def output_chart(issues_df, output_mode='static'):
import datetime
import bokeh
from bokeh.models import HoverTool
# Add timestamp to title
issues_chart = Bar(issues_df,
label='value_delivered',
values='status',
agg='count',
stack='status',
title=ISSUES_TITLE + " (Updated " +
datetime.datetime.now().strftime('%m/%d/%Y') + ")",
xlabel="Value Delivered",
ylabel="Number of Use Cases",
legend='top_right',
tools='hover',
color=brewer["GnBu"][3])
issues_chart.plot_width = DESTINATION_FRAME_WIDTH - (HTML_BODY_MARGIN * 2)
issues_chart.plot_height = DESTINATION_FRAME_HEIGHT - (HTML_BODY_MARGIN *
2)
issues_chart.logo = None
issues_chart.toolbar_location = None
hover = issues_chart.select(dict(type=HoverTool))
hover.tooltips = [("Value Delivered", "$x")]
#--- Configure output ---
reset_output()
if output_mode == 'static':
# Static file. CDN is most space efficient
output_file(ISSUES_FILE,
title=ISSUES_TITLE,
autosave=False,
mode='cdn',
root_dir=None) # Generate file
save(issues_chart, filename=ISSUES_FILE)
elif output_mode == 'notebook':
output_notebook() # Show inline
show(issues_chart)
else:
# Server (using internal server IP, rather than localhost or external)
session = bokeh.session.Session(root_url=BOKEH_SERVER_IP,
load_from_config=False)
output_server("ddod_chart", session=session)
show(issues_chart)
def output_chart(issues_df,output_mode='static'):
import datetime
import bokeh
from bokeh.models import HoverTool
# Add timestamp to title
issues_chart = Bar(issues_df, label='value_delivered',
values='status', agg='count', stack='status',
title=ISSUES_TITLE+" (Updated "+datetime.datetime.now().strftime('%m/%d/%Y')+")",
xlabel="Value Delivered",ylabel="Number of Use Cases",
legend='top_right',
tools='hover',
color=brewer["GnBu"][3]
)
issues_chart.plot_width = DESTINATION_FRAME_WIDTH - (HTML_BODY_MARGIN * 2)
issues_chart.plot_height = DESTINATION_FRAME_HEIGHT - (HTML_BODY_MARGIN * 2)
issues_chart.logo = None
issues_chart.toolbar_location = None
hover = issues_chart.select(dict(type=HoverTool))
hover.tooltips = [ ("Value Delivered", "$x")]
#--- Configure output ---
reset_output()
if output_mode == 'static':
# Static file. CDN is most space efficient
output_file(ISSUES_FILE, title=ISSUES_TITLE,
autosave=False, mode='cdn',
root_dir=None
) # Generate file
save(issues_chart,filename=ISSUES_FILE)
elif output_mode == 'notebook':
output_notebook() # Show inline
show(issues_chart)
else:
# Server (using internal server IP, rather than localhost or external)
session = bokeh.session.Session(root_url = BOKEH_SERVER_IP, load_from_config=False)
output_server("ddod_chart", session=session)
show(issues_chart)
# Go to http://localhost:5006/bokeh to view this plot
from collections import OrderedDict
import time
import numpy as np
from bokeh.charts import Line, curdoc, cursession, output_server, show
from bokeh.models import GlyphRenderer
N = 80
x = np.linspace(0, 4*np.pi, N)
xyvalues = OrderedDict(sin=np.sin(x), cos=np.cos(x))
output_server("line_animate")
chart = Line(xyvalues, title="Lines", ylabel='measures')
curdoc().add(chart)
show(chart)
renderer = chart.select(dict(type=GlyphRenderer))
ds = renderer[0].data_source
while True:
for i in np.hstack((np.linspace(1, -1, 100), np.linspace(-1, 1, 100))):
for k, values in xyvalues.items():
if k != 'x':
ds.data['y_%s'%k] = values * i
x = sys.argv[1]
mod = sys.argv[2]
limit = sys.argv[3]
try:
conn = psycopg2.connect("dbname='cta' user='******' host='localhost' password=''")
except:
print "I am unable to connect to the database"
cur = conn.cursor()
try:
c = "SELECT "+x+", COUNT("+x+") FROM cta_stops GROUP BY "+x+" ORDER BY COUNT("+x+") "+mod+" LIMIT "+limit+";"
cur.execute(c)
except:
print "Query Failed"
rows = cur.fetchall()
df = pd.DataFrame.from_records(rows, columns=[x, 'count_'+x])
p = Bar(df, x, values='count_'+x, title="Graph")
output_server("bar.html")
select = Select(title="Max or Min:", value="ASC", options=["ASC", "DESC"])
slider = Slider(start=0, end=100, value=1, step=1, title="Number of Elements")
button = Button(label="Submit", type="success")
layout = vform(select, slider, button)
show(layout)
# Go to http://localhost:5006/bokeh to view this plot
from collections import OrderedDict
import time
import numpy as np
from bokeh.charts import Line, curdoc, cursession, output_server, show
from bokeh.models import GlyphRenderer
N = 80
x = np.linspace(0, 4 * np.pi, N)
xyvalues = OrderedDict(sin=np.sin(x), cos=np.cos(x))
output_server("line_animate")
chart = Line(xyvalues, title="Lines", ylabel='measures')
curdoc().add(chart)
show(chart)
renderer = chart.select(dict(type=GlyphRenderer))
ds = renderer[0].data_source
while True:
for i in np.hstack((np.linspace(1, -1, 100), np.linspace(-1, 1, 100))):
for k, values in xyvalues.items():
if k != 'x':
ds.data['y_%s' % k] = values * i
