Downloading and analyzing financial data, including indices, stocks, and mutual funds, from India, that is Bharat.
Project description
BharatFinTrack
BharatFinTrack is a Python package designed to simplify the process of downloading and analyzing financial data from India. Conceptualized on September 1, 2024, and launched on September 8, 2024, this package is tailored for long-term investors seeking to streamline their financial data workflows. It focuses on open-source financial data and currently provides functionality for analyzing NSE equity indices. However, it is important to note that the package does not include features for technical indicators or real-time trading at this time. Active development is ongoing, with exciting new features planned for future releases. The goal of BharatFinTrack is to empower users by offering easy access to open-source data, enabling them to make informed financial decisions. Currently, the package offers the following features:
-
- Provides access to the characteristics of NSE equity indices.
- Calculates the CAGR(%) of all NSE equity indices (excluding dividend reinvestment) from launch.
- Facilitates downloading Total Return Index, including both price and dividend reinvestment, data for all NSE equity indices.
Roadmap
- Add support for downloading equity index price data without dividend reinvestment.
- Provide a summary of daily updated values of equity index price data.
- Include NAV (Net Asset Value) data for mutual funds.
- Include NAV data for the National Pension System (NPS).
Easy Installation
To install, use pip:
pip install BharatFinTrack
Quickstart
A brief example of how to start:
>>> import BharatFinTrack
>>> nse_product = BharatFinTrack.NSEProduct()
>>> nse_product.equity_index_category
['broad', 'sector', 'thematic', 'strategy', 'variant']
# get the list of all NSE equity indices
>>> nse_product.all_equity_indices
['NIFTY 100',
'NIFTY 200',
'NIFTY 50',
'NIFTY 50 ARBITRAGE',
...]
# download TRI data for a specified NSE equity index
>>> nse_tri = BharatFinTrack.NSETRI()
>>> nse_tri.download_historical_daily_data(
index='NIFTY 50',
start_date='23-Sep-2024',
end_date='27-Sep-2024'
)
Date Close
0 2024-09-23 38505.51
1 2024-09-24 38507.55
2 2024-09-25 38602.21
3 2024-09-26 38916.76
4 2024-09-27 38861.64
Documentation
For detailed information, see the documentation.
Toolkit
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PyPI | |
GitHub | |
Codecov | |
Read the Docs | |
PePy | |
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