def draw_power(request):
start = request.GET.get('day')
if not start:
start = datetime.date.today()
else:
try:
start = datetime.datetime.strptime(start, '%Y-%m-%d')
except:
start = datetime.date.today()
end = start + datetime.timedelta(days=1)
sql = "select time, voltage, current, rate, consumption from tbl_power where time>=%s and time<%s order by time"
with connection.cursor() as c:
c.execute(sql, (start, end))
rows = c.fetchall()
time_list, voltage_list, current_list, rate_list, consumption_list = [], [], [], [], []
for time, voltage, current, rate, consumption in rows:
time_list.append(time)
voltage_list.append(voltage)
current_list.append(current)
rate_list.append(rate)
consumption_list.append(consumption)
c = (charts.Line().add_xaxis(time_list).add_yaxis(
"电压", voltage_list).add_yaxis("电流", current_list).add_yaxis(
"功率",
rate_list).add_yaxis("累计耗电量", consumption_list).set_global_opts(
title_opts=opts.TitleOpts(title="测试监控", subtitle="耗电基本信息")))
return HttpResponse(c.render_embed())
def index(request):
c = (charts.Line().add_xaxis([i for i in range(1000)]).add_yaxis(
"商家A", [random.randint(50, 100) for i in range(1000)]).add_yaxis(
"商家B",
[random.randint(1, 50) for i in range(1000)]).set_global_opts(
title_opts=opts.TitleOpts(title="Bar-基本示例", subtitle="我是副标题")))
return HttpResponse(c.render_embed())
def draw_action(request):
start = request.GET.get('day')
if not start:
start = datetime.date.today()
else:
try:
start = datetime.datetime.strptime(start, '%Y-%m-%d')
except:
start = datetime.date.today()
end = start + datetime.timedelta(days=1)
sql = "select time, yaw, pitch, roll, acc_x, acc_y, acc_z from tbl_door where time>=%s and time<%s order by time"
with connection.cursor() as c:
c.execute(sql, (start, end))
rows = c.fetchall()
time_list, yaw_list, pitch_list, roll_list, accx_list, accy_list, accz_list = [
[] for _ in range(7)
]
for time, yaw, pitch, roll, acc_x, acc_y, acc_z in rows:
time_list.append(time)
yaw_list.append(yaw)
roll_list.append(roll)
accx_list.append(acc_x)
accy_list.append(acc_y)
accz_list.append(acc_z)
c = (charts.Line().add_xaxis(time_list).add_yaxis(
"yaw", yaw_list).add_yaxis("pitch", pitch_list).add_yaxis(
"roll", roll_list).add_yaxis(
"x向加速度", accx_list).add_yaxis("y向加速度", accy_list).add_yaxis(
"z向加速度",
accz_list).set_global_opts(title_opts=opts.TitleOpts(
title="测试监控", subtitle="门的开关监控数据流")))
return HttpResponse(c.render_embed())
def echarts(self):
self._echarts_align_data()
c = charts.Line()
for k, v in self.curve_values.items():
c.add_xaxis([str(i) for i in self.x_axis])
break
# max_v_dict = defaultdict(list)
for _, v in self.curve_values.items():
# max_v_dict[k].append([max(v[self.y_key]),min(v[self.y_key])])
c.add_yaxis(
v[self.name_key],
v[self.y_key],
label_opts=opts.LabelOpts(is_show=False),
is_symbol_show=False,
)
c.set_global_opts(title_opts=opts.TitleOpts(
title=self.title, padding=5),
yaxis_opts=opts.AxisOpts(
min_='dataMin',
max_='dataMax',
),
legend_opts=opts.LegendOpts(type_='scroll', pos_bottom=10),
tooltip_opts=opts.TooltipOpts(is_show=True, trigger='axis'), )
return c
def draw_temperature(request):
start = request.GET.get('day')
if not start:
start = datetime.date.today()
else:
try:
start = datetime.datetime.strptime(start, '%Y-%m-%d')
except:
start = datetime.date.today()
end = start + datetime.timedelta(days=1)
sql = 'SELECT time, code, value FROM tbl_temperature where time>=%s AND time<%s order by code, time'
with connection.cursor() as c:
c.execute(sql, (start, end))
rows = c.fetchall()
time_list = []
lines = []
for key, content in groupby(rows, key=lambda x: x[1]):
if not time_list:
values = []
for time, _, value in content:
time_list.append(time)
values.append(value)
else:
values = [value for _, _, value in content]
lines.append((layer_map[key], values))
if len(lines) != 6:
c = (charts.Line().add_xaxis(time_list).add_yaxis(
"传感器异常", []).set_global_opts(
title_opts=opts.TitleOpts(title="测试监控", subtitle="传感器温度信息")))
else:
c = (charts.Line().add_xaxis(time_list).add_yaxis(
lines[0][0],
lines[0][1]).add_yaxis(lines[1][0], lines[1][1]).add_yaxis(
lines[2][0],
lines[2][1]).add_yaxis(lines[3][0], lines[3][1]).add_yaxis(
lines[4][0], lines[4][1]).add_yaxis(
lines[5][0],
lines[5][1]).set_global_opts(title_opts=opts.TitleOpts(
title="测试监控", subtitle="传感器温度信息")))
return HttpResponse(c.render_embed())
def drawtable(request):
json_data = request.body.decode('utf-8')
info = json.loads(json_data)
table_name = info.get('table_name', '').strip()
# line_path = 'mycharts/render/tabledata/charts_%s.html' % table_name.split('.')[1]
# 部署到apache服务器后需要使用绝对路径
line_path = os.path.join(
app_dir, 'render/tabledata/charts_%s.html' % table_name.split('.')[1])
if not os.path.exists(
line_path) or time.time() - os.path.getmtime(line_path) > 86400:
table = get_object_or_404(TableData, table_name=table_name)
line_name = table.table_name
table_data = table.table_data
x_data = table_data.get("total_diff_rate").keys()
y_data = table_data.get("total_diff_rate").values()
line = (charts.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),
),
title_opts=opts.TitleOpts(
title="差异比",
subtitle="单位1")).add_xaxis(xaxis_data=x_data).add_yaxis(
series_name=line_name,
y_axis=y_data,
symbol="circle",
itemstyle_opts=opts.ItemStyleOpts(border_color='#fff'),
markpoint_opts=opts.MarkPointOpts(
label_opts=opts.LabelOpts(color='#fff'),
data=[
opts.MarkPointItem(type_='max', name='最大值'),
opts.MarkPointItem(type_='min', name='最小值'),
opts.MarkLineItem(type_="average", name="平均值")
]),
markline_opts=opts.MarkLineItem(type_='average'),
is_symbol_show=True,
label_opts=opts.LabelOpts(is_show=False),
is_connect_nones=True))
line.render(line_path)
chart = open(line_path).read()
return HttpResponse(chart)
def echarts(self):
self._align_data()
c = charts.Line()
for k, v in self.curve_values.items():
c.add_xaxis([str(i) for i in self.x_axis])
break
for k, v in self.curve_values.items():
c.add_yaxis(
v[self.name_key],
v[self.y_key],
label_opts=opts.LabelOpts(is_show=False),
is_symbol_show=False,
)
c.set_global_opts(
title_opts=opts.TitleOpts(title=self.title),
tooltip_opts=opts.TooltipOpts(is_show=True, trigger='axis'),
)
return c
#增加一个数据系列
y1 = [1200,500,200]
bar.add_yaxis(series_name = '公司B',yaxis_data=y1)
bar.render(r'D:\Python Spyder\数据可视化\My PyEcharts\柱状图3.html')
# 变成条形图
bar.reversal_axis()
bar.render(r'D:\Python Spyder\数据可视化\My PyEcharts\条形图.html')
#========================================================================
# 折线图
x1 = ['2017','2018','2019']
y1 = [300,900,500]
line = pyec.Line()
line.add_xaxis(x1)
line.add_yaxis(series_name='A',y_axis = y1)
line.render(r'D:\Python Spyder\数据可视化\My PyEcharts\折线图.html')
# Line 增加提示项目
#提示项 Tool
line.set_global_opts(title_opts=opts.TitleOpts(title = '我的pyecharts'),
tooltip_opts = opts.TooltipOpts(trigger='axis',axis_pointer_type='cross'),
# 工具箱设置 is_show = True 默认展示图例
#orient 参数 ：horizontal 横向 v 纵向
toolbox_opts = opts.ToolboxOpts(is_show=True,orient='horizontal'),
# 设置滚动条
datazoom_opts=opts.DataZoomOpts(type_='slider',range_start=(),range_end=2500)
)
def drawtable_detail(request):
# time.sleep(0.1) # 测试前端用户感知
json_data = request.body.decode('utf-8')
info = json.loads(json_data)
table_name = info.get('table_name', '').strip()
JSFUNC = """<span style='color:yellow;font-size:20px'>节点<span>
<span style='color:red;font-size:30px'>{line}<br>------<span>""" # { 图表的名字 line } 或者{ @[index] }
# line_path = 'mycharts/render/tabledata/charts_%s.html' % table_name.split('.')[1]
# 部署到apache服务器后需要使用绝对路径
line_path = os.path.join(
app_dir, 'render/tabledata/charts_%s.html' % table_name.split('.')[1])
print("line_path %s" % line_path)
if not os.path.exists(
line_path) or time.time() - os.path.getmtime(line_path) > 60:
table = get_object_or_404(TableData, table_name=table_name)
line_name = table.table_name
table_data = table.table_data
x_data = table_data.get("total_diff_rate").keys()
y_data = table_data.get("total_diff_rate").values()
column_diff_rate = table_data.get("column_diff_rate")
line = (
charts.Line(init_opts=opts.InitOpts(
theme=ThemeType.SHINE)).set_series_opts(
label_opts=opts.LabelOpts(formatter=JSFUNC,
position='right')).
set_global_opts(
# toolbox_opts=opts.ToolboxOpts(is_show=True, feature=opts.ToolBoxFeatureOpts(
# save_as_image=opts.ToolBoxFeatureSaveAsImageOpts(is_show=True))),
tooltip_opts=opts.TooltipOpts(is_show=True),
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),
),
title_opts=opts.TitleOpts(
title="差异比",
subtitle="单位1")).add_xaxis(xaxis_data=x_data).add_yaxis(
series_name=line_name,
y_axis=y_data,
symbol="circle",
itemstyle_opts=opts.ItemStyleOpts(border_color='#fff'),
markpoint_opts=opts.MarkPointOpts(
label_opts=opts.LabelOpts(color='red'),
data=[
opts.MarkPointItem(type_='max', name='最大值'),
opts.MarkPointItem(type_='min', name='最小值'),
opts.MarkLineItem(type_="average", name="平均值")
]),
markline_opts=opts.MarkLineItem(type_='average'),
is_symbol_show=True,
label_opts=opts.LabelOpts(is_show=False),
is_connect_nones=True))
for column, diff_data in column_diff_rate.items():
tmp = []
for day in x_data:
tmp.append(diff_data.get(day, None))
line.add_yaxis(
series_name=column,
y_axis=tmp,
symbol="circle",
# itemstyle_opts=opts.ItemStyleOpts(border_color='#fff'),
# markpoint_opts=opts.MarkPointOpts(
# label_opts=opts.LabelOpts(color='#fff'),
# data=[opts.MarkPointItem(type_='max', name='最大值'), opts.MarkPointItem(type_='min', name='最小值'),
# opts.MarkLineItem(type_="average", name="平均值")]
#
# ),
markline_opts=opts.MarkLineItem(type_='average'),
is_symbol_show=True,
label_opts=opts.LabelOpts(is_show=False),
is_connect_nones=True)
line.render(line_path)
chart = open(line_path).read()
return HttpResponse(chart)
line = pyc.Line(init_opts=opts.InitOpts(
theme=glbs.ThemeType.DARK, width='100%')).add_xaxis(list(
data.iloc[:, 0])).add_yaxis('Beijing AQI', list(
data.iloc[:, 1])).set_series_opts(
label_opts=opts.LabelOpts(is_show=False),
markline_opts=opts.MarkLineOpts(
label_opts=opts.LabelOpts(position='end'),
linestyle_opts=opts.LineStyleOpts(color='#333'),
data=[{
'yAxis': y
} for y in [50, 100, 150, 200, 300]])).set_global_opts(
title_opts=opts.TitleOpts(title='Beijing AQI',
pos_left='1%'),
legend_opts=opts.LegendOpts(is_show=False),
visualmap_opts=opts.VisualMapOpts(is_piecewise=True,
pos_top=50,
pos_right=10,
pieces=[{
'min':
0,
'max':
50,
'color':
'#93CE07'
}, {
'min':
50,
'max':
100,
'color':
'#FBDB0F'
}, {
'min':
100,
'max':
150,
'color':
'#FC7D02'
}, {
'min':
150,
'max':
200,
'color':
'#FD0100'
}, {
'min':
200,
'max':
300,
'color':
'#AA069F'
}, {
'min':
300,
'color':
'#AC3B2A'
}]),
datazoom_opts=[
opts.DataZoomOpts(start_value='2014-06-01',
range_start=None,
range_end=None),
opts.DataZoomOpts(type_='inside')
],
tooltip_opts=opts.TooltipOpts(trigger='axis'),
toolbox_opts=opts.ToolboxOpts(pos_left=None,
pos_right=10,
feature={
'dataZoom': {},
'restore': {},
'saveAsImage': {}
}),
yaxis_opts=opts.AxisOpts(
splitline_opts=opts.SplitLineOpts(is_show=True)))
line = (c.Line().add_xaxis(x_data).add_yaxis(
'pv', pv, label_opts=opts.LabelOpts(is_show=False)).add_yaxis(
'uv',
yaxis_index=1,
y_axis=uv,
label_opts=opts.LabelOpts(is_show=False)).extend_axis(
yaxis=opts.AxisOpts(name='uv',
type_='value',
min_=0,
max_=1.6,
interval=.4,
axislabel_opts=opts.LabelOpts(
formatter='{value}万人'))).
set_global_opts(
tooltip_opts=opts.TooltipOpts(is_show=True,
trigger="axis",
axis_pointer_type="cross"),
xaxis_opts=opts.AxisOpts(
type_="category",
axispointer_opts=opts.AxisPointerOpts(is_show=True,
type_="shadow"),
),
yaxis_opts=opts.AxisOpts(
name="pv",
type_="value",
min_=0,
max_=100,
interval=20,
axislabel_opts=opts.LabelOpts(formatter="{value} 万次"),
axistick_opts=opts.AxisTickOpts(is_show=True),
splitline_opts=opts.SplitLineOpts(is_show=True),
),
title_opts=opts.TitleOpts(title="pv与uv趋势图"),
))