def grid_mutil_yaxis() -> Grid:
x_data = ["{}月".format(i) for i in range(1, 13)]
bar = (Bar().add_xaxis(x_data).add_yaxis(
"蒸发量",
[2.0, 4.9, 7.0, 23.2, 25.6, 76.7, 135.6, 162.2, 32.6, 20.0, 6.4, 3.3],
yaxis_index=0,
color="#d14a61",
).add_yaxis(
"降水量",
[2.6, 5.9, 9.0, 26.4, 28.7, 70.7, 175.6, 182.2, 48.7, 18.8, 6.0, 2.3],
yaxis_index=1,
color="#5793f3",
).extend_axis(yaxis=opts.AxisOpts(
name="蒸发量",
type_="value",
min_=0,
max_=250,
position="right",
axisline_opts=opts.AxisLineOpts(linestyle_opts=opts.LineStyleOpts(
color="#d14a61")),
axislabel_opts=opts.LabelOpts(formatter="{value} ml"),
)).extend_axis(yaxis=opts.AxisOpts(
type_="value",
name="温度",
min_=0,
max_=25,
position="left",
axisline_opts=opts.AxisLineOpts(linestyle_opts=opts.LineStyleOpts(
color="#675bba")),
axislabel_opts=opts.LabelOpts(formatter="{value} °C"),
splitline_opts=opts.SplitLineOpts(
is_show=True, linestyle_opts=opts.LineStyleOpts(opacity=1)),
)).set_global_opts(
yaxis_opts=opts.AxisOpts(
name="降水量",
min_=0,
max_=250,
position="right",
offset=80,
axisline_opts=opts.AxisLineOpts(linestyle_opts=opts.LineStyleOpts(
color="#5793f3")),
axislabel_opts=opts.LabelOpts(formatter="{value} ml"),
),
title_opts=opts.TitleOpts(title="Grid-多 Y 轴示例"),
tooltip_opts=opts.TooltipOpts(trigger="axis",
axis_pointer_type="cross"),
))
line = (Line().add_xaxis(x_data).add_yaxis(
"平均温度",
[2.0, 2.2, 3.3, 4.5, 6.3, 10.2, 20.3, 23.4, 23.0, 16.5, 12.0, 6.2],
yaxis_index=2,
color="#675bba",
label_opts=opts.LabelOpts(is_show=False),
))
bar.overlap(line)
return Grid().add(bar,
opts.GridOpts(pos_left="5%", pos_right="20%"),
is_control_axis_index=True)
def draw_tendency(month, day):
dates = ['1-%d' % i for i in range(16, day + 1)]
v0 = [4, 17, 59, 78, 92, 149, 131, 259, 444, 688, 769, 1771, 1459, 1576]
v1 = [4, 17, 59, 77, 72, 105, 69, 105, 180, 323, 371, 1291, 840, 1032]
c = (Line().add_xaxis(dates).add_yaxis(
"全国新增确诊病例",
v0,
is_smooth=True,
linestyle_opts=opts.LineStyleOpts(width=4, color='#B44038'),
itemstyle_opts=opts.ItemStyleOpts(
color='#B44038', border_color="#B44038",
border_width=5)).add_yaxis(
"湖北新增确诊病例",
v1,
is_smooth=True,
linestyle_opts=opts.LineStyleOpts(width=2, color='6FA0A7'),
label_opts=opts.LabelOpts(position='bottom'),
itemstyle_opts=opts.ItemStyleOpts(
color='#6FA0A7', border_color="#6FA0A7",
border_width=3)).set_global_opts(
title_opts=opts.TitleOpts(title=""),
yaxis_opts=opts.AxisOpts(
type_="log",
name="y",
splitline_opts=opts.SplitLineOpts(is_show=True),
is_scale=True,
axisline_opts=opts.AxisLineOpts(is_show=False))))
c.render('charts/%d%d-新增病例趋势图.html' % (month, day))
return c
def draw_line2(title, x_axis, y_name1, y_data1, y_name2, y_data2):
c = (Line().add_xaxis(xaxis_data=x_axis).add_yaxis(
series_name=y_name1,
y_axis=y_data1,
symbol="circle",
symbol_size=10,
is_symbol_show=True,
label_opts=opts.LabelOpts(is_show=True),
linestyle_opts=opts.LineStyleOpts(width=3)).add_yaxis(
series_name=y_name2,
y_axis=y_data2,
symbol="circle",
symbol_size=10,
is_symbol_show=True,
label_opts=opts.LabelOpts(is_show=True),
linestyle_opts=opts.LineStyleOpts(width=3)).set_global_opts(
tooltip_opts=opts.TooltipOpts(is_show=False),
xaxis_opts=opts.AxisOpts(
type_="category",
axislabel_opts=opts.LabelOpts(rotate=-30),
),
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=title),
))
return c
def line_smooth(index, data, name) -> Line:
c = (
Line(init_opts=opts.InitOpts(
theme=ThemeType.ROMANTIC,
# width="100%",
height="500px",
)).add_xaxis(index).add_yaxis(
"Sentiment value",
data,
is_smooth=True,
is_connect_nones=True,
yaxis_index=0).extend_axis(yaxis=opts.AxisOpts(
name="Stock K-line",
is_scale=True,
position="right",
axisline_opts=opts.AxisLineOpts(
linestyle_opts=opts.LineStyleOpts(color="#675bba")),
splitline_opts=opts.SplitLineOpts(
is_show=True, linestyle_opts=opts.LineStyleOpts(
opacity=1)),
)).set_global_opts(
xaxis_opts=opts.AxisOpts(is_scale=True),
yaxis_opts=opts.AxisOpts(
name="Sentiment Value",
is_scale=True,
splitarea_opts=opts.SplitAreaOpts(
is_show=True,
areastyle_opts=opts.AreaStyleOpts(opacity=1))),
datazoom_opts=[opts.DataZoomOpts(pos_bottom="-2%")],
title_opts=opts.TitleOpts(title="Sentiment Analysis : " +
name),
tooltip_opts=opts.TooltipOpts(trigger="axis",
axis_pointer_type="line"),
))
return c
def uv_line_chart() -> Line:
"""
UV折线图，包括总 UV、新用户 UV、注册 UV
"""
xaxis = get_xaxis_days()
uv_all_redis_keys = [settings.REDIS_UV_ALL_KEY % day for day in xaxis]
uv_new_redis_keys = [settings.REDIS_UV_NEW_KEY % day for day in xaxis]
uv_reg_redis_keys = [settings.REDIS_REG_KEY % day for day in xaxis]
uv_all = R.mget(*uv_all_redis_keys)
uv_new = R.mget(*uv_new_redis_keys)
uv_reg = R.mget(*uv_reg_redis_keys)
line = (Line().add_xaxis(xaxis).add_yaxis(
"总用户数（访问设备）", uv_all, is_connect_nones=True, is_smooth=True).add_yaxis(
"新用户数（一周未访问）", uv_new, is_connect_nones=True,
is_smooth=True).add_yaxis(
"注册用户数", uv_reg, is_connect_nones=True,
is_smooth=True).set_global_opts(
title_opts=options.TitleOpts(title="用户数走势"),
yaxis_opts=options.AxisOpts(
is_scale=True,
splitline_opts=options.SplitLineOpts(is_show=True)),
tooltip_opts=options.TooltipOpts(trigger='axis'),
).dump_options())
return line
def api_profile_line_chart() -> Line:
"""
接口平均耗时
:return:
"""
xaxis = get_xaxis_days(days=10)
apis = list(filter(lambda x: x, R.smembers(settings.REDIS_API_KEY)))
line = (Line().add_xaxis(xaxis).set_global_opts(
title_opts=options.TitleOpts(title="API 耗时走势"),
yaxis_opts=options.AxisOpts(
is_scale=True, splitline_opts=options.SplitLineOpts(is_show=True)),
tooltip_opts=options.TooltipOpts(trigger='axis'),
))
for api in apis:
if api in get_profile_apis():
api_redis_keys = [
settings.REDIS_API_AVG_KEY % (api, day) for day in xaxis
]
api_profile = R.mget(*api_redis_keys)
line.add_yaxis(api,
api_profile,
is_connect_nones=True,
is_smooth=True,
label_opts=options.LabelOpts(is_show=False))
return line.dump_options()
def bar(df, datatype='ABS', show_label=False, label_rotate=90) -> Bar:
axislabel_format = '{value}'
if datatype in ['SHARE', 'GR']:
df = df.multiply(100).round(2)
axislabel_format = '{value}%'
if df.empty is False:
bar = (
Bar()
.add_xaxis(df.index.tolist())
)
for i, item in enumerate(df.columns):
bar.add_yaxis(item,
df[item].values.tolist(),
label_opts=opts.LabelOpts(is_show=show_label),
)
bar.set_global_opts(
# title_opts=opts.TitleOpts(title='Trend', pos_left='center'),
legend_opts=opts.LegendOpts(pos_top='5%', pos_left='10%', pos_right='60%'),
toolbox_opts=opts.ToolboxOpts(is_show=True),
tooltip_opts=opts.TooltipOpts(trigger='axis',
axis_pointer_type='cross',
),
xaxis_opts=opts.AxisOpts(type_='category',
boundary_gap=True,
axislabel_opts=opts.LabelOpts(rotate=label_rotate),
splitline_opts=opts.SplitLineOpts(is_show=False,
linestyle_opts=opts.LineStyleOpts(
type_='dotted',
opacity=0.5,
)
)
),
yaxis_opts=opts.AxisOpts(type_="value",
axislabel_opts=opts.LabelOpts(formatter=axislabel_format),
# axistick_opts=opts.AxisTickOpts(is_show=True),
splitline_opts=opts.SplitLineOpts(is_show=True,
linestyle_opts=opts.LineStyleOpts(
type_='dotted',
opacity=0.5,
)
)
),
)
else:
bar = (Bar())
return bar
def books_pubdate_scatter(id, num) -> Scatter:
(time,times,num) = books_pubdate(id, num)
if time == 0:
return 0
x_data = list(map(str, times.keys()))
y_data = list(map(str, times.values()))
c = (
Scatter() # init_opts=opts.InitOpts(width="1600px", height="1000px")
.add_xaxis(xaxis_data=x_data)
.add_yaxis(
series_name="图书数",
y_axis=y_data,
symbol_size=20,
label_opts=opts.LabelOpts(is_show=False),
)
.set_series_opts()
.set_global_opts(
title_opts=opts.TitleOpts(title="图书发行趋势", subtitle="数据量：" + str(num),),
xaxis_opts=opts.AxisOpts(
splitline_opts=opts.SplitLineOpts(is_show=True),
name="图书发行时间"
),
yaxis_opts=opts.AxisOpts(
# type_="value",
name="图书数量",
name_gap=50,
name_rotate=90,
name_location="center",
axistick_opts=opts.AxisTickOpts(is_show=True),
splitline_opts=opts.SplitLineOpts(is_show=True),
),
tooltip_opts=opts.TooltipOpts(is_show=True),
visualmap_opts=opts.VisualMapOpts(type_="size", max_=5, min_=1),
toolbox_opts=opts.ToolboxOpts(is_show=True,pos_left="95%",
feature={
"dataZoom": {"yAxisIndex": "none"},
"dataView": {},
"restore": {},
"saveAsImage": {},
},
),
)
.dump_options_with_quotes()
)
return c
def s_4():
with open(r'pro.csv', 'r') as f:
reader = csv.reader(f)
result = list(reader)
pro_list = [i[0] for i in result]
total_list = [float(i[1]) for i in result]
p = (EffectScatter(init_opts=opts.InitOpts(
width='1200px', height='800px')).add_xaxis(pro_list).add_yaxis(
"交易额", total_list,
label_opts=opts.LabelOpts(is_show=False)).set_global_opts(
title_opts=opts.TitleOpts(title="本年度交易额省份排名分析"),
xaxis_opts=opts.AxisOpts(splitline_opts=opts.SplitLineOpts(
is_show=True)),
yaxis_opts=opts.AxisOpts(splitline_opts=opts.SplitLineOpts(
is_show=True)),
))
return p
def k_line(self):
# K线主图
print(self.ds.code)
k_line = (Kline(init_opts=INIT_OPTS).add_xaxis(
xaxis_data=self.datetime).add_yaxis(
series_name=self.code,
y_axis=self.ohlc,
itemstyle_opts=opts.ItemStyleOpts(
color="#ef232a",
color0="#14b143",
border_color="#ef232a",
border_color0="#14b143",
),
markpoint_opts=opts.MarkPointOpts(data=[
opts.MarkPointItem(type_="max", name="最大值"),
opts.MarkPointItem(type_="min", name="最小值"),
]),
).set_global_opts(
title_opts=opts.TitleOpts(title=self.code, pos_left="0"),
xaxis_opts=opts.AxisOpts(
type_="category",
is_scale=True,
boundary_gap=False,
axisline_opts=opts.AxisLineOpts(is_on_zero=False),
splitline_opts=opts.SplitLineOpts(is_show=False),
split_number=20,
min_="dataMin",
max_="dataMax",
),
yaxis_opts=opts.AxisOpts(
is_scale=True,
splitline_opts=opts.SplitLineOpts(is_show=True)),
tooltip_opts=opts.TooltipOpts(trigger="axis",
axis_pointer_type="line"),
datazoom_opts=[
opts.DataZoomOpts(is_show=True,
type_="inside",
range_start=self.range_start,
range_end=100),
opts.DataZoomOpts(is_show=True,
pos_bottom="-1%",
range_start=self.range_start,
range_end=100),
],
))
return k_line
def draw_tendency(month, day):
dates = ['1-%d' % i for i in range(22, 31 + 1)]
dates.extend(['2-%02d' % i for i in range(1, day)])
v0 = [
131, 259, 444, 688, 769, 1771, 1459, 1737, 1982, 2102, 2590, 2829,
3235, 3887, 3143, 3399, 2656, 3062, 2478, 2015, 15152, 5090, 2641,
2009, 2051, 1886, 1749, 385
]
v1 = [
69, 105, 180, 323, 371, 1291, 840, 1032, 1220, 1347, 1921, 2103, 2345,
3156, 2447, 2841, 2147, 2618, 2097, 1638, 14840, 4823, 2420, 1843,
1933, 1807, 1693, 349
]
v2 = [v0[i] - v1[i] for i in range(len(v0))]
print(v2)
c = (Line(init_opts=opts.InitOpts(
width='1000px', height='500px')).add_xaxis(dates).add_yaxis(
"全国新增确诊病例",
v0,
is_smooth=True,
linestyle_opts=opts.LineStyleOpts(width=4, color='#B44038'),
itemstyle_opts=opts.ItemStyleOpts(
color='#B44038', border_color="#B44038",
border_width=5)).add_yaxis(
"湖北新增确诊病例",
v1,
is_smooth=True,
linestyle_opts=opts.LineStyleOpts(width=2,
color='#4E87ED'),
label_opts=opts.LabelOpts(position='bottom'),
itemstyle_opts=opts.ItemStyleOpts(
color='#4E87ED',
border_color="#4E87ED",
border_width=3)).add_yaxis(
"其他省份新增病例",
v2,
is_smooth=True,
linestyle_opts=opts.LineStyleOpts(width=2,
color='#F1A846'),
label_opts=opts.LabelOpts(position='bottom'),
itemstyle_opts=opts.ItemStyleOpts(
color='#F1A846',
border_color="#F1A846",
border_width=3)).set_global_opts(
title_opts=opts.TitleOpts(title=""),
yaxis_opts=opts.AxisOpts(
max_=16000,
min_=10,
type_="log",
name="y",
splitline_opts=opts.SplitLineOpts(
is_show=True),
is_scale=True,
axisline_opts=opts.AxisLineOpts(
is_show=False))))
root = 'html-charts/%d%d' % (month, day)
create_dir(root)
c.render('%s/新增病例趋势图.html' % root)
def china_daily_map(wb):
ws_china_confirmed = wb['中国每日累计确诊数据']
ws_china_surplus = wb['中国每日现有确诊数据']
ws_china_crued = wb['中国每日累计治愈数据']
ws_china_died = wb['中国每日累计死亡数据']
ws_china_confirmed.delete_rows(1)
ws_china_surplus.delete_rows(1)
ws_china_crued.delete_rows(1)
ws_china_died.delete_rows(1)
x_date = []
y_china_confirmed = []
y_china_surplus = []
y_china_crued = []
y_china_died = []
for china_confirmed in ws_china_confirmed.values:
y_china_confirmed.append(china_confirmed[1])
for china_surplus in ws_china_surplus.values:
y_china_surplus.append(china_surplus[1])
for china_crued in ws_china_crued.values:
x_date.append(china_crued[0])
y_china_crued.append(china_crued[1])
for china_died in ws_china_died.values:
y_china_died.append(china_died[1])
x_date = clean_date(x_date)
fi_map = (Line(init_opts=opts.InitOpts(height='420px')).add_xaxis(
xaxis_data=x_date).add_yaxis(
series_name='中国累计确诊人数',
y_axis=y_china_confirmed,
label_opts=opts.LabelOpts(is_show=False),
).add_xaxis(xaxis_data=x_date).add_yaxis(
series_name='中国现有确诊人数',
y_axis=y_china_surplus,
label_opts=opts.LabelOpts(is_show=False),
).add_yaxis(
series_name='中国累计治愈人数',
y_axis=y_china_crued,
label_opts=opts.LabelOpts(is_show=False),
).add_yaxis(
series_name='中国累计死亡人数',
y_axis=y_china_died,
label_opts=opts.LabelOpts(is_show=False),
).set_global_opts(
title_opts=opts.TitleOpts(title='中国COVID-19每日数据走势'),
legend_opts=opts.LegendOpts(pos_bottom="bottom",
orient='horizontal'),
tooltip_opts=opts.TooltipOpts(trigger='axis'),
yaxis_opts=opts.AxisOpts(
type_='value',
axistick_opts=opts.AxisTickOpts(is_show=True),
splitline_opts=opts.SplitLineOpts(is_show=True),
),
xaxis_opts=opts.AxisOpts(type_='category', boundary_gap=False),
).dump_options_with_quotes())
return fi_map
def foreign_daily_map(wb):
ws_foreign_confirmed = wb['境外每日累计确诊数据']
ws_foreign_surplus = wb['境外每日现有确诊数据']
ws_foreign_crued = wb['境外每日累计治愈数据']
ws_foreign_died = wb['境外每日累计死亡数据']
ws_foreign_confirmed.delete_rows(1)
ws_foreign_surplus.delete_rows(1)
ws_foreign_crued.delete_rows(1)
ws_foreign_died.delete_rows(1)
x_date = [] # 日期
y_foreign_confirmed = [] # 累计确诊
y_foreign_surplus = []
y_foreign_crued = [] # 累计治愈
y_foreign_died = [] # 累计死亡
for foreign_confirmed in ws_foreign_confirmed.values:
y_foreign_confirmed.append(foreign_confirmed[1])
for foreign_surplus in ws_foreign_surplus.values:
y_foreign_surplus.append(foreign_surplus[1])
for foreign_crued in ws_foreign_crued.values:
x_date.append(foreign_crued[0])
y_foreign_crued.append(foreign_crued[1])
for foreign_died in ws_foreign_died.values:
y_foreign_died.append(foreign_died[1])
x_date = clean_date(x_date)
fte_map = (Line(init_opts=opts.InitOpts(height='420px')).add_xaxis(
xaxis_data=x_date).add_yaxis(
series_name="境外累计确诊人数",
y_axis=y_foreign_confirmed,
label_opts=opts.LabelOpts(is_show=False),
).add_xaxis(xaxis_data=x_date).add_yaxis(
series_name="境外现有确诊人数",
y_axis=y_foreign_surplus,
label_opts=opts.LabelOpts(is_show=False),
).add_yaxis(
series_name="境外累计治愈人数",
y_axis=y_foreign_crued,
label_opts=opts.LabelOpts(is_show=False),
).add_yaxis(
series_name="境外累计死亡人数",
y_axis=y_foreign_died,
label_opts=opts.LabelOpts(is_show=False),
).set_global_opts(
title_opts=opts.TitleOpts(title="境外COVID-19每日数据走势"),
legend_opts=opts.LegendOpts(pos_bottom="bottom",
orient='horizontal'),
tooltip_opts=opts.TooltipOpts(trigger="axis"),
yaxis_opts=opts.AxisOpts(
type_="value",
axistick_opts=opts.AxisTickOpts(is_show=True),
splitline_opts=opts.SplitLineOpts(is_show=True),
),
xaxis_opts=opts.AxisOpts(type_="category", boundary_gap=False),
).dump_options_with_quotes())
return fte_map
def echarts_line(df, datatype="ABS"):
axislabel_format = "{value}"
if datatype in ["SHARE", "GR"]:
df = df.multiply(100).round(2)
axislabel_format = "{value}%"
if df.empty is False:
line = (
Line() # init_opts=opts.InitOpts(width="1200px", height="700px")
.add_xaxis(df.index.strftime("%Y-%m").tolist())
.set_global_opts(
# title_opts=opts.TitleOpts(title='Trend', pos_left='center'),
legend_opts=opts.LegendOpts(pos_top="5%", pos_left="10%", pos_right="60%"),
toolbox_opts=opts.ToolboxOpts(is_show=True),
tooltip_opts=opts.TooltipOpts(trigger="axis", axis_pointer_type="cross",),
xaxis_opts=opts.AxisOpts(
type_="category",
boundary_gap=False,
splitline_opts=opts.SplitLineOpts(
is_show=True, linestyle_opts=opts.LineStyleOpts(type_="dotted", opacity=0.5,),
),
),
yaxis_opts=opts.AxisOpts(
type_="value",
axislabel_opts=opts.LabelOpts(formatter=axislabel_format),
# axistick_opts=opts.AxisTickOpts(is_show=True),
splitline_opts=opts.SplitLineOpts(
is_show=True, linestyle_opts=opts.LineStyleOpts(type_="dotted", opacity=0.5,),
),
),
)
)
for i, item in enumerate(df.columns):
line.add_yaxis(
item,
df[item],
# symbol='circle',
symbol_size=8,
label_opts=opts.LabelOpts(is_show=False),
linestyle_opts=opts.LineStyleOpts(width=3),
itemstyle_opts=opts.ItemStyleOpts(border_width=1, border_color="", border_color0="white"),
)
else:
line = Line()
return line
def line_base():
c = (
Scatter().add_xaxis(Faker.choose()).add_yaxis(
"商家A", Faker.values()).set_global_opts(
# 显示标题
title_opts=opts.TitleOpts(title="Scatter-基本示例"),
# 显示网格线
xaxis_opts=opts.AxisOpts(splitline_opts=opts.SplitLineOpts(
is_show=True)),
yaxis_opts=opts.AxisOpts(splitline_opts=opts.SplitLineOpts(
is_show=True)),
# 显示可视化图形条
visualmap_opts=opts.VisualMapOpts(max_=150),
))
# 绘制图片
pic = c.render()
return pic
def p_kdj_macd(self, echarts_data, ktype='d'):
"""
p_kdj_macd的百分比图
"""
bar = (
Bar()
.add_xaxis(xaxis_data=echarts_data['date'])
.add_yaxis(
series_name="P_MACD_KDJ",
y_axis=echarts_data['p_kdj_macd_%s' % ktype],
xaxis_index=2,
yaxis_index=2,
label_opts=opts.LabelOpts(is_show=False),
itemstyle_opts=opts.ItemStyleOpts(
color=JsCode(
"""
function(params) {
var colorList;
if (params.data >= 0) {
colorList = '#ef232a';
} else {
colorList = '#14b143';
}
return colorList;
}
"""
)
),
)
.set_global_opts(
xaxis_opts=opts.AxisOpts(
type_="category",
grid_index=2,
axislabel_opts=opts.LabelOpts(is_show=False),
# axisline_opts=opts.AxisLineOpts(is_on_zero=False),
axistick_opts=opts.AxisTickOpts(is_show=False), # 不显示刻度
# splitline_opts=opts.SplitLineOpts(is_show=False), # 不显示刻度
# axislabel_opts=opts.LabelOpts(is_show=False),
# split_number=20,
),
yaxis_opts=opts.AxisOpts(
grid_index=2,
split_number=4,
axisline_opts=opts.AxisLineOpts(is_on_zero=False),
axistick_opts=opts.AxisTickOpts(is_show=False),
splitline_opts=opts.SplitLineOpts(is_show=False),
axislabel_opts=opts.LabelOpts(is_show=True),
),
legend_opts=opts.LegendOpts(is_show=False),
# title_opts=opts.TitleOpts(subtitle="KDJ_MACD"),
title_opts=opts.TitleOpts(subtitle="P_KDJ_M_%s" % ktype, pos_top="52%"), # 标题
# legend_opts=opts.LegendOpts(pos_top="45%"), # 图例位置
)
)
return bar
def get_scatter(data_dict, title, save_path):
scatter = Scatter()
for key, value_list in data_dict.items():
nparray = np.array(value_list)
scatter.add_xaxis(nparray[:, 0])
scatter.add_yaxis(key, nparray[:, 1])
scatter.set_global_opts(
title_opts=opts.TitleOpts(title=""),
xaxis_opts=opts.AxisOpts(splitline_opts=opts.SplitLineOpts(
is_show=True)),
yaxis_opts=opts.AxisOpts(splitline_opts=opts.SplitLineOpts(
is_show=True)),
)
scatter.width = "1600px"
scatter.height = "650px"
scatter.render("data/analysis/{0}/{1}.html".format(save_path, title))
def show_scatter():
scatter = (
Scatter(init_opts=opts.InitOpts(width="1600px", height="1000px")).
add_xaxis(xaxis_data=co_friend_count).add_yaxis(
series_name="Covid",
y_axis=covid_polarity,
symbol="triangle",
symbol_size=15,
label_opts=opts.LabelOpts(is_show=False),
).add_xaxis(xaxis_data=cr_friend_count).add_yaxis(
series_name="Crime",
y_axis=crime_polarity,
symbol="circle",
symbol_size=15,
label_opts=opts.LabelOpts(is_show=False),
).set_series_opts().set_global_opts(
title_opts=opts.TitleOpts(
title="Twitter Friend Count VS Polarity"),
xaxis_opts=opts.AxisOpts(
name='Friend Count',
name_location='middle',
name_gap=20,
type_="value",
splitline_opts=opts.SplitLineOpts(is_show=True)),
yaxis_opts=opts.AxisOpts(
name='Polarity',
name_location='middle',
name_gap=20,
type_="value",
axistick_opts=opts.AxisTickOpts(is_show=True),
splitline_opts=opts.SplitLineOpts(is_show=True),
),
# tooltip_opts=opts.TooltipOpts(is_show=False),
toolbox_opts=opts.ToolboxOpts(),
visualmap_opts=opts.VisualMapOpts(
type_="color",
max_=1,
min_=-1,
range_text=['Positive', 'Negative'],
),
))
return scatter
def get_volome(self, xdatas, vols, kdatas):
bar = (
Bar(init_opts=opts.InitOpts())
.add_xaxis(xaxis_data=xdatas)
.add_yaxis(
series_name="Volume",
yaxis_data=[
[i, vols[i], 1 if kdatas[i][0] < kdatas[i][1] else -1]
for i in range(len(kdatas))
],
# yaxis_data = vols,
xaxis_index=1,
yaxis_index=1,
label_opts=opts.LabelOpts(is_show=False)
)
.set_global_opts(
xaxis_opts=opts.AxisOpts(
type_="category",
is_scale=True,
grid_index=1,
boundary_gap=False,
axisline_opts=opts.AxisLineOpts(is_on_zero=False),
axistick_opts=opts.AxisTickOpts(is_show=False),
splitline_opts=opts.SplitLineOpts(is_show=False),
axislabel_opts=opts.LabelOpts(is_show=False),
split_number=20,
min_="dataMin",
max_="dataMax",
),
yaxis_opts=opts.AxisOpts(
grid_index=1,
is_scale=True,
split_number=2,
axislabel_opts=opts.LabelOpts(is_show=False),
axisline_opts=opts.AxisLineOpts(is_show=True),
axistick_opts=opts.AxisTickOpts(is_show=True),
splitline_opts=opts.SplitLineOpts(is_show=True),
),
legend_opts=opts.LegendOpts(is_show=False),
)
)
return bar
def bar_with_custom_splitline():
bar = Bar(
init_opts=opts.InitOpts(theme='light', width='1000px', height='600px'))
bar.add_xaxis(Faker.choose())
bar.add_yaxis('A', Faker.values())
bar.add_yaxis('B', Faker.values())
# x,y轴翻转
bar.set_global_opts(yaxis_opts=opts.AxisOpts(
splitline_opts=opts.SplitLineOpts(
is_show=True, linestyle_opts=opts.LineStyleOpts(type_='dotted'))))
return bar
def get(self, request, name='治愈人数'):
from pyecharts.globals import CurrentConfig
from pyecharts import options as opts
from pyecharts.charts import Bar
CurrentConfig.ONLINE_HOST = "https://cdn.jsdelivr.net/gh/pyecharts/pyecharts-assets@latest/assets/"
data = ReadCsv(name).dump_as_json()
c = (Bar(init_opts=opts.InitOpts(
renderer="svg", width='400px', height='277px')).add_xaxis(
data['labels']).add_yaxis(
"人数",
data['data'],
label_opts=opts.LabelOpts(
is_show=False, color='white')).set_series_opts(
itemstyle_opts={
"normal": {
"barBorderRadius": [25, 25, 25, 25],
"shadowColor": "#2f89cf",
"color": "#2f89cf"
}
}).set_global_opts(
datazoom_opts=opts.DataZoomOpts(
type_="inside"),
tooltip_opts=opts.TooltipOpts(
is_show=True,
trigger_on='mousemove|click',
axis_pointer_type='shadow',
trigger='axis'),
xaxis_opts=opts.AxisOpts(
is_show=True,
axislabel_opts=opts.LabelOpts(
color='rgba(255,255,255,.6)'),
axisline_opts=opts.AxisLineOpts(
is_show=True,
linestyle_opts=opts.LineStyleOpts(
color='rgba(255,255,255,.1)',
type_='solid',
width=1))),
yaxis_opts=opts.AxisOpts(
is_show=True,
axislabel_opts=opts.LabelOpts(
color='rgba(255,255,255,.6)'),
axisline_opts=opts.AxisLineOpts(
is_show=True,
linestyle_opts=opts.LineStyleOpts(
color='rgba(255,255,255,.1)',
type_='solid',
width=1)),
splitline_opts=opts.SplitLineOpts(
is_show=True,
linestyle_opts=opts.LineStyleOpts(
color='rgba(255,255,255,.1)'))),
legend_opts=opts.LegendOpts(is_show=False),
))
return Response(json.loads(c.dump_options()))
def paintCandlestick(bar_series, sample):
x_data = ["2017-10-24", "2017-10-25", "2017-10-26", "2017-10-27"]
y_data = [[20, 30, 10, 35], [40, 35, 30, 55], [33, 38, 33, 40],
[40, 40, 32, 42]]
(Candlestick(init_opts=opts.InitOpts(width="1440px", height="720px")).
add_xaxis(xaxis_data=x_data).add_yaxis(
series_name="", y_axis=y_data).set_series_opts().set_global_opts(
yaxis_opts=opts.AxisOpts(splitline_opts=opts.SplitLineOpts(
is_show=True, linestyle_opts=opts.LineStyleOpts(
width=1)))).render("basic_candlestick.html"))
def grid_mutil_yaxis(data, info):
"""折线图与柱状图"""
try:
x_data = data[0]
bar = (Bar().add_xaxis(x_data).add_yaxis(
info[0],
list(map(lambda x: round(x, 1), data[1])),
yaxis_index=0,
color="#5793f3",
).extend_axis(yaxis=opts.AxisOpts(
name=info[1],
type_="value",
min_=0,
max_=max(data[2]) * 1.2,
position="right",
axisline_opts=opts.AxisLineOpts(linestyle_opts=opts.LineStyleOpts(
color="#d14a61")),
axislabel_opts=opts.LabelOpts(formatter="{value}"),
splitline_opts=opts.SplitLineOpts(
is_show=True, linestyle_opts=opts.LineStyleOpts(opacity=1)),
)).set_global_opts(
xaxis_opts=opts.AxisOpts(type_="category",
axislabel_opts=opts.LabelOpts(
rotate=30,
interval=0,
font_size=10,
font_weight="bold")),
yaxis_opts=opts.AxisOpts(
name=info[0],
max_=8,
position="left",
axisline_opts=opts.AxisLineOpts(
linestyle_opts=opts.LineStyleOpts(color="#5793f3")),
axislabel_opts=opts.LabelOpts(formatter="{value}"),
),
title_opts=opts.TitleOpts(title="生育率与GDP增长率对比图"),
tooltip_opts=opts.TooltipOpts(trigger="axis",
axis_pointer_type="cross"),
))
line = (Line().add_xaxis(x_data).add_yaxis(
"生育率",
data[2],
yaxis_index=1,
color="#675bba",
label_opts=opts.LabelOpts(is_show=False),
linestyle_opts=opts.LineStyleOpts(width=4, opacity=1)))
bar.overlap(line)
log.info("折线图与柱状图创建成功")
return Grid().add(bar,
opts.GridOpts(pos_left="5%", pos_right="20%"),
is_control_axis_index=True)
except Exception as ex:
log.error("折线图与柱状图创建失败: {0}".format(str(ex)))
return None
def line_bar_draw(data,html_name):
x_data = data.index.tolist()
bars = data.iloc[:,1].values.tolist()
change = data.iloc[:,0].values.tolist()
bar = (
Bar(init_opts=opts.InitOpts(width="1200px", height="700px"))
.add_xaxis(xaxis_data=x_data)
.add_yaxis(
series_name="Stock_Price",
yaxis_data=bars,
label_opts=opts.LabelOpts(is_show=False),
)
.extend_axis(
yaxis=opts.AxisOpts(
name="Value_Series",
type_="value",
)
)
.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="Stock_Price",
type_="value",
axistick_opts=opts.AxisTickOpts(is_show=True),
splitline_opts=opts.SplitLineOpts(is_show=True),
axislabel_opts=opts.LabelOpts(formatter="￥ {value}"),
),
datazoom_opts=[
opts.DataZoomOpts(range_start=0, range_end=100),
opts.DataZoomOpts(type_="inside", range_start=0, range_end=100),
],
)
)
line = (
Line()
.add_xaxis(xaxis_data=x_data)
.add_yaxis(
series_name="Value_Series",
yaxis_index=1,
y_axis=change,
label_opts=opts.LabelOpts(is_show=False),
)
)
bar.overlap(line).render('./output/'+html_name+'.html')
def get_line_charts():
line_chart_1 = (
Line(init_opts=opts.InitOpts(width='500px', height='250px'))
.add_xaxis(time_list)
.add_yaxis(series_name="迁出指数",
y_axis=hubei_out_data,
# symbol="emptyCircle",
is_symbol_show=True,
is_smooth=True, )
.add_yaxis(series_name="迁入指数",
y_axis=hubei_in_data,
# symbol="emptyCircle",
is_symbol_show=True,
is_smooth=True, )
.set_global_opts(
title_opts=opts.TitleOpts(title='01-01至03-10湖北省迁徙指数',
pos_left='72%', pos_top='15%'),
tooltip_opts=opts.TooltipOpts(trigger="axis", axis_pointer_type='shadow'),
legend_opts=opts.LegendOpts(is_show=True ,orient='horizontal', pos_left='75%', pos_top='20%'),
yaxis_opts=opts.AxisOpts(
name='迁徙指数',
type_='value',
axistick_opts=opts.AxisTickOpts(is_show=True),
splitline_opts=opts.SplitLineOpts(is_show=True),
)
)
.set_series_opts(label_opts=opts.LabelOpts(is_show=False), splitline_opts=opts.SplitLineOpts(is_show=True))
)
wordcloud = (
WordCloud()
.add(series_name="城市", data_pair=get_out_cities(), word_size_range=[10, 66],
pos_left='-8%', pos_top='10%', shape='triangle-forward')
.set_global_opts(
title_opts=opts.TitleOpts(
title="1-21湖北省迁出热门城市", pos_left='20%', pos_top='15%'
),
tooltip_opts=opts.TooltipOpts(is_show=True),
)
)
grid_chart = (
Grid(init_opts=opts.InitOpts(width='1500px', height='700px'))
.add(
line_chart_1,
grid_opts=opts.GridOpts(
pos_left='65%', pos_right='80', pos_top='30%', pos_bottom='30%'
)
)
.add(wordcloud, grid_opts=opts.GridOpts(pos_left="20%", pos_top="10%"))
)
return grid_chart
def bar1_line1_with_two_axis(x, y_bar, y_line, y_bar_name, y_line_name, sub_title, index, title_left, titel_top):
bar = (
Bar(init_opts=opts.InitOpts(width='600px', height='300px'))
.add_xaxis(x)
.add_yaxis(
y_bar_name,
y_bar,
xaxis_index=index, # 需要变动的，图层中第几条X轴
yaxis_index=index * 2, # 需要变动的，，图层中第几条Y轴
color="#5793f3",
)
.set_global_opts(
yaxis_opts=opts.AxisOpts(
name=y_bar_name,
min_=0,
max_=25000,
position="right",
grid_index=index, # 需要变动的 y轴
axisline_opts=opts.AxisLineOpts(linestyle_opts=opts.LineStyleOpts(color="#5793f3")),
axislabel_opts=opts.LabelOpts(formatter="{value}"),
),
title_opts=opts.TitleOpts(title=sub_title, pos_left=title_left, pos_top=titel_top),
tooltip_opts=opts.TooltipOpts(trigger="axis", axis_pointer_type="cross"),
legend_opts=opts.LegendOpts(pos_left="40%", pos_bottom="0%"), # 图例的位置
)
.extend_axis(
yaxis=opts.AxisOpts(
type_="value",
name=y_line_name,
min_=0,
max_=3,
position="left",
axisline_opts=opts.AxisLineOpts(linestyle_opts=opts.LineStyleOpts(color="#675bba")),
axislabel_opts=opts.LabelOpts(formatter="{value}"),
splitline_opts=opts.SplitLineOpts(is_show=True, linestyle_opts=opts.LineStyleOpts(opacity=1)),
)
)
)
line = (
Line()
.add_xaxis(x)
.add_yaxis(
y_line_name,
y_line,
xaxis_index=index, # 需要变动的，图层中第几条X轴
yaxis_index=index * 2 + 1, # 需要变动的，图层中第几条Y轴
color="#675bba",
label_opts=opts.LabelOpts(is_show=True),
z_level=1 # z_level将折线图置于直方图之上，控制图表的显示层级,不然会被直方图遮挡
)
)
overlap = bar.overlap(line)
return overlap
def echarts_scatter(df):
# x = df.iloc[:, 0]
# y = df.iloc[:, 1]
# n = 100 / np.log(df.shape[0]) # 动态散点大小
n = 10 # 静态散点大小
if df.empty is False:
scatter = Scatter(init_opts=opts.InitOpts())
for index, row in df.iterrows():
x = int(row[0])
y = int(row[1])
scatter.add_xaxis(xaxis_data=[x])
scatter.add_yaxis(
series_name=index,
y_axis=[y],
symbol_size=n,
label_opts=opts.LabelOpts(is_show=False),
)
scatter.set_series_opts()
scatter.set_global_opts(
xaxis_opts=opts.AxisOpts(
type_="value",
name="销售",
splitline_opts=opts.SplitLineOpts(is_show=True),
),
yaxis_opts=opts.AxisOpts(
name="同比净增长",
type_="value",
axistick_opts=opts.AxisTickOpts(is_show=True),
splitline_opts=opts.SplitLineOpts(is_show=True),
),
tooltip_opts=opts.TooltipOpts(
is_show=True, trigger="item", formatter="{a} <br/>{b}: {c}"
),
# toolbox_opts=opts.ToolboxOpts(is_show=True),
legend_opts=opts.LegendOpts(is_show=False),
)
else:
scatter = Scatter()
return scatter
def line_chart(request):
x_data = tname_list
c = (
Line().add_xaxis(xaxis_data=x_data).add_yaxis(
series_name="python",
y_axis=so_dict['k1'],
label_opts=opts.LabelOpts(is_show=False),
).add_yaxis(
series_name="C",
y_axis=so_dict['k2'],
label_opts=opts.LabelOpts(is_show=False),
).add_yaxis(
series_name="C#",
y_axis=so_dict['k3'],
label_opts=opts.LabelOpts(is_show=False),
).add_yaxis(
series_name="C++",
y_axis=so_dict['k4'],
label_opts=opts.LabelOpts(is_show=False),
).add_yaxis(
series_name="JAVA",
y_axis=so_dict['k5'],
label_opts=opts.LabelOpts(is_show=False),
).add_yaxis(
series_name="javascript",
y_axis=so_dict['k6'],
label_opts=opts.LabelOpts(is_show=False),
).add_yaxis(
series_name="PHP",
y_axis=so_dict['k7'],
label_opts=opts.LabelOpts(is_show=False),
).add_yaxis(
series_name="VBS",
y_axis=so_dict['k8'],
label_opts=opts.LabelOpts(is_show=False),
).add_yaxis(
series_name="易语言",
y_axis=so_dict['k9'],
label_opts=opts.LabelOpts(is_show=False),
).set_global_opts(
title_opts=opts.TitleOpts(title=request.session['s'].stuName),
tooltip_opts=opts.TooltipOpts(trigger="axis"),
yaxis_opts=opts.AxisOpts(
type_="value",
axistick_opts=opts.AxisTickOpts(is_show=True),
splitline_opts=opts.SplitLineOpts(is_show=True),
),
xaxis_opts=opts.AxisOpts(type_="category", boundary_gap=False),
)
# .render("stacked_line_chart.html")
)
return HttpResponse(c.render_embed())
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 MACD(self) -> Bar:
c = (Bar().add_xaxis(self.dateindex).add_yaxis(
"macd",
round(self.data.MACD, self.precision).values.tolist(),
stack="v",
category_gap=2,
itemstyle_opts=opts.ItemStyleOpts(color=JsCode("""
function(params) {
var colorList;
if (params.data >= 0) {
colorList = '#ef232a';
} else {
colorList = '#14b143';
}
return colorList;
}
""")),
).set_series_opts(label_opts=opts.LabelOpts(
is_show=False)).set_global_opts(
datazoom_opts=[
opts.DataZoomOpts(range_start=0, range_end=100)
],
legend_opts=opts.LegendOpts(orient='vertical',
pos_left="top",
pos_top="70%"),
xaxis_opts=opts.AxisOpts(
type_="category",
is_scale=True,
grid_index=1,
boundary_gap=False,
axisline_opts=opts.AxisLineOpts(is_on_zero=False),
axistick_opts=opts.AxisTickOpts(is_show=False),
splitline_opts=opts.SplitLineOpts(is_show=False),
axislabel_opts=opts.LabelOpts(is_show=False),
)))
dea = round(self.data.DEA, self.precision).values.tolist()
dif = round(self.data.DIF, self.precision).values.tolist()
macd_line = (Line().add_xaxis(self.dateindex).add_yaxis(
"DIF",
dif,
is_symbol_show=False,
label_opts=opts.LabelOpts(is_show=False),
linestyle_opts=opts.LineStyleOpts(type_='solid', width=2),
).add_yaxis(
"DEA",
dea,
is_symbol_show=False,
label_opts=opts.LabelOpts(is_show=False)).set_series_opts(
label_opts=opts.LabelOpts(is_show=False)).set_global_opts(
datazoom_opts=[opts.DataZoomOpts()], ))
c.overlap(macd_line)
return c
