def gzu_major_satisfied():
data1 = analysis_data.gzu_satisfied()
data1 = data1.iloc[:, :5]
print(data1)
type_sas = {
'综合满意度': 'all',
'办学条件满意度': 'facility',
'教学质量满意度': 'teaching',
'就业满意度': 'job'
}
c = Bar()
for a in type_sas:
c.add_xaxis([str(x) for x in data1['major'].values])
c.add_yaxis(a, [x for x in data1[type_sas[a]].values])
c.set_global_opts(
yaxis_opts=opts.AxisOpts(min_=3),
xaxis_opts=opts.AxisOpts(
axislabel_opts=opts.LabelOpts(font_size=10, interval=0)),
datazoom_opts=opts.DataZoomOpts())
c.set_series_opts(
label_opts=opts.LabelOpts(is_show=False),
markpoint_opts=opts.MarkPointOpts(data=[
opts.MarkPointItem(type_="max", name="最大值"),
]),
markline_opts=opts.MarkLineOpts(data=[
opts.MarkLineItem(type_="average", name="平均值"),
]),
)
return c
def plt_feat_import(model_name, max_cols=9999, max_print=10):
from pyecharts.globals import CurrentConfig, NotebookType
CurrentConfig.NOTEBOOK_TYPE = NotebookType.JUPYTER_LAB
from pyecharts import options as opts
from pyecharts.charts import Bar
# 处理数据并排序
x_name = model_name.feature_name()
y_val = [int(x) for x in model_name.feature_importance()]
val_pairs = [x for x in zip(x_name, y_val)]
val_pairs.sort(key=lambda x: x[1])
# 设置图像属性
bar = Bar()
bar.add_xaxis([x[0] for x in val_pairs][-max_cols:])
bar.add_yaxis("特征重要度", [x[1] for x in val_pairs][-max_cols:])
bar.set_series_opts(
label_opts=opts.LabelOpts(is_show=True, position='right'))
bar.set_global_opts(
title_opts=opts.TitleOpts(title="特征重要度"),
datazoom_opts=opts.DataZoomOpts(),
)
bar.reversal_axis()
print(val_pairs[-max_print:][::-1])
return bar
def coincedence(place) -> Bar:
place = np.array(place)
foo = place[:, 1].astype(np.float)
order = np.argsort(foo)
k = 0
place1 = np.copy(place)
for i in order:
place1[k] = place[i, :]
k = k + 1
place = place1
bar = Bar()
bar.add_xaxis(list(place[:, 0]))
bar.add_yaxis("热度", list(place[:, 1]))
bar.set_global_opts(title_opts=opts.TitleOpts(title="外来旅游人口相关度"))
bar.set_global_opts(xaxis_opts=opts.AxisOpts(boundary_gap=1,
interval=0,
axislabel_opts={"rotate":
45}),
toolbox_opts=opts.ToolboxOpts(is_show=True),
datazoom_opts=[
opts.DataZoomOpts(range_start=0,
range_end=100,
is_zoom_lock=False)
])
#bar.set_global_opts(xaxis_opts=opts.AxisTickOpts(is_align_with_label=0))
bar.set_series_opts(label_opts=opts.LabelOpts(font_size=9))
bar.width = 1200
bar.render(path="外来旅游人口相关度.html")
return True
def draw_balance_bar(xaxis, yaxis, title="消费统计", markline=None, width=2000) -> Bar:
"""
x = [月_日, 月_日, 月_日, ....]
y = [(title1, [num1, num2, num3, num4, ...]), (title2, [num1, num2, num3, num4, ...])]
:param xaxis: x轴
:param yaxis: y轴
:param title: 标题
:param markline: 标记辅助线
:param width: 宽
:return: Bar
"""
bar = Bar()
bar.add_xaxis(xaxis)
for name, axis in yaxis:
bar.add_yaxis(name, axis, category_gap="20%", gap="0%")
bar.set_global_opts(title_opts=opts.TitleOpts(title=title, ),
datazoom_opts=[opts.DataZoomOpts(range_start=0, range_end=100),
opts.DataZoomOpts(type_="inside")],
tooltip_opts=opts.TooltipOpts(trigger='axis', axis_pointer_type='shadow'))
bar.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
if markline is not None:
bar.set_series_opts(markline_opts=opts.MarkLineOpts(
data=[opts.MarkLineItem(
y=markline,
name='预算')
])
)
return bar
def paint_bar(self,
x: list,
collects: list,
title: str,
mark_point: bool = False):
bar = Bar(init_opts=opts.InitOpts(theme=ThemeType.LIGHT))
bar.add_xaxis(x)
for collect in collects:
for i, (name, unit, data) in enumerate(collect):
bar.add_yaxis(f'{name}-单位：{unit}', data, yaxis_index=i)
if i != 0:
bar.extend_axis(yaxis=opts.AxisOpts(
name='',
type_='value',
position='right',
))
bar.set_global_opts(title_opts=opts.TitleOpts(title=title,
pos_left='5%'),
legend_opts=opts.LegendOpts(pos_bottom='0'))
bar.set_series_opts(
label_opts=opts.LabelOpts(position='top'),
tooltip_opts=opts.TooltipOpts(formatter=f'{{b}}年{{a}}：{{c}}'))
if mark_point:
bar.set_series_opts(
markpoint_opts=opts.MarkPointOpts(data=[
opts.MarkPointItem(type_='max', name='最大值'),
opts.MarkPointItem(type_='min', name='最小值')
],
symbol_size=80))
return bar
def bar(x, y):
bar = Bar(init_opts=opts.InitOpts(theme=ThemeType.MACARONS))
bar.add_xaxis(x)
bar.add_yaxis("盈利", y)
bar.set_global_opts(title_opts=opts.TitleOpts(title="380平台月盈利"))
bar.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
bar.render('../graph/4.1平台月盈利.html')
def bar(self,df,legend,title,path):
'''
柱状图
:param df: 要操作的数据
:param legend: 图例
:param title: 报表标题
:param path: 保存路径
:return:
'''
tmp = df.value_counts()
x = list(tmp.index)
y = list(tmp)
bar = Bar()
bar.add_xaxis(x)
bar.add_yaxis(legend, y, category_gap="60%")
bar.set_series_opts(itemstyle_opts={
"normal": {
"color": utils.JsCode("""new echarts.graphic.LinearGradient(0, 0, 0, 1, [{
offset: 0,
color: 'rgba(0, 244, 255, 1)'
}, {
offset: 1,
color: 'rgba(0, 77, 167, 1)'
}], false)"""),
"barBorderRadius": [30, 30, 30, 30],
"shadowColor": 'rgb(0, 160, 221)',
}})
bar.set_global_opts(title_opts=opts.TitleOpts(title=title))
bar.render(path + '/' + title + '.html')
def generte_bar_chart(title: str,
xaxis_caption: str,
range_groups: List[IntegerRangeCounterGroup],
bar_gap: int = 4) -> Bar:
chart = Bar()
chart.set_global_opts(
title_opts=opts.TitleOpts(title=title),
yaxis_opts=opts.AxisOpts(
name='Samples',
name_textstyle_opts=opts.global_options.TextStyleOpts(
font_size=16)),
xaxis_opts=opts.AxisOpts(
name=xaxis_caption,
name_textstyle_opts=opts.global_options.TextStyleOpts(
font_size=16)))
# Data (y axis)
for range_group in range_groups:
# Add values on the yaxis for each file type.
# If the count is 0, replace it by None to avoid overlapped numbers in the chart.
chart.add_yaxis(range_group.file_type,
range_group.counts,
category_gap=bar_gap,
stack="stack1")
# Captions (x axis)
chart.add_xaxis(range_groups[0].captions)
chart.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
return chart
def create_likes(df):
# 排序，降序
df = df.sort_values('likes', ascending=False)
# 获取TOP10的数据
attr = df['name'][0:10]
v1 = [float('%.1f' % (float(i) / 100000000)) for i in df['likes'][0:10]]
# 初始化配置
bar = Bar(init_opts=opts.InitOpts(width="800px", height="400px"))
# x轴数据
bar.add_xaxis(list(reversed(attr.tolist())))
# y轴数据
bar.add_yaxis("", list(reversed(v1)))
# 设置全局配置项，标题、工具箱(下载图片)、y轴分割线
bar.set_global_opts(
title_opts=opts.TitleOpts(title="抖音大V点赞数TOP10(亿)",
pos_left="center",
pos_top="18"),
toolbox_opts=opts.ToolboxOpts(is_show=True,
feature={"saveAsImage": {}}),
xaxis_opts=opts.AxisOpts(splitline_opts=opts.SplitLineOpts(
is_show=True)))
# 设置系列配置项，标签样式
bar.set_series_opts(label_opts=opts.LabelOpts(
is_show=True, position="right", color="black"))
bar.reversal_axis()
bar.render("抖音大V点赞数TOP10(亿).html")
def create_cut_likes(df):
# 将数据分段
Bins = [
0, 1000000, 5000000, 10000000, 25000000, 50000000, 100000000,
5000000000
]
Labels = [
'0-100', '100-500', '500-1000', '1000-2500', '2500-5000', '5000-10000',
'10000以上'
]
len_stage = pd.cut(df['likes'], bins=Bins,
labels=Labels).value_counts().sort_index()
# 获取数据
attr = len_stage.index.tolist()
v1 = len_stage.values.tolist()
# 生成柱状图
bar = Bar(init_opts=opts.InitOpts(width="800px", height="400px"))
bar.add_xaxis(attr)
bar.add_yaxis("", v1)
bar.set_global_opts(
title_opts=opts.TitleOpts(title="抖音大V点赞数分布情况(万)",
pos_left="center",
pos_top="18"),
toolbox_opts=opts.ToolboxOpts(is_show=True,
feature={"saveAsImage": {}}),
yaxis_opts=opts.AxisOpts(splitline_opts=opts.SplitLineOpts(
is_show=True)))
bar.set_series_opts(
label_opts=opts.LabelOpts(is_show=True, position="top", color="black"))
bar.render("抖音大V点赞数分布情况(万).html")
def create_abroad(df):
# 筛选数据
df = df[(df["country"] != "中国") & (df["country"] != "") &
(df["country"] != "暂不设置") & (df["country"] != "China")]
df1 = df.copy()
# 数据替换
df1["country"] = df1["country"].str.replace("United States",
"美国").replace("大韩民国", "韩国")
# 分组计数
df_num = df1.groupby("country")["country"].agg(
count="count").reset_index().sort_values(by="count", ascending=False)
df_country = df_num[:8]["country"].values.tolist()
df_count = df_num[:8]["count"].values.tolist()
# 初始化配置
bar = Bar(init_opts=opts.InitOpts(width="800px", height="400px"))
bar.add_xaxis(df_country)
bar.add_yaxis("", df_count)
bar.set_global_opts(
title_opts=opts.TitleOpts(title="抖音大V国外分布TOP10",
pos_left="center",
pos_top="18"),
toolbox_opts=opts.ToolboxOpts(is_show=True,
feature={"saveAsImage": {}}),
yaxis_opts=opts.AxisOpts(splitline_opts=opts.SplitLineOpts(
is_show=True)))
bar.set_series_opts(
label_opts=opts.LabelOpts(is_show=True, position="top", color="black"))
bar.render("抖音大V国外分布TOP10.html")
def create_avg_likes(df):
# 筛选
df = df[df['videos'] > 0]
# 计算单个视频平均点赞数
df.eval('result = likes/(videos*10000)', inplace=True)
df['result'] = df['result'].round(decimals=1)
df = df.sort_values('result', ascending=False)
# 取TOP10
attr = df['name'][0:10]
v1 = ['%.1f' % (float(i)) for i in df['result'][0:10]]
# 初始化配置
bar = Bar(init_opts=opts.InitOpts(width="800px", height="400px"))
# 添加数据
bar.add_xaxis(list(reversed(attr.tolist())))
bar.add_yaxis("", list(reversed(v1)))
# 设置全局配置项，标题、工具箱(下载图片)、y轴分割线
bar.set_global_opts(
title_opts=opts.TitleOpts(title="抖音大V平均视频点赞数TOP10(万)",
pos_left="center",
pos_top="18"),
toolbox_opts=opts.ToolboxOpts(is_show=True,
feature={"saveAsImage": {}}),
xaxis_opts=opts.AxisOpts(splitline_opts=opts.SplitLineOpts(
is_show=True)))
# 设置系列配置项
bar.set_series_opts(label_opts=opts.LabelOpts(
is_show=True, position="right", color="black"))
# 翻转xy轴
bar.reversal_axis()
bar.render("抖音大V平均视频点赞数TOP10(万).html")
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 __plot_con_notebook(self, split_n)->pyecharts.charts.Bar:
"""
调用echarts,连续变量
:param split_n:
:return:
"""
data = self.data[~np.isnan(self.X)]
data.sort_values('X',inplace=True)
X = data['X'].values
y = data['y'].values
max_x = max(X)
min_x = min(X)
freq,edge = np.histogram(X, np.linspace(min_x, max_x, split_n+1))
freq = np.round(freq/data.shape[0] *100,2)
# print(freq)
# print(edge)
bar = Bar(init_opts=opts.InitOpts(theme=ThemeType.DARK))
bar.load_javascript()
bar.add_xaxis([('（' + str(int(edge[i])) + ' , ' + str(int((edge[i + 1]))) + ']') if i else (
'[' + str(int(edge[i])) + ' , ' + str(int((edge[i + 1]))) + ']') for i in range(len(edge) - 1)])
bar.add_yaxis(self.var_name, freq.tolist(), category_gap=1, )
bar.set_global_opts(title_opts=opts.TitleOpts(title=self.var_name),
datazoom_opts=opts.DataZoomOpts(is_show=True),
xaxis_opts=opts.AxisOpts(name_location='end', name='Groups'),
yaxis_opts=opts.AxisOpts(name_location='end', name='%'),
)
bar.set_series_opts(label_opts=opts.LabelOpts(is_show=True))
return bar
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 drawbar(arrt, value, name):
# 图表初始化配置
init_opts = opts.InitOpts(page_title=name, height="700px")
bar = Bar(init_opts=init_opts)
# 标题配置
title = opts.TitleOpts(title=name, pos_left='center')
# 图例配置
legend_opts = opts.LegendOpts(pos_top="5%", pos_left="15%")
# 工具箱配置
# feature = opts.ToolBoxFeatureOpts(save_as_image=True, restore=True, data_view=True, data_zoom=True)
# 工具箱配置
toolbox_opts = opts.ToolboxOpts(pos_top="5%", pos_right="30%")
bar.set_global_opts(
title_opts=title,
legend_opts=legend_opts,
toolbox_opts=toolbox_opts,
# 区域缩放配置项
datazoom_opts=opts.DataZoomOpts(),
)
# add_yaxis
bar.add_xaxis(arrt)
# 渐变色
bar.add_yaxis(
"",
value,
gap="0%",
category_gap="30%",
# 自定义颜色
itemstyle_opts=opts.ItemStyleOpts(
color=JsCode("""new echarts.graphic.LinearGradient(0, 0, 1, 0,
[{
offset: 0,
color: 'rgb(39, 117, 182)'
},
{
offset: 0.5,
color: 'rgb(147, 181,207)'
},
{
offset: 1,
color: 'rgb(35, 118, 183)'
}], false)""")),
)
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"),
]),
markpoint_opts=opts.MarkPointOpts(data=[
opts.MarkPointItem(type_="max", name="最大值"),
opts.MarkPointItem(type_="min", name="最小值"),
opts.MarkPointItem(type_="average", name="平均值"),
]),
)
bar.render('{0}.html'.format(name))
def bar(x, y, x_name, y_name):
bar = Bar(init_opts=opts.InitOpts(height="600px", width="1200px"))
bar.add_xaxis(xaxis_data=x)
bar.add_yaxis(series_name='每年上架數量', yaxis_data=y)
bar.set_global_opts(title_opts=opts.TitleOpts(title='數量'),
xaxis_opts=opts.AxisOpts(name=x_name),
yaxis_opts=opts.AxisOpts(name=y_name))
bar.set_series_opts(label_opts=opts.LabelOpts(position='right'))
bar.reversal_axis()
return bar
def render(self) -> Bar:
bar = Bar()
bar.add_xaxis(self.balance_axis.x_axis)
bar.add_yaxis("支出", self.balance_axis.y_axis_a, category_gap="20%")
bar.add_yaxis("收入", self.balance_axis.y_axis_b, category_gap="20%")
bar.set_global_opts(title_opts=opts.TitleOpts(title=self.title, ),
datazoom_opts=[opts.DataZoomOpts(range_start=0, range_end=100),
opts.DataZoomOpts(type_="inside")],
tooltip_opts=opts.TooltipOpts(trigger='axis', axis_pointer_type='shadow'))
bar.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
return bar
def bar_stack0():
obj_bar = Bar()
obj_bar.add_xaxis(Faker.choose())
# stack该参数设置
obj_bar.add_yaxis("A", Faker.values(),stack="stack1")
obj_bar.add_yaxis("B", Faker.values(),stack="stack1")
# 设置标签不显示
obj_bar.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
obj_bar.set_global_opts(
title_opts=opts.TitleOpts(title="Bar-堆叠数据（全部）", subtitle="副标题"),)
return obj_bar
def bar_reversal_axis():
obj_bar = Bar()
obj_bar.add_xaxis(Faker.choose())
obj_bar.add_yaxis("A", Faker.values())
obj_bar.add_yaxis("B", Faker.values())
# 设置翻转 XY 轴
obj_bar.reversal_axis()
# 设置标签靠右显示
obj_bar.set_series_opts(label_opts=opts.LabelOpts(position="right"))
obj_bar.set_global_opts(
title_opts=opts.TitleOpts(title="Bar-翻转 XY 轴", subtitle="副标题"),)
return obj_bar
def paintGraph(contestInfo, starttime='2017-09', endtime='2020-07'):
# 先根据指定的起始日期和截止日期构造需要的数据
x, cf, ac, nc, jsk, total = [], [], [], [], [], []
for key, value in sorted(contestInfo.items()):
if key >= starttime and key <= endtime:
x.append(key)
cf.append({'value': value.get('cf', 0)})
ac.append({'value': value.get('ac', 0)})
nc.append({'value': value.get('nc', 0)})
jsk.append({'value': value.get('jsk', 0)})
total.append(value.get('total', 0))
# print(total)
# 绘制图表
bar = Bar(
init_opts=opts.InitOpts(theme=ThemeType.LIGHT, page_title='各年月比赛数量统计'))
bar.set_global_opts(title_opts=opts.TitleOpts(title='各年月比赛数量统计'),
xaxis_opts=opts.AxisOpts(name='比赛年月'),
yaxis_opts=opts.AxisOpts(name='比赛数量统计'))
bar.add_xaxis(x)
bar.add_yaxis("CodeForces", cf, stack="stack1", category_gap="50%")
bar.add_yaxis("NowCoder", nc, stack="stack1", category_gap="50%")
bar.add_yaxis("AtCoder", ac, stack="stack1", category_gap="50%")
bar.add_yaxis("计蒜客", jsk, stack="stack1", category_gap="50%")
bar.set_series_opts(label_opts=opts.LabelOpts(
position="inside",
formatter=JsCode(
"function(x){return x.data.value ? Number(x.data.value) : '';}"),
))
line = Line()
line.set_global_opts(
tooltip_opts=opts.TooltipOpts(is_show=False),
xaxis_opts=opts.AxisOpts(type_="category"),
yaxis_opts=opts.AxisOpts(
type_="value",
axistick_opts=opts.AxisTickOpts(is_show=True),
splitline_opts=opts.SplitLineOpts(is_show=True),
),
)
line.add_xaxis(xaxis_data=x)
line.add_yaxis(
series_name="total",
y_axis=total,
symbol="Circle",
is_symbol_show=True,
label_opts=opts.LabelOpts(is_show=True),
)
# 将柱状图与折线图一起输出到html文件中
bar.overlap(line).render('acmersite02.html')
def bar_markline_type():
obj_bar = Bar()
obj_bar.add_xaxis(Faker.choose())
obj_bar.add_yaxis("商家A",Faker.values())
obj_bar.add_yaxis("商家B",Faker.values())
obj_bar.set_series_opts(
label_opts=opts.LabelOpts(is_show = False),
markline_opts=opts.MarkPointOpts(
data = [opts.MarkLineItem(y=50, name="yAxis=50")]
)
)
obj_bar.set_global_opts(title_opts=opts.TitleOpts(title="Bar-MarkLine（自定义）", subtitle="自定义的线"))
return obj_bar
def dsp_her(): # 显示遗传力
# page = Page(layout=Page.DraggablePageLayout)
import xlrd
# file = "breeding.xlsx"
f1 = xlrd.open_workbook(file)
sheet1 = f1.sheet_by_name('Sheet1')
lst = her(file) # 接收计算的遗传力
y = []
colorArr = [
'1', '2', '3', '4', '5', '6', '7', '8', '9', 'A', 'B', 'C', 'D', 'E',
'F'
]
for i in range(len(lst)):
color = "#"
for j in range(6):
color += colorArr[random.randint(0, 14)]
y.append(
opts.BarItem(
value=lst[i],
itemstyle_opts=opts.ItemStyleOpts(color=str(color)),
# itemstyle_opts=opts.ItemStyleOpts(color=color[i])
))
x_ax = []
y_ax = []
start = load_profile()[0]
end = load_profile()[1]
for i in range(start, end + 1):
x_ax.append(sheet1.cell_value(0, i))
bar = Bar(init_opts=opts.InitOpts( #bg_color='rgba(155,250,205,0.2)',
width="1800px", height="800px"))
bar.set_colors(["#FF6347", "black"]) # FF6347
bar.add_xaxis(x_ax)
bar.add_yaxis("遗传力", y, category_gap="60%")
bar.set_series_opts(
label_opts=opts.LabelOpts(is_show=False),
markpoint_opts=opts.MarkPointOpts(
data=[opts.MarkPointItem(type_="max", name="最大值")]))
# bar.add_yaxis("商家B", [57, 134, 137, 129, 145, 60, 49])
bar.set_global_opts(title_opts=opts.TitleOpts(title="显示已有数据遗传力"))
for i in range(sheet1.nrows - 1):
y_ax.append(i)
line = Line(init_opts=opts.InitOpts(width="1800px", height="800px"))
line.add_xaxis(y_ax)
line.add_yaxis(series_name="",
y_axis=lst,
label_opts=opts.LabelOpts(is_show=True))
picture = bar.overlap(line)
return render_template("display.html",
picture_options=picture.dump_options())
def show_bar_figure(self, figure_name, title):
bar = Bar(init_opts=opts.InitOpts(bg_color='white'))
bar.add_xaxis(self.x_axis)
for y_set in self.y_input_sets:
self.format_yaxis(y_set)
# for y_set in self.y_output_sets:
# self.format_yaxis(y_set, self.top, -1, 1)
for idx, y_axis in enumerate(self.y_axiss[:self.top]):
bar.add_yaxis("", y_axis, gap="0", stack="stack{}".format(idx))
# for idx, y_axis in enumerate(self.y_axiss[self.top:]):
# bar.add_yaxis("", y_axis, gap="0", stack="stack{}".format(idx))
bar.set_global_opts(title_opts=opts.TitleOpts(title=title,
pos_left="center"), )
bar.set_series_opts(label_opts=opts.LabelOpts(is_show=False), )
bar.render(figure_name)
def bar(keywords):
xaxis = []
yaxis = []
for i in keywords:
xaxis.append(i[0])
yaxis.append(i[1])
bar = Bar(init_opts=opts.InitOpts(theme=ThemeType.WALDEN))
bar.add_xaxis(xaxis[:25])
bar.add_yaxis("重要性", yaxis[:25])
bar.set_global_opts(title_opts=opts.TitleOpts(title='TF-IDF Ranking'))
bar.set_global_opts(toolbox_opts=opts.ToolboxOpts(is_show=True))
bar.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
bar.reversal_axis()
return bar
def show_bar(id):
fix_data()
bar = Bar(init_opts=opts.InitOpts(
width='1200px', height='800px', page_title='page'))
bar.add_xaxis(fix_id)
bar.add_yaxis('线程', fix_time, stack="stack1", color=Faker.rand_color())
bar.reversal_axis()
bar.set_global_opts(title_opts=opts.TitleOpts(title="压测时间图"),
datazoom_opts=opts.DataZoomOpts(orient="vertical"))
bar.set_series_opts(label_opts=opts.LabelOpts(is_show=False),
markpoint_opts=opts.MarkPointOpts(data=[
opts.MarkPointItem(type_="max", name="最大值"),
opts.MarkPointItem(type_="min", name="最小值"),
opts.MarkPointItem(type_="average", name="平均值"),
]))
bar.render('压力测试{}.html'.format(id + 1))
def bar_chart():
# 柱状图
bar = Bar()
x_y_axis = get_chart_data()
bar.add_xaxis(x_y_axis[0])
for j in x_y_axis[1]:
for key, value in j.items():
bar.add_yaxis(key, value, label_opts=opts.LabelOpts(is_show=False))
bar.set_series_opts(markpoint_opts=opts.MarkPointOpts(data=[
opts.MarkPointItem(type_="max", name="最大值"),
opts.MarkPointItem(type_="min", name="最小值"),
]), )
bar.set_global_opts(
title_opts=opts.TitleOpts(
title="API耗时统计",
subtitle="生产环境",
pos_left="30%",
title_textstyle_opts=opts.TextStyleOpts(color='red'),
subtitle_textstyle_opts=opts.TextStyleOpts(color='blue')),
xaxis_opts=opts.AxisOpts(
name="运行时间",
type_="category",
boundary_gap=True,
# axislabel_opts=opts.LabelOpts(rotate=15)
),
yaxis_opts=opts.AxisOpts(name="实际的响应时间（单位：秒）",
# min_=0,
# max_=20
),
legend_opts=opts.LegendOpts(type_='scroll',
selected_mode='multiple',
pos_left='right',
pos_top='10%',
orient='vertical'),
tooltip_opts=opts.TooltipOpts(trigger="axis",
axis_pointer_type="line"),
toolbox_opts=opts.ToolboxOpts(is_show=True, pos_left='right'),
visualmap_opts=opts.VisualMapOpts(is_show=True,
type_="size",
min_=0,
max_=20,
range_text=["最大值", "最小值"]),
datazoom_opts=[opts.DataZoomOpts(range_start=50, range_end=100)],
)
bar = bar.dump_options_with_quotes()
return bar
def create_percent_stack_bar(title, x_list, data_list, data_unit):
"""
:param title: 图表名称
:param x_list: 横坐标内容为时间序列，纵坐标高度为多个(同级)指标的总和，具体各个指标的数值、比例以不同颜色标出
:param data_list: 字典{key1:value1,key2:value2...}，构成柱状图的多个不同类型的bar
:param data_unit: y轴的数值单位
:return:
"""
# 数据格式重构：
count = len(x_list) # 数据期数
sumList = [] # 汇总
for i in range(count):
sumList.append(0)
for key in data_list.keys():
for i in range(count):
if data_list[key][i] is not None: # 空数据处理
sumList[i] = sumList[i] + data_list[key][i]
for key in data_list.keys():
value_list = []
for i in range(count):
new_dic = {}
new_dic["value"] = data_list[key][i]
if data_list[key][i] is not None: # 空数据处理,sumList[i]不会为None或为0，指标选择时已经做了规避
new_dic["percent"] = data_list[key][i]/sumList[i]
else:
new_dic["percent"] = None
value_list.append(new_dic)
data_list[key] = value_list
c = Bar(init_opts=opts.InitOpts(theme=THEME_TYPE))
c.add_xaxis(x_list)
for key in data_list.keys():
c.add_yaxis(key, data_list[key],stack="stack1") # stack参数设置层叠样式
c.set_series_opts(label_opts=opts.LabelOpts(position="right",
formatter=JsCode(
"function(x){console.log(x);return Number(x.data.percent * 100).toFixed() + '%';}"
)))
c.set_global_opts(title_opts=opts.TitleOpts(title=title),
legend_opts=opts.LegendOpts(pos_left="right"),
yaxis_opts=opts.AxisOpts(name="单位:" + data_unit))
src_path = "./指标-年度-图片生成/"
html_file_name = src_path + title + ".html"
img_file_name = src_path + title + ".png"
make_snapshot(snapshot, c.render(html_file_name), img_file_name)
print(img_file_name+":生成完毕...")
def process_statistics():
para = {'size': 80}
data_source = requests.post("http://localhost:7000/es_virus_data",
data=json.dumps(para)).json()
# 得出地理信息/感染数量/
confirmedCount_province_list = {}
suspectedCount_province_list = {}
curedCount_province_list = {}
deadCount_province_list = {}
for source in province_souce['hits']['hits']:
base = source['_source']
provinceShortName = base['provinceShortName']
confirmedCount = base['confirmedCount']
suspectedCount = base['suspectedCount']
curedCount = base['curedCount']
deadCount = base['deadCount']
# print('{}-{}-{}-{}-{}'.format(provinceShortName,confirmedCount,suspectedCount,curedCount,deadCount))
if provinceShortName not in confirmedCount_province_list.keys():
confirmedCount_province_list[provinceShortName] = int(
confirmedCount)
if provinceShortName not in suspectedCount_province_list.keys():
suspectedCount_province_list[provinceShortName] = int(
suspectedCount)
if provinceShortName not in curedCount_province_list.keys():
curedCount_province_list[provinceShortName] = int(curedCount)
if provinceShortName not in deadCount_province_list.keys():
deadCount_province_list[provinceShortName] = int(deadCount)
provinces = list(confirmedCount_province_list.keys())
confirm_list = list(confirmedCount_province_list.values())
suspect_list = list(suspectedCount_province_list.values())
cure_list = list(curedCount_province_list.values())
dead_list = list(deadCount_province_list.values())
# bar = Line()
bar = Bar()
bar.add_xaxis(provinces)
bar.add_yaxis("确诊", confirm_list, stack="stack1")
bar.add_yaxis("疑似", suspect_list, stack="stack1")
bar.add_yaxis("治愈", cure_list, stack="stack1")
bar.add_yaxis("死亡", dead_list, stack="stack1")
bar.set_series_opts(label_opts=opts.LabelOpts(is_show=True))
bar.set_global_opts(title_opts=opts.TitleOpts(title="省份疫情统计"))
return bar
# if __name__ == '__main__':
# process_statistics()
def draw_balance_bar(xaxis,
yaxis,
difference=None,
title="消费统计",
markline=None,
width=2000) -> Bar:
"""
x = [月_日, 月_日, 月_日, ....]
y = [(title1, [num1, num2, num3, num4, ...]), (title2, [num1, num2, num3, num4, ...])]
:param difference: 差值 (比如：收入100，消费80，差值就是20) : ['title', [1,2,3,4]]
:param xaxis: x轴
:param yaxis: y轴
:param title: 标题
:param markline: 标记辅助线
:param width: 宽
:return: Bar
"""
bar = Bar()
bar.add_xaxis(xaxis)
for name, axis in yaxis:
bar.add_yaxis(name, axis, category_gap="20%", gap="0%")
bar.set_global_opts(title_opts=opts.TitleOpts(title=title, ),
datazoom_opts=[
opts.DataZoomOpts(range_start=0, range_end=100),
opts.DataZoomOpts(type_="inside")
],
tooltip_opts=opts.TooltipOpts(
trigger='axis', axis_pointer_type='shadow'))
bar.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
if difference:
name, diff_yaxis = difference
line = Line().add_xaxis(xaxis).add_yaxis(
name,
diff_yaxis,
symbol_size=15,
z_level=1,
is_symbol_show=False,
)
bar.overlap(line)
if markline is not None:
bar.set_series_opts(markline_opts=opts.MarkLineOpts(
data=[opts.MarkLineItem(y=markline, name='预算')]))
return bar
