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tweak README and version; tested test.pypi
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README.md

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[![Build Status](https://travis-ci.org/matplotlib/mplfinance.svg?branch=master)](https://travis-ci.org/matplotlib/mplfinance)
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# mplfinance
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(to replace mpl-finance sometime in 2020).
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## matplotlib utilities for the visualization, and visual analysis, of financial data
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## The `mplfinance` package provides utilities for the visualization, and visual analysis, of financial data
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## Installation
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###    `pip install mplfinance`
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# Installation
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##    `pip install mplfinance`
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- mplfinance requires [matplotlib](https://pypi.org/project/matplotlib/) and [pandas](https://pypi.org/project/pandas/)
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## Usage
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# Usage
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Start with a Pandas DataFrame containing OHLC data. For example,
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```python
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</tbody>
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</table>
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<br>
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After importing mplfinance, plotting open,high,low,close data is as simple as calling `mpf.plot()` on the dataframe
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<br>
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After importing mplfinance, plotting OHLC data is as simple as calling `mpf.plot()` on the dataframe
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```python
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import mplfinance as mpf
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![png](https://raw.githubusercontent.com/matplotlib/mplfinance/master/readme_files/readme_4_0.png)
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<br>
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The default plot type, as you can see above, is `'ohlc'`. Other plot types can be specified with the keyword argument `type`, for example, `type='candle'` or `type='line'`
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![png](https://raw.githubusercontent.com/matplotlib/mplfinance/master/readme_files/readme_7_0.png)
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<br>
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We can also plot moving averages with the `mav` keyword
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- use an scaler for a single moving average
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- use a scaler for a single moving average
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- use a tuple or list of integers for multiple moving averages
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src/mplfinance/_version.py

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version_info = (0, 11, 0, 'alpha', 0)
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version_info = (0, 11, 1, 'alpha', 0)
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_specifier_ = {'alpha': 'a', 'beta': 'b', 'candidate': 'rc', 'final': ''}
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