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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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---
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- ## The ` mplfinance ` package provides utilities for the visualization, and visual analysis, of financial data
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-
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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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+ ---
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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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+
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---
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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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+
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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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---
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+ <br >
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+
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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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@@ -149,8 +155,10 @@ mpf.plot(daily,type='line')
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![ png] ( https://raw.githubusercontent.com/matplotlib/mplfinance/master/readme_files/readme_7_0.png )
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---
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+ <br >
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+
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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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