Metadata-Version: 1.1
Name: dyplot
Version: 0.7.10
Summary: matplotlib-like plot functions for dygraphs.js and c3.js.
Home-page: http://pypi.python.org/pypi/dyplot/
Author: Tsung-Han Yang
Author-email: blacksburg98@yahoo.com
License: LICENSE.txt
Description: dyplot
        ======
        matplotlib-like plot functions for dygraphs.js c3.js. 
        See dygraphs.com and c3js.org for detail.
        Interactive out of the box: zoom, pan and mouseover are on by default.
        Drag your mouse to zoom in and double click to zoom out.
        You can clone the source code from 
        https://github.com/blacksburg98/dyplot
        The series needs to be pandas.Series
        Tutorial 1. 
        ===========
        See the output at http://store-demo.appspot.com/tutorial/tutorial1.html 
        ::
        
            import pandas as pd
            from dyplot.dygraphs import Dygraphs
            a = pd.Series([1,2,3,4,5,6,7,9,10])
            b = pd.Series([1,3,5,9,2,8,5,5,15])
            lc= pd.Series([1,3,4,5,6,7,9,3,2])
            c = pd.Series([2,4,5,7,8,8,9,4,3])
            hc= pd.Series([3,5,7,7,9,11,9,5,8])
            dg = Dygraphs(a.index, "index")
            dg.plot(series="a", mseries=a)
            dg.plot(series="b", mseries=b)
            dg.plot(series="c", mseries=c,lseries=lc, hseries=hc)
            dg.set_options(title="Test")
            div = dg.savefig(csv_file="tutorial.csv", html_file="tutorial1.html")
        
        Tutorial 2. 
        ===========
        See the output at http://store-demo.appspot.com/tutorial/tutorial2.html 
        ::
        
            import datetime as dt
            from finpy.equity import get_tickdata
            import finpy.fpdateutil as du
            from finpy.portfolio import Portfolio
            from dyplot.dygraphs import Dygraphs
            if __name__ == '__main__':
                dt_timeofday = dt.timedelta(hours=16)
                dt_start = dt.datetime(2010, 1, 1)
                dt_end = dt.datetime(2010, 12, 31)
                ls_symbols = ['AAPL','XOM', 'MSFT', 'WMT']
                ldt_timestamps = du.getNYSEdays(dt_start, dt_end, dt_timeofday)
                all_data = get_tickdata(ls_symbols=ls_symbols, ldt_timestamps=ldt_timestamps)
                all_stocks = Portfolio(all_data, 0, ldt_timestamps, [])
                dg = Dygraphs(ldt_timestamps, "date") 
                for tick in ls_symbols:
                    dg.plot(series=tick, mseries=all_stocks.normalized(tick))
                dg.set_options(title="Tutorial 2")
                div = dg.savefig(csv_file="tutorial2.csv", html_file="tutorial2.html")
        
        Tutorial 3. 
        ===========
        See the output at http://store-demo.appspot.com/tutorial/tutorial3.html 
        ::
        
            import datetime as dt
            from finpy.equity import get_tickdata
            import finpy.fpdateutil as du
            from dyplot.dygraphs import Dygraphs
            if __name__ == '__main__':
                dt_timeofday = dt.timedelta(hours=16)
                dt_start = dt.datetime(2010, 1, 1)
                dt_end = dt.datetime(2010, 12, 31)
                ls_symbols = ['AAPL','$RUA']
                ldt_timestamps = du.getNYSEdays(dt_start, dt_end, dt_timeofday)
                all_stocks = get_tickdata(ls_symbols=ls_symbols, ldt_timestamps=ldt_timestamps)
                dg = Dygraphs(ldt_timestamps, "date") 
                dg.plot(series="AAPL", mseries=all_stocks["AAPL"]['close'], axis='y2')
                dg.plot(series="$RUA", mseries=all_stocks["$RUA"]['close'])
                dg.set_options(title="Tutorial 3")
                div = dg.savefig(csv_file="tutorial3.csv", html_file="tutorial3.html")
        Tutorial 4. 
        ===========
        See the output at http://store-demo.appspot.com/tutorial/tutorial4.html 
        :: 
        
            import datetime as dt
            from finpy.equity import get_tickdata
            import finpy.fpdateutil as du
            from finpy.portfolio import Portfolio
            from dyplot.dygraphs import Dygraphs
            if __name__ == '__main__':
                dt_timeofday = dt.timedelta(hours=16)
                dt_start = dt.datetime(2010, 1, 1)
                dt_end = dt.datetime(2010, 12, 31)
                ls_symbols = ['AAPL','$RUA']
                ldt_timestamps = du.getNYSEdays(dt_start, dt_end, dt_timeofday)
                all_data = get_tickdata(ls_symbols=ls_symbols, ldt_timestamps=ldt_timestamps)
                all_stocks = Portfolio(all_data, 0, ldt_timestamps, [])
                dg = Dygraphs(ldt_timestamps, "date") 
                dg.plot(series="AAPL", mseries=all_data["AAPL"]['close'], axis='y2')
                dg.plot(series="Russel 3000", mseries=all_data["$RUA"]['close'])
                max_ratio = max(all_stocks.normalized("AAPL").max(), all_stocks.normalized("$RUA").max())
                min_ratio = min(all_stocks.normalized("AAPL").min(), all_stocks.normalized("$RUA").min())
                max_ratio *= 1.05
                min_ratio *= 0.95
                dg.set_axis_options(axis='y', valueRange=[all_data["$RUA"]['close'][0]*min_ratio, \
                    all_data["$RUA"]['close'][0]*max_ratio])
                dg.set_axis_options(axis='y2', valueRange=[all_data["AAPL"]['close'][0]*min_ratio, \
                    all_data["AAPL"]['close'][0]*max_ratio])
                dg.annotate('AAPL', '2010-06-21', "B", "Buy on 2010-06-21")
                dg.annotate('AAPL', '2010-08-13', "S", "Sell on 2010-08-13")
                dg.set_options(title="Tutorial 4", ylabel="Russel 3000", y2label="AAPL")
                div = dg.savefig(csv_file="tutorial4.csv", html_file="tutorial4.html")
        
        Tutorial 5. 
        ===========
        See the output at http://store-demo.appspot.com/tutorial/tutorial5.html 
        ::
        
            from dyplot.c3.pie import Pie
            frac = [30, 20, 50]
            labels = ["setosa", "versicolor", "viginica"]
            g = Pie(frac=frac, labels=labels)
            c = {}
            c["columns"] = []
            c["columns"].append(["setosa", 100])
            g.animate("load", c, 1000)
            g.savefig(html_file="tutorial5.html")
        Tutorial 6. 
        ===========
        See the output at http://store-demo.appspot.com/tutorial/tutorial6.html 
        ::
        
            from dyplot.c3.bar import Bar
            h = [30, 20, 50, 40]
            label = "setosa"
            g = Bar(height=h, label=label)
            h2 = [50, 30, 20, 30]
            label2 = "barora"
            h3 = [40, 20, 10, 50]
            label3 = "exama"
            g = Bar(height=h, label=label)
            g(height=h2, label=label2)
            g(height=h3, label=label3)
            g.set_xticklabels(["G1", "G2", "G3", "G4"])
            g.savefig(html_file="tutorial6.html")
        Tutorial 7. 
        ===========
        See the output at http://store-demo.appspot.com/tutorial/tutorial7.html 
        ::
        
            import datetime as dt
            from finpy.equity import get_tickdata
            import finpy.fpdateutil as du
            from finpy.portfolio import Portfolio
            from dyplot.dygraphs import Dygraphs
            if __name__ == '__main__':
                dt_timeofday = dt.timedelta(hours=16)
                dt_start = dt.datetime(2014, 1, 1)
                dt_end = dt.datetime(2014, 12, 31)
                ls_symbols = ['AAPL']
                ldt_timestamps = du.getNYSEdays(dt_start, dt_end, dt_timeofday)
                all_stocks = get_tickdata(ls_symbols=ls_symbols, ldt_timestamps=ldt_timestamps)
                p = Portfolio(all_stocks, 0, ldt_timestamps) 
                p.normalized_price(tick="AAPL")
                dg = Dygraphs(ldt_timestamps, "date") 
                dg.candleplot(open=p.equities["AAPL"]['open'],
                              high=p.equities["AAPL"]['high'],
                              low=p.equities["AAPL"]['low'],
                              close=p.equities["AAPL"]['close'])
                dg.set_options(title="Tutorial 7")
                div = dg.savefig(csv_file="tutorial7.csv", html_file="tutorial7.html")
        Tutorial 8. 
        ===========
        See the output at http://store-demo.appspot.com/tutorial/tutorial8.html 
        ::
        
            import datetime as dt
            from finpy.equity import get_tickdata
            import finpy.fpdateutil as du
            from finpy.portfolio import Portfolio
            from dyplot.dygraphs import Dygraphs
            if __name__ == '__main__':
                dt_timeofday = dt.timedelta(hours=16)
                dt_start = dt.datetime(2014, 9, 1)
                dt_end = dt.datetime(2014, 12, 31)
                ls_symbols = ['AAPL']
                ldt_timestamps = du.getNYSEdays(dt_start, dt_end, dt_timeofday)
                all_stocks = get_tickdata(ls_symbols=ls_symbols, ldt_timestamps=ldt_timestamps, source="Google")
                p = Portfolio(all_stocks, 0, ldt_timestamps) 
                dg = Dygraphs(ldt_timestamps, "date") 
                dg.candleplot(open=p.equities["AAPL"]['open'],
                              high=p.equities["AAPL"]['high'],
                              low=p.equities["AAPL"]['low'],
                              close=p.equities["AAPL"]['close'])
                dg.plot(series="10D MA", mseries=p.moving_average(window=20, tick="AAPL"))
                dg.set_options(title="Tutorial 8")
                div = dg.savefig(csv_file="tutorial8.csv", html_file="tutorial8.html")
        
Platform: UNKNOWN
Classifier: Topic :: Text Processing :: Markup :: HTML
Classifier: Topic :: Software Development :: Code Generators
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: Programming Language :: JavaScript
