def withbokeh(self,dfMergeWithInfo):
from bokeh.charts import Bar, output_file, show
details = dfMergeWithInfo["videoSid"].values.tolist()
amount = list(dfMergeWithInfo["playCount"].astype(float).values)
print amount
bar = Bar(dfMergeWithInfo, filename="bar.html")
bar.title("MN Capital Budget - 2014").xlabel("Detail").ylabel("Amount")
show(bar)
def generate_chart(year):
data = get_data(year)
barchart = Bar(data,
values=blend(*SCORED_EVENTS, labels_name='event'),
label=cat(columns='Team', sort=False),
stack=cat(columns='event', sort=False),
color=color(columns='event', palette=Spectral9, sort=False),
xgrid=False, ygrid=False, legend='top_right',
plot_width=1000, plot_height=625,
tools="pan,wheel_zoom,box_zoom,reset,resize")
barchart.title = "Formula SAE Michigan " + str(year) + " Total Scores by Place"
barchart._xaxis.axis_label = "Teams"
barchart._xaxis.axis_line_color = None
barchart._xaxis.major_tick_line_color = None
barchart._xaxis.minor_tick_line_color = None
barchart._xaxis.major_label_text_font_size = '0.6em'
barchart._yaxis.axis_label = "Total Score"
barchart._yaxis.axis_line_color = None
barchart._yaxis.major_tick_line_color = None
barchart._yaxis.minor_tick_line_color = None
barchart.outline_line_color = None
barchart.toolbar_location = 'right'
barchart.logo = None
return barchart
def generate_chart(event):
data = get_data(TIMED_EVENTS[event])
# Bokeh doesn't let me control the order of the grouping! This is
# frustrating since it will be different on every server launch
barchart = Bar(data,
values='percentage_dnf',
label='year',
color="FireBrick",
xgrid=False,
ygrid=False,
plot_width=800,
plot_height=500,
tools="pan,wheel_zoom,box_zoom,reset,resize")
barchart.title = "Formula SAE Michigan DNFs - " + event
barchart._xaxis.axis_label = "Year"
barchart._xaxis.axis_line_color = None
barchart._xaxis.major_tick_line_color = None
barchart._xaxis.minor_tick_line_color = None
barchart._yaxis.axis_label = "Percentage DNF"
barchart._yaxis.axis_line_color = None
barchart._yaxis.major_tick_line_color = None
barchart._yaxis.minor_tick_line_color = None
barchart._yaxis.formatter = NumeralTickFormatter(format="0%")
barchart.y_range = Range1d(0, 1)
barchart.outline_line_color = None
barchart.toolbar_location = 'right'
barchart.logo = None
for renderer in barchart.select(GlyphRenderer):
if renderer.data_source.data['height'] != [0]:
year = renderer.data_source.data['year']
num_dnf = data['dnfs'].loc[data['year'] == year]
num_entries = data['entries'].loc[data['year'] == year]
percent_dnf = data['percentage_dnf'].loc[data['year'] == year]
hover = HoverTool(renderers=[renderer],
tooltips=[
("# DNFs", '%d' % num_dnf.values[0]),
("# Entries", '%d' % num_entries.values[0]),
("% DNF",
'%.2f%%' % (100 * percent_dnf.values[0]))
])
barchart.add_tools(hover)
return barchart
def generate_chart(team):
data = generate_data(team)
selectable_years = list(map(str, data.index.unique()))
# Generate the chart UNFORTUNATELY using the high level plots. Streaming
# a bunch of quads resulted in lots of graphics corruption when switching
# teams. I would rather have the plots work all the time but really slow
# then have the plot show the wrong information.
barchart = Bar(data,
values=blend(*SCORED_EVENTS, labels_name='event'),
label=cat(columns='Year', sort=False),
stack=cat(columns='event', sort=False),
color=color(columns='event', palette=Spectral9, sort=False),
xgrid=False, ygrid=False,
plot_width=1000, plot_height=625,
tools="pan,wheel_zoom,box_zoom,reset,resize")
barchart.title = "Formula SAE Michigan - " + team
barchart._xaxis.axis_label = "Teams"
barchart._xaxis.axis_line_color = None
barchart._xaxis.major_tick_line_color = None
barchart._xaxis.minor_tick_line_color = None
barchart._yaxis.axis_label = "Total Score"
barchart._yaxis.axis_line_color = None
barchart._yaxis.major_tick_line_color = None
barchart._yaxis.minor_tick_line_color = None
barchart.outline_line_color = None
barchart.toolbar_location = 'right'
barchart.logo = None
# Hacky tooltips
for renderer in barchart.select(GlyphRenderer):
if renderer.data_source.data['height'] != [0]:
year = renderer.data_source.data['Year']
place = data['Place'].loc[data['Year'] == year]
score = data['Total Score'].loc[data['Year'] == year]
hover = HoverTool(renderers=[renderer],
tooltips=[("Year", '@Year'),
("Selection", '@event'),
("Event Score", '@height'),
("Total Score", '%.2f' % score.values[0]),
("Overall Place", '%d' % place.values[0])])
barchart.add_tools(hover)
return barchart
def generate_chart(event):
data = get_data(TIMED_EVENTS[event])
# Bokeh doesn't let me control the order of the grouping! This is
# frustrating since it will be different on every server launch
barchart = Bar(data,
values='percentage_dnf',
label='year',
color="FireBrick",
xgrid=False, ygrid=False,
plot_width=800, plot_height=500,
tools="pan,wheel_zoom,box_zoom,reset,resize")
barchart.title = "Formula SAE Michigan DNFs - " + event
barchart._xaxis.axis_label = "Year"
barchart._xaxis.axis_line_color = None
barchart._xaxis.major_tick_line_color = None
barchart._xaxis.minor_tick_line_color = None
barchart._yaxis.axis_label = "Percentage DNF"
barchart._yaxis.axis_line_color = None
barchart._yaxis.major_tick_line_color = None
barchart._yaxis.minor_tick_line_color = None
barchart._yaxis.formatter = NumeralTickFormatter(format="0%")
barchart.y_range = Range1d(0, 1)
barchart.outline_line_color = None
barchart.toolbar_location = 'right'
barchart.logo = None
for renderer in barchart.select(GlyphRenderer):
if renderer.data_source.data['height'] != [0]:
year = renderer.data_source.data['year']
num_dnf = data['dnfs'].loc[data['year'] == year]
num_entries = data['entries'].loc[data['year'] == year]
percent_dnf = data['percentage_dnf'].loc[data['year'] == year]
hover = HoverTool(renderers=[renderer],
tooltips=[("# DNFs", '%d' % num_dnf.values[0]),
("# Entries", '%d' % num_entries.values[0]),
("% DNF", '%.2f%%' % (100 * percent_dnf.values[0]))])
barchart.add_tools(hover)
return barchart
def generate_chart(year):
data = get_data(year)
plot_data = {
'country': data.index.tolist(),
'count': [float(i) for i in data.values.tolist()]
}
barchart = Bar(plot_data,
label='country',
values='count',
color="red",
xgrid=False,
ygrid=False,
plot_width=800,
plot_height=500,
tools="pan,wheel_zoom,box_zoom,reset,resize")
barchart.title = "Formula SAE Michigan " + year + " Countries"
barchart.x_range = FactorRange(factors=data.index.tolist())
barchart._xaxis.axis_label = "Country"
barchart._xaxis.axis_line_color = None
barchart._xaxis.major_tick_line_color = None
barchart._xaxis.minor_tick_line_color = None
barchart._yaxis.axis_label = "Number of Teams"
barchart._yaxis.axis_line_color = None
barchart._yaxis.major_tick_line_color = None
barchart._yaxis.minor_tick_line_color = None
barchart.outline_line_color = None
barchart.toolbar_location = 'right'
barchart.logo = None
hover = HoverTool(tooltips=[("Country", '@x'), ("# Teams", '@height')])
barchart.add_tools(hover)
return barchart
def generate_chart(year):
data = get_data(year)
plot_data = {'country': data.index.tolist(),
'count': [float(i) for i in data.values.tolist()]}
barchart = Bar(plot_data,
label='country',
values='count',
color="red",
xgrid=False, ygrid=False,
plot_width=800, plot_height=500,
tools="pan,wheel_zoom,box_zoom,reset,resize")
barchart.title = "Formula SAE Michigan " + year + " Countries"
barchart.x_range = FactorRange(factors=data.index.tolist())
barchart._xaxis.axis_label = "Country"
barchart._xaxis.axis_line_color = None
barchart._xaxis.major_tick_line_color = None
barchart._xaxis.minor_tick_line_color = None
barchart._yaxis.axis_label = "Number of Teams"
barchart._yaxis.axis_line_color = None
barchart._yaxis.major_tick_line_color = None
barchart._yaxis.minor_tick_line_color = None
barchart.outline_line_color = None
barchart.toolbar_location = 'right'
barchart.logo = None
hover = HoverTool(tooltips=[("Country", '@x'),
("# Teams", '@height')])
barchart.add_tools(hover)
return barchart
def generate_chart():
data = get_data()
# Bokeh doesn't let me control the order of the grouping! This is
# frustrating since it will be different on every server launch
barchart = Bar(data,
label='year',
values='count',
group=cat(columns='size', ascending=True, sort=True),
color=color(columns='size', palette=Spectral4),
legend='top_left',
xgrid=False,
ygrid=False,
plot_width=800,
plot_height=500,
tools="pan,wheel_zoom,box_zoom,reset,resize")
barchart.title = "Formula SAE Michigan Engine Cylinders"
barchart._xaxis.axis_label = "Year"
barchart._xaxis.axis_line_color = None
barchart._xaxis.major_tick_line_color = None
barchart._xaxis.minor_tick_line_color = None
barchart._yaxis.axis_label = "Frequency"
barchart._yaxis.axis_line_color = None
barchart._yaxis.major_tick_line_color = None
barchart._yaxis.minor_tick_line_color = None
barchart.outline_line_color = None
barchart.toolbar_location = 'right'
barchart.logo = None
hover = HoverTool(tooltips=[("Engine", '@size'), ("# Teams", '@height')])
barchart.add_tools(hover)
return barchart
def generate_chart():
data = get_data()
# Bokeh doesn't let me control the order of the grouping! This is
# frustrating since it will be different on every server launch
barchart = Bar(data,
label='year',
values='count',
group=cat(columns='size', ascending=True, sort=True),
color=color(columns='size', palette=Spectral4),
legend='top_left',
xgrid=False, ygrid=False,
plot_width=800, plot_height=500,
tools="pan,wheel_zoom,box_zoom,reset,resize")
barchart.title = "Formula SAE Michigan Engine Cylinders"
barchart._xaxis.axis_label = "Year"
barchart._xaxis.axis_line_color = None
barchart._xaxis.major_tick_line_color = None
barchart._xaxis.minor_tick_line_color = None
barchart._yaxis.axis_label = "Frequency"
barchart._yaxis.axis_line_color = None
barchart._yaxis.major_tick_line_color = None
barchart._yaxis.minor_tick_line_color = None
barchart.outline_line_color = None
barchart.toolbar_location = 'right'
barchart.logo = None
hover = HoverTool(tooltips=[("Engine", '@size'),
("# Teams", '@height')])
barchart.add_tools(hover)
return barchart
def generate_chart(year):
data = get_data(year)
barchart = Bar(data,
values=blend(*SCORED_EVENTS, labels_name='event'),
label=cat(columns='Team', sort=False),
stack=cat(columns='event', sort=False),
color=color(columns='event', palette=Spectral9, sort=False),
xgrid=False,
ygrid=False,
legend='top_right',
plot_width=1000,
plot_height=625,
tools="pan,wheel_zoom,box_zoom,reset,resize")
barchart.title = "Formula SAE Michigan " + str(
year) + " Total Scores by Place"
barchart._xaxis.axis_label = "Teams"
barchart._xaxis.axis_line_color = None
barchart._xaxis.major_tick_line_color = None
barchart._xaxis.minor_tick_line_color = None
barchart._xaxis.major_label_text_font_size = '0.6em'
barchart._yaxis.axis_label = "Total Score"
barchart._yaxis.axis_line_color = None
barchart._yaxis.major_tick_line_color = None
barchart._yaxis.minor_tick_line_color = None
barchart.outline_line_color = None
barchart.toolbar_location = 'right'
barchart.logo = None
return barchart
from collections import OrderedDict
import pandas as pd
# we throw the data into a pandas df
from bokeh.sampledata.olympics2014 import data
from bokeh.charts import Bar
df = pd.io.json.json_normalize(data['data'])
# we filter by countries with at least one medal and sort
df = df[df['medals.total'] > 0]
df = df.sort("medals.total", ascending=False)
# then, we get the countries and we group the data by medal type
countries = df.abbr.values.tolist()
gold = df['medals.gold'].astype(float).values
silver = df['medals.silver'].astype(float).values
bronze = df['medals.bronze'].astype(float).values
# later, we build a dict containing the grouped data
medals = OrderedDict(bronze=bronze, silver=silver, gold=gold)
# any of the following commented are valid Bar inputs
#medals = pd.DataFrame(medals)
#medals = list(medals.values())
bar = Bar(medals, countries, filename="stacked_bar.html")
bar.title("Stacked bars").xlabel("countries").ylabel("medals")
bar.legend(True).width(600).height(400).stacked(True)
bar.show()
dstat[dname] = grp
# later, we build a dict containing the grouped data
["negative","neutral","positive"]
posavglist = []
negavglist = []
namelist = []
for k,v in dstat.items():
posavglist.append(list(v.poscount))
negavglist.append(list(v.negcount))
namelist.append([k+"_neg",k+"_neu",k+"_pos"])
counts = OrderedDict(poscount=posavglist, negcount=negavglist)
bar = Bar(counts, namelist , filename="counts.html")
bar.title("Occurrence of positive and negative counts").xlabel("class").ylabel("count")
bar.legend(True).width(900).height(400).stacked(True)
bar.show()
# Display *all* columns in the tooltips
hover.tooltips = [(c, '@' + c) for c in df.columns]
else:
# Display just the given columns in the tooltips
hover.tooltips = [(c, '@' + c) for c in cols]
hover.tooltips.append(('index', '$index'))
# Finally add/enable the tool
fig.add_tools(hover)
return fig
p2 = scatter_with_hover(test2, 'abs_third_less_adv_simple', 'abs_third_less_adv', marker='circle', fig_width=800, fig_height=800, cols=['bea_code', 'date', 'abs_third_less_adv_simple', 'abs_third_less_adv'], size=20)
p2.title ="Offsetting revisions"
p2.xaxis.axis_label="Absolute (third less adv)"
p2.yaxis.axis_label="Aggregate absolute (third less adv)"
p2.x_range= Range1d(0,test2['abs_third_less_adv_simple'].max()*1.1)
p2.y_range= Range1d(0,test2['abs_third_less_adv'].max()*1.1)
sum_rev = test2['abs_third_less_adv']
simple = test2['abs_third_less_adv_simple']
regression = np.polyfit(simple, sum_rev, 1)
r_x, r_y = zip(*((i, i*regression[0] + regression[1]) for i in range(len(test2['abs_third_less_adv']))))
p2.line(r_x, r_y, color="red", line_width=6)
output_file("regression.html")
show(p2)
docs["poscount"] = docs["hash"].map(countpos)
docs["negcount"] = docs["hash"].map(countneg)
#display
from collections import OrderedDict
# we throw the data into a pandas df
from bokeh.charts import Bar
grp = docs.groupby("polarity").mean()
dstat[dname] = grp
# later, we build a dict containing the grouped data
["negative", "neutral", "positive"]
posavglist = []
negavglist = []
namelist = []
for k, v in dstat.items():
posavglist.append(list(v.poscount))
negavglist.append(list(v.negcount))
namelist.append([k + "_neg", k + "_neu", k + "_pos"])
counts = OrderedDict(poscount=posavglist, negcount=negavglist)
bar = Bar(counts, namelist, filename="counts.html")
bar.title("Occurrence of positive and negative counts").xlabel("class").ylabel(
"count")
bar.legend(True).width(900).height(400).stacked(True)
bar.show()
import pandas as pd
# we throw the data into a pandas df
from bokeh.sampledata.olympics2014 import data
df = pd.io.json.json_normalize(data['data'])
# we filter by countries with at least one medal and sort
df = df[df['medals.total'] > 0]
df = df.sort("medals.total", ascending=False)
# then, we get the countries and we group the data by medal type
countries = df.abbr.values.tolist()
gold = df['medals.gold'].astype(float).values
silver = df['medals.silver'].astype(float).values
bronze = df['medals.bronze'].astype(float).values
# later, we build a dict containing the grouped data
medals = dict(bronze=bronze, silver=silver, gold=gold)
# and finally we drop the countries and medals dict into our Bar chart
from bokeh.charts import Bar
bar = Bar(medals, countries, filename="stacked_bar.html")
bar.title("Stacked bars").xlabel("countries").ylabel("medals")\
.legend(True).width(600).height(400).stacked().show()
