def getRadar(self, sheet: xlrd.sheet) -> Radar:
namelist = sheet.col_values(0, 1)
maxvaluelist = sheet.col_values(1, 1)
maxlist = [
opts.RadarIndicatorItem(name=namelist[i], max_=maxvaluelist[i])
for i in range(len(namelist))
]
valuelists = dict()
for i in range(2, sheet.ncols):
valuelists[sheet.cell(0, i).value] = sheet.col_values(i, 1)
r = Radar()
r.add_schema(
schema=maxlist,
splitarea_opt=opts.SplitAreaOpts(
is_show=True, areastyle_opts=opts.AreaStyleOpts(opacity=1)),
textstyle_opts=opts.TextStyleOpts(color="#fff"),
)
#设置颜色的列表
colorstr = ["#CD0000", "#5CACEE", "#7B68EE", "#FFFF00"]
colorth = 0
for name, values in valuelists.items():
r.add(
series_name=name,
data=values,
linestyle_opts=opts.LineStyleOpts(color=colorstr[colorth]),
)
colorth = (colorth + 1) % len(colorstr) #颜色循环
r.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
r.set_global_opts(title_opts=opts.TitleOpts(
title=sheet.name,
title_textstyle_opts=opts.TextStyleOpts(color="#fff")),
legend_opts=opts.LegendOpts())
return r
def year_store_order_base():
# 不同门店的年营业额数据查询
dataX, dataY1, dataY2 = year_store_query()
# 对象声明
radar = Radar(init_opts=opts.InitOpts(
width="1280px", height="720px", bg_color="#CCCCCC"))
radar.add_schema(
schema=[
opts.RadarIndicatorItem(name="门店订单金额", max_=34000),
opts.RadarIndicatorItem(name="门店顾客数", max_=10000),
opts.RadarIndicatorItem(name="门店商品类型", max_=10000),
opts.RadarIndicatorItem(name="门店订单量", max_=10000)
],
splitarea_opt=opts.SplitAreaOpts(
is_show=True, areastyle_opts=opts.AreaStyleOpts(opacity=1)),
textstyle_opts=opts.TextStyleOpts(color="#fff"),
)
radar.add(
series_name="Store 1",
data=[list(dataY1)],
linestyle_opts=opts.LineStyleOpts(color="#CD0000"),
)
radar.add(
series_name="Store 2",
data=[list(dataY2)],
linestyle_opts=opts.LineStyleOpts(color="#5CACEE"),
)
radar.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
radar.set_global_opts(title_opts=opts.TitleOpts(title="2005年门店竞争优势多维分析"),
legend_opts=opts.LegendOpts())
return radar
def drawRadar(arr, value, valuemax, name):
radar = Radar(init_opts=opts.InitOpts(
width="1280px", height="720px", bg_color="#CCCCCC"))
v_max = [list(z) for z in zip(arr, valuemax)]
radar.add_schema(
schema=[opts.RadarIndicatorItem(name=k, max_=v) for k, v in v_max],
splitarea_opt=opts.SplitAreaOpts(
is_show=True, areastyle_opts=opts.AreaStyleOpts(opacity=1)),
textstyle_opts=opts.TextStyleOpts(color="#fff"),
)
radar.add(
series_name=name,
data=value,
linestyle_opts=opts.LineStyleOpts(color="#CD0000"),
)
radar.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
radar.set_global_opts(title_opts=opts.TitleOpts(title=name),
legend_opts=opts.LegendOpts())
radar.render("{0}.html".format(name))
def DrawRadar(title, data, savepath):
print('正在分析评分构成...')
radar = Radar()
radar.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
radar.set_global_opts(
title_opts=opts.TitleOpts(title="Radar-评分分布统计雷达图", pos_left='center'),
legend_opts=opts.LegendOpts(orient="vertical",
pos_top="middle",
pos_left="2%"),
)
values = [[data[i][1] for i in range(len(data))]] # 把整个列表当做一个要画的东西
attrs = [data[i][0] for i in range(len(data))] # 改名字
attrs = list(map(int, attrs))
attrs = [str(i) + '星' for i in attrs]
num = len(attrs) # 雷达图有几项
schema = [{"name": attrs[i], "max": 230} for i in (range(num))]
radar.add_schema(schema=schema)
radar.add('豆瓣评分构成', values)
radar.render(os.path.join(savepath, '%s.html' % title))
def draw_radar_for_observation_result():
value = [[43, 58, 78, 65, 86, 63]]
min_val = 0
max_val = 100
# 用于调整雷达各维度的范围大小
c_schema = [{"name": "交往能力", "max": max_val, "min": min_val, },
{"name": "感知能力", "max": max_val, "min": min_val, "color": "#ff0000"},
{"name": "运动能力", "max": max_val, "min": min_val, "color": "#000000"},
{"name": "注意力", "max": max_val, "min": min_val, "color": "#00ffff"},
{"name": "语言能力", "max": max_val, "min": min_val, "color": "#ff00ff"},
{"name": "自我照顾能力", "max": max_val, "min": min_val, "color": "#ff00ff"}
]
# 画图
radar = Radar()
radar.add_schema(c_schema, textstyle_opts=opts.TextStyleOpts(color="#3344ff"))
radar.add(None, value, color="#f9713c",
symbol='circle', label_opts=opts.LabelOpts(is_show=True),
areastyle_opts=opts.AreaStyleOpts(opacity=0.5, color="#f9713c"))
radar.set_global_opts(title_opts=opts.TitleOpts(title="Radar-基本示例"))
radar.render("observation_result.html")
connection.close()
# 执行主函数
if __name__ == '__main__':
print(store_query())
data1, data2, data3 = store_query()
radar = Radar(init_opts=opts.InitOpts(theme=ThemeType.DARK,width="1280px", height="720px"))
radar.add_schema(schema=[
opts.RadarIndicatorItem(name="门店订单金额", max_=50000),
opts.RadarIndicatorItem(name="门店订单量", max_=10000),
opts.RadarIndicatorItem(name="门店顾客数", max_=10000),
opts.RadarIndicatorItem(name="门店商品类型", max_=10000),
],
splitarea_opt=opts.SplitAreaOpts(
is_show=True, areastyle_opts=opts.AreaStyleOpts(opacity=1)
),
textstyle_opts=opts.TextStyleOpts(color="#fff"),
)
radar.add(series_name="1号门店",
data=[list(data1)],
linestyle_opts=opts.LineStyleOpts(color="#CD0000")
)
radar.add(series_name="2号门店",
data=[list(data2)],
linestyle_opts=opts.LineStyleOpts(color="#5CACEE")
)
radar.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
radar.set_global_opts(
title_opts=opts.TitleOpts(title="门店竞争优势多维分析"), legend_opts=opts.LegendOpts()
)
radar.render('radar.html')
# 雷达图
v1 = [[4300, 10000, 28000, 35000, 50000, 19000],
[3300, 13000, 25000, 30000, 48000, 24000]]
v2 = [[5000, 14000, 28000, 31000, 42000, 21000]]
radar = Radar()
radar.add_schema(schema=[
opts.RadarIndicatorItem(name='销售', max_=6500),
opts.RadarIndicatorItem(name='管理', max_=16000),
opts.RadarIndicatorItem(name='信息技术', max_=30000),
opts.RadarIndicatorItem(name='客服', max_=38000),
opts.RadarIndicatorItem(name='研发', max_=52000),
opts.RadarIndicatorItem(name='市场', max_=25000),
])
radar.add('预算分配', v1)
radar.add('实际开销', v2)
radar.set_global_opts(title_opts=opts.TitleOpts(title='Radar Sample'))
radar.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
radar.render('pyecharts-radar.html')
# 词云图
words = [
('Sam S Club', 10000),
('Macys', 6181),
('Amy Schumer', 4386),
('Jurassic World', 4055),
('Charter Communications', 2467),
]
wordcloud = WordCloud()
wordcloud.add('', words, word_size_range=[20, 100])
wordcloud.set_global_opts(title_opts=opts.TitleOpts(title='WordCloud Sample'))
wordcloud.render('pyecharts-wordcloud.html')
def dsp_bv(): # 显示育种值
import xlrd
prepare = locals()
# file = "breeding.xlsx"
f1 = xlrd.open_workbook(file)
sheet1 = f1.sheet_by_name('Sheet1')
radar = Radar(init_opts=opts.InitOpts(
width="1280px",
height="720px",
#bg_color='rgba(255,250,205,0.2)'
))
lst1 = bv(file)[0] # 接收计算的给性状各公牛的育种值
lst2 = bv(file)[1] # 公牛编号
lst3 = bv(file)[2] # 性状名
for i in range(len(lst1[0])): # 初始化各公牛的个性状育种值列表（每个列表代表一头公牛个性状的育种值）
prepare["blupscore" + str(i)] = []
for i in range(len(lst2)): # 公牛编号
for j in range(len(lst3)): # 性状
prepare["blupscore" + str(i)].append(round(lst1[j][i], 4))
scoreprint = [[] for i in range(3)]
for i in range(len(lst2)):
scoreprint[i].append(prepare["blupscore" + str(i)])
# for i in range(len(lst2)):
# print(scoreprint[i])
# lst3 = cbv(file)[2]
radar.add_schema(schema=[
opts.RadarIndicatorItem(name="体重", max_=10, min_=-10),
opts.RadarIndicatorItem(name="体高", max_=10, min_=-10),
opts.RadarIndicatorItem(name="体长", max_=10, min_=-10),
opts.RadarIndicatorItem(name="胸围", max_=10, min_=-10),
opts.RadarIndicatorItem(name="眼肌面积", max_=10, min_=-10)
],
splitarea_opt=opts.SplitAreaOpts(
is_show=True,
areastyle_opts=opts.AreaStyleOpts(opacity=1)),
textstyle_opts=opts.TextStyleOpts(color="black"))
color = ["red", "blue", "green", "black", "purple"]
for i in range(len(lst2)):
radar.add(series_name=str(int(lst2[i])),
data=scoreprint[i],
color=color[i]
) # series_name的value要为str类型，否则不会显示opts.LegendOpts()效果
# radar.add(series_name=str(lst2[0]), data=scoreprint[0], color=color[0])
# radar.add(series_name=str(lst2[1]), data=scoreprint[1], color=color[1])
radar.set_global_opts(title_opts=opts.TitleOpts(title="显示已有数据的各公牛的性状育种值"),
legend_opts=opts.LegendOpts())
# v1 = [[4300, 10000, 28000, 35000, 50000, 19000]]
# v2 = [[5000, 14000, 28000, 31000, 42000, 21000]]
# c = (
# Radar()
# .add_schema(
# schema=[
# opts.RadarIndicatorItem(name="销售", max_=6500),
# opts.RadarIndicatorItem(name="管理", max_=16000),
# opts.RadarIndicatorItem(name="信息技术", max_=30000),
# opts.RadarIndicatorItem(name="客服", max_=38000),
# opts.RadarIndicatorItem(name="研发", max_=52000),
# opts.RadarIndicatorItem(name="市场", max_=25000),
# ]
# )
# .add("预算分配", v1)
# .add("实际开销", v2)
# .set_series_opts(label_opts=opts.LabelOpts(is_show=False))
# .set_global_opts(
# legend_opts=opts.LegendOpts(selected_mode="single"),
# title_opts=opts.TitleOpts(title="Radar-单例模式"),
# ))
# radar.render("display.html")
picture = radar
return render_template("display.html",
picture_options=picture.dump_options())
def Cartography():
#创建地图
map = Map( init_opts=opts.InitOpts(width="1900px", height="900px", bg_color="#d0effa", page_title="全球新冠疫情_1"))
map.add("确诊人数",[list(z) for z in zip(names_new, confirm)],is_map_symbol_show=False,
maptype="world",label_opts=opts.LabelOpts(is_show=False),itemstyle_opts=opts.ItemStyleOpts(color="rgb(98,121,146)"))#地图区域颜色
map.set_global_opts(title_opts = opts.TitleOpts(title='全球新冠疫情确诊人数'),legend_opts=opts.LegendOpts(is_show=False),
visualmap_opts=opts.VisualMapOpts(max_=2000000, is_piecewise=True,
pieces=[
{"max": 3000000,"min": 500001,"label":">500000","color":"#460303"},
{"max": 500000, "min": 100001, "label": "100001-500000", "color": "#8A0808"},
{"max": 100000, "min": 10001, "label": "10001-100000", "color": "#B40404"},
{"max": 10000, "min": 1001, "label": "1001-10000", "color": "#DF0101"},
{"max": 1000, "min": 101, "label": "101-1000", "color": "#F78181"},
{"max": 100, "min": 1, "label": "1-100", "color": "#F5A9A9"},
{"max": 0, "min": 0, "label": "0", "color": "#fababa"},
])
)
map.render('Global_new_crown_epidemic_map.html')
#创建饼图
pie = Pie(init_opts=opts.InitOpts(width='1900px', height='900px',page_title="全球新冠疫情_2",bg_color="#fee4e7"))
# 添加数据
pie.add("", [list(z) for z in zip(country_list, dead_list)],
radius=['20%', '100%'],#设置内径外径
center=['60%', '65%'],
rosetype='area')#圆心角相同，通过半径展现数据大小#rosetype='radius'圆心角展现数据百分比，半径展现数据大小
# 设置全局配置
pie.set_global_opts(title_opts=opts.TitleOpts(title='全球新冠疫情',subtitle='死亡人数超过\n5000的国家\n (除中国)',
title_textstyle_opts=opts.TextStyleOpts(font_size=15,color= '#f40909'),
subtitle_textstyle_opts= opts.TextStyleOpts(font_size=15,color= '#8a0b0b'),
pos_right= 'center',pos_left= '57%',pos_top= '60%',pos_bottom='center'),
legend_opts=opts.LegendOpts(is_show=False))
# 设置系列配置和颜色
pie.set_series_opts(label_opts=opts.LabelOpts(is_show=True, position='inside', font_size=13,
formatter='{b}：{c}', font_style='italic',
font_family='Microsoft YaHei'))
pie.set_colors(color_matching)
pie.render('Global_new_crown_epidemic_Rose.html')
#创建雷达图
radar = Radar(init_opts=opts.InitOpts(width='1900px',height='900px',page_title="全球新冠疫情_3",bg_color="#d1eff3"))
#由于雷达图传入的数据得为多维数据，所以这里需要做一下处理
radar_data1 = [list(dead_list)]
radar_data2 = [list(heal_list)]
radar.add_schema(
schema=[
opts.RadarIndicatorItem(name='巴西', max_=8000),
opts.RadarIndicatorItem(name='荷兰', max_=8000),
opts.RadarIndicatorItem(name='伊朗', max_=20000),
opts.RadarIndicatorItem(name='德国', max_=40000),
opts.RadarIndicatorItem(name='比利时', max_=70000),
opts.RadarIndicatorItem(name='英国', max_=80000),
opts.RadarIndicatorItem(name='法国 ', max_=110000),
opts.RadarIndicatorItem(name='西班牙', max_=150000),
opts.RadarIndicatorItem(name='意大利', max_=170000),
opts.RadarIndicatorItem(name='美国', max_=220000),
]
)
radar.add("死亡人数",radar_data1,color='blue',areastyle_opts = opts.AreaStyleOpts(opacity = 0.2,color='blue'))
radar.add("治愈人数",radar_data2,color='red',areastyle_opts=opts.AreaStyleOpts(opacity=0.3,color='red'))
radar.set_series_opts(label_opts=opts.LabelOpts(is_show=True))
radar.set_global_opts(title_opts=opts.TitleOpts(title="死亡人数与治愈人数对比"))
radar.render("Death_Versus_Heal.html")
def plt(key):
"""连接hbase"""
connection = happybase.Connection(host="localhost", port=9090)
"""打开传输"""
connection.open()
"""连接表"""
basicFeaturesTable = happybase.Table('basicFeaturesTable', connection)
socialAttributesTable = happybase.Table('socialAttributesTable',
connection)
consumptionFeaturesTable = happybase.Table('consumptionFeaturesTable',
connection)
internetFeaturesTable = happybase.Table('internetFeaturesTable',
connection)
consumptionCharacteristicsTable = happybase.Table(
'consumptionCharacteristicsTable', connection)
internetBehaviorTable = happybase.Table('internetBehaviorTable',
connection)
"""获取信息"""
try:
key_name = basicFeaturesTable.row(key, columns=["name"])
except:
"""连接hbase"""
connection = happybase.Connection(host="localhost", port=9090)
"""打开传输"""
connection.open()
"""连接表"""
basicFeaturesTable = happybase.Table('basicFeaturesTable', connection)
socialAttributesTable = happybase.Table('socialAttributesTable',
connection)
consumptionFeaturesTable = happybase.Table('consumptionFeaturesTable',
connection)
internetFeaturesTable = happybase.Table('internetFeaturesTable',
connection)
consumptionCharacteristicsTable = happybase.Table(
'consumptionCharacteristicsTable', connection)
internetBehaviorTable = happybase.Table('internetBehaviorTable',
connection)
key_name = basicFeaturesTable.row(key, columns=["name"])
key_name = list(key_name.values())
key_name = key_name[0].decode()
try:
sInfo = socialAttributesTable.row(key,
columns=["incLevel", "eduLevel"])
cInfo = consumptionFeaturesTable.row(key,
columns=["CMLevel", "CTLevel"])
iInfo = internetFeaturesTable.row(key, columns=["intLevel"])
consumptionCharacteristicsInfo = consumptionCharacteristicsTable.row(
key, columns=["commodity", "price", "date"])
internetBehaviorInfo = internetBehaviorTable.row \
(key, columns=
["date", "news", "communications", "entertainment", "domersticServices", "busApp", "toolUse"]
)
except:
"""连接hbase"""
connection = happybase.Connection(host="localhost", port=9090)
"""打开传输"""
connection.open()
"""连接表"""
basicFeaturesTable = happybase.Table('basicFeaturesTable', connection)
socialAttributesTable = happybase.Table('socialAttributesTable',
connection)
consumptionFeaturesTable = happybase.Table('consumptionFeaturesTable',
connection)
internetFeaturesTable = happybase.Table('internetFeaturesTable',
connection)
consumptionCharacteristicsTable = happybase.Table(
'consumptionCharacteristicsTable', connection)
internetBehaviorTable = happybase.Table('internetBehaviorTable',
connection)
sInfo = socialAttributesTable.row(key,
columns=["incLevel", "eduLevel"])
cInfo = consumptionFeaturesTable.row(key,
columns=["CMLevel", "CTLevel"])
iInfo = internetFeaturesTable.row(key, columns=["intLevel"])
consumptionCharacteristicsInfo = consumptionCharacteristicsTable.row(
key, columns=["commodity", "price", "date"])
internetBehaviorInfo = internetBehaviorTable.row \
(key, columns=
["date", "news", "communications", "entertainment", "domersticServices", "busApp", "toolUse"]
)
"""消费情况图"""
consumptionCharacteristicsValues = list(
consumptionCharacteristicsInfo.values())
consumptionCharacteristicsValues = list(
map(lambda x: x.decode(), consumptionCharacteristicsValues))
consumptionCharacteristicsValues[
int(len(consumptionCharacteristicsValues) / 3):-int(len(consumptionCharacteristicsValues) / 3)] \
= list(map(int, consumptionCharacteristicsValues[int(len(consumptionCharacteristicsValues) / 3):
-int(len(consumptionCharacteristicsValues) / 3)]))
consumptionCharacteristicsValues[-int(len(consumptionCharacteristicsValues) / 3):] \
= list(map(int, consumptionCharacteristicsValues[-int(len(consumptionCharacteristicsValues) / 3):]))
consumptionCharacteristicsData = []
consumptionCharacteristicsData.append(
consumptionCharacteristicsValues[:int(
len(consumptionCharacteristicsValues) / 3)])
consumptionCharacteristicsData.append(consumptionCharacteristicsValues[
int(len(consumptionCharacteristicsValues) /
3):-int(len(consumptionCharacteristicsValues) / 3)])
consumptionCharacteristicsData.append(consumptionCharacteristicsValues[
-int(len(consumptionCharacteristicsValues) / 3):])
consumptionCharacteristicsData = pd.DataFrame(
consumptionCharacteristicsData).T
consumptionCharacteristicsData.columns = ["commodity", "date", "price"]
consumptionCharacteristicsData.sort_values(by="date", inplace=True)
consumptionCharacteristicsData_y = consumptionCharacteristicsData.loc[:,
"date"].tolist(
)
consumptionCharacteristicsData_y = list(
map(str, consumptionCharacteristicsData_y))
consumptionCharacteristicsData_x = consumptionCharacteristicsData.loc[:,
"price"].tolist(
)
consumptionCharacteristicsData_commodity = consumptionCharacteristicsData.loc[:,
"commodity"].tolist(
)
quzhong_consumptionCharacteristicsData_y = list(
set(consumptionCharacteristicsData_y))
if len(quzhong_consumptionCharacteristicsData_y) != len(
consumptionCharacteristicsData_y):
for i in range(len(quzhong_consumptionCharacteristicsData_y)):
count_consumptionCharacteristicsData_y = consumptionCharacteristicsData_y. \
count(quzhong_consumptionCharacteristicsData_y[i])
if count_consumptionCharacteristicsData_y != 1:
index = consumptionCharacteristicsData_y.index(
quzhong_consumptionCharacteristicsData_y[i])
consumptionCharacteristicsData_y = consumptionCharacteristicsData_y[:index + 1] + \
consumptionCharacteristicsData_y[
index + count_consumptionCharacteristicsData_y:]
consumptionCharacteristicsData_x[index] = sum(
consumptionCharacteristicsData_x[
index:index + count_consumptionCharacteristicsData_y])
consumptionCharacteristicsData_x = consumptionCharacteristicsData_x[:index + 1] + \
consumptionCharacteristicsData_x[
index + count_consumptionCharacteristicsData_y:]
consumptionCharacteristicsData_commodity[index] = \
",".join(
consumptionCharacteristicsData_commodity[index:index + count_consumptionCharacteristicsData_y])
consumptionCharacteristicsData_commodity \
= consumptionCharacteristicsData_commodity[:index + 1] + \
consumptionCharacteristicsData_commodity[index + count_consumptionCharacteristicsData_y:]
consumptionCharacteristicsData_xx = \
[list(z) for z in zip(consumptionCharacteristicsData_x, consumptionCharacteristicsData_commodity)]
scatter = Scatter(init_opts=opts.InitOpts(width="850px", height="380px"))
scatter.add_xaxis(consumptionCharacteristicsData_y)
scatter.add_yaxis("", consumptionCharacteristicsData_xx, color="red")
scatter.set_global_opts(
tooltip_opts=opts.TooltipOpts(
trigger="item",
axis_pointer_type="cross",
formatter=JsCode(
"function (params) {return '消费日期：' + params.name + ' <br/>消费金额：' + params.value[1] + '元 <br/>消费产品：' + params.value[2];}"
)),
yaxis_opts=opts.AxisOpts(
name="消费金额",
type_="value",
name_textstyle_opts=opts.TextStyleOpts(color="white"), ###########
axislabel_opts=opts.LabelOpts(formatter="{value} 元",
border_color="white",
color="white"), ########
axistick_opts=opts.AxisTickOpts(is_show=True),
splitline_opts=opts.SplitLineOpts(is_show=True),
),
xaxis_opts=opts.AxisOpts(
name="消费日期",
type_="category",
name_textstyle_opts=opts.TextStyleOpts(color="white"), ###########
axislabel_opts=opts.LabelOpts(border_color="white",
color="white"), ##############
axispointer_opts=opts.AxisPointerOpts(is_show=True,
type_="shadow"),
),
legend_opts=opts.LegendOpts(is_show=False))
scatter.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
line = Line(init_opts=opts.InitOpts(width="850px", height="380px"))
line.add_xaxis(consumptionCharacteristicsData_y)
line.add_yaxis(series_name="",
y_axis=consumptionCharacteristicsData_x,
color="red")
scatter.overlap(line)
scatter.render("./static/html/pictureConsumptionCharacteristics.html")
"""互联网行为图"""
internetBehaviorInfoKeys = list(internetBehaviorInfo.keys())
internetBehaviorInfoKeys = list(
map(lambda x: x.decode(), internetBehaviorInfoKeys))
internetBehaviorInfoKeys = list(
map(lambda x: x[:x.index(':')], internetBehaviorInfoKeys))
internetBehaviorInfoValues = list(internetBehaviorInfo.values())
internetBehaviorInfoValues = list(
map(lambda x: x.decode(), internetBehaviorInfoValues))
internetBehaviorInfoValues = list(map(int, internetBehaviorInfoValues))
internetBehaviorData = []
splitNum = int(len(internetBehaviorInfoValues) / 7)
internetBehaviorData.append(internetBehaviorInfoValues[:splitNum])
internetBehaviorData.append(internetBehaviorInfoValues[splitNum:2 *
splitNum])
internetBehaviorData.append(internetBehaviorInfoValues[2 * splitNum:3 *
splitNum])
internetBehaviorData.append(internetBehaviorInfoValues[3 * splitNum:4 *
splitNum])
internetBehaviorData.append(internetBehaviorInfoValues[4 * splitNum:5 *
splitNum])
internetBehaviorData.append(internetBehaviorInfoValues[5 * splitNum:6 *
splitNum])
internetBehaviorData.append(internetBehaviorInfoValues[6 * splitNum:7 *
splitNum])
internetBehaviorData = pd.DataFrame(internetBehaviorData).T
internetBehaviorData.columns = [
internetBehaviorInfoKeys[0], internetBehaviorInfoKeys[splitNum],
internetBehaviorInfoKeys[2 * splitNum],
internetBehaviorInfoKeys[3 * splitNum],
internetBehaviorInfoKeys[4 * splitNum],
internetBehaviorInfoKeys[5 * splitNum],
internetBehaviorInfoKeys[6 * splitNum]
]
internetBehaviorData.sort_values(by="date", inplace=True)
internetBehaviorData_y = internetBehaviorData.loc[:, "date"].tolist()
internetBehaviorData_y = list(map(str, internetBehaviorData_y))
bar = Bar(init_opts=opts.InitOpts(width="800px", height="380px"))
bar.add_xaxis(internetBehaviorData_y)
bar.add_yaxis(series_name="新闻资讯",
yaxis_data=internetBehaviorData.loc[:, "news"].tolist(),
stack="stack")
bar.add_yaxis(
series_name="通信交流",
yaxis_data=internetBehaviorData.loc[:, "communications"].tolist(),
stack="stack")
bar.add_yaxis(
series_name="娱乐休闲",
yaxis_data=internetBehaviorData.loc[:, "entertainment"].tolist(),
stack="stack")
bar.add_yaxis(
series_name="生活服务",
yaxis_data=internetBehaviorData.loc[:, "domersticServices"].tolist(),
stack="stack")
bar.add_yaxis(series_name="商务应用",
yaxis_data=internetBehaviorData.loc[:, "busApp"].tolist(),
stack="stack")
bar.add_yaxis(series_name="工具使用",
yaxis_data=internetBehaviorData.loc[:, "toolUse"].tolist(),
stack="stack")
bar.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
bar.set_global_opts(
tooltip_opts=opts.TooltipOpts(is_show=True,
trigger="axis",
axis_pointer_type="cross"),
xaxis_opts=opts.AxisOpts(
name="日期",
name_textstyle_opts=opts.TextStyleOpts(color="white"), ###########
type_="category",
axislabel_opts=opts.LabelOpts(border_color="white",
color="white"), #############
axispointer_opts=opts.AxisPointerOpts(is_show=True),
),
yaxis_opts=opts.AxisOpts(
name="时间",
name_textstyle_opts=opts.TextStyleOpts(color="white"),
type_="value",
min_=0,
max_=24,
interval=4,
axislabel_opts=opts.LabelOpts(formatter="{value} 小时",
border_color="white",
color="white"), ###########
axistick_opts=opts.AxisTickOpts(is_show=True),
),
datazoom_opts=opts.DataZoomOpts(type_="inside"),
legend_opts=opts.LegendOpts(is_show=True,
textstyle_opts=opts.TextStyleOpts(
border_color="white", color="wihte"),
orient='horizontal'))
bar.render("./static/html/pictureInternetBehavior.html")
"""个人特征图"""
sValue = list(sInfo.values())
sValue = list(map(lambda x: x.decode(), sValue))
cValue = list(cInfo.values())
cValue = list(map(lambda x: x.decode(), cValue))
iValue = list(iInfo.values())
iValue = list(map(lambda x: x.decode(), iValue))
value = sValue + cValue + iValue
value = list(map(int, value))
value = [value[1], value[2], value[3], value[0], value[4]]
value = [value]
rader = Radar(init_opts=opts.InitOpts(width="350px", height="350px"))
rader.add_schema(schema=[
opts.RadarIndicatorItem(name="收入指数", max_=5),
opts.RadarIndicatorItem(name="消费金\n额指数", max_=5),
opts.RadarIndicatorItem(name="消费次数指数", max_=5),
opts.RadarIndicatorItem(name="学历指数", max_=5),
opts.RadarIndicatorItem(name="网络依\n赖指数", max_=5),
],
shape='polygon')
rader.add(series_name=key_name, data=value)
rader.set_global_opts(legend_opts=opts.LegendOpts(is_show=False))
rader.render("./static/html/pictureCompositiveInfo.html")
def find_difference_render(data,X,query,table_path,answer):
colorList = ['#f36c6c', '#e6cf4e', '#20d180', '#0093ff',"#ca8622","#726930",]
if len(data)==2:
bar1=Bar()
bar1.add_xaxis(X[1])
bar1.add_yaxis("",data[0][1],label_opts=opts.LabelOpts(position="insideLeft"))
bar1.reversal_axis()
bar1.set_global_opts(
datazoom_opts=[opts.DataZoomOpts(range_start=10,range_end=90,orient="vertical"), opts.DataZoomOpts(type_="inside")],
xaxis_opts=opts.AxisOpts(
position="top"
),
yaxis_opts=opts.AxisOpts(
is_inverse=True
),
graphic_opts=[opts.GraphicText(
graphic_item=opts.GraphicItem(
left="center",
top="bottom",
),
graphic_textstyle_opts=opts.GraphicTextStyleOpts(
# 可以通过jsCode添加js代码，也可以直接用字符串
text=['\n' + "Q:" + ' ' + query + '\n' +"\n"+ 'A:' + ' ' + answer],
font="14px Microsoft YaHei",
graphic_basicstyle_opts=opts.GraphicBasicStyleOpts(
fill="#333"
)
)
)]
)
bar2=Bar()
bar2.add_xaxis(X[1])
bar2.add_yaxis("",data[1][1],label_opts=opts.LabelOpts(position="insideRight"))
bar2.reversal_axis()
bar2.set_global_opts(
datazoom_opts=[opts.DataZoomOpts(range_start=10, range_end=90, orient="vertical"),
opts.DataZoomOpts(type_="inside")],
xaxis_opts=opts.AxisOpts(
position="top",
is_inverse=True
),
yaxis_opts=opts.AxisOpts(
is_inverse=True,
position="right"
),
graphic_opts=[opts.GraphicText(
graphic_item=opts.GraphicItem(
left="center",
top="bottom",
),
graphic_textstyle_opts=opts.GraphicTextStyleOpts(
# 可以通过jsCode添加js代码，也可以直接用字符串
text=['\n' + "Q:" + ' ' + query + '\n' +"\n"+ 'A:' + ' ' + answer],
font="14px Microsoft YaHei",
graphic_basicstyle_opts=opts.GraphicBasicStyleOpts(
fill="#333"
)
)
)]
)
grid1 = Grid(init_opts=opts.InitOpts(
width="100%",
height="100%",
renderer=globals.RenderType.SVG, ) )
grid1.add(bar1, grid_opts=opts.GridOpts(
pos_left="60%",pos_bottom="30%"
))
grid1.add(bar2, grid_opts=opts.GridOpts(
pos_right="60%",pos_bottom="30%"
))
grid1.render("a.html")
option1 = grid1.dump_options_with_quotes()
option1 = json.loads(option1)
lable=[]
for i in range(len(X[1])):
lable.append(opts.RadarIndicatorItem(name=X[1][i]))
# r_data=[]
# for record in data:
# r_data.append(record[1])
radar=Radar(init_opts=opts.InitOpts(bg_color="#CCCCCC"))
radar.add_schema(
schema=lable,
splitarea_opt=opts.SplitAreaOpts(
is_show=True, areastyle_opts=opts.AreaStyleOpts(opacity=1)
),
textstyle_opts=opts.TextStyleOpts(color="#fff"),
)
for i in range(len(data)):
radar.add(
series_name=data[i][0],
label_opts=opts.LabelOpts(is_show=False),
data=[data[i][1]],
linestyle_opts=opts.LineStyleOpts(
color=colorList[i],
width=3
)
)
radar.set_global_opts(
graphic_opts=[opts.GraphicText(
graphic_item=opts.GraphicItem(
left="center",
top="bottom",
z=100,
),
graphic_textstyle_opts=opts.GraphicTextStyleOpts(
# 可以通过jsCode添加js代码，也可以直接用字符串
text=['\n' + "Q:" + ' ' + query + '\n'+"\n" + 'A:' + ' ' + answer],
font="10px Microsoft YaHei",
graphic_basicstyle_opts=opts.GraphicBasicStyleOpts(
fill="#333"
)
)
)]
)
grid2 = Grid(init_opts=opts.InitOpts(
width="100%",
height="100%",
renderer=globals.RenderType.SVG, ))
grid2.add(radar, grid_opts={'left': '20%', 'bottom': '40%',"top":"1%"})
option2 = grid2.dump_options_with_quotes()
option2 = json.loads(option2)
bar3=Bar()
bar3.add_xaxis(X[1])
for i in range(len(data)):
bar3.add_yaxis(data[i][0],data[i][1],label_opts=opts.LabelOpts(is_show=False))
bar3.set_global_opts(
datazoom_opts=[opts.DataZoomOpts(range_start=10, range_end=90),
opts.DataZoomOpts(type_="inside")],
xaxis_opts=opts.AxisOpts(
name=X[0]
),
graphic_opts=[opts.GraphicText(
graphic_item=opts.GraphicItem(
left="center",
top="bottom",
),
graphic_textstyle_opts=opts.GraphicTextStyleOpts(
# 可以通过jsCode添加js代码，也可以直接用字符串
text=['\n' + "Q:" + ' ' + query + '\n' +"\n"+ 'A:' + ' ' + answer],
font="14px Microsoft YaHei",
graphic_basicstyle_opts=opts.GraphicBasicStyleOpts(
fill="#333"
)
)
)]
)
grid3 = Grid(init_opts=opts.InitOpts(
width="100%",
height="100%",
renderer=globals.RenderType.SVG, ))
grid3.add(bar3, grid_opts={'left': '20%', 'bottom': '30%'})
option3 = grid3.dump_options_with_quotes()
option3 = json.loads(option3)
option = {"option": [option1,option2,option3], "query": query}
return option
elif len(data)>2 and len(data[0][1])>1:
lable=[]
for i in range(len(X[1])):
lable.append(opts.RadarIndicatorItem(name=X[1][i]))
# r_data=[]
# for record in data:
# r_data.append(record[1])
radar=Radar(init_opts=opts.InitOpts(bg_color="#CCCCCC"))
radar.add_schema(
schema=lable,
splitarea_opt=opts.SplitAreaOpts(
is_show=True, areastyle_opts=opts.AreaStyleOpts(opacity=1)
),
textstyle_opts=opts.TextStyleOpts(color="#fff"),
)
radar.set_global_opts(
graphic_opts=[opts.GraphicText(
graphic_item=opts.GraphicItem(
left="center",
top="bottom",
),
graphic_textstyle_opts=opts.GraphicTextStyleOpts(
# 可以通过jsCode添加js代码，也可以直接用字符串
text=['\n' + "Q:" + ' ' + query + '\n' +"\n"+ 'A:' + ' ' + answer],
font="14px Microsoft YaHei",
graphic_basicstyle_opts=opts.GraphicBasicStyleOpts(
fill="#333"
)
)
)]
)
for i in range(len(data)):
radar.add(
series_name=data[i][0],
label_opts=opts.LabelOpts(is_show=False),
data=[data[i][1]],
linestyle_opts=opts.LineStyleOpts(
color=colorList[i],
width=3
)
)
grid1 = Grid(init_opts=opts.InitOpts(
width="100%",
height="100%",
renderer=globals.RenderType.SVG, ))
grid1.add(radar, grid_opts={'left': '20%', 'bottom': '30%'})
option1 = grid1.dump_options_with_quotes()
option1 = json.loads(option1)
bar = Bar()
bar.add_xaxis(X[1])
for i in range(len(data)):
bar.add_yaxis(data[i][0], data[i][1],label_opts=opts.LabelOpts(is_show=False))
bar.set_global_opts(
datazoom_opts=[opts.DataZoomOpts(range_start=10, range_end=90),
opts.DataZoomOpts(type_="inside")],
xaxis_opts=opts.AxisOpts(
name=X[0]
),
graphic_opts=[opts.GraphicText(
graphic_item=opts.GraphicItem(
left="center",
top="bottom",
),
graphic_textstyle_opts=opts.GraphicTextStyleOpts(
# 可以通过jsCode添加js代码，也可以直接用字符串
text=['\n' + "Q:" + ' ' + query + '\n' +"\n"+ 'A:' + ' ' + answer],
font="14px Microsoft YaHei",
graphic_basicstyle_opts=opts.GraphicBasicStyleOpts(
fill="#333"
)
)
)]
)
grid2 = Grid(init_opts=opts.InitOpts(
width="100%",
height="100%",
renderer=globals.RenderType.SVG, ))
grid2.add(bar, grid_opts={'left': '20%', 'bottom': '30%'})
option2 = grid2.dump_options_with_quotes()
option2 = json.loads(option2)
option = {"option": [option1,option2], "query": query}
return option
elif len(data)>2 and len(data[0][1])==1:
bar = Bar()
bar.add_xaxis(X[1])
for i in range(len(data)):
bar.add_yaxis(data[i][0], data[i][1],label_opts=opts.LabelOpts(is_show=False))
bar.set_global_opts(
datazoom_opts=[opts.DataZoomOpts(range_start=10, range_end=90),
opts.DataZoomOpts(type_="inside")],
xaxis_opts=opts.AxisOpts(
name=X[0]
),
graphic_opts=[opts.GraphicText(
graphic_item=opts.GraphicItem(
left="center",
top="bottom",
),
graphic_textstyle_opts=opts.GraphicTextStyleOpts(
# 可以通过jsCode添加js代码，也可以直接用字符串
text=['\n' + "Q:" + ' ' + query + '\n' +"\n"+ 'A:' + ' ' + answer],
font="14px Microsoft YaHei",
graphic_basicstyle_opts=opts.GraphicBasicStyleOpts(
fill="#333"
)
)
)]
)
grid2 = Grid(init_opts=opts.InitOpts(
width="100%",
height="100%",
renderer=globals.RenderType.SVG, ))
grid2.add(bar, grid_opts={'left': '20%', 'bottom': '34%'})
option2 = grid2.dump_options_with_quotes()
option2 = json.loads(option2)
option = {"option": [option2], "query": query}
return option