def duotu4_fun():
from pyecharts import Bar, Grid
title = "Height For Class"
df = pd.DataFrame(
pd.read_csv('mycharts/class.csv', encoding='gbk', header=0))
df1 = pd.DataFrame(df['Height'])
df2 = pd.DataFrame(df['Name'])
dtvalue1 = [i[0] for i in df1.values]
index1 = [i[0] for i in df2.values.tolist()]
grid = Grid()
bar = Bar(title, "Height For Class")
bar.add('Height',
index1,
dtvalue1,
is_datazoom_show=True,
xaxis_interval=0,
xaxis_rotate=30)
grid.add(bar, grid_bottom="25%")
return grid
def test_grid_inverse_yaxis():
attr = ["{}天".format(i) for i in range(1, 31)]
line_top = Line("折线图示例", width=1200, height=700)
line_top.add(
"最高气温",
attr,
[random.randint(20, 100) for i in range(30)],
mark_point=["max", "min"],
mark_line=["average"],
legend_pos="38%",
)
line_bottom = Line()
line_bottom.add(
"最低气温",
attr,
[random.randint(20, 100) for i in range(30)],
mark_point=["max", "min"],
mark_line=["average"],
is_yaxis_inverse=True,
xaxis_pos="top",
)
grid = Grid()
grid.add(line_top, grid_bottom="60%")
grid.add(line_bottom, grid_top="50%")
grid.render()
def view(numList):
line = Line('折线图', width=2000)
atter = ['数据异常', '不及格', '及格', '良好', '优秀', '满分']
v1 = [numList[0], numList[1], numList[2], numList[3], numList[4], numList[5]]
line.add('最高成绩', atter, v1,
mark_point=['max'], # 标点最大值
mark_line=['average']) # 虚线位置是平均分
line.add('最低成绩', atter, v1,
mark_point=['min'],
legend_pos='20%')
es = EffectScatter() # 调用闪烁点
es.add('', atter, v1, effect_scale=8)
# 调用合并函数，再一个图表上输出
overlop = Overlap()
overlop.add(line)
overlop.add(es)
pie = Pie('饼图', title_pos='80%')
pie.add('', atter, v1,
radius=[60, 30], # 控制内外半径的
center=[65, 50],
legend_pos='80%',
legend_orient='vertical')
# 显示两个示例图的调用函数，不然会覆盖
grid = Grid()
grid.add(overlop, grid_right='50%')
grid.add(pie, grid_left='60%')
grid.render('abc.html')
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 get_bar(item_name, subtitle, item_name_list, item_num_list):
bar = Bar(item_name,
page_title=item_name,
title_text_size=30,
title_pos='center',
subtitle=subtitle,
subtitle_text_size=25)
bar.add("",
item_name_list,
item_num_list,
title_pos='center',
xaxis_interval=0,
xaxis_rotate=27,
xaxis_label_textsize=20,
yaxis_label_textsize=20,
yaxis_name_pos='end',
yaxis_pos="%50")
bar.show_config()
grid = Grid(width=1300, height=800)
grid.add(bar,
grid_top="13%",
grid_bottom="23%",
grid_left="15%",
grid_right="15%")
out_file_name = './analyse/' + item_name + '.html'
grid.render(out_file_name)
def get_line(item_name, subtitle, item_name_list, item_num_list):
line = Line(item_name,
subtitle,
title_text_size=30,
subtitle_text_size=25,
title_pos='center')
line.add("",
item_name_list,
item_num_list,
mark_point=["max", "min"],
mark_line=["average"],
title_pos='center',
xaxis_interval=0,
xaxis_rotate=27,
xaxis_label_textsize=20,
yaxis_label_textsize=20,
yaxis_name_pos='end',
yaxis_pos="%50")
line.show_config()
grid = Grid(width=1300, height=800)
grid.add(line,
grid_top="13%",
grid_bottom="23%",
grid_left="15%",
grid_right="15%")
out_file_name = './analyse/' + item_name + '.html'
grid.render(out_file_name)
def grids(data):
kline = Kline(data.symbol[0])
kline.add(
'',
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],
)
turnover = Bar()
turnover.add(
'',
data.index,
data['turnover'].values / pow(10, 9),
mark_line=['max', 'min'],
is_datazoom_show=True,
)
grid = Grid(page_title=data['symbol'][0], width=1800, height=900)
grid.add(kline, grid_bottom='40%')
grid.add(turnover, grid_top='65%')
grid.show_config()
return grid
def RowAnalyse():
'''
统计聊天条数分布
个人
'''
chatrooms = getChat.GetChatrooms(typename=2)
RowNum = {}
print("总聊天数：" + str(len(chatrooms)))
for chatroom in chatrooms:
RowNum[chatroom] = toMySQL.GetRowNum(chatroom)
# sorted_list = sorted(RowNum.items(), key=operator.itemgetter(1),reverse=True)
# f = open("../../rows.txt","w+",encoding="utf-8")
# for i in sorted_list:
# f.write(i[0]+","+str(getChat.GetWXID(i[0]))+","+str(i[1])+"\n")
# f.close()
data = sorted(RowNum.values(), reverse=True)
x_axis = list(range(len(chatrooms)))
y_axis = data
bar_top = Bar("条数统计", title_pos="10%")
bar_top.add("", x_axis, y_axis, yaxis_name="条数", is_xaxislabel_align=True)
bar_bottom = Bar("条数统计-对数坐标", title_top="55%", title_pos="10%")
bar_bottom.add("",
x_axis,
y_axis,
yaxis_name="条数",
yaxis_type='log',
is_xaxislabel_align=True)
grid = Grid(width=1920, height=1080)
grid.add(bar_top, grid_bottom="60%")
grid.add(bar_bottom, grid_top="60%")
grid.render(path="../../output/row_analyse.html")
grid.render(path="../../output/row_analyse.pdf")
def unicorn_china5(data):
data = data.groupby(by='Industry').sum()
data = data.sort_values(by='Valuation', ascending=False)
data2 = data[:10]['Valuation']
data3 = data[10:]['Valuation'].sum()
data2.loc['其他行业'] = data3
data2 = data2[::-1]
attr = list(data2.index)
value = list(data2.values)
bar = Bar("独角兽公司所在行业估值对比", '互联网金融行业成香饽饽', title_pos="center")
bar.add('单位(亿人民币)',
attr,
value,
is_label_show=True,
label_pos='right',
xaxis_interval=0,
# yaxis_roate=45,
is_convert=True,
legend_pos='right'
)
# Grid 控制图表布局，避免坐标标签折断
grid = Grid(width=600, height=1000) # 修改图形尺寸
grid.add(bar, grid_left='15%')
grid.render(path='独角兽公司所在行业估值对比.png', dpi=200)
def unicorn_china2(data):
data.sort_values(by='Valuation', ascending=False, inplace=True)
data = data[:20][::-1]
attr = list(data['Company'].values)
value = list(data['Valuation'].values)
# print(value,attr)
bar = Bar("大中华区独角兽公司估值前二十名", '巨无霸蚂蚁金服', title_pos="center")
bar.add("单位(亿人民币)",
attr,
value,
is_label_show=True,
label_pos='right',
xaxis_interval=0,
yaxis_roate=45,
is_convert=True,
legend_pos='right'
)
# Grid 控制图表布局，避免坐标标签折断
grid = Grid(width=600, height=1000) # 修改图形尺寸
grid.add(bar, grid_left='15%')
grid.render(path='大中华区独角兽企业估值前二十.png', dpi=200)
def spot_line(cnt,name):
follow_spot=df[df['channel_id']==cnt]
follow_spot=follow_spot.groupby(by=['spot_id','date'],as_index=False).sum()[['spot_id','date','cost_r']]
spt=follow_spot[follow_spot['date'].apply(lambda x:str(x))==end_time.replace('-', '')].sort_values(by='cost_r').tail(7)['spot_id']
top_spt=follow_spot[follow_spot['spot_id'].isin(spt)] #TOP广告位
lists=[]
for i,j in itertools.product(top_spt['spot_id'].drop_duplicates(),df['date'].drop_duplicates()):
lists.append([i,j])
lists=pd.DataFrame(lists,columns=['spot_id','date'])
top_spt=pd.merge(lists,top_spt,how='left',on=['spot_id','date'])
top_spt=top_spt.fillna(0)
top_spt=pd.merge(top_spt,meta_spot,how='left',left_on='spot_id',right_on='spotid')
top_spt.loc[top_spt['name'].isnull(),'name']=top_spt[top_spt['name'].isnull()]['spot_id']
line = Line(name+'TOP广告位消耗')
for i in top_spt['name'].drop_duplicates():
line.add(i,top_spt[top_spt['name']==i]['date'].apply(lambda x:str(x)),top_spt[top_spt['name']==i]['cost_r'].apply(lambda x:int(x)),legend_pos="84%",mark_point=['max'])
# grid= Grid(width=1000,height=350)
# grid.add(line,grid_right="25%")
# page.add_chart(grid)
''' 涨跌幅TOP广告位 '''
lists=[]
for i,j in itertools.product(follow_spot['spot_id'].drop_duplicates(),df['date'].drop_duplicates()):
lists.append([i,j])
lists=pd.DataFrame(lists,columns=['spot_id','date'])
follow_spt=pd.merge(lists,follow_spot,how='left',on=['spot_id','date'])#笛卡尔积
follow_spt=follow_spt.fillna(0)
diff_spt=follow_spt.groupby(by='spot_id',as_index=False).diff()['cost_r'].rename('rise')
diff_spt=pd.concat([follow_spt,diff_spt],axis=1)
#涨幅TOP 7
spt=diff_spt[diff_spt['date'].apply(lambda x:str(x))==end_time.replace('-', '')].sort_values(by='rise').tail(7)['spot_id']
rise_spt=diff_spt[diff_spt['spot_id'].isin(spt)] #TOP广告位
rise_spt=pd.merge(rise_spt,meta_spot,how='left',left_on='spot_id',right_on='spotid')
rise_spt.loc[rise_spt['name'].isnull(),'name']=rise_spt[rise_spt['name'].isnull()]['spot_id']
line1 = Line(name+'涨幅TOP广告位',width=1000,height=450)
for i in rise_spt['name'].drop_duplicates():
line1.add(i,rise_spt[rise_spt['name']==i]['date'].apply(lambda x:str(x)),rise_spt[rise_spt['name']==i]['cost_r'].apply(lambda x:int(x)),legend_pos="84%")
#跌幅TOP 7
spt=diff_spt[diff_spt['date'].apply(lambda x:str(x))==end_time.replace('-', '')].sort_values(by='rise').head(7)['spot_id']
fall_spt=diff_spt[diff_spt['spot_id'].isin(spt)] #TOP广告位
fall_spt=pd.merge(fall_spt,meta_spot,how='left',left_on='spot_id',right_on='spotid')
fall_spt.loc[fall_spt['name'].isnull(),'name']=fall_spt[fall_spt['name'].isnull()]['spot_id']
line2 = Line(name+'跌幅TOP广告位',width=1000,height=450)
for i in fall_spt['name'].drop_duplicates():
line2.add(i,fall_spt[fall_spt['name']==i]['date'].apply(lambda x:str(x)),fall_spt[fall_spt['name']==i]['cost_r'].apply(lambda x:int(x)),legend_pos="84%")
#画图
grid= Grid(width=900,height=350)
timeline = Timeline(timeline_bottom=0)
timeline.add(line, name+'TOP消耗')
timeline.add(line1, name+'涨幅TOP消耗')
timeline.add(line2, name+'跌幅TOP消耗')
grid.add(timeline)
# grid= Grid(width=1200,height=350)
# grid.add(line,grid_right="55%")
# grid.add(line1,grid_left="55%")
page.add_chart(grid)
def draw(self):
line_price = Line()
line_price.add('Close',
self.price_timeline,
self.data_price,
is_datazoom_show=True,
datazoom_type='both',
datazoom_xaxis_index=[0, 1],
is_fill=False,
line_opacity=0.8,
is_smooth=True)
line_pe = Line()
line_pe.add('EPS',
self.pe_timeline,
self.data_pe,
is_fill=False,
line_opacity=0.8,
is_smooth=True,
legend_top='58%')
grid = Grid(width=1000, height=700)
grid.add(line_price, grid_bottom="50%")
grid.add(line_pe, grid_top="60%")
page = Page()
page.add(grid)
page.render()
def stream_status(streams, is_reload=0):
grid = Grid(width="100%", height="100%")
# stream_time = ['00:00', '01:00', '02:00', '03:00', '04:00', '05:00', '06:00', '07:00', '08:00', '09:00', '10:00',
# '11:00', '12:00', '13:00', '14:00', '15:00', '16:00', '17:00', '18:00', '19:00', '20:00', '21:00',
# '22:00', '23:00', '24:00']
# stream_in = [13, 6, 22, 5, 58, 3, 75, 98, 48, 83, 8, 38, 89, 99, 8, 21, 77, 86, 47, 76, 31, 92, 77, 47, 0]
# stream_out = [5, 81, 99, 83, 55, 89, 58, 5, 38, 76, 46, 17, 68, 4, 12, 81, 2, 73, 54, 71, 50, 28, 90, 46, 0]
stream_time = list(streams.keys())
val = list(streams.values())
stream_in = [v[0] for v in val]
stream_out = [v[1] for v in val]
stream = Line(' 进出口流量统计\n -------------------', width="100%", height="100%",
title_color="#6cb7c9", title_pos="left", title_top=10)
stream.add("入口流量", stream_time, stream_in, is_fill=True, line_opacity=1,
line_color="#6cb7c9", label_color=["#6cb7c9", "#344356"],
area_opacity=0.7, is_smooth=True, is_toolbox_show=False, is_yaxis_show=False)
stream.add("出口流量", stream_time, stream_out, is_fill=True, area_color='#000',
area_opacity=0.4, is_smooth=True, is_toolbox_show=False, is_yaxis_show=False,
is_legend_show=True, legend_text_color="#6cb7c9", xaxis_line_color="#6cb7c9")
grid.add(stream, grid_bottom=30, grid_left=30, grid_top=50, grid_right=30)
if is_reload:
option = grid.get_options()
option = TRANSLATOR.translate(option)
option = option.as_snippet()
return option
else:
return grid
def test_grid_properties():
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", CLOTHES, v1, is_stack=True)
bar.add("商家B", CLOTHES, v2, is_stack=True)
line = Line("折线图示例", title_top="50%")
line.add(
"最高气温",
WEEK,
[11, 11, 15, 13, 12, 13, 10],
mark_point=["max", "min"],
mark_line=["average"],
)
line.add(
"最低气温",
WEEK,
[1, -2, 2, 5, 3, 2, 0],
mark_point=["max", "min"],
mark_line=["average"],
legend_top="50%",
)
grid = Grid(width=1024, height=768)
grid.add(bar, grid_bottom="60%")
grid.add(line, grid_top="60%")
eq_(grid.width, 1024)
eq_(grid.height, 768)
assert ('echarts' in bar.js_dependencies) or ('echarts.min'
in bar.js_dependencies)
def test_grid_top_bottom():
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", CLOTHES, v1, is_stack=True)
bar.add("商家B", CLOTHES, v2, is_stack=True)
line = Line("折线图示例", title_top="50%")
line.add(
"最高气温",
WEEK,
[11, 11, 15, 13, 12, 13, 10],
mark_point=["max", "min"],
mark_line=["average"],
)
line.add(
"最低气温",
WEEK,
[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.render()
def test_grid_properties():
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", CLOTHES, v1, is_stack=True)
bar.add("商家B", CLOTHES, v2, is_stack=True)
line = Line("折线图示例", title_top="50%")
line.add(
"最高气温",
WEEK,
[11, 11, 15, 13, 12, 13, 10],
mark_point=["max", "min"],
mark_line=["average"],
)
line.add(
"最低气温",
WEEK,
[1, -2, 2, 5, 3, 2, 0],
mark_point=["max", "min"],
mark_line=["average"],
legend_top="50%",
)
grid = Grid(width=1024, height=768)
grid.add(bar, grid_bottom="60%")
grid.add(line, grid_top="60%")
eq_(grid.width, 1024)
eq_(grid.height, 768)
assert (
("echarts" in bar.js_dependencies)
or ("echarts.min" in bar.js_dependencies)
)
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 test_grid_line_pie():
line = Line("折线图示例", width=1200)
line.add(
"最高气温",
WEEK,
[11, 11, 15, 13, 12, 13, 10],
mark_point=["max", "min"],
mark_line=["average"],
)
line.add(
"最低气温",
WEEK,
[1, -2, 2, 5, 3, 2, 0],
mark_point=["max", "min"],
mark_line=["average"],
legend_pos="20%",
)
v1 = [11, 12, 13, 10, 10, 10]
pie = Pie("饼图示例", title_pos="55%")
pie.add(
"",
CLOTHES,
v1,
radius=[45, 65],
center=[65, 50],
legend_pos="80%",
legend_orient="vertical",
)
grid = Grid()
grid.add(line, grid_right="55%")
grid.add(pie, grid_left="60%")
grid.render()
def test_grid_5():
import random
x_axis = [
"12a", "1a", "2a", "3a", "4a", "5a", "6a", "7a", "8a", "9a", "10a",
"11a", "12p", "1p", "2p", "3p", "4p", "5p", "6p", "7p", "8p", "9p",
"10p", "11p"
]
y_axis = [
"Saturday", "Friday", "Thursday", "Wednesday", "Tuesday", "Monday",
"Sunday"
]
data = [[i, j, random.randint(0, 50)] for i in range(24) for j in range(7)]
heatmap = HeatMap("热力图示例", height=700)
heatmap.add("热力图直角坐标系",
x_axis,
y_axis,
data,
is_visualmap=True,
visual_top="45%",
visual_text_color="#000",
visual_orient='horizontal')
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", title_top="52%")
bar.add("商家A", attr, v1, is_stack=True)
bar.add("商家B", attr, v2, is_stack=True, legend_top="50%")
grid = Grid()
grid.add(heatmap, grid_bottom="60%")
grid.add(bar, grid_top="60%")
grid.render()
def drawfunc(self,
A,
text,
yaxis_max=200000,
yaxis_force_interval=0.25,
width=1000):
'''坏账率绘图函数'''
bar = Bar(text, title_pos='center', width='100%')
line = Line(text, title_pos='center', width='100%')
bar.add("好客户",
A.iloc[:, 0].tolist(),
A['好客户'].tolist(),
yaxis_min=0,
yaxis_max=yaxis_max,
is_label_show=True,
label_pos='inside',
label_color=['#FFB6B9'],
legend_pos='right',
legend_orient='vertical',
is_stack=True)
bar.add("坏客户",
A.iloc[:, 0].tolist(),
A['坏账'].tolist(),
yaxis_min=0,
yaxis_max=yaxis_max,
is_label_show=True,
label_pos='inside',
label_color=['#BBDED6'],
legend_pos='right',
legend_orient='vertical',
is_stack=True)
line.add('坏账率',
A.iloc[:, 0].tolist(),
A['坏账率'].tolist(),
yaxis_min=0,
yaxis_max=1,
yaxis_force_interval=yaxis_force_interval,
is_smooth=True,
legend_pos='right',
point_symbol='circle',
legend_orient='vertical',
line_width=2,
is_label_show=True)
line.add('总体坏账率',
A.iloc[:, 0].tolist(),
A['总体坏账率'].tolist(),
yaxis_min=0,
yaxis_max=1,
yaxis_force_interval=yaxis_force_interval,
is_smooth=True,
legend_pos='right',
legend_orient='vertical',
line_width=2,
line_type='dotted')
overlap = Overlap(width='100%')
overlap.add(bar)
overlap.add(line, is_add_yaxis=True, yaxis_index=1)
grid = Grid(width=width)
grid.add(overlap, grid_right='10%')
return grid
def draw(self):
"""
:return:
"""
path = self.config.get('CTP', 'navfigpath')
lastNav = round(self.navDF['nav'].iloc[-1], 3)
dates = self.navDF['tradingDay'].apply(lambda s: str(s.date()))
grid = Grid('净值-回撤', width=2000, height=1000)
l = Line('净值')
nav = self.navDF['nav'].apply(lambda d: round(d, 3)).values
l.add(
'净值',
dates,
nav,
# yaxis_max='dataMax',
yaxis_min='dataMin',
mark_point=[
"max", {
"coord": [dates.iloc[-1], nav[-1]],
"name": "最新"
}
],
# line_color=,
is_legend_show=True,
line_width=2,
is_datazoom_show=True,
)
grid.add(l, grid_bottom='55%')
bar = Bar('回撤', title_top='50%')
dropdown = self.navDF['dropdown'].apply(lambda d: round(d, 3)).values
bar.add(
'回撤',
dates,
dropdown,
# yaxis_max='dataMax',
# yaxis_min='dataMin',
mark_point=[
"min", {
"coord": [dates.iloc[-1], dropdown[-1]],
"name": "最新"
}
],
is_legend_show=True,
legend_top='50%',
# is_datazoom_show=True,
)
grid.add(bar, grid_top='55%')
fn = '{}_nav.html'.format(self.userID)
_path = os.path.join(path, fn)
self.logger.info('生成净值 {}'.format(_path))
grid.render(_path)
def test_grid_top_bottom():
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", CLOTHES, v1, is_stack=True)
bar.add("商家B", CLOTHES, v2, is_stack=True)
line = Line("折线图示例", title_top="50%")
line.add(
"最高气温",
WEEK,
[11, 11, 15, 13, 12, 13, 10],
mark_point=["max", "min"],
mark_line=["average"],
)
line.add(
"最低气温",
WEEK,
[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.render()
def visualize():
max10 = getMaxTop()
min10 = getMinTop()
max_cities = list(map(lambda x: x['city'], max10))
max_top = list(map(lambda x: x['max'], max10))
min_cities = list(map(lambda x: x['city'], min10))
min_top = list(map(lambda x: x['min'], min10))
bar_max = Bar('中国最高温排行榜')
bar_max.add('', max_cities, max_top)
bar_min = Bar('中国最低温排行榜', title_top="50%")
bar_min.add('', min_cities, min_top)
grid = Grid(height=720)
grid.add(bar_max, grid_bottom="60%")
grid.add(bar_min, grid_top="60%")
grid.render('temperature.html')
print(max10)
print(min10)
def test_grid_add_overlap():
from pyecharts import Overlap
grid = Grid()
attr = ["{}月".format(i) for i in range(1, 13)]
v1 = [2.0, 4.9, 7.0, 23.2, 25.6, 76.7, 135.6, 162.2, 32.6, 20.0, 6.4, 3.3]
v2 = [2.6, 5.9, 9.0, 26.4, 28.7, 70.7, 175.6, 182.2, 48.7, 18.8, 6.0, 2.3]
v3 = [2.0, 2.2, 3.3, 4.5, 6.3, 10.2, 20.3, 23.4, 23.0, 16.5, 12.0, 6.2]
bar = Bar("Overlap+Grid 示例", width=1200, height=600, title_pos="40%")
bar.add("蒸发量", attr, v1)
bar.add(
"降水量",
attr,
v2,
yaxis_formatter=" ml",
yaxis_max=250,
legend_pos="85%",
legend_orient="vertical",
legend_top="45%",
)
line = Line()
line.add("平均温度", attr, v3, yaxis_formatter=" °C")
overlap = Overlap()
overlap.add(bar)
overlap.add(line, is_add_yaxis=True, yaxis_index=1)
grid.add(overlap, grid_right="20%")
grid.render()
def test_grid_inverse_yaxis():
attr = ["{}天".format(i) for i in range(1, 31)]
line_top = Line("折线图示例", width=1200, height=700)
line_top.add(
"最高气温",
attr,
[random.randint(20, 100) for i in range(30)],
mark_point=["max", "min"],
mark_line=["average"],
legend_pos="38%",
)
line_bottom = Line()
line_bottom.add(
"最低气温",
attr,
[random.randint(20, 100) for i in range(30)],
mark_point=["max", "min"],
mark_line=["average"],
is_yaxis_inverse=True,
xaxis_pos="top",
)
grid = Grid()
grid.add(line_top, grid_bottom="60%")
grid.add(line_bottom, grid_top="50%")
grid.render()
def test_grid_3():
line = Line("折线图示例", width=1200)
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_pos="20%")
attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
v1 = [11, 12, 13, 10, 10, 10]
pie = Pie("饼图示例", title_pos="55%")
pie.add("",
attr,
v1,
radius=[45, 65],
center=[65, 50],
legend_pos="80%",
legend_orient='vertical')
grid = Grid()
grid.add(line, grid_right="55%")
grid.add(pie, grid_left="60%")
grid.render()
def test_grid_line_pie():
line = Line("折线图示例", width=1200)
line.add(
"最高气温",
WEEK,
[11, 11, 15, 13, 12, 13, 10],
mark_point=["max", "min"],
mark_line=["average"],
)
line.add(
"最低气温",
WEEK,
[1, -2, 2, 5, 3, 2, 0],
mark_point=["max", "min"],
mark_line=["average"],
legend_pos="20%",
)
v1 = [11, 12, 13, 10, 10, 10]
pie = Pie("饼图示例", title_pos="55%")
pie.add(
"",
CLOTHES,
v1,
radius=[45, 65],
center=[65, 50],
legend_pos="80%",
legend_orient="vertical",
)
grid = Grid()
grid.add(line, grid_right="55%")
grid.add(pie, grid_left="60%")
grid.render()
def get_bar(item_name, item_name_list, item_num_list):
subtitle = 'Leo的好友地区分布统计柱状图'
bar = Bar(item_name,
page_title=item_name,
title_text_size=30,
title_pos='center',
subtitle=subtitle,
subtitle_text_size=25)
bar.add('',
item_name_list,
item_num_list,
title_pos='center',
xaxis_interval=0,
xaxis_rotate=27,
xaxis_label_textsize=20,
yaxis_label_textsize=20,
yaxis_name_pos='end',
yaxis_pos='%50')
bar.show_config()
grid = Grid(width=1300, height=800)
grid.add(bar,
grid_top='13%',
grid_bottom='23%',
grid_left='15%',
grid_right='15%')
out_file_name = './analyse/' + item_name + '.html'
grid.render(out_file_name)
def test_grid_add_overlap():
from pyecharts import Overlap
grid = Grid()
attr = ["{}月".format(i) for i in range(1, 13)]
v1 = [2.0, 4.9, 7.0, 23.2, 25.6, 76.7, 135.6, 162.2, 32.6, 20.0, 6.4, 3.3]
v2 = [2.6, 5.9, 9.0, 26.4, 28.7, 70.7, 175.6, 182.2, 48.7, 18.8, 6.0, 2.3]
v3 = [2.0, 2.2, 3.3, 4.5, 6.3, 10.2, 20.3, 23.4, 23.0, 16.5, 12.0, 6.2]
bar = Bar("Overlap+Grid 示例", width=1200, height=600, title_pos="40%")
bar.add("蒸发量", attr, v1)
bar.add(
"降水量",
attr,
v2,
yaxis_formatter=" ml",
yaxis_max=250,
legend_pos="85%",
legend_orient="vertical",
legend_top="45%",
)
line = Line()
line.add("平均温度", attr, v3, yaxis_formatter=" °C")
overlap = Overlap()
overlap.add(bar)
overlap.add(line, is_add_yaxis=True, yaxis_index=1)
grid.add(overlap, grid_right="20%")
grid.render()
def duotu1_fun():
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%")
return grid
def get_bar(title, name_list, num_list):
'''地区统计条形图'''
bar = Bar(title, page_title=title, title_text_size=30, title_pos='center')
bar.add("",
name_list,
num_list,
title_pos='center',
xaxis_interval=0,
xaxis_rotate=27,
xaxis_label_textcolor=20,
yaxis_label_textcolor=20,
yaxis_name_pos='end',
yaxis_pos="%50")
bar.show_config()
grid = Grid(width=1300, height=800)
grid.add(bar,
grid_top='13%',
grid_bottom='23%',
grid_left='15%',
grid_right='15%')
out_file_name = './analyse/' + title + '.html'
grid.render(out_file_name)
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 create_dash_yield(hours):
"""
create bar+line to show yield rate in the time interval
:param: kwargs: requests parameter
:return: grid: pyechart object
"""
data_cam0 = filmdata_all(hours=hours, cam=0)
data_cam1 = filmdata_all(hours=hours, cam=1)
# sort data by key
data_filter_cam0 = OrderedDict(
sorted(data_cam0.items(), key=lambda t: t[0]))
data_filter_cam1 = OrderedDict(
sorted(data_cam1.items(), key=lambda t: t[0]))
attr_cam0 = list(data_filter_cam0.keys())
cam0 = list(data_filter_cam0.values())
attr_cam1 = list(data_filter_cam1.keys())
cam1 = list(data_filter_cam1.values())
bar = Bar("產能柱狀圖", height=720)
bar.add(
"cam0",
attr_cam0,
cam0,
is_stack=True,
)
bar.add(
"cam1",
attr_cam1,
cam1,
is_stack=True,
)
line = Line("產能折線圖", title_top="50%")
line.add(
"cam0",
attr_cam0,
cam0,
mark_point=["max", "min"],
mark_line=["average"],
)
line.add(
"cam1",
attr_cam1,
cam1,
mark_point=["max", "min"],
mark_line=["average"],
is_datazoom_show=True,
)
grid = Grid(width='100%')
grid.add(bar, grid_bottom="60%")
grid.add(line, grid_top="60%")
grid.render()
return grid
def get_visual_TOP10():
bar1 = nums_Top10()
bar2 = food_top10()
bar3 = jd_top10()
grid = Grid(height=1000)
grid.add(bar1, grid_bottom="80%")
grid.add(bar2, grid_top="30%", grid_bottom="50%")
grid.add(bar3, grid_top="60%", grid_bottom="20%")
grid.render()
def test_grid_6():
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"],
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()
def get_bar(item_name,item_name_list,item_num_list):
subtitle = "微信公众号：大数据前沿"
bar = Bar(item_name,page_title = item_name,title_text_size=30,title_pos='center',\
subtitle = subtitle,subtitle_text_size = 25)
bar.add("", item_name_list, item_num_list,title_pos='center', xaxis_interval=0,xaxis_rotate=27,\
xaxis_label_textsize = 20,yaxis_label_textsize = 20,yaxis_name_pos='end',yaxis_pos = "%50")
bar.show_config()
grid = Grid(width=1300,height= 800)
grid.add(bar,grid_top = "13%",grid_bottom = "23%",grid_left = "15%",grid_right = "15%")
out_file_name = './analyse/'+item_name+'.html'
grid.render(out_file_name)
def test_grid_left_right():
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
scatter = Scatter(width=1200)
scatter.add("散点图示例", v1, v2, legend_pos="70%")
es = EffectScatter()
es.add("动态散点图示例", [11, 11, 15, 13, 12, 13, 10], [1, -2, 2, 5, 3, 2, 0],
effect_scale=6, legend_pos="20%")
grid = Grid()
grid.add(scatter, grid_left="60%")
grid.add(es, grid_right="60%")
grid.render()
def test_grid_four_direction():
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
bar = Bar("柱状图示例", height=720, width=1200, title_pos="65%")
bar.add("商家A", CLOTHES, v1, is_stack=True)
bar.add("商家B", CLOTHES, v2, is_stack=True, legend_pos="80%")
line = Line("折线图示例")
line.add("最高气温", WEEK, [11, 11, 15, 13, 12, 13, 10],
mark_point=["max", "min"], mark_line=["average"])
line.add("最低气温", WEEK, [1, -2, 2, 5, 3, 2, 0],
mark_point=["max", "min"], mark_line=["average"],
legend_pos="20%")
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
scatter = Scatter("散点图示例", title_top="50%", title_pos="65%")
scatter.add("scatter", v1, v2, legend_top="50%", legend_pos="80%")
es = EffectScatter("动态散点图示例", title_top="50%")
es.add("es", [11, 11, 15, 13, 12, 13, 10], [1, -2, 2, 5, 3, 2, 0],
effect_scale=6, legend_top="50%", legend_pos="20%")
grid = Grid()
grid.add(bar, grid_bottom="60%", grid_left="60%")
grid.add(line, grid_bottom="60%", grid_right="60%")
grid.add(scatter, grid_top="60%", grid_left="60%")
grid.add(es, grid_top="60%", grid_right="60%")
grid.render()
def test_grid_multiple_datazoom_index():
line = Line("折线图示例", width=1200, height=700)
line.add("最高气温", WEEK, [11, 11, 15, 13, 12, 13, 10],
mark_point=["max", "min"], mark_line=["average"])
line.add("最低气温", WEEK, [1, -2, 2, 5, 3, 2, 0],
mark_point=["max", "min"], legend_top="50%",
mark_line=["average"], 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()
def test_grid_heatmap_bar():
data = [[i, j, random.randint(0, 50)]
for i in range(24) for j in range(7)]
heatmap = HeatMap("热力图示例", height=700)
heatmap.add("热力图直角坐标系", X_TIME, Y_WEEK, data, is_visualmap=True,
visual_top="45%", visual_text_color="#000",
visual_orient='horizontal')
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
bar = Bar("柱状图示例", title_top="52%")
bar.add("商家A", CLOTHES, v1, is_stack=True)
bar.add("商家B", CLOTHES, v2, is_stack=True, legend_top="50%")
grid = Grid()
grid.add(heatmap, grid_bottom="60%")
grid.add(bar, grid_top="60%")
grid.render()
ip_sales = data.loc['iPhone销售额'].values
ip_unit = data.loc['iPhone销量'].values
bar = Bar("iPhone销售状况")
bar.add("iPhone销售额", years, ip_sales)
bar2 = Bar()
bar2.add("iPhone销量", years, ip_unit, bar_category_gap=25)
percent = ip_sales.astype('float') / net_sales.astype('float')
line = Line()
line.add("收入占比", years, percent, line_width=3, yaxis_margin=60, yaxis_pos='left')
ol = Overlap()
ol.add(bar)
ol.add(bar2, is_add_yaxis=True, yaxis_index=1)
ol.add(line, is_add_yaxis=True, yaxis_index=2)
grid = Grid()
grid.add(ol, grid_left="15%")
grid
# In[189]:
cn_sales = data.loc['国行'].values
bar = Bar("国行销售状况")
bar.add("国行", years, cn_sales)
percent = cn_sales.astype('float') / net_sales.astype('float')
line = Line()
line.add("国行占比", years, percent, line_width=3)
ol = Overlap()
ol.add(bar)
ol.add(line, is_add_yaxis=True, yaxis_index=1)
def test_page_grid_timeline_overlap():
# Grid
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
bar = Bar("柱状图示例", height=720, width=1200, title_pos="65%")
bar.add("商家A", CLOTHES, v1, is_stack=True)
bar.add("商家B", CLOTHES, v2, is_stack=True, legend_pos="80%")
line = Line("折线图示例")
line.add(
"最高气温",
WEEK,
[11, 11, 15, 13, 12, 13, 10],
mark_point=["max", "min"],
mark_line=["average"],
)
line.add(
"最低气温",
WEEK,
[1, -2, 2, 5, 3, 2, 0],
mark_point=["max", "min"],
mark_line=["average"],
legend_pos="20%",
)
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
scatter = Scatter("散点图示例", title_top="50%", title_pos="65%")
scatter.add("scatter", v1, v2, legend_top="50%", legend_pos="80%")
es = EffectScatter("动态散点图示例", title_top="50%")
es.add(
"es",
[11, 11, 15, 13, 12, 13, 10],
[1, -2, 2, 5, 3, 2, 0],
effect_scale=6,
legend_top="50%",
legend_pos="20%",
)
grid = Grid()
grid.add(bar, grid_bottom="60%", grid_left="60%")
grid.add(line, grid_bottom="60%", grid_right="60%")
grid.add(scatter, grid_top="60%", grid_left="60%")
grid.add(es, grid_top="60%", grid_right="60%")
# Timeline
bar_1 = Bar("2012 年销量", "数据纯属虚构")
bar_1.add("春季", CLOTHES, [randint(10, 100) for _ in range(6)])
bar_1.add("夏季", CLOTHES, [randint(10, 100) for _ in range(6)])
bar_1.add("秋季", CLOTHES, [randint(10, 100) for _ in range(6)])
bar_1.add("冬季", CLOTHES, [randint(10, 100) for _ in range(6)])
bar_2 = Bar("2013 年销量", "数据纯属虚构")
bar_2.add("春季", CLOTHES, [randint(10, 100) for _ in range(6)])
bar_2.add("夏季", CLOTHES, [randint(10, 100) for _ in range(6)])
bar_2.add("秋季", CLOTHES, [randint(10, 100) for _ in range(6)])
bar_2.add("冬季", CLOTHES, [randint(10, 100) for _ in range(6)])
bar_3 = Bar("2014 年销量", "数据纯属虚构")
bar_3.add("春季", CLOTHES, [randint(10, 100) for _ in range(6)])
bar_3.add("夏季", CLOTHES, [randint(10, 100) for _ in range(6)])
bar_3.add("秋季", CLOTHES, [randint(10, 100) for _ in range(6)])
bar_3.add("冬季", CLOTHES, [randint(10, 100) for _ in range(6)])
bar_4 = Bar("2015 年销量", "数据纯属虚构")
bar_4.add("春季", CLOTHES, [randint(10, 100) for _ in range(6)])
bar_4.add("夏季", CLOTHES, [randint(10, 100) for _ in range(6)])
bar_4.add("秋季", CLOTHES, [randint(10, 100) for _ in range(6)])
bar_4.add("冬季", CLOTHES, [randint(10, 100) for _ in range(6)])
bar_5 = Bar("2016 年销量", "数据纯属虚构", height=720, width=1200)
bar_5.add("春季", CLOTHES, [randint(10, 100) for _ in range(6)])
bar_5.add("夏季", CLOTHES, [randint(10, 100) for _ in range(6)])
bar_5.add("秋季", CLOTHES, [randint(10, 100) for _ in range(6)])
bar_5.add(
"冬季",
CLOTHES,
[randint(10, 100) for _ in range(6)],
is_legend_show=True,
)
timeline = Timeline(is_auto_play=True, timeline_bottom=0)
timeline.add(bar_1, "2012 年")
timeline.add(bar_2, "2013 年")
timeline.add(bar_3, "2014 年")
timeline.add(bar_4, "2015 年")
timeline.add(bar_5, "2016 年")
# Overlap
attr = ["{}月".format(i) for i in range(1, 13)]
v1 = [2.0, 4.9, 7.0, 23.2, 25.6, 76.7, 135.6, 162.2, 32.6, 20.0, 6.4, 3.3]
v2 = [2.6, 5.9, 9.0, 26.4, 28.7, 70.7, 175.6, 182.2, 48.7, 18.8, 6.0, 2.3]
v3 = [2.0, 2.2, 3.3, 4.5, 6.3, 10.2, 20.3, 23.4, 23.0, 16.5, 12.0, 6.2]
bar = Bar(height=720, width=1200)
bar.add("蒸发量", attr, v1)
bar.add("降水量", attr, v2, yaxis_formatter=" ml", yaxis_max=250)
line = Line()
line.add("平均温度", attr, v3, yaxis_formatter=" °C")
overlap = Overlap()
overlap.add(bar)
overlap.add(line, yaxis_index=1, is_add_yaxis=True)
page = Page()
page.add(grid)
page.add(timeline)
page.add(overlap)
page.render()
# In[14]:
rank_boxoffice = []
rank_element = []
from pyecharts import Bar
for i, element in enumerate(collections_detail.find({'boxoffice_num':{'$exists':True}}).sort('boxoffice_num',-1)):
rank_boxoffice.append(round(element['boxoffice_num']/10000,2))
rank_element.append(element['title'])
bar = Bar('2018总票房排名')
bar.add('', rank_element[:10], rank_boxoffice[:10], grid_bottom=0.5, xaxis_interval=0, is_toolbox_show=False, xaxis_rotate=45, is_legend_show=False, xaxis_name='名称', yaxis_name='票房（亿）', xaxis_name_gap=100, yaxis_name_gap=30)
grid = Grid()
grid.add(bar, grid_bottom="30%")
grid#.render('总排名.html')
# 上图为2018年电影总票房前十名，‘红海行动’票房第一，共36.51亿票房。前十名中，国产电影占了5部，且票房前四名都是国产片。好的国产片能拿到越来越多的票房了。
# In[15]:
genres = {}
other_list = ['武侠', '悬疑', '儿童', '历史', '家庭', '古装', '传记', '纪录片', '音乐', '歌舞', '恐怖', '灾难', '运动', '同性', '西部', '戏曲']
for i, element in enumerate(collections_detail.find({'boxoffice_num':{'$exists':True}})):
for genre in element['genres']:
if genre in other_list:
genre = '其它'
if genre not in genres:
class HKUFigure(object):
def __init__(self, width, height, num=1):
if num < 1:
self._num = 1
elif num > 4:
self._num = 4
else:
self._num = num
self._added_flag = [False, False, False, False]
self._grid = Grid(width=width, height=height)
self._width = width
self._height = height
self._axis_num = {}
self._axis_list = [None, None, None, None]
for i in range(self._num):
overlap = Overlap(width=width, height=height)
self._axis_num[overlap] = i
self._axis_list[i] = overlap
self._current_axis = 0
self._xaxis = None
self._label_color = []
def _repr_html_(self):
return self.get_grid()._repr_html_()
def get_current_axis(self):
return self._axis_list[self._current_axis]
def get_axis(self, pos):
return self._axis_list[pos]
def get_grid(self):
return self._grid
def set_xaxis(self, xaxis):
self._xaxis = xaxis
def get_xaxis(self):
return self._xaxis
def add_axis(self, axis):
if axis not in self._axis_num:
return
pos = self._axis_num[axis]
self._current_axis = pos
self._added_flag[pos] = True
self._flush()
return axis
def _flush(self):
self._grid = Grid(width=self._width, height=self._height)
for pos, axis in enumerate(self._axis_list):
if axis is None or axis.options is None \
or axis.options.get('yAxis') is None:
continue
if self._num == 1:
self._grid.add(axis, grid_top="8%")
elif self._num == 2:
if pos == 0:
self._grid.add(axis, grid_top="8%", grid_height='52%')
else:
self._grid.add(axis, grid_top="62%")
elif self._num == 3:
if pos == 0:
self._grid.add(axis, grid_top='8%', grid_height='40%')
elif pos == 1:
self._grid.add(axis, grid_top='50%', grid_height='19%')
else:
self._grid.add(axis, grid_bottom='10%', grid_height='19%')
else:
if pos == 0:
self._grid.add(axis, grid_top='8%', grid_height='30%')
elif pos == 1:
self._grid.add(axis, grid_top='40%', grid_height='18%')
elif pos == 2:
self._grid.add(axis, grid_top='60%', grid_height='15%')
else:
self._grid.add(axis, grid_top='77%', grid_height='15%')
def get_style(self, axis, **kwargs):
pos = self._axis_num[axis]
num = self._num
style = Style()
default_datazoom_type = 'both'
result = None
if num == 1:
result = style.add(legend_text_size='10',
legend_top='8%',
legend_pos='10%',
legend_orient='vertical',
is_symbol_show=False,
is_datazoom_show=True,
datazoom_type=default_datazoom_type)
elif num == 2:
if pos == 0:
result = style.add(legend_text_size='10',
legend_top='8%',
legend_pos='10%',
legend_orient='vertical',
is_symbol_show=False,
is_datazoom_show=True,
datazoom_type=default_datazoom_type,
datazoom_xaxis_index=[0,1],
is_xaxis_show=False)
else:
result = style.add(legend_text_size='10',
legend_top='62%',
legend_pos='10%',
#legend_orient='vertical',
is_symbol_show=False,
is_datazoom_show=True,
datazoom_type=default_datazoom_type,
datazoom_xaxis_index=[0,1],
is_xaxis_show=True)
elif num == 3:
if pos == 0:
result = style.add(legend_text_size='10',
legend_top='8%',
legend_pos='10%',
legend_orient='vertical',
is_symbol_show=False,
is_datazoom_show=True,
datazoom_type=default_datazoom_type,
datazoom_xaxis_index=[0,1,2],
is_xaxis_show=False)
elif pos == 1:
result = style.add(legend_text_size='10',
legend_top='50%',
legend_pos='10%',
#legend_orient='vertical',
is_symbol_show=False,
is_datazoom_show=True,
datazoom_type=default_datazoom_type,
datazoom_xaxis_index=[0,1,2],
is_xaxis_show=False)
else:
result = style.add(legend_text_size='10',
legend_top='71%',
legend_pos='10%',
#legend_orient='vertical',
is_symbol_show=False,
is_datazoom_show=True,
datazoom_type=default_datazoom_type,
datazoom_xaxis_index=[0,1,2],
is_xaxis_show=True)
else:
if pos == 0:
result = style.add(legend_text_size='10',
legend_top='8%',
legend_pos='10%',
legend_orient='vertical',
is_symbol_show=False,
is_datazoom_show=True,
datazoom_type=default_datazoom_type,
datazoom_xaxis_index=[0,1,2,3],
is_xaxis_show=False)
elif pos == 1:
result = style.add(legend_text_size='10',
legend_top='40%',
legend_pos='10%',
#legend_orient='vertical',
is_symbol_show=False,
is_datazoom_show=True,
datazoom_type=default_datazoom_type,
datazoom_xaxis_index=[0,1,2,3],
is_xaxis_show=False)
elif pos == 2:
result = style.add(legend_text_size='10',
legend_top='60%',
legend_pos='10%',
#legend_orient='vertical',
is_symbol_show=False,
is_datazoom_show=True,
datazoom_type=default_datazoom_type,
datazoom_xaxis_index=[0,1,2,3],
is_xaxis_show=False)
else:
result = style.add(legend_text_size='10',
legend_top='77%',
legend_pos='10%',
#legend_orient='vertical',
is_symbol_show=False,
is_datazoom_show=True,
datazoom_type=default_datazoom_type,
datazoom_xaxis_index=[0,1,2,3],
is_xaxis_show=True)
color_map = {'r': '#CD0000',
'g': '#008B00',
'b': '#0000EE',
'c':'#40E0D0',
'm': '#CD00CD',
'y': '#EE9A00',
'k': '#000000',
'w': '#FFFFFF'
}
line_map = {'-' : 'solid',
'--': 'dashed',
':' : 'dotted'}
for item in kwargs.items():
if 'color' == item[0]:
color = color_map[item[1]] if item[1] in color_map else color_map['r']
result['line_color'] = color
self._label_color += [color]
result['label_color'] = self._label_color
elif 'linestyle' == item[0]:
result['line_type'] = line_map[item[1]] if item[1] in line_map else line_map['-']
else:
result[item[0]] = item[1]
return result
