def btn_update__click(dom):
symbol = dom['select_stock']['value']
if symbol == 'AAPL':
df = AAPL
elif symbol == 'GOOG':
df = GOOG
else:
return dom
bounds = [dom[x]['value'] if dom[x]['value'] else None
for x in ['date_start', 'date_end']]
ts = df['Close'][bounds[0]:bounds[1]]
if ts.any():
try:
ts.plot()
for win in [int(dom[x]['value'])
for x in ['slider_window_1', 'slider_window_2']]:
pd.rolling_mean(ts, win).plot()
plt.title("Weekly closing prices for {}".format(symbol))
# get_svg is added by ashiba.plot
dom['img_plot'].set_image(plt.get_svg(), 'svg')
finally:
plt.close()
return dom
def btn_plot__click(dom):
ra = calc(dom)
plotNumber(ra,dom['label']['value'])
#plt.plot([1,2,3],[1,2,3])
#plt.savefig('image.jpg')
dom['img_plot'].set_image(plt.get_svg(), 'svg')
return dom
def _plot_control__change(dom):
year = int(dom['slider_year']['value'])
sex = None
if dom['radio_male']['checked']:
sex = 1
elif dom['radio_female']['checked']:
sex = 2
if year == 1890 or sex is None:
return
subset = df[df.year == year][df.sex == sex][df.age >= 15]
# Does this need to be a new instantiation?
dom['my_table'] = ashiba.dom.DataTable(data=subset)
pivot = subset.pivot('age', 'marst', 'people')
if 3 not in pivot:
pivot[3] = [0] * len(pivot)
pivot.plot(kind='bar', stacked=True, sort_columns=True)
gender = {1: 'male', 2: 'female'}[sex]
plt.title('Marriage records for year {}, {}'.format(year, gender))
statuses = (
'Unknown',
'Married',
'Married, Spouse Absent',
'Separated',
'Divorced',
'Widowed',
'Single',
)
plt.legend(statuses)
dom['img_plot'].set_image(plt.get_svg(), 'svg')
plt.close()
def btn_update__click(dom):
symbol = dom['select_stock']['value']
if symbol == 'AAPL':
df = AAPL
elif symbol == 'GOOG':
df = GOOG
else:
return dom
bounds = [
dom[x]['value'] if dom[x]['value'] else None
for x in ['date_start', 'date_end']
]
ts = df['Close'][bounds[0]:bounds[1]]
if ts.any():
try:
ts.plot()
for win in [
int(dom[x]['value'])
for x in ['slider_window_1', 'slider_window_2']
]:
pd.rolling_mean(ts, win).plot()
plt.title("Weekly closing prices for {}".format(symbol))
# get_svg is added by ashiba.plot
dom['img_plot'].set_image(plt.get_svg(), 'svg')
finally:
plt.close()
return dom
def mybutton__click(dom):
user = dom['usersearch']['value']
repo = dom['reposearch']['value']
ts = weekly_commit_timeline(user, repo)
ts2 = daily_commit_timeline(user, repo)
ts.plot()
plt.title("Weekly commits for %s".format('Github') % repo)
dom['img_plot'].set_image(plt.get_svg(), 'svg')
ts2.plot()
plt.title("Daily commits for %s".format('Github') % repo)
dom['img_plot2'].set_image(plt.get_svg(), 'svg')
plt.close()
return dom
def mybutton__click(dom):
user = dom['usersearch']['value']
repo = dom['reposearch']['value']
ts = weekly_commit_timeline(user, repo)
ts2 = daily_commit_timeline(user, repo)
ts.plot()
plt.title("Weekly commits for %s".format('Github') %repo)
dom['img_plot'].set_image(plt.get_svg(), 'svg')
ts2.plot()
plt.title("Daily commits for %s".format('Github') % repo)
dom['img_plot2'].set_image(plt.get_svg(), 'svg')
plt.close()
return dom
def _plot_control__change(dom):
year = int(dom["slider_year"]["value"])
sex = None
if dom["radio_male"]["checked"]:
sex = 1
elif dom["radio_female"]["checked"]:
sex = 2
if year == 1890 or sex is None:
return
subset = df[df.year == year][df.sex == sex][df.age >= 15]
# Does this need to be a new instantiation?
dom["my_table"] = ashiba.dom.DataTable(data=subset)
pivot = subset.pivot("age", "marst", "people")
if 3 not in pivot:
pivot[3] = [0] * len(pivot)
pivot.plot(kind="bar", stacked=True, sort_columns=True)
gender = {1: "male", 2: "female"}[sex]
plt.title("Marriage records for year {}, {}".format(year, gender))
statuses = ("Unknown", "Married", "Married, Spouse Absent", "Separated", "Divorced", "Widowed", "Single")
plt.legend(statuses)
dom["img_plot"].set_image(plt.get_svg(), "svg")
plt.close()
def calculate__click(dom):
# Here we grab the equity info from the dom and perform a few conversions
stock1 = stock2 = stock3 = stock4 = None
stock1 = dom['stock1']['value']
stock2 = dom['stock2']['value']
stock3 = dom['stock3']['value']
stock4 = dom['stock4']['value']
ls_symbols = [stock1, stock2, stock3, stock4]
symbols = filter(lambda a: len(a) > 0, ls_symbols)
stock1_ratio = dom['stock1_ratio']['value']
stock2_ratio = dom['stock2_ratio']['value']
stock3_ratio = dom['stock3_ratio']['value']
stock4_ratio = dom['stock4_ratio']['value']
ratios = [stock1_ratio, stock2_ratio, stock3_ratio, stock4_ratio]
ls_alloc = [float(i) for i in ratios]
allocations = filter(lambda a: a > 0, ls_alloc)
#get the trading days in the time period
bounds = [dom[x]['value'] if dom[x]['value'] else None
for x in ['date_start', 'date_end']]
if bounds[0] != None:
start = bounds[0].split('-')
dt_start = dt.datetime(int(start[0]),int(start[1]), int(start[2]))
else:
dt_start = dt.datetime(2006, 1, 1)
if bounds[1] != None:
end = bounds[1].split('-')
dt_end = dt.datetime(int(end[0]), int(end[1]), int(end[2]))
else:
dt_end = dt.datetime(2012, 5, 20)
#timestamps of trading days
timestamps = get_NYSE_days(dt_start, dt_end)
#close prices
normalized_close_prices = close_prices(ls_symbols, timestamps)
portfolio_total, market_per, final_stddev, final_daily_ret, final_cum_ret, max_sharpe = portfolio_stats(symbols, allocations, normalized_close_prices, timestamps)
text = '''Symbols : %s \n\n
Std. Deviation : %f
Daily Returns : %f
Cum. Returns : %f
Sharpe Ratio : %f ''' % (symbols, final_stddev, final_daily_ret, final_cum_ret, max_sharpe)
dom['my_tabs'].add_tab('[%s]' % ', '.join(map(str, symbols)), text)
plt.clf()
plt.plot(timestamps, normalized_close_prices)
plt.legend(symbols)
plt.ylabel('Normalized Close')
plt.xlabel('Date')
dom['close_prices'].set_image(plt.get_svg(), 'svg')
plt.clf()
plt.plot(timestamps, portfolio_total, label='Portfolio')
plt.plot(timestamps, market_per, label='SPY')
plt.legend()
plt.ylabel('Returns')
plt.xlabel('Date')
dom['daily_returns'].set_image(plt.get_svg(), 'svg')
return dom
