def stat_floors_distribution():
df = load_data()
summary = df.groupby('层数').count()
min_date = min(df['发证日期'])
max_date = max(df['发证日期'])
chart = (PictorialBar().add_xaxis(summary.index.tolist()).add_yaxis(
"层数",
summary['序号'].tolist(),
symbol_repeat="fixed",
symbol_offset=[0, -5],
is_symbol_clip=True,
).reversal_axis().set_global_opts(
title_opts=opts.TitleOpts(title="长沙预售房屋层数分布",
subtitle="统计日期:{}至{}，数据来源：{}".format(
min_date, max_date, DATA_SOURCE)),
legend_opts=opts.LegendOpts(is_show=False),
toolbox_opts=opts.ToolboxOpts(is_show=True),
yaxis_opts=opts.AxisOpts(name="层数",
is_show=True,
name_location='center',
name_gap=30)).set_series_opts(
label_opts=opts.LabelOpts(is_show=False)))
filename = os.path.join('..', 'assets',
'01_changsha_zhufangyushou_层数分布.html')
chart.render(filename)
def pyechart_PictorialBar_plot(self, filedata, para):
from pyecharts.charts import PictorialBar
file_name = '象形条形图.html'
path_plotly = self.path_dir_plotly_html + os.sep + file_name # 文件路径，前面是文件夹后面是文件名
costumeTheme = self.themedict[para['theme']]
# -----------------------------------------------------------------------
PictorialBar = (
PictorialBar(init_opts=opts.InitOpts(
theme=costumeTheme, width=para['width'],
height=para['height'])) # ThemeType.LIGHT para['theme']
)
chart = PictorialBar
df = pd.read_excel(filedata, sheet_name='Sheet1')
columns = df.columns.values.tolist()
xlabel = columns[0]
xdata = df[xlabel].values.tolist()
chart.add_xaxis(xaxis_data=xdata)
for i in range(1, len(columns)):
ylabel = columns[i]
ydata = df[ylabel].values.tolist()
chart.add_yaxis(series_name=ylabel,
y_axis=ydata,
symbol=para['Tsymbol'],
symbol_size=18,
symbol_repeat="fixed",
symbol_offset=[0, 0])
if para['x2y']:
chart.reversal_axis()
self.Common_code(chart, path_plotly, para)
print('成功绘制象形条形图')
return path_plotly # 返回该HTML文件路径
def pictorialbar_base() -> PictorialBar:
c = (
PictorialBar()
.add_xaxis(location)
.add_yaxis(
"",
values,
label_opts=opts.LabelOpts(is_show=False),
symbol_size=18,
symbol_repeat="fixed",
symbol_offset=[0, 0],
is_symbol_clip=True,
symbol=SymbolType.ROUND_RECT,
)
.reversal_axis()
.set_global_opts(
title_opts=opts.TitleOpts(title="PictorialBar-各省份人口数量（虚假数据）"),
xaxis_opts=opts.AxisOpts(is_show=False),
yaxis_opts=opts.AxisOpts(
axistick_opts=opts.AxisTickOpts(is_show=False),
axisline_opts=opts.AxisLineOpts(
linestyle_opts=opts.LineStyleOpts(opacity=0)
),
),
)
)
return c
def pictorialbar_custom_symbol() -> PictorialBar:
c = (
PictorialBar()
.add_xaxis(location)
.add_yaxis(
"",
values,
label_opts=opts.LabelOpts(is_show=False),
symbol_size=22,
symbol_repeat="fixed",
symbol_offset=[0, -5],
is_symbol_clip=True,
symbol=symbols["boy"],
)
.reversal_axis()
.set_global_opts(
title_opts=opts.TitleOpts(title="PictorialBar-自定义 Symbol"),
xaxis_opts=opts.AxisOpts(is_show=False),
yaxis_opts=opts.AxisOpts(
axistick_opts=opts.AxisTickOpts(is_show=False),
axisline_opts=opts.AxisLineOpts(
linestyle_opts=opts.LineStyleOpts(opacity=0)
),
),
)
)
return c
def pictorialbar_base(self, x_data, y_data):
c = (
PictorialBar()
.add_xaxis(x_data)
.add_yaxis(
"",
y_data,
label_opts=opts.LabelOpts(is_show=False),
symbol_size=22,
symbol_repeat="fixed",
symbol_offset=[0, -5],
is_symbol_clip=True,
symbol=SymbolType.ROUND_RECT,
)
.reversal_axis()
.set_global_opts(
title_opts=opts.TitleOpts(title="各学院人数占比"),
xaxis_opts=opts.AxisOpts(is_show=False),
yaxis_opts=opts.AxisOpts(
axistick_opts=opts.AxisTickOpts(is_show=False),
axisline_opts=opts.AxisLineOpts(
linestyle_opts=opts.LineStyleOpts(opacity=0)
),
),
)
)
return c
def drawPictorialBar(location,values,name):
c = (
PictorialBar()
.add_xaxis(location)
.add_yaxis(
"",
values,
label_opts=opts.LabelOpts(is_show=False),
symbol_size=22,
symbol_repeat="10000",
symbol_offset=[0, -5],
is_symbol_clip=True,
# symbol='image://https://github.githubassets.com/images/spinners/octocat-spinner-32.gif'
symbol='image://http://weizhendong.top/images/1.png'
)
.reversal_axis()
.set_global_opts(
title_opts=opts.TitleOpts(title=name),
xaxis_opts=opts.AxisOpts(is_show=False),
yaxis_opts=opts.AxisOpts(
axistick_opts=opts.AxisTickOpts(is_show=False),
axisline_opts=opts.AxisLineOpts(
linestyle_opts=opts.LineStyleOpts(opacity=0)
),
),
)
.render("{0}.html".format(name))
)
def test_pictorialbar_base(fake_writer):
c = (PictorialBar().add_xaxis(["山西", "四川", "西藏", "北京", "上海",
"内蒙古"]).add_yaxis(
"",
[13, 42, 67, 81, 86, 94, 166],
symbol_size=18,
symbol_repeat="fixed",
symbol_offset=[0, 0],
is_symbol_clip=True,
).reversal_axis())
c.render()
_, content = fake_writer.call_args[0]
eq_(c.theme, "white")
eq_(c.renderer, "canvas")
def pictorialbar_multi_custom_symbols() -> PictorialBar:
c = (
PictorialBar()
.add_xaxis(["reindeer", "ship", "plane", "train", "car"])
.add_yaxis(
"2015",
[
{"value": 157, "symbol": symbols["reindeer"]},
{"value": 21, "symbol": symbols["ship"]},
{"value": 66, "symbol": symbols["plane"]},
{"value": 78, "symbol": symbols["train"]},
{"value": 123, "symbol": symbols["car"]},
],
label_opts=opts.LabelOpts(is_show=False),
symbol_size=22,
symbol_repeat="fixed",
symbol_offset=[0, 5],
is_symbol_clip=True,
)
.add_yaxis(
"2016",
[
{"value": 184, "symbol": symbols["reindeer"]},
{"value": 29, "symbol": symbols["ship"]},
{"value": 73, "symbol": symbols["plane"]},
{"value": 91, "symbol": symbols["train"]},
{"value": 95, "symbol": symbols["car"]},
],
label_opts=opts.LabelOpts(is_show=False),
symbol_size=22,
symbol_repeat="fixed",
symbol_offset=[0, -25],
is_symbol_clip=True,
)
.reversal_axis()
.set_global_opts(
title_opts=opts.TitleOpts(title="PictorialBar-Vehicles in X City"),
xaxis_opts=opts.AxisOpts(is_show=False),
yaxis_opts=opts.AxisOpts(
axistick_opts=opts.AxisTickOpts(is_show=False),
axisline_opts=opts.AxisLineOpts(
linestyle_opts=opts.LineStyleOpts(opacity=0)
),
),
)
)
return c
def draw(self, indexs, values, filename):
c = (PictorialBar().add_xaxis(indexs).add_yaxis(
"",
values,
label_opts=opts.LabelOpts(is_show=False),
symbol_size=18,
symbol_repeat="fixed",
symbol_offset=[0, 0],
is_symbol_clip=True,
symbol=SymbolType.ROUND_RECT,
).reversal_axis().set_global_opts(
title_opts=opts.TitleOpts(title="报道香港新闻热门博主前十名"),
xaxis_opts=opts.AxisOpts(is_show=False),
yaxis_opts=opts.AxisOpts(
axistick_opts=opts.AxisTickOpts(is_show=False),
axisline_opts=opts.AxisLineOpts(
linestyle_opts=opts.LineStyleOpts(opacity=0)),
),
))
c.render(filename)
def place_top(self):
print('正在生成销售地Top10...')
group_count = self.collection.aggregate([{
'$group': {
'_id': '$店铺地址',
'count': {
'$sum': 1
}
}
}])
addr = []
count = []
sorted_list = sorted([list(item.values()) for item in group_count],
key=lambda x: x[-1],
reverse=True)
for item in sorted_list[:10][::-1]:
addr.append(item[0])
count.append(item[1])
c = (PictorialBar().add_xaxis(addr).add_yaxis(
'',
count,
label_opts=opts.LabelOpts(is_show=False),
symbol_size=16,
symbol_repeat='fixed',
symbol_offset=[0, 0],
is_symbol_clip=True,
symbol=SymbolType.ROUND_RECT,
).reversal_axis().set_global_opts(
title_opts=opts.TitleOpts(title='销售地Top10'),
xaxis_opts=opts.AxisOpts(is_show=False),
yaxis_opts=opts.AxisOpts(
axistick_opts=opts.AxisTickOpts(is_show=False),
axisline_opts=opts.AxisLineOpts(
linestyle_opts=opts.LineStyleOpts(opacity=0)),
),
).render("销售地Top10.html"))
print('生成完成')
return c
def field(self):
sql = 'select industryField from jobs'
results = self.query(sql)
rows = []
for row in results:
r = row[0].replace(',', ' ').replace('丨', ' ').replace('、', ' ')
rows.extend(r.split(' '))
sum = {}
for r in rows:
num = sum.get(r, 0) + 1
sum[r] = num
tup = sorted(sum.items(), key=lambda kv: (kv[1], kv[0]), reverse=True)
sum = {}
for k, v in tup[0:20]:
sum[k + str(v)] = v
location = list(sum.keys())
values = list(sum.values())
c = (PictorialBar().add_xaxis(location).add_yaxis(
"",
values,
label_opts=opts.LabelOpts(is_show=False),
symbol_size=18,
symbol_repeat="fixed",
symbol_offset=[0, 0],
is_symbol_clip=True,
symbol=SymbolType.ROUND_RECT,
).reversal_axis().set_global_opts(
title_opts=opts.TitleOpts(title="热门行业"),
xaxis_opts=opts.AxisOpts(is_show=False),
yaxis_opts=opts.AxisOpts(
axistick_opts=opts.AxisTickOpts(is_show=False),
axisline_opts=opts.AxisLineOpts(
linestyle_opts=opts.LineStyleOpts(opacity=0)),
),
).render("拉勾行业.html"))
def pic_bar_microchip(values, label):
pictorialbar = PictorialBar(
init_opts=opts.InitOpts(width='480px', height='700px'))
pictorialbar.add_xaxis(label)
pictorialbar.add_yaxis("",
values[0],
symbol_size=18,
symbol_repeat='20',
symbol_offset=[0, 0],
is_symbol_clip=True,
symbol='rect',
color='#F95DBA',
gap='-100%',
symbol_margin=10,
label_opts=opts.LabelOpts(is_show=False))
pictorialbar.add_yaxis("高通骁龙",
values[1],
symbol_size=18,
label_opts=opts.LabelOpts(is_show=False),
symbol_repeat='20',
symbol_offset=[0, 0],
is_symbol_clip=True,
symbol='rect',
color='#FFCE2B',
gap='-100%',
symbol_margin=10)
pictorialbar.add_yaxis("联发科天玑/MT",
values[2],
label_opts=opts.LabelOpts(is_show=False),
symbol_size=18,
symbol_repeat='20',
symbol_offset=[0, 0],
is_symbol_clip=True,
symbol='rect',
color='#009688',
gap='-100%',
symbol_margin=10)
pictorialbar.add_yaxis("华为麒麟",
values[3],
yaxis_index=0,
label_opts=opts.LabelOpts(is_show=False),
symbol_size=18,
symbol_repeat='20',
symbol_offset=[0, 0],
is_symbol_clip=True,
symbol='rect',
color='#1720D1',
gap='-100%',
symbol_margin=10)
pictorialbar.add_yaxis("三星Exynos",
values[4],
yaxis_index=0,
label_opts=opts.LabelOpts(is_show=False),
symbol_size=18,
symbol_repeat='20',
symbol_offset=[0, 0],
is_symbol_clip=True,
symbol='rect',
color='white',
gap='-100%',
symbol_margin=10)
pictorialbar.set_global_opts(
xaxis_opts=opts.AxisOpts(is_show=False),
yaxis_opts=opts.AxisOpts(
is_show=True, axistick_opts=opts.AxisTickOpts(is_show=False)),
legend_opts=opts.LegendOpts(pos_bottom='9%',
pos_right='10%',
orient='vertical',
item_width=18,
item_height=18),
title_opts=opts.TitleOpts(title='各品牌5G手机芯片比较',
pos_left='center',
pos_top='2%'))
pictorialbar.reversal_axis()
pictorialbar.render('各品牌5G手机芯片比较.html')
def pic_bar_price(values, label):
"""
5G手机价位比较
"""
# 初始化，设置图表大小
pictorialbar = PictorialBar(
init_opts=opts.InitOpts(width='480px', height='700px'))
# x轴标签信息
pictorialbar.add_xaxis(label)
# 添加象形图
pictorialbar.add_yaxis("",
values[0],
symbol_size=18,
symbol_repeat='20',
symbol_offset=[0, 0],
is_symbol_clip=True,
symbol='rect',
color='#FCA46A',
gap='-100%',
symbol_margin=10,
label_opts=opts.LabelOpts(is_show=False))
pictorialbar.add_yaxis("5000元及以上",
values[1],
symbol_size=18,
label_opts=opts.LabelOpts(is_show=False),
symbol_repeat='20',
symbol_offset=[0, 0],
is_symbol_clip=True,
symbol='rect',
color='#F95DBA',
gap='-100%',
symbol_margin=10)
pictorialbar.add_yaxis("3000-4999元",
values[2],
label_opts=opts.LabelOpts(is_show=False),
symbol_size=18,
symbol_repeat='20',
symbol_offset=[0, 0],
is_symbol_clip=True,
symbol='rect',
color='#4E70F0',
gap='-100%',
symbol_margin=10)
pictorialbar.add_yaxis("1000-2999元",
values[3],
yaxis_index=0,
label_opts=opts.LabelOpts(is_show=False),
symbol_size=18,
symbol_repeat='20',
symbol_offset=[0, 0],
is_symbol_clip=True,
symbol='rect',
color='#1720D1',
gap='-100%',
symbol_margin=10)
pictorialbar.add_yaxis("999元及以下",
values[4],
yaxis_index=0,
label_opts=opts.LabelOpts(is_show=False),
symbol_size=18,
symbol_repeat='20',
symbol_offset=[0, 0],
is_symbol_clip=True,
symbol='rect',
color='white',
gap='-100%',
symbol_margin=10)
pictorialbar.set_global_opts(
# 隐藏x坐标轴
xaxis_opts=opts.AxisOpts(is_show=False),
# 显示y坐标轴，隐藏刻度线
yaxis_opts=opts.AxisOpts(
is_show=True, axistick_opts=opts.AxisTickOpts(is_show=False)),
# 显示图例，设置图例位置
legend_opts=opts.LegendOpts(pos_bottom='9%',
pos_right='10%',
orient='vertical',
item_width=18,
item_height=18),
# 添加标题，设置标题位置
title_opts=opts.TitleOpts(title='各品牌5G手机价位比较',
pos_left='center',
pos_top='2%'))
pictorialbar.reversal_axis()
pictorialbar.render('各品牌5G手机价位比较.html')
wea = weather_dict['cloud']
elif wea[-1:] == '雨':
wea = weather_dict['rain']
elif wea[-1:] == '阴':
wea = weather_dict['overcast']
return wea
# 获取降水和温度信息
weather_data = map(check_weather, zhongqiu['wea'].values.tolist())
weather_data = list(weather_data)
tem_data = map(trans_tem, zhongqiu['tem'].values.tolist())
tem_data = list(tem_data)
# 降水和温度柱状图
pictorialbar = PictorialBar()
pictorialbar.add_xaxis(zhongqiu_city)
pictorialbar.add_yaxis(
"weather", weather_data,
label_opts=opts.LabelOpts(is_show=False),
symbol_size=18,
symbol_repeat="fixed",
symbol_offset=[0, 0],
is_symbol_clip=True,
symbol=SymbolType.ROUND_RECT
)
pictorialbar.add_yaxis(
"temperature", tem_data,
label_opts=opts.LabelOpts(is_show=False),
symbol_size=18,
symbol_repeat="fixed",
def showData(request):
data = {}
# 数据类型 float
SuccessRate = 1.0
c1 = (Liquid(init_opts=opts.InitOpts(width="350px", height="350px")).add(
series_name="平均成功率",
data=[SuccessRate, SuccessRate],
tooltip_opts=liquid_format(SuccessRate),
))
# 数据类型 hours.minute
timeCost = 5.45
c2 = (Gauge(init_opts=opts.InitOpts(width="300px", height="300px")).add(
series_name="平均成功耗时",
data_pair=[("耗时", timeCost)],
min_=0,
max_=24,
split_number=12,
title_label_opts=opts.LabelOpts(font_size=20,
color="#C23531",
font_family="Microsoft YaHei"),
detail_label_opts=opts.GaugeDetailOpts(offset_center=[0, "30%"],
formatter="{value}h"),
).set_global_opts(
legend_opts=opts.LegendOpts(is_show=False),
tooltip_opts=opts.TooltipOpts(is_show=True,
formatter=gauge_format(timeCost)),
))
# 数据类型：考点+排队人数
location = ["山西", "四川", "山东"]
values = [13, 42, 2]
c3 = (PictorialBar(init_opts=opts.InitOpts(
height="500px")).add_xaxis(location).add_yaxis(
"",
values,
label_opts=opts.LabelOpts(is_show=False),
symbol_size=40,
symbol_repeat="fixed",
symbol_offset=[0, -5],
is_symbol_clip=True,
symbol="image://../../static/img/wait_people.svg",
category_gap="10px",
gap="10px",
).reversal_axis().set_global_opts(
xaxis_opts=opts.AxisOpts(is_show=False),
yaxis_opts=opts.AxisOpts(
axistick_opts=opts.AxisTickOpts(is_show=False),
axisline_opts=opts.AxisLineOpts(
linestyle_opts=opts.LineStyleOpts(opacity=0)),
),
))
points = ["四川大学", "成都理工大学", "湖南大学"]
counts = [4, 5, 1]
# 时.分
cost = [4.20, 0.32, 7.40]
c4 = (Bar().add_xaxis(xaxis_data=points).add_yaxis(
series_name="总人数",
y_axis=counts,
yaxis_index=0,
label_opts=opts.LabelOpts(is_show=False),
).add_yaxis(
series_name="时耗",
y_axis=cost,
yaxis_index=1,
label_opts=opts.LabelOpts(is_show=False),
).extend_axis(yaxis=opts.AxisOpts(
name="时耗",
type_="value",
min_=0,
max_=24,
interval=4,
axislabel_opts=opts.LabelOpts(formatter="{value}h"),
)).set_global_opts(
tooltip_opts=opts.TooltipOpts(
is_show=True,
trigger="axis",
formatter="{b}<br>{a0}: {c0}<br>{a1}: {c1}h"),
xaxis_opts=opts.AxisOpts(
type_="category",
axispointer_opts=opts.AxisPointerOpts(is_show=True,
type_="shadow"),
),
))
data['averageRate'] = c1.render_embed()
data['averageCost'] = c2.render_embed()
data['pointCurrent'] = c3.render_embed()
data['pointDetail'] = c4.render_embed()
return render(request, 'showEcharts.html', {
'active_menu': 'charts',
'data': data
})
print('生成结果文件：' + out_filename)
##象形柱状图
pictorialbar = (PictorialBar().add_xaxis(key_words).add_yaxis(
"",
words_freq,
label_opts=opts.LabelOpts(is_show=False),
symbol_size=18,
symbol_repeat="fixed",
symbol_offset=[0, 0],
is_symbol_clip=True,
symbol=SymbolType.ROUND_RECT,
).reversal_axis().set_global_opts(
title_opts=opts.TitleOpts(title="时间简史词频象形柱状图", subtitle="仅统计前40个关键词"),
xaxis_opts=opts.AxisOpts(is_show=False),
yaxis_opts=opts.AxisOpts(
axistick_opts=opts.AxisTickOpts(is_show=False),
axisline_opts=opts.AxisLineOpts(linestyle_opts=opts.LineStyleOpts(
opacity=0)),
),
toolbox_opts=opts.ToolboxOpts(),
visualmap_opts=opts.VisualMapOpts(min_=30,
max_=700,
orient="vertical",
dimension=0),
datazoom_opts=opts.DataZoomOpts(range_start=20,
range_end=50,
orient="vertical",
pos_left="right")))
out_filename = './output/pictorialbar_keywords.html'
pictorialbar.render(out_filename)
print('生成结果文件：' + out_filename)
# 按人口数排序，从高到低
test = sorted(test, key=(lambda x: x[1]), reverse=True)
print(test)
area_test = [i[0] for i in test]
popu_test = [i[1] for i in test]
# area = area_test[4:]
# popu = popu_test[4:]
# 总人口图
xValues = area_test[4:]
yValues_total = popu_test[4:]
a = (PictorialBar().add_xaxis(xValues[::-1]).add_yaxis(
"",
yValues_total[::-1],
label_opts=opts.LabelOpts(is_show=False),
symbol_size=10,
symbol_repeat="fixed",
symbol_offset=[2, 0],
is_symbol_clip=True,
symbol=SymbolType.ROUND_RECT,
).reversal_axis().set_global_opts(
title_opts=opts.TitleOpts(title="中国各地区人口数", subtitle="第六次人口普查"),
xaxis_opts=opts.AxisOpts(is_show=True, name="人口数"),
yaxis_opts=opts.AxisOpts(
axistick_opts=opts.AxisTickOpts(is_show=False),
axisline_opts=opts.AxisLineOpts(linestyle_opts=opts.LineStyleOpts(
opacity=0.5)),
),
))
a.render("各省份人口数.html")
from pyecharts.charts import PictorialBar
from pyecharts.globals import SymbolType
location = t4["analyze_t4.saledesc"][10:0:-1].values.tolist()
values = t4["analyze_t4.sales"][10:0:-1].values.tolist()
c = (PictorialBar(init_opts=opts.InitOpts(
width="1600px", height="400px")).add_xaxis(location).add_yaxis(
"",
values,
label_opts=opts.LabelOpts(is_show=False),
symbol_size=18,
symbol_repeat="fixed",
symbol_offset=[0, 0],
is_symbol_clip=True,
symbol=SymbolType.ROUND_RECT,
).reversal_axis().set_global_opts(
title_opts=opts.TitleOpts(title="客户公司订单金额排行"),
xaxis_opts=opts.AxisOpts(is_show=False),
yaxis_opts=opts.AxisOpts(
axistick_opts=opts.AxisTickOpts(is_show=False),
axisline_opts=opts.AxisLineOpts(linestyle_opts=opts.LineStyleOpts(
opacity=0)),
),
).render("analyzed_pic5.html"))
#c.render_notebook()
# ## 六、购买次数最高的用户词云
# In[13]:
