def bookreport():
bar = Bar()
bar.add_xaxis(['Last Day', 'Last 7 days', 'Last 30 days'])
conn = connect_to_database()
borrowedBookNums = []
returnedNums = []
days = [1, 7, 30]
for day in days:
sql = "select count(*) from BookBorrowed where (CURRENT_DATE - BorrowedDate) <= %s" % day
cursor = conn.cursor()
try:
cursor.execute(sql)
except Exception as e:
print(e)
conn.commit()
res = cursor.fetchone()
borrowedBookNums.append(res[0])
sql = "select count(*) from BookBorrowed where (CURRENT_DATE - ReturnedDate) <= %s" % day
cursor = conn.cursor()
try:
cursor.execute(sql)
except Exception as e:
print(e)
conn.commit()
res = cursor.fetchone()
returnedNums.append(res[0])
bar.add_yaxis('Borrowed Book', borrowedBookNums)
bar.add_yaxis('Returned Book', returnedNums)
return render_template('report.html', myechart=bar.render_embed())
def show(x: list, y: list, title: str = "键盘键入统计"):
bar = Bar(init_opts=opts.InitOpts(theme=ThemeType.WONDERLAND))
bar.add_xaxis(x)
bar.add_yaxis("", y, category_gap="60%")
bar.set_series_opts(
itemstyle_opts={
"normal": {
"color":
JsCode("""new echarts.graphic.LinearGradient(0, 0, 0, 1, [{
offset: 0,
color: 'rgba(0, 244, 255, 1)'
}, {
offset: 1,
color: 'rgba(250, 177, 160, 1)'
}], false)"""),
"barBorderRadius": [30, 30, 30, 30],
"shadowColor":
"rgb(0, 160, 221)",
}
})
bar.set_global_opts(
title_opts=opts.TitleOpts(title=title),
datazoom_opts=[opts.DataZoomOpts(),
opts.DataZoomOpts(type_="inside")],
)
bar.load_javascript()
bar.render_notebook()
return Markup(bar.render_embed())
def score_dis(request):
"""获取教师所教学生的成绩分布"""
nid = 't1'
# 获取教师所授课程编号
course_number = sqlheper.get_list('select course_number from course where teacher_number=%s', [nid, ])
cn = []
for i in course_number:
for key, value in i.items():
cn.append(value)
# 在学生选课表中查找选择该课程的学生的成绩
student_mark = sqlheper.get_list('select mark from stu_c where course_number=%s', [cn, ])
mark_a, mark_b, mark_c, mark_d, mark_f = [], [], [], [], []
for i in student_mark:
for key, values in i.items():
values = int(values)
if values >= 90:
mark_a.append(values)
elif 80 <= values < 90:
mark_b.append(values)
elif 70 <= values < 80:
mark_c.append(values)
elif 60 <= values < 70:
mark_d.append(values)
else:
mark_f.append(values)
mark = [len(mark_a), len(mark_b), len(mark_c), len(mark_d), len(mark_d)]
bar = Bar(init_opts=opts.InitOpts(width='800px', height='500px', theme=ThemeType.LIGHT))
bar.add_xaxis(['优秀', '良好', '中等', '及格', '不及格'])
bar.add_yaxis('学生成绩', mark)
return render(request, 'student_mark_ana.html', {'bar': bar.render_embed()})
def generate_top_bar_html(rows, title):
xx1 = []
yy1 = []
for row in rows:
xx1.append(row[0].replace('转债', ''))
yy1.append(row[1])
bar = Bar(init_opts=opts.InitOpts(
height='700px', width='1424px', theme=ThemeType.SHINE))
# 底部x轴
bar.add_xaxis(xx1)
bar.add_yaxis(
'价格(元)',
yy1,
bar_width=25,
category_gap='1%',
gap='1%',
label_opts=opts.LabelOpts(position="top", ),
)
bar.set_series_opts(itemstyle_opts=opts.ItemStyleOpts(
color=JsCode("function(x){return x.data>0?'#c23531':'#1d953f'}")))
bar.set_global_opts(
title_opts=opts.TitleOpts(
title="=========" + title + "=========",
pos_left='center',
pos_top='-1px',
),
tooltip_opts=opts.TooltipOpts(is_show=False),
legend_opts=opts.LegendOpts(is_show=False),
xaxis_opts=opts.AxisOpts(
# data=None,
# type_='category',
# name_gap=0,
# name_rotate=90,
axislabel_opts=opts.LabelOpts(rotate=-60, ),
is_scale=True,
name_location='middle',
splitline_opts=opts.SplitLineOpts(is_show=False),
axisline_opts=opts.AxisLineOpts(is_on_zero=True,
# symbol=['none', 'arrow']
)),
yaxis_opts=opts.AxisOpts(
type_='value',
name='价格(元)',
# name_rotate=90,
name_gap=40,
name_location='middle',
# min_=0,
is_scale=True,
# axislabel_opts=opts.LabelOpts(formatter='{value}%'),
splitline_opts=opts.SplitLineOpts(is_show=False),
axisline_opts=opts.AxisLineOpts(is_on_zero=False,
# symbol=['none', 'arrow']
)),
)
bar_html = bar.render_embed('template.html', html_utils.env)
return bar_html
def bookreport():
bar = Bar()
bar.add_xaxis([
'Sunday', 'Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday',
'Saturday'
])
bar.add_yaxis('Borrowed Book', [12, 15, 20, 10, 5, 8, 10])
bar.add_yaxis('Returned Book', [10, 18, 10, 7, 6, 6, 4])
return render_template('report.html', myechart=bar.render_embed())
def bar1() -> Bar:
bar=Bar() # instantiation
bar.add_yaxis("商家A", [5, 20, 36, 10, 75, 90])
bar.add_yaxis("商家B", [15, 25, 16, 55, 48, 8])
bar.add_xaxis(["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"])
bar.set_global_opts(
title_opts=opts.TitleOpts(
title="柱状图基本事例",
subtitle="我是副标题"))
return Markup(bar.render_embed())
def BarCharts(datas):
bar = Bar(init_opts=opts.InitOpts(width="100%"))
bar.add_xaxis(datas[1])
for data in datas[2]:
bar.add_yaxis(data[0], data[1])
# .add_yaxis("商家B", [20, 10, 40, 30, 40, 50])
bar.set_global_opts(
xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(rotate=-15)),
title_opts=opts.TitleOpts(title=datas[0]),
)
return bar.render_embed()
def demo(request):
import store
bar = Bar(init_opts=opts.InitOpts(theme=ThemeType.LIGHT))
#x = store.models.Product.objects.get(sortno=1)
#y = store.models.Product.objects.get(sortno=2)
bar.add_xaxis(["純色腮紅", "三色修容餅", "柔焦無瑕粉餅", "經典緞光唇膏", "精萃水亮唇膏"])
bar.add_yaxis("康是美", [100, 50, 45, 20, 50])
bar.add_yaxis("寶雅", [80, 40, 10, 100, 70])
bar.add_yaxis("屈臣氏", [20, 30, 45, 130, 80])
bar.set_global_opts(title_opts=opts.TitleOpts(title="品類需求量", subtitle="個"))
return HttpResponse(bar.render_embed())
def trendresult():
word = request.form.get("word")
begin = request.form.get("begin")
end = request.form.get("end")
if begin == "" and end == "":
date_list = mp.Get_time_14() # 当前时间回溯14天
else:
date_list = mp.Get_time_every(begin, end) # 当前时间段
[date_list_new, date_every_sentiment] = mp.get_sentiment(date_list, word)
[date_list_new, date_every_num] = mp.draw_bar(date_list, word)
[date_l, true_l, predict_l] = arima.arima_model(date_list_new,
date_every_sentiment)
bar = Bar(init_opts=opts.InitOpts(theme=ThemeType.WESTEROS))
dictd = {}
for i in range(len(date_every_sentiment)):
if date_every_sentiment[i] < 0.2:
dictd[date_list_new[i]] = "高度预警"
elif date_every_sentiment[i] < 0.3:
dictd[date_list_new[i]] = "中度预警"
elif date_every_sentiment[i] < 0.4:
dictd[date_list_new[i]] = "低度预警"
# 统计趋势
c = (Line(init_opts=opts.InitOpts(
theme=ThemeType.WESTEROS)).add_xaxis(date_l).add_yaxis(
'实际值', true_l, is_connect_nones=True).add_yaxis(
'预测值', predict_l, is_connect_nones=True).set_series_opts(
label_opts=opts.LabelOpts(is_show=False)))
# 统计数量
bar.add_xaxis(date_list_new)
bar.add_yaxis("涉及的词条数量", date_every_num)
# 预警
return render_template('trendresult.html',
myechart1=c.render_embed(),
myechart2=bar.render_embed(),
begin=date_list[0],
end=date_list[-1],
data=dictd,
length=len(dictd))
def bar():
cursor = connection.cursor()
cursor.execute("""SELECT
DATE_FORMAT( rev.create_time, '%Y-%m-%d' ) create_time,
revt.`name`,
count( * )
FROM
resource_event rev
LEFT JOIN resource_eventtype revt ON rev.event_type_id = revt.id
GROUP BY
create_time,
event_type_id""")
rows = cursor.fetchall()
name_list = []
event_type_list = []
for row in rows:
name = row[0]
if name not in name_list:
name_list.append(name)
event_type = row[1]
if event_type not in event_type_list:
event_type_list.append(event_type)
bar = Bar(init_opts=opts.InitOpts(height="350px"))
bar.add_xaxis(name_list)
for event_type in event_type_list:
tmp_list = [0 for i in range(len(name_list))]
for row in rows:
if event_type == row[1]:
index = name_list.index(row[0])
tmp_list[index] = row[2]
bar.add_yaxis(event_type, tmp_list)
bar.set_global_opts(title_opts=opts.TitleOpts(title="违章记录统计"), toolbox_opts=opts.ToolboxOpts(is_show=False,
feature=opts.ToolBoxFeatureOpts(
restore=None,
data_zoom=None)))
return bar.render_embed()
def ana(request):
# 获取学生所有科目成绩，绘制柱状图
nid = '2017322001'
course = []
mark = []
course_list = sqlheper.get_list(
'select course.course_name,mark from stu_c left join course on stu_c.course_number=course.course_number where student_id=%s',
[
nid,
])
for i in course_list:
for key, values in i.items():
if key == 'course_name':
course.append(values)
else:
mark.append(values)
print(course, mark)
bar = Bar(init_opts=opts.InitOpts(
width='800px', height='500px', theme=ThemeType.LIGHT))
bar.add_xaxis(course)
bar.add_yaxis('学生成绩', mark)
return render(request, 'student_mark_ana.html',
{'bar': bar.render_embed()})
def detail(request):
try:
if request.session['username']==None:
return HttpResponseRedirect('/login/')
except KeyError:
return HttpResponseRedirect('/login/')
subject = request.GET.get('subject')
taskid = request.GET.get('taskid')
username = request.session['username']
r={}
result = DoubanSubject.objects.get(subject=subject,taskid=taskid)
bar=Bar()
mychartname = result.name+"评分占比"
bar.add_xaxis(["五星", "四星", "三星", "二星", "一星"])
bar.add_yaxis(mychartname, [float(result.star_five[:-1]), float(result.star_four[:-1]), float(result.star_three[:-1]), float(result.star_two[:-1]),float(result.star_one[:-1])])
bar.set_global_opts(
title_opts=opts.TitleOpts(title=mychartname),
toolbox_opts=opts.ToolboxOpts(),
legend_opts=opts.LegendOpts(is_show=False),
)
r['myechart'] = bar.render_embed()
r['result']=result
return render(request,'detail.html',r)
def admin_ana(request):
"""
了解专业人数分布情况
1.获取所有专业名称
2.获取每个专业人数
"""
major_list = sqlheper.get_list('select major_name from major', [])
major = []
for i in major_list:
for key, value in i.items():
major.append(value)
major_num = []
for i in major:
num = len(
sqlheper.get_list('select * from student where major_name=%s',
[i]))
major_num.append(num)
bar = Bar(init_opts=opts.InitOpts(
width='1200px', height='500px', theme=ThemeType.LIGHT))
bar.set_global_opts(title_opts=opts.TitleOpts(title='不同专业人数分布情况'))
bar.add_xaxis(major)
bar.add_yaxis('人数', major_num, bar_max_width='40px')
# 了解课程和成绩的相关性
course_list = sqlheper.get_list(
'select course_number,course_name from course order by id', [])
print(course_list)
course_name, course_num = [], []
for i in course_list:
for key, value in i.items():
if key == 'course_name':
course_name.append(value)
else:
course_num.append(value)
print(course_num)
course_h, course_m, course_l = [], [], []
for i in course_num:
# 对每一门课程，分别计算高、中、低的成绩人数
high, med, low = 0, 0, 0
mark = sqlheper.get_list(
'select mark from stu_c where course_number=%s', [
i,
])
for j in mark:
for key, value in j.items():
# 遍历所有选择该课程的学生成绩
value = int(value)
if value > 85:
high += 1
elif 60 < value <= 85:
med += 1
elif value <= 60:
low += 1
course_h.append(high)
course_m.append(med)
course_l.append(low)
bar_c = Bar(init_opts=opts.InitOpts(
width='1200px', height='500px', theme=ThemeType.LIGHT))
bar_c.set_global_opts(title_opts=opts.TitleOpts(title='课程和成绩的相关性'))
print(course_name)
bar_c.add_xaxis(course_name)
bar_c.add_yaxis('高分段', course_h)
bar_c.add_yaxis('中分段', course_m)
bar_c.add_yaxis('低分段', course_l)
stu_num = len(sqlheper.get_list('select * from student', []))
cou_num = len(sqlheper.get_list('select * from course', []))
tea_num = len(sqlheper.get_list('select * from teacher', []))
return render(
request, 'admin_ana.html', {
'bar': bar.render_embed(),
'bar_c': bar_c.render_embed(),
'stu_num': stu_num,
'cou_num': cou_num,
'tea_num': tea_num,
})
def generate_bar_html(rows, title):
x = []
y = []
for row in rows:
x.append(row[0])
y.append({'value': row[1], 'range': [row[2], row[3]]})
bar = Bar(init_opts=opts.InitOpts(height='700px',
width='1424px',
theme=ThemeType.SHINE,
chart_id="cb_tree_map"))
bar.add_xaxis(x)
bar.add_yaxis(
"个数",
y,
yaxis_index=0,
bar_width=50,
category_gap='1%',
gap='1%',
label_opts=opts.LabelOpts(
position="top",
formatter=JsCode("function(x){return x.data[0];}")),
)
bar.set_series_opts(itemstyle_opts=opts.ItemStyleOpts(color=JsCode(
"function(x){return x.data['range'][0]=='0'?'lightgray':(x.data['range'][0] < 0 ? 'lightgreen':'lightcoral')}"
)))
bar.set_global_opts(
title_opts=opts.TitleOpts(
title="=========" + title + "=========",
subtitle_textstyle_opts=opts.TextStyleOpts(font_weight='bold',
font_size='15px'),
pos_left='center',
pos_top='-1px',
),
tooltip_opts=opts.TooltipOpts(is_show=False),
legend_opts=opts.LegendOpts(is_show=False),
xaxis_opts=opts.AxisOpts(
# data=None,
# type_='category',
# name_gap=0,
# name_rotate=90,
# axislabel_opts=opts.LabelOpts(
# rotate=-60,
# ),
name='价格涨跌区间',
name_gap=35,
is_scale=True,
name_location='middle',
splitline_opts=opts.SplitLineOpts(is_show=False),
axisline_opts=opts.AxisLineOpts(is_on_zero=True,
# symbol=['none', 'arrow']
)),
yaxis_opts=opts.AxisOpts(
type_='value',
name='个数',
# name_rotate=90,
name_gap=35,
name_location='middle',
# min_=0,
# max_=max_value,
is_scale=True,
axislabel_opts=opts.LabelOpts(formatter='{value}'),
splitline_opts=opts.SplitLineOpts(is_show=False),
axisline_opts=opts.AxisLineOpts(is_on_zero=False,
# symbol=['none', 'arrow']
)),
)
bar_html = bar.render_embed('template.html', html_utils.env)
return bar_html
def analyze(request):
try:
if request.session['username']==None:
return HttpResponseRedirect('/login/')
except KeyError:
return HttpResponseRedirect('/login/')
r={}
r['username'] = request.session['username']
taskid = request.GET.get('taskid')
finshed = DoubanSubject.objects.filter(taskid=taskid)
typelist=[]
l=[]
for i in finshed:
m=i.type.split(' ')
for k in m:
if k not in typelist and k!='' :
typelist.append(k)
l.append(1)
elif k!='':
l[typelist.index(k)]=l[typelist.index(k)]+1
bar=Bar()
bar.add_xaxis(typelist)
print(typelist)
print(l)
bar.add_yaxis("数量",l)
bar.set_global_opts(
title_opts=opts.TitleOpts(title="类型数量"),
toolbox_opts=opts.ToolboxOpts(),
legend_opts=opts.LegendOpts(is_show=False),
xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(rotate=-15)),
)
r['myechart'] = bar.render_embed()
data_pair = [list(z) for z in zip(typelist, l)]
data_pair.sort(key=lambda x: x[1])
pie=Pie(init_opts=opts.InitOpts(width="1600px", height="800px", bg_color="#DDDD77"))
pie.add(
series_name="类型占比",
data_pair=data_pair,
rosetype="radius",
radius="55%",
center=["50%", "50%"],
label_opts=opts.LabelOpts(is_show=False, position="center"),
)
pie.set_series_opts(
tooltip_opts=opts.TooltipOpts(
trigger="item", formatter="{a} <br/>{b}: {c} ({d}%)"
),
label_opts=opts.LabelOpts(color="rgba(255, 255, 255, 0.3)"),
)
r['mypie']=pie.render_embed()
namelist=[]
scorelist=[]
for i in finshed:
score=i.score
name=i.name
namelist.append(name)
scorelist.append(score)
bar=Bar()
bar.add_xaxis(namelist)
print(typelist)
print(l)
bar.add_yaxis("评分",scorelist)
bar.set_global_opts(
title_opts=opts.TitleOpts(title="评分"),
toolbox_opts=opts.ToolboxOpts(),
legend_opts=opts.LegendOpts(is_show=False),
xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(rotate=-15)),
)
bar.set_series_opts(
label_opts=opts.LabelOpts(is_show=False),
markline_opts=opts.MarkLineOpts(
data=[
opts.MarkLineItem(type_="min", name="最小值"),
opts.MarkLineItem(type_="max", name="最大值"),
opts.MarkLineItem(type_="average", name="平均值"),
]
),
)
r['score'] = bar.render_embed()
return render(request,'analyze.html',r)
def pyecharts(request):
"""dashboard view"""
# 工单数量统计
chart_dao = ChartDao()
data = chart_dao.workflow_by_date(30)
today = date.today()
one_month_before = today - relativedelta(days=+30)
attr = chart_dao.get_date_list(one_month_before, today)
_dict = {}
for row in data['rows']:
_dict[row[0]] = row[1]
value = [_dict.get(day) if _dict.get(day) else 0 for day in attr]
bar1 = Bar(init_opts=opts.InitOpts(width='600', height='380px'))
bar1.add_xaxis(attr)
bar1.add_yaxis("", value)
# 工单按组统计
data = chart_dao.workflow_by_group(30)
attr = [row[0] for row in data['rows']]
value = [row[1] for row in data['rows']]
pie1 = Pie(init_opts=opts.InitOpts(width='600', height='380px'))
pie1.set_global_opts(title_opts=opts.TitleOpts(title=''),
legend_opts=opts.LegendOpts(orient="vertical",
pos_top="15%",
pos_left="2%",
is_show=False))
pie1.set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}"))
pie1.add("", [list(z) for z in zip(attr, value)])
# 工单按人统计
data = chart_dao.workflow_by_user(30)
attr = [row[0] for row in data['rows']]
value = [row[1] for row in data['rows']]
bar2 = Bar(init_opts=opts.InitOpts(width='600', height='380px'))
bar2.add_xaxis(attr)
bar2.add_yaxis("", value)
# SQL语句类型统计
data = chart_dao.syntax_type()
attr = [row[0] for row in data['rows']]
value = [row[1] for row in data['rows']]
pie2 = Pie()
pie2.set_global_opts(title_opts=opts.TitleOpts(title='SQL上线工单统计(类型)'),
legend_opts=opts.LegendOpts(orient="vertical",
pos_top="15%",
pos_left="2%"))
pie2.set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}"))
pie2.add("", [list(z) for z in zip(attr, value)])
# SQL查询统计(每日检索行数)
attr = chart_dao.get_date_list(one_month_before, today)
effect_data = chart_dao.querylog_effect_row_by_date(30)
effect_dict = {}
for row in effect_data['rows']:
effect_dict[row[0]] = int(row[1])
effect_value = [
effect_dict.get(day) if effect_dict.get(day) else 0 for day in attr
]
count_data = chart_dao.querylog_count_by_date(30)
count_dict = {}
for row in count_data['rows']:
count_dict[row[0]] = int(row[1])
count_value = [
count_dict.get(day) if count_dict.get(day) else 0 for day in attr
]
line1 = Line(init_opts=opts.InitOpts(width='600', height='380px'))
line1.set_global_opts(title_opts=opts.TitleOpts(title=''),
legend_opts=opts.LegendOpts(selected_mode='single'))
line1.add_xaxis(attr)
line1.add_yaxis("检索行数",
effect_value,
is_smooth=True,
markpoint_opts=opts.MarkPointOpts(
data=[opts.MarkPointItem(type_="average")]))
line1.add_yaxis("检索次数",
count_value,
is_smooth=True,
markline_opts=opts.MarkLineOpts(data=[
opts.MarkLineItem(type_="max"),
opts.MarkLineItem(type_="average")
]))
# SQL查询统计(用户检索行数)
data = chart_dao.querylog_effect_row_by_user(30)
attr = [row[0] for row in data['rows']]
value = [int(row[1]) for row in data['rows']]
pie4 = Pie(init_opts=opts.InitOpts(width='600', height='380px'))
pie4.set_global_opts(title_opts=opts.TitleOpts(title=''),
legend_opts=opts.LegendOpts(orient="vertical",
pos_top="15%",
pos_left="2%",
is_show=False))
pie4.set_series_opts(label_opts=opts.LabelOpts(formatter="{b}: {c}"))
pie4.add("", [list(z) for z in zip(attr, value)])
# SQL查询统计(DB检索行数)
data = chart_dao.querylog_effect_row_by_db(30)
attr = [row[0] for row in data['rows']]
value = [int(row[1]) for row in data['rows']]
pie5 = Pie(init_opts=opts.InitOpts(width='600', height='380px'))
pie5.set_global_opts(title_opts=opts.TitleOpts(title=''),
legend_opts=opts.LegendOpts(orient="vertical",
pos_top="15%",
pos_left="2%",
is_show=False))
pie5.set_series_opts(
label_opts=opts.LabelOpts(formatter="{b}: {c}", position="left"))
pie5.add("", [list(z) for z in zip(attr, value)])
# 可视化展示页面
chart = {
"bar1": bar1.render_embed(),
"pie1": pie1.render_embed(),
"bar2": bar2.render_embed(),
"pie2": pie2.render_embed(),
"line1": line1.render_embed(),
"pie4": pie4.render_embed(),
"pie5": pie5.render_embed(),
}
# 获取统计数据
dashboard_count_stats = {
"sql_wf_cnt": SqlWorkflow.objects.count(),
"query_wf_cnt": QueryPrivilegesApply.objects.count(),
"user_cnt": Users.objects.count(),
"ins_cnt": Instance.objects.count()
}
return render(request, "dashboard.html", {
"chart": chart,
"count_stats": dashboard_count_stats
})
def generate_bar_html(rows, title):
xx1 = []
xx2 = []
yy1 = []
yy2 = []
count = 0
for row in rows:
count += 1
bond_code = row[0]
bond_code = trade_utils.rebuild_bond_code(bond_code)
if count <= 20:
xx1.append(row[1].replace('转债', ''))
yy1.append({'value': row[2], 'bond_code': bond_code, 'price': row[3], 'premium': row[4], 'name': row[1]})
else:
xx2.append(row[1].replace('转债', ''))
yy2.append({'value': row[2], 'bond_code': bond_code, 'price': row[3], 'premium': row[4], 'name': row[1]})
max_value = 0
size = len(yy1)
for i in range(size):
if yy1[i]['value'] + abs(yy2[i]['value']) > max_value:
max_value = yy1[i]['value'] + abs(yy2[i]['value'])
max_value = round(max_value * 1.1, 2) + 1
chart_id = str(abs(hash(title)))
bar = Bar(init_opts=opts.InitOpts(height='700px', width='1424px', theme=ThemeType.SHINE, chart_id=chart_id))
view_utils.add_popwin_js_code(bar, chart_id)
# 底部x轴
bar.add_xaxis(xx1)
# 顶部x轴
bar.extend_axis(
xaxis_data=xx2,
xaxis=opts.AxisOpts(
type_="category",
position='top',
axislabel_opts=opts.LabelOpts(
rotate=-60,
)
),
)
# 右侧y轴
bar.extend_axis(
yaxis=opts.AxisOpts(
type_="value",
position="right",
name='跌幅(%)',
name_gap=45,
name_location='middle',
min_=-max_value,
axisline_opts=opts.AxisLineOpts(
linestyle_opts=opts.LineStyleOpts(
is_show=True,
)
),
axislabel_opts=opts.LabelOpts(formatter="{value}%"),
)
)
# 添加涨的柱状图
bar.add_yaxis("涨", yy1,
bar_width=25,
category_gap='1%',
gap='1%',
label_opts=opts.LabelOpts(
position="top",
formatter=JsCode(
"function(x){return x.data['value'] +'%';}"
)
),
)
# 添加跌的柱状图
bar.add_yaxis("跌",
yy2,
bar_width=25,
yaxis_index=1,
label_opts=opts.LabelOpts(
position="bottom",
formatter=JsCode(
"function(x){return x.data['value'] +'%';}"
)
),
)
# bar.reversal_axis()
bar.set_series_opts(
itemstyle_opts=opts.ItemStyleOpts(
color=JsCode(
"function(x){return x.data['value']>0?'#c23531':'#1d953f'}"
)
)
)
bar.set_global_opts(
title_opts=opts.TitleOpts(
title="=========" + title + "=========",
pos_left='center',
pos_top='-1px',
),
tooltip_opts=opts.TooltipOpts(
is_show=True,
formatter=JsCode("function (params){return '名 称: ' + params.data['name'] + '<br/>' + '价 格: ' + params.data['price'] + '元<br/>' + '溢价率: ' + params.data['premium']}")
),
legend_opts=opts.LegendOpts(is_show=False),
xaxis_opts=opts.AxisOpts(
# data=None,
# type_='category',
# name_gap=0,
# name_rotate=90,
axislabel_opts=opts.LabelOpts(
rotate=-60,
),
is_scale=True,
name_location='middle',
splitline_opts=opts.SplitLineOpts(is_show=False),
axisline_opts=opts.AxisLineOpts(
is_on_zero=True,
# symbol=['none', 'arrow']
)
),
yaxis_opts=opts.AxisOpts(
type_='value',
name='涨幅(%)',
# name_rotate=90,
name_gap=35,
name_location='middle',
# min_=0,
max_=max_value,
is_scale=True,
axislabel_opts=opts.LabelOpts(formatter='{value}%'),
splitline_opts=opts.SplitLineOpts(is_show=False),
axisline_opts=opts.AxisLineOpts(
is_on_zero=False,
# symbol=['none', 'arrow']
)
),
)
bar_html = bar.render_embed('template.html', html_utils.env)
return bar_html
