def dashboard(request):
tasks = Task.objects.all()[0:5]
my_tasks = Task.objects.filter(tester=request.user)[0:5]
attr = Results.objects.show_task_id()
script_list = []
line = line_time_kf(attr)
bar = bar_mp_kf(attr)
# myechart = bar.render_embed()
# myechart = line.render_embed()
script_list.extend(line.get_js_dependencies())
# script_list = bar.get_js_dependencies()
script_list.extend(bar.get_js_dependencies())
grid = Grid(width="auto")
grid.add(line, grid_bottom="60%")
grid.add(bar, grid_top="60%")
myechart = grid.render_embed()
script_list.extend(grid.get_js_dependencies())
# run_rtv_numbers = Results.objects.order_by('-id').values_list('id').first()[0]
# seconds = sum([int(i[0]) for i in Results.objects.values_list('time')])
# m, s = divmod(seconds, 60)
# h, m = divmod(m, 60)
# d, h = divmod(h, 24)
# time_cost = "%02dd:%02dh:%02dm:%02ds" % (d, h, m, s)
return render(request, 'dashboard.html', {
# 'run_rtv_numbers': run_rtv_numbers,
# 'time_cost': time_cost,
'tasks': tasks,
'my_tasks': my_tasks,
'if_dashboard_active': 'active',
'myechart': myechart,
'script_list': script_list
})
def echart1(request):
template = loader.get_template('ewpyecharts.html')
line = Line("压力分析", width=1200, height=700)
attr = ['周一', '周二', '周三', '周四', '周五', '周六', '周日']
line.add("最高压力", attr, [11, 11, 15, 13, 12, 13, 10],
mark_point=["max", "min"], mark_line=["average"])
line.add("最低压力", attr, [1, -2, 2, 5, 3, 2, 0],
mark_point=["max", "min"], legend_top="50%", mark_line=["average"],
# 设置 dataZoom 控制索引为 0,1 的 x 轴，即第一个和第二个
is_datazoom_show=True, datazoom_xaxis_index=[0, 1])
v1 = [[2320.26, 2320.26, 2287.3, 2362.94],
[2300, 2291.3, 2288.26, 2308.38],
[2295.35, 2346.5, 2295.35, 2345.92],
[2347.22, 2358.98, 2337.35, 2363.8],
[2360.75, 2382.48, 2347.89, 2383.76],
[2383.43, 2385.42, 2371.23, 2391.82],
[2377.41, 2419.02, 2369.57, 2421.15],
[2425.92, 2428.15, 2417.58, 2440.38],
[2411, 2433.13, 2403.3, 2437.42],
[2432.68, 2334.48, 2427.7, 2441.73],
[2430.69, 2418.53, 2394.22, 2433.89],
[2416.62, 2432.4, 2414.4, 2443.03],
[2441.91, 2421.56, 2418.43, 2444.8],
[2420.26, 2382.91, 2373.53, 2427.07],
[2383.49, 2397.18, 2370.61, 2397.94],
[2378.82, 2325.95, 2309.17, 2378.82],
[2322.94, 2314.16, 2308.76, 2330.88],
[2320.62, 2325.82, 2315.01, 2338.78],
[2313.74, 2293.34, 2289.89, 2340.71],
[2297.77, 2313.22, 2292.03, 2324.63],
[2322.32, 2365.59, 2308.92, 2366.16],
[2364.54, 2359.51, 2330.86, 2369.65],
[2332.08, 2273.4, 2259.25, 2333.54],
[2274.81, 2326.31, 2270.1, 2328.14],
[2333.61, 2347.18, 2321.6, 2351.44],
[2340.44, 2324.29, 2304.27, 2352.02],
[2326.42, 2318.61, 2314.59, 2333.67],
[2314.68, 2310.59, 2296.58, 2320.96],
[2309.16, 2286.6, 2264.83, 2333.29],
[2282.17, 2263.97, 2253.25, 2286.33],
[2255.77, 2270.28, 2253.31, 2276.22]]
kline = Kline("考核表分析", title_top="50%")
kline.add("日K", ["2017/7/{}".format(i + 1) for i in range(31)],
v1, is_datazoom_show=True)
grid = Grid()
grid.add(line, grid_top="60%")
grid.add(kline, grid_bottom="60%")
# grid.render()
context = dict(
myechart=grid.render_embed(),
host=REMOTE_HOST,
script_list=grid.get_js_dependencies()
)
return HttpResponse(template.render(context, request))
def get_realtime_data():
# 历史数据优先从hdf5中获取 获取不到则实时从接口获取并添加到hdf5中
store = pd.HDFStore(app.config['STOCKS_PRICE_HDF5'], mode='r+')
code = request.args.get("code")
# sh_index_data = ts.get_k_data('000001', index=True)
real_data = ts.get_realtime_quotes(code)
if 'sh_index_data' in store:
sh_index_data = pd.read_hdf(app.config['STOCKS_PRICE_HDF5'],
'sh_index_data',
mode='r+')
else:
sh_index_data = ts.get_k_data('000001', index=True)
sh_index_data.to_hdf(app.config['STOCKS_PRICE_HDF5'],
'sh_index_data',
format='table',
data_columns=True)
if code in store:
hist_data = pd.read_hdf(app.config['STOCKS_PRICE_HDF5'],
code,
mode='r+')
else:
hist_data = ts.get_k_data(code)
hist_data.to_hdf(app.config['STOCKS_PRICE_HDF5'],
code,
format='table',
data_columns=True)
store.close()
kline = kline_chart(code, hist_data)
# 这时还没转dict
kline_sh = kline_chart_sh(sh_index_data)
grid = Grid(width="100%")
grid.add(kline, grid_bottom="60%")
grid.add(kline_sh, grid_top="60%")
real_data['delta'] = (real_data['price'].astype('float') -
real_data['pre_close'].astype('float'))
real_data['delta'] = real_data['delta'].apply(lambda x: round(x, 4))
real_data['delta%'] = real_data['delta'] / real_data['pre_close'].astype(
'float')
real_data['delta%'] = real_data['delta%'].apply(
lambda x: round(x * 100, 2))
real_data = real_data.to_dict('record')
hist_data = hist_data.sort_values('date', ascending=False)
hist_data = hist_data.to_dict('record')
return render_template(
"table_with_chart.html",
basic_data=url_for('get_stock_basics_json', code=code),
basic_data_columns=stock_basics_columns,
real_data=url_for('get_realtime_data_json', code=code),
real_data_columns=real_data_columns,
hist_data_columns=hist_data_columns,
hist_data=hist_data,
title=('{0}:({1})股票实时价格'.format(real_data[0]['name'], code)),
grid=grid.render_embed(),
host=app.config['REMOTE_HOST'],
grid_script_list=grid.get_js_dependencies(),
)
def get(self, request, *args, **kwargs):
template_name = 'echart/echart.html'
bar = Bar()
bar.add('服装', ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"],
[5, 20, 36, 10, 75, 90])
line = Line()
line.add("服装", ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"],
[5, 20, 36, 10, 75, 90])
echart = Grid(page_title='组合图', width=1200, height=250)
echart.add(bar, grid_left='50%')
echart.add(line, grid_right='55%')
context = dict(myechart=echart.render_embed(),
host=REMOTE_HOST,
script_list=echart.get_js_dependencies())
return render(request, template_name, context)
def test():
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("柱状图示例", height=720)
bar.add("商家A", attr, v1, is_stack=True)
bar.add("商家B", attr, v2, is_stack=True)
line = Line("折线图示例", title_top="50%")
attr = ["周一", "周二", "周三", "周四", "周五", "周六", "周日"]
line.add(
"最高气温",
attr,
[11, 11, 15, 13, 12, 13, 10],
mark_point=["max", "min"],
mark_line=["average"],
)
line.add(
"最低气温",
attr,
[1, -2, 2, 5, 3, 2, 0],
mark_point=["max", "min"],
mark_line=["average"],
legend_top="50%",
)
grid = Grid()
grid.add(bar, grid_bottom="60%")
grid.add(line, grid_top="60%")
grid_javascript_snippet = TRANSLATOR.translate(grid.options)
return render_template(
'test.html',
host=REMOTE_HOST,
# 饼状图
grid_id=grid.chart_id,
grid_renderer=grid.renderer,
my_width=600,
my_height=400,
grid_custom_function=grid_javascript_snippet.function_snippet,
grid_options=grid_javascript_snippet.option_snippet,
script_list=grid.get_js_dependencies(),
)
def echart1(request):
template = loader.get_template('myfirstvis/pyecharts.html')
#
# # 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')
# #map.render()
# # context = dict(
# # myechart=map.render_embed(),
# # host=REMOTE_HOST,
# # script_list=map.get_js_dependencies()
# # )
#
# # gauge = Gauge("仪表盘示例")
# # gauge.add("业务指标", "完成率", 66.66)
# # gauge.show_config()
#
line = Line("折线图示例", width=1200, height=700)
attr = ['周一', '周二', '周三', '周四', '周五', '周六', '周日']
line.add("最高气温", attr, [11, 11, 15, 13, 12, 13, 10],
mark_point=["max", "min"], mark_line=["average"])
line.add("最低气温", attr, [1, -2, 2, 5, 3, 2, 0],
mark_point=["max", "min"], legend_top="50%", mark_line=["average"],
# 设置 dataZoom 控制索引为 0,1 的 x 轴，即第一个和第二个
is_datazoom_show=True, datazoom_xaxis_index=[0, 1])
v1 = [[2320.26, 2320.26, 2287.3, 2362.94],
[2300, 2291.3, 2288.26, 2308.38],
[2295.35, 2346.5, 2295.35, 2345.92],
[2347.22, 2358.98, 2337.35, 2363.8],
[2360.75, 2382.48, 2347.89, 2383.76],
[2383.43, 2385.42, 2371.23, 2391.82],
[2377.41, 2419.02, 2369.57, 2421.15],
[2425.92, 2428.15, 2417.58, 2440.38],
[2411, 2433.13, 2403.3, 2437.42],
[2432.68, 2334.48, 2427.7, 2441.73],
[2430.69, 2418.53, 2394.22, 2433.89],
[2416.62, 2432.4, 2414.4, 2443.03],
[2441.91, 2421.56, 2418.43, 2444.8],
[2420.26, 2382.91, 2373.53, 2427.07],
[2383.49, 2397.18, 2370.61, 2397.94],
[2378.82, 2325.95, 2309.17, 2378.82],
[2322.94, 2314.16, 2308.76, 2330.88],
[2320.62, 2325.82, 2315.01, 2338.78],
[2313.74, 2293.34, 2289.89, 2340.71],
[2297.77, 2313.22, 2292.03, 2324.63],
[2322.32, 2365.59, 2308.92, 2366.16],
[2364.54, 2359.51, 2330.86, 2369.65],
[2332.08, 2273.4, 2259.25, 2333.54],
[2274.81, 2326.31, 2270.1, 2328.14],
[2333.61, 2347.18, 2321.6, 2351.44],
[2340.44, 2324.29, 2304.27, 2352.02],
[2326.42, 2318.61, 2314.59, 2333.67],
[2314.68, 2310.59, 2296.58, 2320.96],
[2309.16, 2286.6, 2264.83, 2333.29],
[2282.17, 2263.97, 2253.25, 2286.33],
[2255.77, 2270.28, 2253.31, 2276.22]]
kline = Kline("K 线图示例", title_top="50%")
kline.add("日K", ["2017/7/{}".format(i + 1) for i in range(31)],
v1, is_datazoom_show=True)
grid = Grid()
grid.add(line, grid_top="60%")
grid.add(kline, grid_bottom="60%")
# grid.render()
context = dict(
myechart=grid.render_embed(),
host=REMOTE_HOST,
script_list=grid.get_js_dependencies()
)
# # value = [155, 10, 66, 78]
# # attr = ["福建", "山东", "北京", "上海"]
# # map = Map("全国地图示例", width=1200, height=600)
# # map.add("", attr, value, maptype='china',
# # is_visualmap=True, is_piecewise=True,
# # visual_text_color="#000",
# # visual_range_text=["", ""],
# # pieces=[
# # {"max": 160, "min": 70, "label": "高数值"},
# # {"max": 69, "min": 0, "label": "低数值"},
# # ])
# #
# # context = dict(
# # myechart=map.render_embed(),
# # host=REMOTE_HOST,
# # script_list=map.get_js_dependencies()
#
# style = Style(
# title_top="#fff",
# title_pos="center",
# width=1200,
# height=600,
# background_color="#404a59"
# )
#
# data_guangzhou = [
# ["广州", "上海"],
# ["广州", "北京"],
# ["广州", "南京"],
# ["广州", "重庆"],
# ["广州", "兰州"],
# ["广州", "杭州"]
# ]
# geolines = GeoLines("GeoLines 示例", **style.init_style)
# geolines.add("从广州出发", data_guangzhou, is_legend_show=False)
#
# context = dict(
# myechart=geolines.render_embed(),
# host=REMOTE_HOST,
# script_list=geolines.get_js_dependencies()
# )
return HttpResponse(template.render(context, request))
def dataManagerStudent():
stuID = (request.args.get('stuID'))
if stuID == None:
return render_template('dataManagerStudent.html', data=None)
else:
from pyecharts import Bar
from pyecharts_javascripthon.api import TRANSLATOR
REMOTE_HOST = "https://pyecha rts.github.io/assets/js"
data, len_data = mongo.get_data_by_condition(request.args.get('stuID'))
data_day_out = {}
data_day_in = {}
data_shop = []
data_shop_money = {} # 这个月花费的金额
data_shop_num = {} # 这个月消费的次数
data_shop_money_avg = {} # 每次消费平均金额
import time
fun = lambda year, month: list(
range(1, 1 + time.localtime(time.mktime((year, month + 1, 1, 0, 0, 0, 0, 0, 0)) - 86400).tm_mday))
days = fun(2017, 11)
# for i in days:
# if i < 10:
# index = days.index(i)
# days[index] = int('0' + str(i))
# print(days)
for item in days:
# '2017-11-' +
data_day_in[str(item)] = 0
data_day_out[str(item)] = 0
for item in data:
time = str(int(str(item[4]).split(' ')[0].split('-')[2]))
# print(time)
money = -float(item[3])
shop = str(item[2])
if shop == '407010002':
pass
else:
shop = shop.replace(str(item[2])[:3], str(item[2])[:3] + '\n')
if shop not in data_shop:
data_shop.append(shop)
data_shop_money[shop] = money
data_shop_money[shop] = float(format(data_shop_money[shop], '.2f'))
data_shop_num[shop] = 1
else:
data_shop_money[shop] += money
data_shop_money[shop] = float(format(data_shop_money[shop], '.2f'))
data_shop_num[shop] += 1
if money > 0:
data_day_out[time] += money
data_day_out[time] = float(format(data_day_out[time], '.2f'))
else:
data_day_in[time] += money
data_day_in[time] = float(format(data_day_in[time], '.2f'))
# data_shop = data_shop.sort()
# 计算每次在店消费的平均值
for i in data_shop:
data_shop_money_avg[i] = float(format(data_shop_money[i] / data_shop_num[i], '.2f'))
# data_shop.pop(data_shop.index('407010002'))
# data_shop_money.pop('407010002')
# data_shop_num.pop('407010002')
# data_shop_money_avg.pop('407010002')
# 拼接返回值
no_out_days_num = 0
no_out_days = []
for i in data_day_out.keys():
if data_day_out[i] == 0:
no_out_days_num += 1
no_out_days.append(str(list(data_day_out.keys()).index(i)) + '号')
else:
print(i)
'''
max 最大值
min 最小值
avg 平均值
in 充值金额
not_eat_days 没有消费的天数
'''
res_analyse = {
'max': format(max(list(data_day_out.values())), '.2f'),
'min': format(min(list(data_day_out.values())), '.2f'),
'avg': format(sum(list(data_day_out.values())) / len(days), '.2f'),
'sum_in': format(-sum(list(data_day_in.values())), '.2f'),
'sum_out': format(sum(list(data_day_out.values())), '.2f'),
'no_out_days_num': no_out_days_num,
'no_out_days': no_out_days.__str__().replace('[', '').replace(']', '').replace("'", ''),
}
##########图
bar = Bar(height=600) # 柱形图
bar.add('消费金额', days, list(data_day_out.values()), mark_line=["average"], mark_point=["max", "min"],
)
bar.add('充值金额', days, list(data_day_in.values()), bar_category_gap=0.05, mark_line=["average"],
mark_point=["max", "min"])
overlap = Overlap()
bar2 = Bar("消费地点分析", title_top="50%", )
bar2.add('消费金额', data_shop, list(data_shop_money.values()), mark_point=["max", "min"], legend_top="50%")
bar2.add('消费次数', data_shop, list(data_shop_num.values()), mark_point=["max", "min"], legend_top="50%")
line = Line()
line.add('消费均值', data_shop, list(data_shop_money_avg.values()), legend_top="50%", mark_point=["max", "min"])
overlap.add(bar2)
overlap.add(line)
grid = Grid()
grid.add(bar, grid_bottom="60%")
grid.add(overlap, grid_top="60%")
javascript_snippet = TRANSLATOR.translate(grid.options)
return render_template('dataManagerStudent.html',
data=res_analyse,
chart_id=grid.chart_id,
host=REMOTE_HOST,
renderer=grid.renderer,
my_width="100%",
my_height=1200,
custom_function=javascript_snippet.function_snippet,
options=javascript_snippet.option_snippet,
script_list=grid.get_js_dependencies())
