def bars_show(bar_data):
# 显示多个柱状图
page = Page()
for b in bar_data:
bar = create_bar(b['x'], b['head'], b['data'], b['dict'])
page.add(bar)
page.render()
def create_geo_charts(data, title):
'''地图'''
page = Page()
# 样式
style = Style(title_color="#fff",
title_pos="center",
width=1200,
height=600,
background_color='#c4ccd3')
# 创建地图模型
chart = Geo(title, "", **style.init_style)
# 数据 ['上海', '北京', '广州', '深圳', '苏州'] [5, 40, 10, 15, 5]
attr, value = chart.cast(data)
# 添加数据
chart.add("",
attr,
value,
maptype='china',
is_visualmap=True,
type="effectScatter",
is_legend_show=False,
geo_emphasis_color='c4ccd3',
visual_text_color='#2f4554')
page.add(chart)
return page
def get_pic_html():
data = get_data("logs.txt")
#获取DataFrame的行数
rows = data.shape[0]
#获取DataFrame的列数
columns = data.shape[1]
#绘制多幅图在一个页面，实例Page
page = Page()
#两个相同类型的曲线图间隔的列数
# division=get_division()
division = (int(columns) / int(files_number))
for index in range((division - 1) / 3):
type = [i[3 * index + 1] for i in data.values]
title = type[0]
subtitle = type[11]
if "Sensitivity" not in title:
line_pic = Line(title, subtitle)
for compare in range(files_number):
#添加曲线的limit
if OK_Limit == True:
limit_path = "./limit/%s" % (station + ".txt")
x_Upper, y_Upper, x_Lower, y_Lower = get_limit_data(
title, limit_path)
if x_Upper != None and y_Upper != None:
line_pic.add("Upper Limit",
x_Upper,
y_Upper,
is_legend_show=False)
if x_Lower != None and y_Lower != None:
line_pic.add("Lower Limit",
x_Lower,
y_Lower,
is_legend_show=False)
x = [
i[3 * index + 2 + compare * division] for i in data.values
]
while 'NaN' in x:
x.remove('NaN')
y = [
i[3 * index + 3 + compare * division] for i in data.values
]
while 'NaN' in y:
y.remove('NaN')
if int(float(x[0])) > int(float(x[1])):
x.reverse()
y.reverse()
sn_info = [i[compare * division] for i in data.values][0]
#print sn_info,x,y
#line_pic=Line(title,subtitle)
line_pic.add(sn_info,
x,
y,
is_smooth=True,
is_legend_show=False,
is_more_utils=True)
page.add(line_pic)
page.render('log.html')
print u"Log图完成绘制，并生成log.html文件，请用浏览器打开"
print u"Tips:每幅图都可以查看每条曲线的SN并进行图片下载"
def create_charts():
page = Page()
style = Style(width=WIDTH, height=HEIGHT)
df = pd.read_csv('./data_cleaned.csv')
table6 = pd.pivot_table(df,
values=['DISPOSE_UNIT_NAME'],
index=['INTIME_ARCHIVE_NUM'],
columns=['EVENT_TYPE_NAME'],
aggfunc='count',
fill_value=0)
table6_2 = table6 / table6.sum()
name = [i[1] for i in table6_2]
value = [float(table6_2.values[0][j]) for j in range(len(name))]
chart = Bar("超时结案", **style.init_style)
chart.add("",
name,
value,
is_datazoom_show=True,
mark_line=["average"],
is_stack=True,
datazoom_type='both',
datazoom_range=[10, 60])
page.add(chart)
return page
def create_two_bars():
page = Page()
# bar
attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
bar = Bar("柱状图数据堆叠示例")
bar.add("商家A", attr, v1, is_stack=True)
bar.add("商家B", attr, v2, is_stack=True)
page.add(bar)
# scatter3D
import random
data = [[
random.randint(0, 100),
random.randint(0, 100),
random.randint(0, 100)
] for _ in range(80)]
range_color = [
'#313695', '#4575b4', '#74add1', '#abd9e9', '#e0f3f8', '#ffffbf',
'#fee090', '#fdae61', '#f46d43', '#d73027', '#a50026'
]
scatter3D = Scatter3D("3D 散点图示例", width=1200, height=600)
scatter3D.add("", data, is_visualmap=True, visual_range_color=range_color)
page.add(scatter3D)
return page
def create_combine_charts(dataframe):
page = Page()
# df= get_df_fromSQL('ori_data')
df_new = pd.DataFrame()
list1 = coltype_filter(dataframe, '套餐类型')
num = len(list1)
v1 = [x for x in range(0, num)]
v2 = [x for x in range(0, num)]
v3 = [x for x in range(0, num)]
v4 = [x for x in range(0, num)]
for i in range(0, num):
df_new = detailed_info_filter(dataframe, '套餐类型', [list1[i]])
v1[i] = month_Chuzhang(df_new)
for i in range(0, num):
df_new = detailed_info_filter(dataframe, '套餐类型', [list1[i]])
v2[i] = APRU_Chuzhang(df_new)
# for i in range(0,num):
# df=dataframe[dataframe['套餐类型']==list1[i]]
# v3[i]=MOU(df)
# for i in range(0,num):
# df = dataframe[dataframe['套餐类型']==list1[i]]
# v4[i]=DOU(df)
chart = Bar("数据分析", '总收入/平均出帐收入/MOU/DOU')
chart.add('总收入', list, v1)
chart.add("月平均收入", list, v2)
# chart.add('MOU',list,v3)
# chart.add('DOU',list,v4)
page.add(chart)
return page
def brush(data):
data = hist_sum(data)
kline = Kline()
kline.add(
'Kline',
data.index,
data.loc[:, ['open', 'close', 'low', 'high']].values,
mark_line=['max', 'min'],
mark_line_valuedim=['highest', 'lowest'],
is_datazoom_show=True,
datazoom_xaxis_index=[0, 1],
)
brush = Line()
brush.add(
'Brush',
data.index,
data.endpoint.values,
)
overlap = Overlap()
overlap.add(kline)
overlap.add(brush)
macd = Bar()
macd.add(
'MACD',
data.index,
data.hist_sum.values,
)
page = Page()
page.add(overlap)
page.add(macd)
return page
def genReport2(date):
DB = DBfunction.getDB()
ListU = DBfunction.getUserlist(DB)
for i in range(0, len(ListU)):
User = ListU[i]
ListS = DBfunction.getUserStock(DB, User)
ListM = DBfunction.getUserMethod(DB, User)
page = Page()
l1 = Reporter.plotKline('sh')
l3 = Reporter.plotKline('hs300')
page.add_chart(l1, name='the 200 day Kline of SH ')
page.add_chart(l3, name='the 200 day Kline of HS300')
for i in range(0, len(ListS)):
Symbol = ListS[i]
l1 = Reporter.plotKline(Symbol)
page.add_chart(l1, name='the 200 day Kline of ' + Symbol)
for j in range(0, len(ListM)):
stg = ListM[j]
exec('l = Reporter.plot2{}(Symbol)'.format(stg))
exec('page.add_chart(l)')
page.render('./report/' + User + '.html')
page.render('./hist/' + User + ' ' + date + '.html')
def create_charts():
page = Page()
style = Style(
width=WIDTH, height=HEIGHT
)
_data = []
for t in range(0, 25000):
_t = t / 1000
x = (1 + 0.25 * math.cos(75 * _t)) * math.cos(_t)
y = (1 + 0.25 * math.cos(75 * _t)) * math.sin(_t)
z = _t + 2.0 * math.sin(75 * _t)
_data.append([x, y, z])
chart = Line3D("3D 折线图-默认", **style.init_style)
chart.add("", _data, is_visualmap=True, visual_range_color=RANGE_COLOR,
visual_range=[0, 30], grid3d_rotate_sensitivity=5)
page.add(chart)
_data = []
for t in range(0, 25000):
_t = t / 1000
x = (1 + 0.25 * math.cos(75 * _t)) * math.cos(_t)
y = (1 + 0.25 * math.cos(75 * _t)) * math.sin(_t)
z = _t + 2.0 * math.sin(75 * _t)
_data.append([x, y, z])
chart = Line3D("3D 折线图-自动旋转", **style.init_style)
chart.add("", _data, is_visualmap=True, visual_range_color=RANGE_COLOR,
visual_range=[0, 30], is_grid3d_rotate=True,
grid3d_rotate_speed=180)
page.add(chart)
return page
def create_three():
page = Page()
# bar
attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
bar = Bar("柱状图数据堆叠示例")
bar.add("商家A", attr, v1, is_stack=True)
bar.add("商家B", attr, v2, is_stack=True)
page.add(bar)
# scatter3D
import random
data = [
[random.randint(0, 100), random.randint(0, 100), random.randint(0, 100)] for _ in range(80)
]
range_color = ['#313695', '#4575b4', '#74add1', '#abd9e9', '#e0f3f8', '#ffffbf',
'#fee090', '#fdae61', '#f46d43', '#d73027', '#a50026']
scatter3d = Scatter3D("3D 散点图示例", width=1200, height=600)
scatter3d.add("", data, is_visualmap=True, visual_range_color=range_color)
page.add(scatter3d)
# guangdong
value = [20, 190, 253, 77, 65]
attr = ['汕头市', '汕尾市', '揭阳市', '阳江市', '肇庆市']
map = Map("广东地图示例", width=1200, height=600)
map.add("", attr, value, maptype='广东', is_visualmap=True,
visual_text_color='#000')
page.add(map)
return page
def main():
'''
# 测试词云图
x = [
"python", "lxj", "zj", "big data", "python", "lxj", "zj", "big data",
"python", "lxj", "zj", "big data", "python", "lxj", "zj", "big data"
]
y = [
10000, 8000, 6000, 3000, 10000, 8000, 6000, 3000,
10000, 8000, 6000, 3000, 10000, 8000, 6000, 3000
]
label = "词云"
wordCloud(x, y, label)
'''
'''
# 测试统计图表
x = ["衬衫", "袜子", "高跟鞋", "羊毛衫", "裤子"]
y1 = [5, 10, 38, 75, 90]
y2 = [15, 4, 70, 25, 190]
label = "服装"
type = 2
get_charts(x, y, label, type)
'''
'''
# 测试多个统计图
page = Page()
get_otherCharts(page)
'''
# 测试三维散点图
page = Page()
get_scatter3D(page)
def analysisProvince():
friends_info = get_friends_info()
df = pd.DataFrame(friends_info)
province_count = df.groupby(
'province', as_index=True)['province'].count().sort_values()
print('province', province_count)
print(list(province_count))
temp = list(
map(lambda x: x if x != '' else '未知', list(province_count.index)))
print('temp', temp)
# 画图
page = Page()
style = Style(width=1100, height=600)
style_middle = Style(width=900, height=500)
attr, value = temp, list(province_count)
chart1 = Map('好友分布(中国地图)', **style.init_style)
chart1.add('',
attr,
value,
is_label_show=True,
is_visualmap=True,
visual_text_color='#000')
page.add(chart1)
chart2 = Bar('好友分布柱状图', **style_middle.init_style)
chart2.add('',
attr,
value,
is_stack=True,
is_convert=True,
label_pos='inside',
is_legend_show=True,
is_label_show=True)
page.add(chart2)
page.render('analysisProvince.html')
def analysisSex():
friends_info = get_friends_info()
print('friends_info', friends_info)
df = pd.DataFrame(friends_info)
df.to_excel('C:/Users/15432/Desktop/df.xlsx')
sex_count = df.groupby(['sex'], as_index=True)['sex'].count()
print('sex_count', type(sex_count), sex_count)
temp = dict(zip(list(sex_count.index), list(sex_count))) # zip对俩个列表打包成元组
print('temp', temp)
data = {}
data['保密'] = temp.pop(0) # 取出字典给定键 key 所对应的值
data['男'] = temp.pop(1)
data['女'] = temp.pop(2)
print('data', data)
# 画图
page = Page()
attr, value = data.keys(), data.values()
chart = Pie('微信好友性别比')
chart.add('',
attr,
value,
center=[50, 50],
redius=[30, 70],
is_label_show=True,
legend_orient='horizontal',
legend_pos='center',
legend_top='bottom',
is_area_show=True)
page.add(chart)
page.render('analysisSex.html')
def liquid_charts():
page = Page()
chart_init = {
"width": WIDTH,
"height": HEIGHT,
}
chart = Liquid("水球图-单数据", **chart_init)
chart.add("Liquid", [0.6])
page.add(chart)
chart = Liquid("水球图-多数据", **chart_init)
chart.add("Liquid", [0.6, 0.5, 0.4, 0.3], is_liquid_outline_show=False)
page.add(chart)
chart = Liquid("水球图-圆角", **chart_init)
chart.add("Liquid", [0.6, 0.5, 0.4, 0.3],
is_liquid_outline_show=False,
shape='roundRect')
page.add(chart)
chart = Liquid("水球图-箭头", **chart_init)
chart.add("Liquid", [0.6, 0.5, 0.4, 0.3],
is_liquid_outline_show=False,
shape='arrow')
page.add(chart)
chart = Liquid("水球图-动画静止", **chart_init)
chart.add("Liquid", [0.6, 0.5, 0.4, 0.3],
is_liquid_animation=False,
shape='diamond')
page.add(chart)
return page
def make_plot(city):
city_dict = make_city_dict()
# 倒入包
data = pd.read_csv('csv_files/%s/groupby_region_df.csv'%city)
# 读取数据
configure(global_theme='vintage')
# 设置主题
X_axis = data["地区"].tolist()
v1 = data["每平方米单价(单位:元)"].tolist()
v2 = data["总价(单位:万元)"].tolist()
bar1 = Bar(title="%s各区域二手房单价分布条形图"%city_dict[city], width=1500, height=600)
bar1.add("单价",
X_axis,
v1,
mark_point=["max", "min"],
mark_line=['average'],
mark_point_textcolor='#000',
xaxis_rotate=45,
mark_point_symbol="pin", )
bar2 = Bar(title="%s各区域二手房总价分布条形图"%city_dict[city], width=1500, height=600)
bar2 = bar2.add("总价",
X_axis,
v2,
mark_point=["max", "min"],
mark_line=['average'],
xaxis_rotate=45,
mark_point_textcolor='#000',
mark_point_symbol="pin", )
page = Page()
page.add_chart(bar1)
page.add_chart(bar2)
return page
def draw_publisher_author_word_cloud(self, publisher: list, author: list):
"""
画出版社和作者的词云
:param publisher:
:param author:
:return: 无返回值(如果self._json_mode为True则有返回值)
"""
if len(publisher) < 1:
logger.error("No Data!")
raise ValueError("Publisher list is empty!")
elif len(author) < 1:
logger.error("No Data!")
raise ValueError("Author list is empty!")
name = ['热门出版社', '热门作者']
# 画图
page = Page()
chart = WordCloud(name[0], **self.style.init_style)
chart.add("", publisher[0], publisher[1], word_size_range=[12, 80], shape="cardioid")
page.add(chart)
chart_1 = WordCloud(name[1], **self.style.init_style)
chart_1.add("", author[0], author[1], word_size_range=[12, 80], shape="pentagon")
page.add(chart_1)
if self._json_mode:
chart_json = [chart.options, chart_1.options]
return chart_json
else:
logger.debug("正在导出: " + Echart_Output_Path + "&".join(name) + ".html")
page.render(Echart_Output_Path + "&".join(name) + ".html")
def create_total_charts(df):
page = Page()
df_new = pd.DataFrame()
list1 = coltype_filter(df, '套餐类型')
num = len(list1)
v1 = [x for x in range(0, num)]
for i in range(0, num):
df_new = df[df['套餐类型'] == list1[i]]
v1[i] = month_Chuzhang(df_new)
# v2 = [10, 25, 8, 60, 20, 80]
v2 = [x for x in range(0, num)]
for i in range(0, num):
df_new = df[df['套餐类型'] == list1[i]]
v2[i] = APRU_Chuzhang(df_new)
v3 = [x for x in range(0, num)]
for i in range(0, num):
df_new = df[df['套餐类型'] == list1[i]]
v3[i] = MOU(df_new)
v4 = [x for x in range(0, num)]
for i in range(0, num):
df_new = df[df['套餐类型'] == list1[i]]
v4[i] = DOU(df_new)
chart = Bar("数据分析", "月总收入/平均收入/MOU/DOU")
chart.add("月总收入", list1, v1)
chart.add("各套餐平均收入", list1, v2)
chart.add("MOU", list1, v3)
chart.add("DOU", list1, v4)
# chart.add("月平均收入", attr, v2, is_stack=True, is_more_utils=True)
page.add(chart)
return page
def draw_book_price_chart(self, stage_list: list):
"""
图书价格分布图
:param stage_list: 各分段数据
:return:
"""
page = Page()
x = ["0~20", "20~40", "40~60", "60~80", "80~100", "100~"]
bar_chart = Bar("图书价格分布(柱状图)", **self.style.init_style)
bar_chart.add("", x, stage_list, is_more_utils=True, is_label_show=True)
page.add(bar_chart)
pie_chart = Pie("图书价格分布(饼图)", **self.style.init_style)
pie_chart.add("", x, stage_list,
is_label_show=True,
legend_orient='vertical',
legend_pos='left',
legend_top="center")
page.add(pie_chart)
if self._json_mode:
chart_json = [bar_chart.options, pie_chart.options]
return chart_json
else:
logger.debug("正在导出: " + Echart_Output_Path + "图书价格分布图" + ".html")
page.render(Echart_Output_Path + "图书价格分布图" + ".html")
def create_three():
page = Page(page_title=TEST_PAGE_TITLE)
# bar
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
bar = Bar("柱状图数据堆叠示例")
bar.add("商家A", CLOTHES, v1, is_stack=True)
bar.add("商家B", CLOTHES, v2, is_stack=True)
page.add(bar)
# scatter3D
import random
data = [[
random.randint(0, 100),
random.randint(0, 100),
random.randint(0, 100)
] for _ in range(80)]
scatter3d = Scatter3D("3D 散点图示例", width=1200, height=600)
scatter3d.add("", data, is_visualmap=True, visual_range_color=RANGE_COLOR)
page.add(scatter3d)
# guangdong
value = [20, 190, 253, 77, 65]
attr = ['汕头市', '汕尾市', '揭阳市', '阳江市', '肇庆市']
map = Map("广东地图示例", width=1200, height=600)
map.add("",
attr,
value,
maptype='广东',
is_visualmap=True,
visual_text_color='#000')
page.add(map)
return page
def create_charts():
page = Page()
attr = ["男性", "女性", "无性别"]
gender = [12773970, 6479097, 797077]
chart = Pie("性别", title_pos='center')
chart.add("", attr, gender, is_label_show=True)
page.add(chart)
attr = ["50后", "60后", "70后", "80后", "90后", "其他"]
age = [971253, 2758022, 5078234, 7395064, 1514256, 945754]
chart = Bar("性别", title_pos='center')
chart.add("", attr, age, is_stack=True)
page.add(chart)
attr = [
"@qq.com", " @163.com", "@126.com", "@hotmail.com", "@sina.com",
"@yahoo.com.cn", "@gmail.com", "@139.com", "@sohu.com", "@yahoo.cn"
]
email = [
611842, 594392, 274512, 203237, 151798, 101692, 96346, 67565, 50179,
31274
]
chart = Pie("Top10 邮箱域名", title_pos='center')
chart.add("",
attr,
email,
is_random=True,
radius=[20, 80],
rosetype='radius',
legend_orient='vertical',
legend_pos='left')
page.add(chart)
return page
def creat_lan_charts(data_list):
page = Page()
style = Style(title_color="#fff",
title_pos="center",
width=1200,
height=600,
background_color='#404a59')
chart = Geo("python", "python-city", **style.init_style)
attr, value = chart.cast(data_list)
chart.add("",
attr,
value,
visual_range=[0, 200],
visual_text_color="#fff",
is_legend_show=False,
symbol_size=15,
is_visualmap=True,
tooltip_formatter='{b}',
label_emphasis_textsize=15,
label_emphasis_pos='right')
page.add(chart)
chart = Geo("全国主要城市空气质量", "data from pm2.5", **style.init_style)
attr, value = chart.cast(data_list)
chart.add("",
attr,
value,
type="heatmap",
is_visualmap=True,
visual_range=[0, 200],
visual_text_color='#fff',
is_legend_show=False)
page.add(chart)
return page
def huati(name,num,k):#看各级的销量
kk=[]
for i in range(len(name)):
if not numpy.isnan(num[i]):
q = []
q.append(name[i])
q.append(num[i])
# q[name[i]]=hot[i]
kk.append(q)
hh=sorted(kk,key=lambda i:i[1],reverse=True)
page=Page()
att,val=[],[]
for i in hh[:20]:
att.append(i[0])
val.append(i[1])
bar1 = Bar("", k+"A景区销量排行", title_pos="center", width=1200, height=600)
bar1.add("",att,val, is_visualmap=True, visual_text_color='#fff', mark_point=["average"],
mark_line=["average"],
is_more_utils=True, is_label_show=True, is_datazoom_show=True, xaxis_rotate=45)
page.add_chart(bar1)
att, val = [], []
for i in hh[-20:]:
att.append(i[0])
val.append(i[1])
bar2 = Bar("", k+"A景区销量排行", title_pos="center", width=1200, height=600)
bar2.add("", att, val, is_visualmap=True, visual_text_color='#fff', mark_point=["average"],
mark_line=["average"],
is_more_utils=True, is_label_show=True, is_datazoom_show=True, xaxis_rotate=45)
page.add_chart(bar2)
page.render(k+"A景区销量bar.html")
def create_charts():
page = Page()
conn=mysql2pd('140.143.161.111', '3306', 'mm', 'root', 'a091211')
data=conn.doget("select 监测点,AQI指数,`PM2.5`,PM10,Co,No2,So2,O3,updata_time from aqi")
conn.close()
ps=data['监测点'].drop_duplicates().values
ts=data['updata_time'].drop_duplicates().values
cs=['AQI指数','PM2.5','PM10','Co','No2','So2','O3']
for p in ps:
res = []
data1=data[data['监测点']==p]
for i,c in enumerate(cs):
for x,t in enumerate(ts):
data2=data1[data1['updata_time']==t]
for l in list(data2[c].values):
res.append([i,x,l])
style = Style(
width=WIDTH, height=HEIGHT
)
chart = Bar3D(p, **style.init_style)
chart.add(p, ts, cs, [{'name':ts[d[1]],'value':[d[1], d[0], d[2]]} for d in res],
is_visualmap=True, visual_range=[0, 180],
visual_range_color=RANGE_COLOR,
grid3d_width=80, grid3d_depth=80)
page.add(chart)
return page
def gen_zwyx_dd(zwlb):
qs = ZpZwByAreaModel.objects
if zwlb:
qs = qs.filter(zwlb=zwlb)
path = f'zwyx_dd/{zwlb}.html'
else:
path = 'zwyx_dd.html'
page = Page()
df = read_frame(qs.all())
if len(df) > 0:
df_group = df.groupby(['year', 'month'])
time_line_chart1 = Timeline(width=1500,
height=450,
is_auto_play=False,
timeline_bottom=0)
time_line_chart2 = Timeline(width=1500,
height=450,
is_auto_play=False,
timeline_bottom=0)
for name, group in df_group:
# 地图 平均薪资
month = group['month'].tolist()[0]
year = group['year'].tolist()[0]
df_new = group.groupby('province').apply(
get_echarts_all_by_zwyx_value, 'province')
data = [
(a, (b + c) / 2)
for a, b, c in zip(df_new['province'].tolist(
), df_new['max_zwyx'].tolist(), df_new['min_zwyx'].tolist())
]
chart = Map(f'{zwlb}平均职位月薪与地点', width=1500, height=450)
attr, value = chart.cast(data)
chart.add(f'平均薪资',
attr,
value,
wmaptype='china',
is_label_show=True,
is_visualmap=True,
visual_range=[int(min(value)),
int(max(value))],
visual_pos='right',
visual_top='top')
time_line_chart1.add(chart, f'{year}年{month}月')
# 本月职位量Top20
chart3 = Pie(f'{zwlb}职位量及招聘人数', width=1500)
chart3.add('职位量',
df_new['province'].tolist(),
df_new['count'].tolist(),
center=[25, 50],
is_label_show=True)
chart3.add('招聘人数',
df_new['province'].tolist(),
df_new['zprs'].tolist(),
center=[75, 50],
is_label_show=True)
time_line_chart2.add(chart3, f'{year}年{month}月')
page.add(time_line_chart1)
page.add(time_line_chart2)
page.render(os.path.join(BASE_DIR, 'templates/{}'.format(path)))
def drawKline(datadf, tradeRecorddf):
datadf["datetime"] = datadf["datetime"].dt.strftime("%Y-%m-%d %H:%M:%S")
OHLC = df[["open", "close", "low", "high"]]
OHLC = OHLC.values
DATETIME = df["datetime"].values
longOrderDF = tradeRecorddf[tradeRecorddf["direction"] == "long position"]
longOrderDF = longOrderDF[["time", "deal price", "kaiping"]].values
shortOrderDF = tradeRecorddf[tradeRecorddf["direction"] == "short position"]
shortOrderDF = shortOrderDF[["time", "deal price", "kaiping"]].values
markpointlist = []
for longorders in longOrderDF:
markpointlist.append(RedArrow(longorders[0], longorders[1], longorders[2]))
for shortorders in shortOrderDF:
markpointlist.append(GreenArrow(shortorders[0], shortorders[1], shortorders[2]))
page = Page()
grid = Grid(width=1920, height=900)
kline = Kline("candlestick")
kline.add("candlestick", DATETIME, OHLC, is_datazoom_show=True, datazoom_type='inside',
datazoom_range=[90, 100], tooltip_tragger_on='mousemove|click', tooltip_axispointer_type='cross',
is_label_show=False, mark_point_raw=markpointlist)
grid.add(kline, grid_top="3%", grid_height="95%")
page.add(grid)
now = dt.datetime.now()
today = now.strftime('%Y%m%d')
time = now.strftime("%H_%M_%S")
home = os.environ['HOME']
page.render(home + "/Pictures/" + today + "/" + "plotKlineChartandSignal" + time + ".html")
def gen_zwyx_type(zwlb):
qs = ZpZwyxByTypeModel.objects
if zwlb:
qs = qs.filter(zwlb=zwlb)
path = f'zwyx_type/{zwlb}.html'
else:
path = 'zwyx_type.html'
# 当月职位月薪与公司性质
df = read_frame(qs.all())
if len(df) > 0:
page = Page()
Grid_chart1 = Timeline(width=1500, height=450, timeline_bottom=0)
Grid_chart2 = Timeline(width=1500, height=450, timeline_bottom=0)
df_group = df.groupby(['year', 'month'])
for name, group in df_group:
month = group['month'].tolist()[0]
year = group['year'].tolist()[0]
df_new = group.groupby('type').apply(get_echarts_all_by_zwyx_value,
'type')
# 薪资
Overlap_chart = Overlap(width=800, height=450)
bar_chart = Bar(f'{zwlb}职位月薪与公司性质')
bar_chart.add('最低薪资',
df_new['type'].tolist(),
df_new['min_zwyx'].tolist(),
is_label_show=True,
is_more_utils=True)
bar_chart.add('最高薪资',
df_new['type'].tolist(),
df_new['max_zwyx'].tolist(),
is_label_show=True,
is_more_utils=True)
line_chart = Line()
line_chart.add("平均薪资",
df_new['type'].tolist(),
[(a + b) / 2
for a, b in zip(df_new['min_zwyx'].tolist(),
df_new['max_zwyx'].tolist())],
is_label_show=True)
Overlap_chart.add(bar_chart)
Overlap_chart.add(line_chart)
Grid_chart1.add(Overlap_chart, f'{year}年{month}月')
# 职位量
chart3 = Pie(f'{zwlb}职位量及招聘人数', width=1500)
chart3.add('职位量'.format(zwlb),
df_new['type'].tolist(),
df_new['count'].tolist(),
is_label_show=True,
is_stack=True,
center=[25, 50])
chart3.add('招聘人数'.format(zwlb),
df_new['type'].tolist(),
df_new['zprs'].tolist(),
is_label_show=True,
is_stack=True,
center=[75, 50])
Grid_chart2.add(chart3, f'{year}年{month}月')
page.add(Grid_chart1)
page.add(Grid_chart2)
page.render(os.path.join(BASE_DIR, 'templates/{}'.format(path)))
def create_charts():
page = Page()
chart_init = {
"width": WIDTH,
"height": HEIGHT,
}
attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
value = [20, 40, 60, 80, 100, 120]
chart = Funnel("漏斗图示例", **chart_init)
chart.add("商品",
attr,
value,
is_label_show=True,
label_pos="inside",
label_text_color="#fff")
page.add(chart)
chart = Funnel("漏斗图示例", title_pos='center', **chart_init)
chart.add("商品",
attr,
value,
is_label_show=True,
label_pos="outside",
legend_orient='vertical',
legend_pos='left')
page.add(chart)
return page
def gen_gwzz_word(zwlb):
qs = ZpWordByZwlbModel.objects
if zwlb:
qs = qs.filter(zwlb=zwlb)
path = f'zp_word/{zwlb}.html'
else:
path = 'zp_word.html'
df = read_frame(qs.all())
if len(df) > 0:
page = Page()
Grid_chart1 = Timeline(width=1500, height=800, timeline_bottom=0)
df_group = df.groupby(['year', 'month'])
for name, group in df_group:
month = group['month'].tolist()[0]
year = group['year'].tolist()[0]
df_new = group.groupby('word').apply(get_echarts_all_by_value,
'word')
chart = WordCloud(f'{zwlb}岗位需求词云', width=1500)
shape_list = [
None, 'circle', 'cardioid', 'diamond', 'triangle-forward',
'triangle', 'pentagon', 'star'
]
chart.add("",
df_new['word'].tolist(),
df_new['count'].tolist(),
word_size_range=[30, 100],
rotate_step=66,
shape=shape_list[random.randint(0,
len(shape_list) - 1)])
Grid_chart1.add(chart, f'{year}年{month}月')
page.add(Grid_chart1)
page.render(os.path.join(BASE_DIR, 'templates/{}'.format(path)))
def create_charts():
page = Page()
style = Style(
width=1100, height=600
)
name = [
'Sam S Club', 'Macys', 'Amy Schumer', 'Jurassic World',
'Charter Communications', 'Chick Fil A', 'Planet Fitness',
'Pitch Perfect', 'Express', 'Home', 'Johnny Depp', 'Lena Dunham',
'Lewis Hamilton', 'KXAN', 'Mary Ellen Mark', 'Farrah Abraham',
'Rita Ora', 'Serena Williams', 'NCAA baseball tournament', 'Point Break']
value = [
10000, 6181, 4386, 4055, 2467, 2244, 1898, 1484, 1112,
965, 847, 582, 555, 550, 462, 366, 360, 282, 273, 265]
chart = WordCloud("词云图-默认形状", **style.init_style)
chart.add("", name, value, word_size_range=[30, 100], rotate_step=66)
page.add(chart)
chart = WordCloud("词云图-自定义形状", **style.init_style)
chart.add("", name, value, word_size_range=[30, 100], shape='diamond')
page.add(chart)
return page
def lines_show(line_data):
# 显示多个曲线图
page = Page()
for b in line_data:
line = create_line(b['x'], b['head'], b['data'], b['dict'])
page.add(line)
page.render()
