dyplot 0.7.10

matplotlib-like plot functions for dygraphs.js and c3.js.

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")