dyplot 0.6.000

matplotlib-like plot functions for dygraphs.js.

dyplot
======
matplotlib-like plot functions for dygraphs.js. See dygraphs.com 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.dyplot import Dyplot
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 = Dyplot(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.utils import get_tickdata
import finpy.fpdateutil as du
from dyplot.dyplot import Dyplot
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_stocks = get_tickdata(ls_symbols=ls_symbols, ldt_timestamps=ldt_timestamps)
dg = Dyplot(ldt_timestamps, "date")
for tick in ls_symbols:
dg.plot(series=tick, mseries=all_stocks[tick].normalized())
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.utils import get_tickdata
import finpy.fpdateutil as du
from dyplot.dyplot import Dyplot
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','$RUA']
ldt_timestamps = du.getNYSEdays(dt_start, dt_end, dt_timeofday)
all_stocks = get_tickdata(ls_symbols=ls_symbols, ldt_timestamps=ldt_timestamps)
dg = Dyplot(ldt_timestamps, "date")
dg.plot(series="AAPL", mseries=all_stocks["AAPL"]['close'], axis='y2')
dg.plot(series="$RUA", mseries=all_stocks["$RUA"]['close'])
dg.set_options(title="Tutorial 3")
div = dg.savefig(csv_file="tutorial3.csv", html_file="tutorial3.html")
Tutorial 4. See the output at http://store-demo.appspot.com/tutorial/tutorial4.html
===================================================================================
import datetime as dt
from finpy.utils import get_tickdata
import finpy.fpdateutil as du
from dyplot.dyplot import Dyplot
if __name__ == '__main__':
dt_timeofday = dt.timedelta(hours=16)
dt_start = dt.datetime(2010, 1, 1)
dt_end = dt.datetime(2010, 12, 31)
ls_symbols = ['AAPL','$RUA']
ldt_timestamps = du.getNYSEdays(dt_start, dt_end, dt_timeofday)
all_stocks = get_tickdata(ls_symbols=ls_symbols, ldt_timestamps=ldt_timestamps)
dg = Dyplot(ldt_timestamps, "date")
dg.plot(series="AAPL", mseries=all_stocks["AAPL"]['close'], axis='y2')
dg.plot(series="$RUA", mseries=all_stocks["$RUA"]['close'])
max_ratio = max(all_stocks["AAPL"].normalized().max(), all_stocks["$RUA"].normalized().max())
min_ratio = min(all_stocks["AAPL"].normalized().min(), all_stocks["$RUA"].normalized().min())
max_ratio *= 1.05
min_ratio *= 0.95
dg.set_axis_options(axis='y', valueRange=[all_stocks["$RUA"]['close'][0]*min_ratio, \
all_stocks["$RUA"]['close'][0]*max_ratio])
dg.set_axis_options(axis='y2', valueRange=[all_stocks["AAPL"]['close'][0]*min_ratio, \
all_stocks["AAPL"]['close'][0]*max_ratio])
dg.set_options(title="Tutorial 4")
div = dg.savefig(csv_file="tutorial4.csv", html_file="tutorail4.html")
Tutorial 5. See the output at http://store-demo.appspot.com/tutorial/tutorial5.html
===================================================================================
import datetime as dt
from finpy.utils import get_tickdata
import finpy.fpdateutil as du
from dyplot.dyplot import Dyplot
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','$RUA']
ldt_timestamps = du.getNYSEdays(dt_start, dt_end, dt_timeofday)
all_stocks = get_tickdata(ls_symbols=ls_symbols, ldt_timestamps=ldt_timestamps)
dg = Dyplot(ldt_timestamps, "date")
dg.plot(series="AAPL", mseries=all_stocks["AAPL"]['close'], axis='y2')
dg.plot(series="$RUA", mseries=all_stocks["$RUA"]['close'])
max_ratio = max(all_stocks["AAPL"].normalized().max(), all_stocks["$RUA"].normalized().max())
min_ratio = min(all_stocks["AAPL"].normalized().min(), all_stocks["$RUA"].normalized().min())
max_ratio *= 1.05
min_ratio *= 0.95
dg.set_axis_options(axis='y', valueRange=[all_stocks["$RUA"]['close'][0]*min_ratio, \
all_stocks["$RUA"]['close'][0]*max_ratio])
dg.set_axis_options(axis='y2', valueRange=[all_stocks["AAPL"]['close'][0]*min_ratio, \
all_stocks["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 5")
div = dg.savefig(csv_file="tutorial5.csv", html_file="tutorial5.html")