DOC updated readme

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Kevin Johnson
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# Technical Analysis Library in Python 3.7
![Example Chart](/images/TA_Chart.png)
Technical Analysis (TA) is an easy to use library that is built upon Python's Pandas library with more than 60 Indicators. These indicators are comminly used for financial time series datasets with columns or labels similar to: datetime, open, high, low, close, volume, et al. Many commonly used indicators are included, such as: _Moving Average Convergence Divergence_ (*MACD*), _Hull Exponential Moving Average_ (*HMA*), _Bollinger Bands_ (*BBANDS*), _On-Balance Volume_ (*OBV*), _Aroon Oscillator_ (*AROON*) and more.
Technical Analysis (TA) is an easy to use library that is built upon Python's Pandas library with more than 80 Indicators. These indicators are comminly used for financial time series datasets with columns or labels similar to: datetime, open, high, low, close, volume, et al. Many commonly used indicators are included, such as: _Moving Average Convergence Divergence_ (*MACD*), _Hull Exponential Moving Average_ (*HMA*), _Bollinger Bands_ (*BBANDS*), _On-Balance Volume_ (*OBV*), _Aroon Oscillator_ (*AROON*) and more.
This version contains both the orignal code branch as well as a newly refactored branch with the option to use [Pandas DataFrame Extension](https://pandas.pydata.org/pandas-docs/stable/extending.html) mode.
All the indicators return a named Series or a DataFrame in uppercase underscore parameter format. For example, MACD(fast=12, slow=26, signal=9) will return a DataFrame with columns: ['MACD_12_26_9', 'MACDH_12_26_9', 'MACDS_12_26_9'].