def pieChart(df):
bokeh.io.output_file('static/graphics/pie.html')
labels = list(df['source'].unique())
cant = list(df['source'].value_counts())
x = {labels[i]: cant[i] for i in range(len(labels))}
data = pd.Series(x).reset_index(name='value').rename(
columns={'index': 'country'})
data['angle'] = data['value'] / data['value'].sum() * 2 * pi
data['color'] = viridis(len(x))
p = figure(plot_height=350,
title="Pie Chart",
toolbar_location=None,
tools="hover",
tooltips="@country: @value",
x_range=(-0.5, 1.0))
p.wedge(x=0,
y=1,
radius=0.4,
start_angle=cumsum('angle', include_zero=True),
end_angle=cumsum('angle'),
line_color="white",
fill_color='color',
legend_field='country',
source=data)
p.axis.axis_label = None
p.axis.visible = False
p.grid.grid_line_color = None
# output_file('static/graphics/pie.html')
return p
def generate_chart(self):
"""
Generation of the pie chart bokeh.plotting.figure and different display settings
:return: Pie chart bokeh.plotting.figure
"""
self.data['angle'] = self.data['value'] / self.data['value'].sum(
) * 2 * pi
self.chart = figure(plot_height=400,
title=self.title,
toolbar_location=None,
tools="hover",
tooltips="@{}: @value".format(self.index_name),
x_range=(-0.5, 1.0))
self.chart.wedge(x=0,
y=1,
radius=0.4,
start_angle=cumsum('angle', include_zero=True),
end_angle=cumsum('angle'),
line_color="white",
fill_color='color',
legend=self.index_name,
source=self.data)
self.chart.axis.axis_label = None
self.chart.axis.visible = False
self.chart.grid.grid_line_color = None
self.chart.title.align = "center"
self.chart.title.text_font_style = "bold"
self.chart.title.text_color = "olive"
def _create_varexp_pie_plt(comptable_cds, n_comps):
fig = plotting.figure(plot_width=400,
plot_height=400,
title='Variance Explained View',
tools=['hover,tap,save'],
tooltips=[('Component ID', ' @component'),
('Kappa', '@kappa{0.00}'),
('Rho', '@rho{0.00}'),
('Var. Exp.', '@varexp{0.00}%')])
fig.wedge(x=0,
y=1,
radius=.9,
start_angle=transform.cumsum('angle', include_zero=True),
end_angle=transform.cumsum('angle'),
line_color="white",
fill_color='color',
source=comptable_cds,
fill_alpha=0.7)
fig.axis.visible = False
fig.grid.visible = False
fig.toolbar.logo = None
circle = models.Circle(x=0,
y=1,
size=150,
fill_color='white',
line_color='white')
fig.add_glyph(circle)
return fig
def create_price_grade_chart():
group_by_grade = housing[['price', 'grade']].groupby(['grade']).mean()
group_by_grade['angle'] = group_by_grade['price'] / group_by_grade[
'price'].sum() * 2 * math.pi
group_by_grade['color'] = color.Category20c[len(group_by_grade.index)]
group_by_grade['index'] = group_by_grade.index
p1 = figure(title="Average price of houses depending on grade",
toolbar_location=None,
tools='hover',
sizing_mode="scale_width")
p1.ygrid.grid_line_color = None
p1.xaxis.visible = False
p1.yaxis.visible = False
p1.toolbar.logo = None
p1.toolbar_location = None
p1.wedge(x=0,
y=1,
radius=0.4,
start_angle=cumsum('angle', include_zero=True),
end_angle=cumsum('angle'),
line_color="black",
fill_color='color',
legend='grade',
source=group_by_grade)
hover = p1.select(dict(type=HoverTool))
hover.tooltips = [('Average price', '@price{0,0}$'), ('Grade', '@grade')]
tab1 = Panel(child=p1, title='Grade')
return tab1
def pie_plot(str1):
x = count_items(str1)
data = pd.DataFrame.from_dict(
dict(x), orient='index').reset_index().rename(index=str,
columns={
0: 'value',
'index': str1
})
data['angle'] = data['value'] / sum(x.values()) * 2 * pi
if len(x) < 3:
colours = ['#3182bd', '#6baed6', '#9ecae1']
data['color'] = colours[:len(x)]
else:
data['color'] = Category20c[len(x)]
p = figure(plot_height=350,
title=str1.capitalize(),
toolbar_location=None,
tools="hover",
tooltips="@{}: @value".format(str1))
p.wedge(x=0,
y=1,
radius=0.4,
start_angle=cumsum('angle', include_zero=True),
end_angle=cumsum('angle'),
line_color="white",
fill_color='color',
legend=str1,
source=data)
p.axis.axis_label = None
p.axis.visible = False
p.grid.grid_line_color = None
return p
def drawPieChart(x, paletteType='Set1'):
'''
Input: x --- Dictionary of names and values
(e.g. x = {'United States': 157, 'United Kingdom': 93}
'''
data = pd.Series(x).reset_index(name='value').rename(columns={'index':'country'})
data['angle'] = data['value']/data['value'].sum() * 2*pi
colors = brewer[paletteType][8]
data['color'] = colors[:len(x)]
## p = figure(plot_height=350, title="Pie Chart", toolbar_location=None,
## tools="hover", tooltips="@country: @value", x_range=(-0.5, 1.0))
p = figure(plot_height=350, toolbar_location=None,
tools="hover", tooltips="@country: @value", x_range=(-0.5, 1.0))
p.wedge(x=0, y=1, radius=0.4,
start_angle=cumsum('angle', include_zero=True), end_angle=cumsum('angle'),
line_color="white", fill_color='color', legend_field='country', source=data)
p.axis.axis_label=None
p.axis.visible=False
p.grid.grid_line_color = None
p.outline_line_color = None
p.sizing_mode = 'scale_width'
script, div = components(p)
return script, div
def show():
output_file("html_table_data.html")
x = {
'Passed': 157,
'Failed': 93,
'Skipped': 89,
}
data = pd.Series(x).reset_index(name='value').rename(
columns={'index': 'country'})
data['angle'] = data['value'] / data['value'].sum() * 2 * pi
data['color'] = Category20c[len(x)]
p = figure(plot_height=350,
title="Pie Chart",
toolbar_location=None,
tools="hover",
x_range=(-0.5, 1.0))
p.wedge(x=0,
y=1,
radius=0.4,
start_angle=cumsum('angle', include_zero=True),
end_angle=cumsum('angle'),
line_color="white",
fill_color='color',
legend='country',
source=data)
p.axis.axis_label = None
p.axis.visible = False
p.grid.grid_line_color = None
show(p)
def generate(self, args):
data = self.get_data_dict(args)
source = {
"empl_name": [],
"hours": [],
}
for empl, hours in data.items():
source["empl_name"].append(
self.get_display_name_for_key_entity(empl))
source["hours"].append(float(hours))
hour_sum = sum(source["hours"])
source["angle"] = [
hours / hour_sum * 2 * math.pi for hours in source["hours"]
]
source["color"] = util.repeat_maxlen(ColorPalette,
len(source["hours"]))
self.figure.wedge(
x=0,
y=1,
radius=0.4,
start_angle=cumsum("angle", include_zero=True),
end_angle=cumsum("angle"),
line_color="black",
fill_color="color",
legend="empl_name",
source=source,
)
def generate_pie_chart(df, title, driver, index, output_file_dir):
df["angle"] = df["value"] / df["value"].sum() * 2 * pi
colors = ["#f44336", "#2196f3"]
df["color"] = colors[:len(df)]
legend = []
for row in df.iterrows():
_, remain = row
legend.append(f"{remain.answer} - {remain.percent} ({remain.value})")
df["legend"] = legend
p = figure(
plot_height=350,
title=title[index],
toolbar_location=None,
tools="hover",
tooltips="@answer: @value",
x_range=(-0.5, 1.0),
output_backend="svg",
)
#
p.wedge(
x=0,
y=1,
radius=0.4,
start_angle=cumsum("angle", include_zero=True),
end_angle=cumsum("angle"),
line_color="white",
fill_color="color",
legend_field="legend",
source=df,
)
p.axis.axis_label = None
p.axis.visible = False
p.grid.grid_line_color = None
write_chart(output_file_dir, title[index], p, driver)
def piechart(src, heads, val, acci, title=''):
title = title + accisev[acci] + " casualties, " + val + " by " + heads
src.columns = src.columns.get_level_values(0)
src['angle'] = src[val] / src[val].sum() * 2 * pi
src['percent'] = src[val] / src[val].sum() * 100.00
src['color'] = viridis(len(src.index))
p = figure(plot_height=350,
title=title,
toolbar_location=None,
tools="hover",
tooltips="@" + heads + ": @" + val + ", @percent",
x_range=(-0.5, 1.0))
p.wedge(x=0,
y=1,
radius=0.4,
start_angle=cumsum('angle', include_zero=True),
end_angle=cumsum('angle'),
line_color="white",
fill_color='color',
legend=heads,
source=src)
p.axis.axis_label = None
p.axis.visible = False
p.grid.grid_line_color = None
show(p)
def get_plot(x):
data = pd.Series(x).reset_index(name='value').rename(
columns={'index': 'country'})
data['angle'] = data['value'] / 100 * 2 * pi
data['color'] = get_color(x)
source = ColumnDataSource(data)
p = figure(plot_height=350,
title="Pie Chart",
toolbar_location=None,
tools="hover",
tooltips="@country: @value",
x_range=(-0.5, 1.0))
p.wedge(x=0,
y=1,
radius=0.4,
start_angle=cumsum('angle', include_zero=True),
end_angle=cumsum('angle'),
line_color="white",
fill_color='color',
source=source)
p.axis.axis_label = None
p.axis.visible = False
p.grid.grid_line_color = None
return p
def plot_gender():
x = {'男性 Male': 150, '女性 Female': 129, '答えたくない Prefer not to say': 7}
data = pd.Series(x).reset_index(name='value').rename(
columns={'index': 'gender'})
data['angle'] = data['value'] / data['value'].sum() * 2 * pi
data['color'] = Category20c[len(x)]
p = figure(plot_height=350,
plot_width=550,
title="Gender",
toolbar_location=None,
tools="hover",
tooltips="@gender: @value",
x_range=(-0.5, 1.0))
p.wedge(x=0,
y=1,
radius=0.4,
start_angle=cumsum('angle', include_zero=True),
end_angle=cumsum('angle'),
line_color="white",
fill_color='color',
legend_field='gender',
source=data)
p.axis.axis_label = None
p.axis.visible = False
p.grid.grid_line_color = None
script, div = components(p)
return script, div
def diagram(a):
x = {
'Организованные мероприятия': a[0],
'Гость мероприятий': a[1],
}
print(type(x))
data = pd.Series(x).reset_index(name='value').rename(
columns={'index': 'country'})
data['angle'] = data['value'] / data['value'].sum() * 2 * pi
data = pd.Series(x).reset_index(name='value').rename(
columns={'index': 'country'})
data['angle'] = data['value'] / data['value'].sum() * 2 * pi
data['color'] = ['#feeaf5', '#ced2ff']
p = figure(plot_height=350,
title="Мероприятия",
toolbar_location=None,
tools="hover",
tooltips="@country: @value",
x_range=(-0.5, 1.0))
p.wedge(x=0,
y=1,
radius=0.4,
start_angle=cumsum('angle', include_zero=True),
end_angle=cumsum('angle'),
line_color="white",
fill_color='color',
legend='country',
source=data)
p.axis.axis_label = None
p.axis.visible = False
p.grid.grid_line_color = None
return p
def graph_pie_sport_origin(title, origin):
# Manage data with Pandas
# Based on code found in https://bokeh.pydata.org/en/latest/docs/gallery/pie_chart.html
data = pd.Series(origin).reset_index(name='value').rename(
columns={'index': 'country'})
data['angle'] = data['value'] / data['value'].sum() * 2 * 3.14159
data['color'] = ['#3288bd', '#99d594', '#e6f598', '#fee08b', '#fc8d59']
graph = figure(plot_height=350,
title=title,
toolbar_location=None,
tools="hover",
tooltips="@country: @value")
# Graph the pie pieces
graph.wedge(x=0,
y=1,
radius=0.4,
start_angle=cumsum('angle', include_zero=True),
end_angle=cumsum('angle'),
line_color="white",
fill_color='color',
legend='country',
source=data)
# Hide background grid and axis
graph.axis.visible = False
graph.xgrid.visible = False
graph.ygrid.visible = False
# Automatically adjust graph size
graph.sizing_mode = default_sizing
return components(graph)
def plot_bokeh_sex_pie(queryset: QuerySet) -> Figure:
values = list(queryset.values("sex"))
data = (pd.DataFrame(values).replace({
"sex": SEX_VALUES
}).value_counts().reset_index(name="value").rename(columns={
"index": "sex"
}).merge(SEX_COLORS, left_on="sex", right_index=True))
data["angle"] = data["value"] / data["value"].sum() * 2 * pi
p = figure(
plot_height=250,
plot_width=350,
title="Sex",
toolbar_location=None,
tools="hover",
tooltips="@sex: @value",
x_range=(-0.5, 1.0),
)
p.wedge(
x=0,
y=1,
radius=0.3,
start_angle=cumsum("angle", include_zero=True),
end_angle=cumsum("angle"),
line_color="white",
fill_color="color",
legend_field="sex",
source=data,
)
p.axis.axis_label = None
p.axis.visible = False
p.grid.grid_line_color = None
return p
def print_pie_chart(data_, filename="outputPie.html", title_="default", top=19):
for k, v in data_.items():
data_[k] = round(v, 1)
output_file(filename)
data_sorted = sorted(data_.items(), key=lambda x:x[1], reverse=True)
if len(data_) > top+1 :
misc = 0
while len(data_sorted) > top:
misc += float(data_sorted.pop()[1])
data_sorted.append(("misc", round(misc,1)))
print(" cut len down to: " + str(len(data_)))
print (data_sorted)
data_ = Counter(data_sorted)
data = pd.DataFrame.from_dict(dict(data_), orient='index').reset_index().rename(index=str, columns={0:'value', 'index':'country'})
data['angle'] = data['value']/sum(data_.values()) * 2*pi
data['color'] = Category20c[len(data_)]
p = figure(plot_height=520, plot_width = 1000, title=title_, toolbar_location="left",
tools="hover", tooltips="@country: @value")
p.wedge(x=0, y=1, radius=0.4,
start_angle=cumsum('angle', include_zero=True), end_angle=cumsum('angle'),
line_color="white", fill_color='color', legend='country', source=data)
p.axis.axis_label=None
p.axis.visible=False
p.grid.grid_line_color = None
show(p)
def sentiment_tab(df):
sentiment_count = df["Sentiment"].value_counts()
x = {
'Positive': sentiment_count.iloc[0],
'Negative': sentiment_count.iloc[1]
}
chart_colors = ['#DAF7A6', '#FF5733']
data = pd.Series(x).reset_index(name='value').rename(columns={'index':'sentiment'})
data['angle'] = data['value']/data['value'].sum() * 2*pi
data['color'] = chart_colors[:len(x)]
p = figure(plot_height=350, title="Sentiment Chart", toolbar_location=None,
tools="hover", tooltips="@sentiment: @value", x_range=(-0.5, 1.0))
p.wedge(x=0, y=1, radius=0.4,
start_angle=cumsum('angle', include_zero=True), end_angle=cumsum('angle'),
line_color="white", fill_color='color', legend='sentiment', source=data)
p.axis.axis_label=None
p.axis.visible=False
p.grid.grid_line_color = None
tab = Panel(child=p, title='Sentiment Chart')
return tab
def draw_piechart(collection, colum, count, asc):
mycollection = mydb[collection]
rs = mycollection.find().limit(count).sort([(colum, asc)])
#data_lastday = get_data_sort('moneyflow_lastday','net_mf_amount',-1,100)
#按照industry分类
#将查询结果转换为Df
data = pd.DataFrame(list(rs))
grouped = data.groupby('industry')
groupcount = grouped.size()
pie_data = pd.DataFrame()
pie_data['value'] = groupcount
#data拼装 industry angle color
pie_data['angle'] = pie_data['value'] / count * 2 * pi
pie_data['color'] = Category20c[len(pie_data)]
p = figure(plot_height=400,
plot_width=400,
toolbar_location=None,
tools="hover",
tooltips="@industry: @value")
p.wedge(x=0,
y=1,
radius=0.4,
start_angle=cumsum('angle', include_zero=True),
end_angle=cumsum('angle'),
line_color="white",
fill_color='color',
legend='industry',
source=pie_data)
p.axis.axis_label = None
p.axis.visible = False
p.grid.grid_line_color = None # 网格线颜色
return p
def get_per_app_usage():
total_time_spent = df.duration.sum()
per_app_df = df.groupby('app_name')['duration'].sum().sort_values(
ascending=False).to_frame().reset_index()
per_app_df['angle'] = np.nan
per_app_df['color'] = np.nan
per_app_df.angle = per_app_df.duration.apply(
lambda x: x.seconds / total_time_spent.seconds * 2 * pi)
per_app_df['color'] = per_app_df.app_name.apply(lambda x: color_map[x])
per_app_df['duration_min'] = per_app_df['duration'].apply(
lambda x: x.seconds // 60)
p = figure(plot_height=400,
plot_width=400,
toolbar_location=None,
tools="hover",
tooltips="@app_name: @duration_min min")
p.wedge(x=0,
y=1,
radius=0.9,
start_angle=cumsum('angle', include_zero=True),
end_angle=cumsum('angle'),
line_color="white",
fill_color='color',
source=per_app_df)
p.axis.axis_label = None
p.axis.visible = False
p.grid.grid_line_color = None
return json.dumps(json_item(p, "per_app_usage"))
def pie_chart(df):
ccounts = df.Country.value_counts()
df.loc[df['Country'].isin(ccounts[ccounts.values < 500].index),
'Country'] = 'Others'
rf = pd.DataFrame(df['Country'].value_counts())
rf['angle'] = rf['Country'] / rf['Country'].sum() * 2 * pi
rf['color'] = Category20c[rf.shape[0]]
p = figure(plot_height=500,
title="Country wise Sales",
toolbar_location=None,
tools="hover",
tooltips="@index: @Country",
x_range=(-0.5, 1.0))
p.wedge(x=0,
y=1,
radius=0.5,
start_angle=cumsum('angle', include_zero=True),
end_angle=cumsum('angle'),
line_color="white",
fill_color='color',
legend='index',
source=rf)
p.axis.axis_label = None
p.axis.visible = False
p.grid.grid_line_color = None
return p
def plot_meals():
x = {
'3食 3 meals': 175,
'3食未満 Less than 3 meals': 88,
'3食以上 More than 3 meals': 23
}
data = pd.Series(x).reset_index(name='value').rename(
columns={'index': 'meals'})
data['angle'] = data['value'] / data['value'].sum() * 2 * pi
data['color'] = Category20c[len(x)]
p = figure(plot_height=350,
plot_width=550,
title="Number of meals",
toolbar_location=None,
tools="hover",
tooltips="@diet: @value",
x_range=(-0.5, 1.0))
p.wedge(x=0,
y=1,
radius=0.4,
start_angle=cumsum('angle', include_zero=True),
end_angle=cumsum('angle'),
line_color="white",
fill_color='color',
legend_field='meals',
source=data)
p.axis.axis_label = None
p.axis.visible = False
p.grid.grid_line_color = None
script, div = components(p)
return script, div
def plot_mental_diseases():
x = {'いいえ No': 182, '多分 Maybe': 43, 'はい Yes': 39}
data = pd.Series(x).reset_index(name='value').rename(
columns={'index': 'mental_diseases'})
data['angle'] = data['value'] / data['value'].sum() * 2 * pi
data['color'] = Category20c[len(x)]
p = figure(plot_height=350,
plot_width=550,
title="Have you experienced any disorder?",
toolbar_location=None,
tools="hover",
tooltips="@mental_diseases: @value",
x_range=(-0.5, 1.0))
p.wedge(x=0,
y=1,
radius=0.4,
start_angle=cumsum('angle', include_zero=True),
end_angle=cumsum('angle'),
line_color="white",
fill_color='color',
legend_field='mental_diseases',
source=data)
p.axis.axis_label = None
p.axis.visible = False
p.grid.grid_line_color = None
script, div = components(p)
return script, div
def plot_diet():
x = {
'同じくらい Balanced': 155,
'肉中心 Meat focused': 98,
'野菜中心 Vegetable focused': 33
}
data = pd.Series(x).reset_index(name='value').rename(
columns={'index': 'diet'})
data['angle'] = data['value'] / data['value'].sum() * 2 * pi
data['color'] = Category20c[len(x)]
p = figure(plot_height=350,
plot_width=550,
title="Diet",
toolbar_location=None,
tools="hover",
tooltips="@diet: @value",
x_range=(-0.5, 1.0))
p.wedge(x=0,
y=1,
radius=0.4,
start_angle=cumsum('angle', include_zero=True),
end_angle=cumsum('angle'),
line_color="white",
fill_color='color',
legend_field='diet',
source=data)
p.axis.axis_label = None
p.axis.visible = False
p.grid.grid_line_color = None
script, div = components(p)
return script, div
def get_question_pie(hotel_id, question):
"""
this function gets hotel_id and question as input and returns pie chart for that questions
answers for that hotel
"""
x = dict(pd.DataFrame({'col1': get_question_answers(hotel_id,question)}).col1.value_counts())
# print(x)
data = pd.Series(x).reset_index(name='value').rename(columns={'index':'answer'})
data['angle'] = data['value']/data['value'].sum() * 2*pi
data['color'] = viridis(len(x))
p = figure(plot_height=250, plot_width = 375, title= question, toolbar_location=None,
tools="hover", tooltips="@answer: @value", x_range=(-0.5, 1.0))
p.wedge(x=0, y=1,radius=0.4,
start_angle=cumsum('angle', include_zero=True), end_angle=cumsum('angle'),
line_color="black", fill_color='color', legend='answer', source=data)
p.axis.axis_label=None
p.axis.visible=False
p.grid.grid_line_color = None
script,div = components(p)
return [script,div]
def first_graph():
df = read_mongo()
df_corona = df[df.corona == 'Ja']
df_new = df_corona['province'].value_counts()
data = pd.Series(df_new).reset_index(name='corona').rename(
columns={'index': 'province'})
data['angle'] = data['corona'] / data['corona'].sum() * 2 * pi
p = figure(plot_height=350,
title="Pie Chart",
toolbar_location=None,
tools="hover",
tooltips="@province : @corona")
p.wedge(x=0,
y=1,
radius=0.4,
start_angle=cumsum('angle', include_zero=True),
end_angle=cumsum('angle'),
line_color="white",
fill_color='red',
legend='province',
source=data)
return p
def getPieChart(d):
import copy
x = copy.deepcopy(d)
del x['timestamp']
for k in x.keys():
tmp = x[k]
x[k] = sum(tmp, 0.0) / len(tmp)
data = pd.Series(x).reset_index(name='value').rename(
columns={'index': 'country'})
data['angle'] = data['value'] / data['value'].sum() * 2 * pi
data['color'] = Category20c[len(x)]
p = figure(plot_height=350,
title="Pie Chart",
toolbar_location=None,
tools="hover",
tooltips="@country: @value",
x_range=(-0.5, 1.0))
p.wedge(x=0,
y=1,
radius=0.4,
start_angle=cumsum('angle', include_zero=True),
end_angle=cumsum('angle'),
line_color="white",
fill_color='color',
legend='country',
source=data)
p.axis.axis_label = None
p.axis.visible = False
p.grid.grid_line_color = None
output_file("html/시간별 평균 활동(pie).html")
show(p)
def pie(list):
data = pd.Series(list).reset_index(name='value').rename(
columns={'index': 'candidat'})
data['angle'] = data['value'] / data['value'].sum() * 2 * pi
data['color'] = Category20c[len(list)]
p = figure(plot_height=500,
title="Pie Chart",
toolbar_location=None,
tools="hover",
tooltips="@candidat: @value",
x_range=(-0.5, 1.0))
p.wedge(x=0,
y=1,
radius=0.4,
start_angle=cumsum('angle', include_zero=True),
end_angle=cumsum('angle'),
line_color="white",
fill_color='color',
legend='candidat',
source=data)
p.axis.axis_label = None
p.axis.visible = False
p.grid.grid_line_color = None
show(p)
def get_total_score_doughnut(hotel_id):
"""
this function will get hotel id as an input and return doughnut graph (script and div)
for total score
"""
score = get_total_review_score(hotel_id)
x = {
# pass the id of selected hotel here to get the doughnut graph
'Score': score,
'Rest' : (5-score)
}
data = pd.Series(x).reset_index(name='value').rename(columns={'index':'scoring'})
data['angle'] = data['value']/5 * 2*pi
data['color'] = ['blue', 'white']
p = figure(plot_height=250, plot_width = 375, title="Overall Score", toolbar_location=None,
tools="hover", tooltips="@scoring: @value", x_range=(-0.5, 1.0))
p.annular_wedge(x=0, y=1,inner_radius = 0.2, outer_radius=0.4,
start_angle=cumsum('angle', include_zero=True), end_angle=cumsum('angle'),
line_color="black", fill_color='color', legend='scoring', source=data)
p.axis.axis_label=None
p.axis.visible=False
p.grid.grid_line_color = None
script,div = components(p)
return [script,div]
def create_pie_chart(self):
data = pd.Series(self._pie_chart_data).reset_index(
name='value').rename(columns={'index': 'category'})
data['angle'] = data['value'] / data['value'].sum() * 2 * pi
data['color'] = self.get_category20c_color()
p = figure(plot_height=self.pie_chart_conf['plot_height'],
title=self.chart_title,
toolbar_location=None,
tools="hover",
tooltips="@category: @value",
x_range=self.pie_chart_conf['xrange'])
p.wedge(x=self.pie_chart_conf['x'],
y=self.pie_chart_conf['y'],
radius=self.pie_chart_conf['radius'],
start_angle=cumsum('angle', include_zero=True),
end_angle=cumsum('angle'),
line_color="white",
fill_color='color',
legend_field='category',
source=data)
p.axis.axis_label = None
p.axis.visible = False
p.grid.grid_line_color = None
plot_html = file_html(p, CDN)
return plot_html
def make_ajax_plot():
test = AjaxDataSource(data_url=request.url_root + 'data/',
polling_interval=2000,
mode='replace')
test.data = dict(angle=[], country=[], value=[], color=[])
print(test.data)
plot = figure(plot_height=350,
title="Pie Chart",
toolbar_location=None,
tools="hover",
tooltips="@country: @value")
plot.annular_wedge(x=0,
y=1,
inner_radius=0.2,
outer_radius=0.4,
start_angle=cumsum('angle', include_zero=True),
end_angle=cumsum('angle'),
line_color=None,
fill_color='color',
legend='country',
source=test)
plot.axis.axis_label = None
plot.axis.visible = False
plot.grid.grid_line_color = None
script, div = components(plot)
return script, div
def test_include_zero(object):
s = bt.cumsum("foo", include_zero=True)
assert isinstance(s, dict)
assert list(s.keys()) == ["expr"]
assert isinstance(s['expr'], CumSum)
assert s['expr'].field == 'foo'
assert s['expr'].include_zero == True
'United States': 157,
'United Kingdom': 93,
'Japan': 89,
'China': 63,
'Germany': 44,
'India': 42,
'Italy': 40,
'Australia': 35,
'Brazil': 32,
'France': 31,
'Taiwan': 31,
'Spain': 29
})
data = pd.DataFrame.from_dict(dict(x), orient='index').reset_index().rename(index=str, columns={0:'value', 'index':'country'})
data['angle'] = data['value']/sum(x.values()) * 2*pi
data['color'] = Category20c[len(x)]
p = figure(plot_height=350, title="Pie Chart", toolbar_location=None,
tools="hover", tooltips="@country: @value")
p.wedge(x=0, y=1, radius=0.4,
start_angle=cumsum('angle', include_zero=True), end_angle=cumsum('angle'),
line_color="white", fill_color='color', legend='country', source=data)
p.axis.axis_label=None
p.axis.visible=False
p.grid.grid_line_color = None
show(p)
