Metadata-Version: 2.1
Name: technical_indicators_lib
Version: 0.0.2
Summary: Technical Indicators Library provides means to derive stock market technical indicators.
Home-page: https://github.com/kunalkini015/technical_indicators_lib.git
Author: Kunal Kini K
Author-email: kunalkini15@gmail.com
License: MIT
Description: # Technical Indicators
        > Technical indicators library provides means to derive stock market technical indicators.
        
        
        
        Provides multiple ways of deriving technical indicators using raw OHLCV(Open, High, Low, Close, Volume) values.
        
        Supports 35 technical Indicators at present.
        
        Provides 2 ways to get the values,
        
        1. You can send a pandas data-frame consisting of required values and you will get a new data-frame with required column appended in return.
        
        	Note: make sure the column names are in lower case and are as follows,
        
        		- Open values should be named 'open'
        
        		- High values should be named 'high'
        
        		- Low values should be named 'low'
        
        		- Close values should be named 'close'
        
        		- Volume values should be named 'volume'
        
        
        
        2. You can send numpy arrays or pandas series of required values and you will get a new pandas series in return.
        
        
        ## Installation
        
        ```
        pip install  technical_indicators_lib
        ```
        
        ## Usage
        ```python
        # import dependencies
        import pandas as pd
        import numpy as np
        
        # importing an indicator class
        from technical_indicators_lib import OBV
        
        # instantiate the class
        obv = OBV()
        
        # load data into a dataframe df
        df = pd.read_csv("./test/data/test_data.csv")
        
        # Method 1: get the data by sending a dataframe
        df = obv.get_value_df(df)
        
        
        # Method 2: get the data by sending series values
        obv_values = obv.get_value_list(df["close"], df["volume"])
        ```
        
        ## Documentation
        https://technical-indicators-library.readthedocs.io/en/latest/
        
        
        ## Development
        
        Want to contribute?
        
        Great. Follow these steps,
        
        ```
        git clone https://github.com/kunalkini015/technical-indicators.git
        
        cd technical_indicator_lib
        
        pip install -r requirements.txt
        
        ```
        
        then you are good to go. You can create a pull request or write to me at kunalkini15@gmail.com
        
        ## Todo
        
        - Divide indicators into separate modules, such as trend, momentum, volatility, volume, etc.
        
        - add tests.
        
        - Add more indicators.
        
        ## Credits
        
        Developed by Kunal Kini K, a software engineer by profession and passion.
        
        If you have any comments, feedbacks or queries, write to me at kunalkini15@gmail.com
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Financial and Insurance Industry
Requires-Python: >=3.5
Description-Content-Type: text/markdown
