

# Example: Print the first few entries
for i, entry in enumerate(nrc_data):
    if i < 5:  # Just show the first 5 entries
        print(entry)
    else:
        break

Data Source and Cleaning

This dataset was created by cleaning and standardizing data from the KBZ MPU (Myanmar Payment Union) website, with additional verification using Wikipedia references for Myanmar townships. The data cleaning process included correcting spelling inconsistencies and standardizing township and state names.

GitHub Repository

For more information and additional formats of this dataset (CSV, JSON), visit: GitHub Repository

For Web and Mobile Developers

If you're developing web applications or mobile apps, you might prefer using our optimized JSON file that's ready for direct integration:

• nrc.json: Optimized dataset specifically prepared for direct use in web applications or mobile apps with minimal post-processing required.

License

This dataset is free to use for any purpose - personal, commercial, or educational.

Contributions

Feel free to create a pull request if you find any errors or have improvements to suggest for the dataset. Contributions to enhance the accuracy and completeness of the data are welcome.