def main():
dutPl0 = []
dutpl1 = []
maxCntPl0 = []
maxCntPl1 = []
page = Page("Cluster Padding Figure")
txtFiles = [name for name in os.listdir('./') if name.endswith('.txt')]
for textLogName in txtFiles:
waferNum = re.split(r'_', textLogName)
with open(textLogName, 'rt') as clusterFile:
for line in clusterFile:
if re.match(r'IncomingBBKCount[A-Za-z0-9_.\+\-\*\/\s]*BBKP', line):
splitColon = re.split(r'\s*[:]\s*', line)
splitColon1 = splitColon[0]
splitColon2 = splitColon[1]
splitColon3 = splitColon[2]
listBlk = re.split(r'\s*[\s]\s*', splitColon3)
padBlk = paddingBlk(listBlk)
maxCnt = clusterBlk(padBlk)
splitSpace = re.split(r'\s*[\s]\s*', splitColon1)
intDut = int(splitSpace[1].replace('DUT', ''))
if splitSpace[2] == "BBKP0":
dutPl0.append(intDut)
maxCntPl0.append(maxCnt)
else:
dutpl1.append(intDut)
maxCntPl1.append(maxCnt)
scatter = Scatter(waferNum[2])
scatter.add("PL0", dutPl0, maxCntPl0, xaxis_name = "DUT", yaxis_name = "Max Padding BB", is_more_utils = True)
scatter.add("PL1", dutpl1, maxCntPl1, xaxis_name = "DUT", yaxis_name = "Max Padding BB", is_more_utils = True)
page.add(scatter)
page.render()
def test_page():
page = Page()
line = Line("折线图示例")
line.chart_id = "id_my_cell_line"
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"],
)
# pie
v1 = [11, 12, 13, 10, 10, 10]
pie = Pie("饼图-圆环图示例", title_pos="center", width="600px")
pie.add(
"",
CLOTHES,
v1,
radius=[40, 75],
label_text_color=None,
is_label_show=True,
legend_orient="vertical",
legend_pos="left",
)
page.add([line, pie, create_a_bar(TITLE)])
# Start render and test
html = page._repr_html_()
# Test base html structure
assert html.count("<script>") == html.count("</script>") == 2
assert html.count("<div") == html.count("</div>") == 3
assert html.count("require.config") == html.count("function(echarts)") == 1
# Test some chart attributes
json_encoded_title = json.dumps(TITLE)
assert json_encoded_title in html
assert "nbextensions/echarts" in html # default jshost
assert html.count("height:400px") == 3
assert html.count("width:600px") == 1
assert html.count("width:800px") == 2
assert html.count("id_my_cell_line") == 6
def main():
'''
# 测试词云图
x = [
"python", "lxj", "zj", "big data", "python", "lxj", "zj", "big data",
"python", "lxj", "zj", "big data", "python", "lxj", "zj", "big data"
]
y = [
10000, 8000, 6000, 3000, 10000, 8000, 6000, 3000,
10000, 8000, 6000, 3000, 10000, 8000, 6000, 3000
]
label = "词云"
wordCloud(x, y, label)
'''
'''
# 测试统计图表
x = ["衬衫", "袜子", "高跟鞋", "羊毛衫", "裤子"]
y1 = [5, 10, 38, 75, 90]
y2 = [15, 4, 70, 25, 190]
label = "服装"
type = 2
get_charts(x, y, label, type)
'''
'''
# 测试多个统计图
page = Page()
get_otherCharts(page)
'''
# 测试三维散点图
page = Page()
get_scatter3D(page)
def create_experience(data, title):
page = Page()
style = Style(width=800,
title_pos="center",
height=400,
background_color='#c4ccd3')
kwargs = dict(radius=(40, 75),
label_text_color=None,
is_label_show=True,
legend_orient='her',
legend_pos='left')
experience_chart = Pie(title, **style.init_style)
attr, value = experience_chart.cast(data)
experience_chart.add("", attr, value, **kwargs)
page.add(experience_chart)
return page
def create_charts():
page = Page()
style = Style(width=WIDTH, height=HEIGHT)
df = pd.read_csv('./data_cleaned.csv')
STREET_NAME = df.STREET_NAME.value_counts()
chart = Bar("街道种类", **style.init_style)
chart.add(
"",
STREET_NAME.index,
STREET_NAME.values,
mark_point=["max", "min"],
mark_line=["average"],
is_stack=True,
)
page.add(chart)
chart = Timeline(is_auto_play=True,
timeline_bottom=0,
width=WIDTH,
height=HEIGHT)
for name, c in df.groupby('STREET_NAME'):
EVENT_TYPE_NAME = c.EVENT_TYPE_NAME.value_counts()
chart_1 = Bar("各社区事件类型", **style.init_style)
chart_1.add("",
EVENT_TYPE_NAME.index,
EVENT_TYPE_NAME.values,
mark_point=["max", "min"],
mark_line=["average"],
is_stack=True)
chart.add(chart_1, name)
page.add(chart)
table = pd.pivot_table(df,
index=['STREET_NAME'],
columns=['EVENT_TYPE_NAME'],
values=['SUB_TYPE_NAME'],
aggfunc='count',
fill_value=0,
margins=1)
table = table.ix[:-1, :-1]
comm = list(table.index)
name = [i[1] for i in table]
value = [[i, j, float(table.values[i][j])] for i in range(len(comm))
for j in range(len(name))]
chart = HeatMap("街道与事件热力图", width=WIDTH, height=HEIGHT)
chart.add("",
comm,
name,
value,
is_visualmap=True,
visual_text_color="#000",
visual_orient='horizontal')
page.add(chart)
return page
def create_charts():
page = Page()
style = Style(width=WIDTH, height=HEIGHT)
attr = ["{}天".format(i) for i in range(30)]
v1 = [random.randint(1, 30) for _ in range(30)]
chart = Bar("柱状图-数据缩放(inside)", **style.init_style)
chart.add("",
attr,
v1,
is_datazoom_show=True,
datazoom_type='inside',
datazoom_range=[10, 60])
page.add(chart)
return page
def create_clound_charts(data, title):
'''词云图'''
page = Page()
# print(data)
style = Style(
width=2000,
height=1000,
title_pos="center",
)
chart = WordCloud(title, **style.init_style)
attr, value = chart.cast(data)
chart.add("", attr, value, shape='circle')
page.add(chart)
return page
def getProvinceCount(cityCount,countName):
indexs = []
counts = []
for index in cityCount.index:
indexs.append(index)
counts.append(cityCount[index])
page = Page()
labels = [indexs]
sizes = [counts]
attr = indexs
v1 = counts
bar = Bar(countName)
bar.add("地区分布", attr, v1, is_stack=True, is_label_show=True, is_datazoom_show=True,
is_random=True)
page.add(bar)
bar.show_config()
bar.render()
def create_three():
page = Page(page_title=TEST_PAGE_TITLE)
# bar
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
bar = Bar("柱状图数据堆叠示例")
bar.add("商家A", CLOTHES, v1, is_stack=True)
bar.add("商家B", CLOTHES, v2, is_stack=True)
page.add(bar)
# scatter3D
import random
data = [
[random.randint(0, 100),
random.randint(0, 100),
random.randint(0, 100)] for _ in range(80)
]
scatter3d = Scatter3D("3D 散点图示例", width=1200, height=600)
scatter3d.add("", data, is_visualmap=True, visual_range_color=RANGE_COLOR)
page.add(scatter3d)
# guangdong
value = [20, 190, 253, 77, 65]
attr = ['汕头市', '汕尾市', '揭阳市', '阳江市', '肇庆市']
map = Map("广东地图示例", width=1200, height=600)
map.add("", attr, value, maptype='广东', is_visualmap=True,
visual_text_color='#000')
page.add(map)
return page
def create_charts():
page = Page()
data = [
['2015/11/08', 10, 'DQ'], ['2015/11/09', 15, 'DQ'], ['2015/11/10', 35, 'DQ'],
['2015/11/14', 7, 'DQ'], ['2015/11/15', 2, 'DQ'], ['2015/11/16', 17, 'DQ'],
['2015/11/17', 33, 'DQ'], ['2015/11/18', 40, 'DQ'], ['2015/11/19', 32, 'DQ'],
['2015/11/20', 26, 'DQ'], ['2015/11/21', 35, 'DQ'], ['2015/11/22', 40, 'DQ'],
['2015/11/23', 32, 'DQ'], ['2015/11/24', 26, 'DQ'], ['2015/11/25', 22, 'DQ'],
['2015/11/08', 35, 'TY'], ['2015/11/09', 36, 'TY'], ['2015/11/10', 37, 'TY'],
['2015/11/11', 22, 'TY'], ['2015/11/12', 24, 'TY'], ['2015/11/13', 26, 'TY'],
['2015/11/14', 34, 'TY'], ['2015/11/15', 21, 'TY'], ['2015/11/16', 18, 'TY'],
['2015/11/17', 45, 'TY'], ['2015/11/18', 32, 'TY'], ['2015/11/19', 35, 'TY'],
['2015/11/20', 30, 'TY'], ['2015/11/21', 28, 'TY'], ['2015/11/22', 27, 'TY'],
['2015/11/23', 26, 'TY'], ['2015/11/24', 15, 'TY'], ['2015/11/25', 30, 'TY'],
['2015/11/26', 35, 'TY'], ['2015/11/27', 42, 'TY'], ['2015/11/28', 42, 'TY'],
['2015/11/08', 21, 'SS'], ['2015/11/09', 25, 'SS'], ['2015/11/10', 27, 'SS'],
['2015/11/11', 23, 'SS'], ['2015/11/12', 24, 'SS'], ['2015/11/13', 21, 'SS'],
['2015/11/14', 35, 'SS'], ['2015/11/15', 39, 'SS'], ['2015/11/16', 40, 'SS'],
['2015/11/17', 36, 'SS'], ['2015/11/18', 33, 'SS'], ['2015/11/19', 43, 'SS'],
['2015/11/20', 40, 'SS'], ['2015/11/21', 34, 'SS'], ['2015/11/22', 28, 'SS'],
['2015/11/14', 7, 'QG'], ['2015/11/15', 2, 'QG'], ['2015/11/16', 17, 'QG'],
['2015/11/17', 33, 'QG'], ['2015/11/18', 40, 'QG'], ['2015/11/19', 32, 'QG'],
['2015/11/20', 26, 'QG'], ['2015/11/21', 35, 'QG'], ['2015/11/22', 40, 'QG'],
['2015/11/23', 32, 'QG'], ['2015/11/24', 26, 'QG'], ['2015/11/25', 22, 'QG'],
['2015/11/26', 16, 'QG'], ['2015/11/27', 22, 'QG'], ['2015/11/28', 10, 'QG'],
['2015/11/08', 10, 'SY'], ['2015/11/09', 15, 'SY'], ['2015/11/10', 35, 'SY'],
['2015/11/11', 38, 'SY'], ['2015/11/12', 22, 'SY'], ['2015/11/13', 16, 'SY'],
['2015/11/14', 7, 'SY'], ['2015/11/15', 2, 'SY'], ['2015/11/16', 17, 'SY'],
['2015/11/17', 33, 'SY'], ['2015/11/18', 40, 'SY'], ['2015/11/19', 32, 'SY'],
['2015/11/20', 26, 'SY'], ['2015/11/21', 35, 'SY'], ['2015/11/22', 4, 'SY'],
['2015/11/23', 32, 'SY'], ['2015/11/24', 26, 'SY'], ['2015/11/25', 22, 'SY'],
['2015/11/26', 16, 'SY'], ['2015/11/27', 22, 'SY'], ['2015/11/28', 10, 'SY'],
['2015/11/08', 10, 'DD'], ['2015/11/09', 15, 'DD'], ['2015/11/10', 35, 'DD'],
['2015/11/11', 38, 'DD'], ['2015/11/12', 22, 'DD'], ['2015/11/13', 16, 'DD'],
['2015/11/14', 7, 'DD'], ['2015/11/15', 2, 'DD'], ['2015/11/16', 17, 'DD'],
['2015/11/17', 33, 'DD'], ['2015/11/18', 4, 'DD'], ['2015/11/19', 32, 'DD'],
['2015/11/20', 26, 'DD'], ['2015/11/21', 35, 'DD'], ['2015/11/22', 40, 'DD'],
['2015/11/23', 32, 'DD'], ['2015/11/24', 26, 'DD'], ['2015/11/25', 22, 'DD']
]
chart = ThemeRiver("主题河流图", width=WIDTH, height=HEIGHT)
chart.add(['DQ', 'TY', 'SS', 'QG', 'SY', 'DD'], data, is_label_show=True)
page.add(chart)
return page
def scatter3d():
from pyecharts import Scatter3D, Page, Bar
import random
page = Page()
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("3D柱状图示例")
bar.add('商家A', attr, v1)
bar.add('商家B', attr, v2)
page.add(bar)
data = [[
random.randint(0, 100),
random.randint(0, 100),
random.randint(0, 100)
] for _ in range(80)]
range_color = [
'#313695', '#4575b4', '#74add1', '#abd9e9', '#e0f3f8', '#ffffbf',
'#fee090', '#fdae61', '#f46d43', '#d73027', '#a50026'
]
scatter3D = Scatter3D("3D 散点图 demo", width=1200, height=600)
scatter3D.add("", data, is_visualmap=True, visual_range_color=range_color)
page.add(scatter3D)
return page.render_embed()
def make_plot(city):
city_dict = make_city_dict()
# 倒入包
data = pd.read_csv('csv_files/%s/room_type.csv' % city)
# 读取数据
configure(global_theme='vintage')
# 设置主题
attr = data["室厅厨卫 布局"].tolist()
v1 = data["数量"].tolist()
# 数据处理
bar = Bar(title="%s各二手房 室厅厨卫 布局 条形图" % city_dict[city],
width=1200,
height=600)
bar.add(
"数量",
attr,
v1,
mark_point=["max", "min"],
xaxis_rotate=35,
mark_point_textcolor='#000',
mark_point_symbol="pin",
)
pie = Pie("%s二手房 室厅厨卫 布局 饼状图" % city_dict[city],
title_pos="left",
width=1200,
height=600)
pie.add("",
attr,
v1,
radius=[40, 80],
label_text_color=None,
is_label_show=True,
legend_orient="vertical",
legend_pos="right",
is_toolbox_show=False)
page = Page()
page.add_chart(bar)
page.add_chart(pie)
return page
def page_all_bivar(data,num_fea,cat_fea,tar,draw_order=['none'],out=False,file_name='bivar.html', draw_type='line',bins=20,tree_depth=4,woe = None,d_reorder=False, custom_bin=[],cut_num=None,cut_start=None,fill_na=-99999): #print all bivar picture on one html page #page_all_bivar(data=df,num_fea=numerical_col,cat_fea=category_col,tar='pass',out=True) page = Page() if len(num_fea) != 0: for c in data[num_fea]: keep_draw = True for k in draw_order: while keep_draw == True: try: temp = draw.bivar(data=data,feature=c,target=tar,t_type='c',draw_type='line', bins=20,tree_depth=4,woe = None,d_reorder=False,custom_bin=[],cut_num=None, cut_start=None,fill_na=-99999) page.add(temp) keep_draw = False except: continue if len(cat_fea) != 0: for d in data[cat_fea]: try: temp = draw.bivar(data=data,feature=d,target=tar,t_type='d',d_reorder = d_reorder) page.add(temp) except: continue if len(num_fea+cat_fea) == 0: return 'no such feature in function' if out: return page.render(file_name) else: return page
def __init__(self, path, ispage=True):
self.page = Page()
self.overlap = Overlap()
self.ispage = ispage
self.path = path
self.range_color = [
"#313695",
"#4575b4",
"#74add1",
"#abd9e9",
"#e0f3f8",
"#ffffbf",
"#fee090",
"#fdae61",
"#f46d43",
"#d73027",
"#a50026",
]
def top_rend():
page = Page()
allmovietype = filewr(movie_type_top, movietype)
allcritic = filewr(all_type_critic_top, allresultfile)
allmoviecritic = filewr(movie_name_top, mostmoviefile)
allonecritic = filewr(movie_critic_top, moviecritic)
mostmovietype = visual(allmovietype, "电影类型数量排行榜", "电影数")
mosttypecritic = visual(allcritic, "电影类型评论排行榜", "评论数量")
mostmoviecritic = visual(allmoviecritic, "电影评论排行榜", "评论数量")
mostonecritic = visual(allonecritic, "评论中词汇排行榜", "词语权重")
page.add(mostmovietype)
page.add(mosttypecritic)
page.add(mostmoviecritic)
page.add(mostonecritic)
return page
def test_page_add_chart():
nc = (Page().add_chart(MagicMock(page_title="Line-Chart"),
name="line").add_chart(
MagicMock(page_title="Bar-Chart")))
nc["map"] = MagicMock(page_title="Map-Chart")
eq_("Line-Chart", nc["line"].page_title)
eq_("Bar-Chart", nc["c1"].page_title)
assert_list_equal(["Line-Chart", "Bar-Chart", "Map-Chart"],
[c.page_title for c in nc])
def test_page_init():
line = MagicMock(page_title="Line-Chart")
bar = MagicMock(page_title="Bar-Chart")
page = Page(line=line, bar=bar)
eq_("Line-Chart", page["line"].page_title)
assert "line" in page
assert "bar" in page
if PY36:
eq_("Line-Chart", page[0].page_title)
def get_all_div():
page = Page()
t1 = create_wordcloud()
t2 = create_map()
t3 = create_pie()
t4 = create_bar()
page.add(t1)
page.add(t2)
page.add(t3)
page.add(t4)
page.render()
def data_show1(): # 公交IC卡分析
data = getICdata()
minute = 60
line_no = list(data.line_id.unique())
# 1
# data_101 = data[data.line_id.isin(line_no)].sort_values(by='TXNDATE').reset_index(drop=True)
# 2
data_101 = data.sort_values(by='TXNDATE').reset_index(drop=True)
data_101['time_2_seconds'] = data_101.TXNDATE.apply(lambda x: x.time())
data_101['time_2_seconds'] = data_101['time_2_seconds'].map(str).map(t2s)
# 站点客流量排序
station_num = data_101['STATION_NAME'].value_counts().sort_values(
ascending=False) # 大到小
station_num_head10 = station_num.head(10)
# 1个小时一划分客流量
time_2_seconds_bins = [
i * minute * 60 for i in range(int(24 / (minute / 60)) + 1)
]
labels = [i for i in range(1, int(24 / (minute / 60)) + 1)]
Time_groups = pd.cut(data_101['time_2_seconds'],
time_2_seconds_bins,
labels=labels).rename('time_2_seconds_labels')
passenger_num = Time_groups.value_counts().sort_index()
from pyecharts import Bar, Scatter3D, EffectScatter, Overlap, Line, Pie
from pyecharts import Page, configure
configure(global_theme='shine') # 更改主题
page = Page()
bar1 = Bar("乘客量top10的站点", "图一")
bar1.add("乘客量top10的站点",
station_num_head10.index,
station_num_head10.values,
xaxis_rotate=45,
is_mor_utils=True)
line1 = Line()
line1.add("乘客量top10的站点(折线图)", station_num_head10.index,
station_num_head10.values)
overlap_1 = Overlap()
overlap_1.add(bar1)
overlap_1.add(line1)
bar2 = Bar("全天一小时时段区间乘客登车数量", "图二")
bar2.add("不同时段区间乘客数量",
passenger_num.index,
passenger_num.values,
xaxis_rotate=90,
is_mor_utils=True,
mark_point=["min", "max"])
# bar.print_echarts_options() # 该行只为了打印配置项，方便调试时使用
page.add(overlap_1)
page.add(bar2)
page.render('app/templates/render/passenger_top10.html') # 生成本地 HTML 文件
return render_template('render/passenger_top10.html')
def CreateCharts():
page = Page()
# 获取到 Chart1() 函数绘制的图，并添加到 page 中
chart1 = Chart1()
page.add(chart1)
# 获取到 Chart2() 函数绘制的图，并添加到 page 中
chart2 = Chart2()
page.add(chart2)
chart3 = Chart3()
page.add(chart3)
chart4 = Chart4()
page.add(chart4)
app.kill()
return page
def get_all_div(sou1):
page = Page()
t1 = create_wordcloud(sou1)
t2 = create_map()
t3 = create_pie()
t4 = create_bar()
page.add(t1)
page.add(t2)
page.add(t3)
page.add(t4)
name = str(sou1) + '.html'
page.render(name)
def create_charts():
page = Page()
style = Style(width=1100, height=600)
# value = [155, 10, 66, 78]
# attr = ["福建", "山东", "北京", "上海"]
# chart = Map("全国地图", **style.init_style)
# chart.add("", attr, value, maptype='china', is_label_show=True)
# page.add(chart)
value = [155, 10, 66, 78, 33, 80, 190, 53, 49.6]
attr = ["福建", "山东", "北京", "上海", "甘肃", "新疆", "河南", "广西", "西藏"]
chart = Map("全国地图-视觉通道", **style.init_style)
chart.add("",
attr,
value,
maptype='china',
is_visualmap=True,
visual_text_color='#000')
page.add(chart)
# value = [20, 190, 253, 77, 65]
# attr = ['汕头市', '汕尾市', '揭阳市', '阳江市', '肇庆市']
# chart = Map("广东地图", **style.init_style)
# chart.add("", attr, value, maptype='广东',
# is_visualmap=True, visual_text_color='#000')
# page.add(chart)
#
# value = [95.1, 23.2, 43.3, 66.4, 88.5, 0.1]
# attr = ["China", "Canada", "Brazil", "Russia",
# "United States", "Unknown Country"]
# chart = Map("世界地图 - 带标记点", **style.init_style)
# chart.add("", attr, value, maptype="world", is_visualmap=True,
# visual_text_color='#000')
# page.add(chart)
#
# chart = Map("世界地图 - 不带标记点", **style.init_style)
# chart.add("", attr, value, maptype="world", is_visualmap=True,
# is_map_symbol_show=False, visual_text_color='#000')
# page.add(chart)
return page
def render_page(self, sex_dict, province_dict, word_list):
"""
渲染页面多图
"""
page = Page()
pie = self.get_sex_pie(sex_dict)
map = self.get_province_map(province_dict)
wordcloud = self.get_wordcloud(word_list)
page.add(pie)
page.add(map)
page.add(wordcloud)
page.render()
def page(player_id: int = None):
# init_list = json_load('matches')
if not player_id:
init_list = get_player_matches_json(129689355)
else:
init_list = get_player_matches_json(player_id)
# print(len(init_list))
init_dict = {}
data = []
for row in init_list:
start_time = datetime.fromtimestamp(
row['start_time']).strftime("%Y-%m-%d")
if start_time not in init_dict:
init_dict[start_time] = 1
else:
init_dict[start_time] += 1
for key in init_dict:
val = init_dict[key]
key = datetime.strptime(key, "%Y-%m-%d")
tmp = []
tmp.extend((key, val))
data.append(tmp)
page = Page()
year = int(datetime.today().strftime("%Y"))
for i in range(year, 2016, -1):
heatmap = HeatMap(height=250, width=1100)
heatmap.add("",
data,
is_calendar_heatmap=True,
visual_text_color='#000',
visual_range_text=['', ''],
visual_range=[0, 15],
calendar_cell_size=['auto', 20],
is_visualmap=True,
calendar_date_range=str(i),
visual_orient="horizontal",
visual_pos="center",
visual_top="90%",
is_piecewise=True)
page.add(heatmap)
return page
def geo_map(data, title):
page = Page()
style = Style(title_color="#fff",
title_pos="center",
width=800,
height=400,
background_color='#c4ccd3')
kwargs = dict(maptype='china',
is_visualmap=True,
type="effectScatter",
is_legend_show=False,
geo_emphasis_color='c4ccd3',
visual_text_color='#2f4554')
# 创建地图模型
chart = Geo(title, "", **style.init_style)
attr, value = chart.cast(data)
# 添加数据
chart.add("", attr, value, **kwargs)
page.add_chart(chart)
return page
async def run_benchmark(option):
urls = option['urls']
# convert to string in order to used in dict
conns = [str(conn) for conn in option['connections']]
for conn in conns:
benchmarks[conn] = {}
cpu_usage[conn] = {}
for url in urls:
benchmarks[conn][url] = []
cpu_usage[conn][url] = []
benchmark_task = asyncio.ensure_future(run_wrk(url, conn, option))
monitor_task = asyncio.ensure_future(
monitor(url, conn, option['duration']))
# TODO: 这里需要修改为如果主任务异常退出，则monitor任务也停止
done, pending = await asyncio.wait(
[benchmark_task, monitor_task],
return_when=asyncio.ALL_COMPLETED,
)
for task in pending:
task.cancel()
print('Result: {} \n{}'.format(benchmarks, cpu_usage))
page = Page()
tps_bar = Bar("测试结果", "")
cpu_line = Line("CPU占用率")
v = {}
for conn in conns:
v[conn] = []
for url in urls:
v[conn].append(benchmarks[conn][url])
for conn in conns:
tps_bar.add(conn + '连接', urls, v[conn])
for url in urls:
cpu_line.add(url + ' ' + conn + '连接',
[i for i in range(option['duration'])],
cpu_usage[conn][url],
yaxis_max=100,
yaxis_formatter=" %")
page.add(tps_bar)
page.add(cpu_line)
page.render()
print('Result on: http://{}:{}'.format(get_ip(), PORT))
server = HTTPServer(('0.0.0.0', PORT), MyServer)
server.serve_forever()
server.server_close()
def get_echarts_instance(self, *args, **kwargs):
device_data = models.Device.objects.values('device_type').annotate(count=Count('device_type'))
device_types, counters = fetch(device_data, 'device_type', 'count')
pie = Pie("设备分类", page_title='设备分类', width='100%')
pie.add("设备分类", device_types, counters, is_label_show=True)
battery_lifes = models.Device.objects.values('name', 'battery_life')
names, lifes = fetch(battery_lifes, 'name', 'battery_life')
bar = Bar('设备电量', page_title='设备电量', width='100%')
bar.add("设备电量", names, lifes)
page = Page.from_charts(pie, bar)
return page
def creat_lan_charts(data_list):
page = Page()
style = Style(title_color="#fff",
title_pos="center",
width=1200,
height=600,
background_color='#404a59')
chart = Geo("全国主要城市空气质量", "data from pm2.5", **style.init_style)
attr, value = chart.cast(data_list)
chart.add("",
attr,
value,
type="heatmap",
is_visualmap=True,
visual_range=[0, 200],
visual_text_color='#fff',
is_legend_show=False)
page.add(chart)
return page
def plot_line_graph():
page = Page('back_testing')
line = Line("K 线图-dataZoom 垂直布局", width=1300, height=400, title_pos="left")
line.add(
"日K",
["2017/7/{}".format(i + 1) for i in range(31)],
[random.randint(1, 2000) for _ in range(31)],
tooltip_trigger="axis",
tooltip_axispointer_type='cross',
mark_line=["max", 'min'],
legend_top="3%",
mark_point=['average', 'max', 'min'],
is_smooth=True,
line_color='#5296de',
line_width=2.5,
# yaxis_type="log",
)
line.add("日收益", ["2017/7/{}".format(i + 1) for i in range(31)],
[random.randint(1, 2000) for _ in range(31)],
tooltip_trigger="axis",
mark_point=['average', 'max', 'min'],
mark_line=["max", 'min'],
is_datazoom_show=True,
legend_top="3%",
is_smooth=True,
line_color='#082039',
line_width=2.5,
**style.init_style
# yaxis_type="log",
)
page.add(line)
# line.show_config()
kline = Kline("K 线图-dataZoom 水平布局",
width=1300,
height=400,
title_pos="left")
kline.add("日K", ["2017/7/{}".format(i + 1) for i in range(31)],
data,
mark_point=["max"],
is_datazoom_show=True,
**style.init_style)
page.add(kline)
# kline.show_config()
page.render(FILE_DIR + 'line_graph.html')
def create_two_bars():
page = Page()
# bar
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("柱状图数据堆叠示例")
bar.add("商家A", attr, v1, is_stack=True)
bar.add("商家B", attr, v2, is_stack=True)
page.add(bar)
# scatter3D
import random
data = [[
random.randint(0, 100),
random.randint(0, 100),
random.randint(0, 100)
] for _ in range(80)]
range_color = [
'#313695', '#4575b4', '#74add1', '#abd9e9', '#e0f3f8', '#ffffbf',
'#fee090', '#fdae61', '#f46d43', '#d73027', '#a50026'
]
scatter3D = Scatter3D("3D 散点图示例", width=1200, height=600)
scatter3D.add("", data, is_visualmap=True, visual_range_color=range_color)
page.add(scatter3D)
return page
def main():
res_list = parse_procrank(sys.argv[1])
df = pd.DataFrame(res_list).fillna(0)
ts = df['ts']
df.drop(columns='ts', inplace=True)
local_list = []
max_list = []
for column in df.columns:
local_max = max(df[column])
max_list.append(local_max)
local_map = {
'comm': column,
'memory': df[column].tolist(),
'max': local_max
}
local_list.append(local_map)
local_list = sorted(local_list, key=operator.itemgetter('max'))
page = Page()
index = 0
line = None
for _map in local_list:
if index % 3 == 0:
line = Line(width=1600)
page.add(line)
line.add(_map['comm'],
ts,
_map['memory'],
is_smooth=True,
xaxis_rotate=45,
xaxis_interval=5,
mark_line=['max', 'average'])
index += 1
page.render('procrank.html')
def create_charts():
page = Page()
style = Style(width=WIDTH, height=HEIGHT)
attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
value = [20, 40, 60, 80, 100, 120]
chart = Funnel("漏斗图示例", **style.init_style)
chart.add("商品",
attr,
value,
is_label_show=True,
label_pos="inside",
label_text_color="#fff")
page.add(chart)
chart = Funnel("漏斗图示例", title_pos='center', **style.init_style)
chart.add("商品",
attr,
value,
is_label_show=True,
label_pos="outside",
legend_orient='vertical',
legend_pos='left')
page.add(chart)
return page
def big_class_radar():
page = Page()
schema = [("产品", 20), ("市场与销售", 20), ("技术", 20), ("职能", 20), ("设计", 20),
("运营", 20), ("金融", 20)]
print("正在计算...")
data = sel_bigClass_avg_salary()
print(data)
salary_list = []
count_list = []
for i in data:
salary_list.append(i[1])
count_list.append(i[2])
v1 = [salary_list]
v2 = [count_list]
#平均薪资雷达图
radar = Radar(background_color='#F4F3EF', )
radar.config(schema)
radar.add("平均薪资", v1, is_splitline=True, is_axisline_show=True)
page.add(radar)
#职位数量雷达图
schema2 = [("产品", 50000), ("市场与销售", 50000), ("技术", 50000), ("职能", 50000),
("设计", 50000), ("运营", 50000), ("金融", 50000)]
radar2 = Radar(background_color='#F4F3EF', )
radar2.config(schema2)
radar2.add("职位数量",
v2,
is_splitline=True,
is_axisline_show=True,
label_color=["#4e79a7"])
page.add(radar2)
return page
def create_three():
# bar
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
bar = Bar("柱状图数据堆叠示例")
bar.add("商家A", CLOTHES, v1, is_stack=True)
bar.add("商家B", CLOTHES, v2, is_stack=True)
# scatter3D
import random
data = [
[random.randint(0, 100),
random.randint(0, 100),
random.randint(0, 100)] for _ in range(80)
]
scatter3d = Scatter3D("3D 散点图示例", width=1200, height=600)
scatter3d.add("", data, is_visualmap=True, visual_range_color=RANGE_COLOR)
return Page.from_charts(bar, scatter3d)
def score_draw(csv_file):
page = Page(csv_file+":评论等级分析")
score, date, val, score_list = [], [], [], []
result = {}
path = os.path.abspath(os.curdir)
csv_file = path + "\\" + csv_file + ".csv"
csv_file = csv_file.replace('\\', '\\\\')
d = pd.read_csv(csv_file, engine='python', encoding='utf-8')[['score', 'date']].dropna() # 读取CSV转为dataframe格式，并丢弃评论为空的记录
for indexs in d.index: # 一种遍历df行的方法（下面还有第二种，iterrows）
score_list.append(tuple(d.loc[indexs].values[:])) # 目前只找到转换为tuple然后统计相同元素个数的方法
#print("有效评分总数量为：",len(score_list), " 条")
for i in set(list(score_list)):
result[i] = score_list.count(i) # dict类型 ('很差', '2018-04-28'): 55
info = []
for key in result:
score= key[0]
date = key[1]
val = result[key]
info.append([score, date, val])
info_new = DataFrame(info) # 将字典转换成为数据框
info_new.columns = ['score', 'date', 'votes']
info_new.sort_values('date', inplace=True) # 按日期升序排列df，便于找最早date和最晚data，方便后面插值
#print("first df", info_new)
# 以下代码用于插入空缺的数据，每个日期的评分类型应该有5中，依次遍历判断是否存在，若不存在则往新的df中插入新数值
mark = 0
creat_df = pd.DataFrame(columns = ['score', 'date', 'votes']) # 创建空的dataframe
for i in list(info_new['date']):
location = info_new[(info_new.date==i)&(info_new.score=="力荐")].index.tolist()
if location == []:
creat_df.loc[mark] = ["力荐", i, 0]
mark += 1
location = info_new[(info_new.date==i)&(info_new.score=="推荐")].index.tolist()
if location == []:
creat_df.loc[mark] = ["推荐", i, 0]
mark += 1
location = info_new[(info_new.date==i)&(info_new.score=="还行")].index.tolist()
if location == []:
creat_df.loc[mark] = ["还行", i, 0]
mark += 1
location = info_new[(info_new.date==i)&(info_new.score=="较差")].index.tolist()
if location == []:
creat_df.loc[mark] = ["较差", i, 0]
mark += 1
location = info_new[(info_new.date==i)&(info_new.score=="很差")].index.tolist()
if location == []:
creat_df.loc[mark] = ["很差", i, 0]
mark += 1
info_new = info_new.append(creat_df.drop_duplicates(), ignore_index=True)
score_list = []
info_new.sort_values('date', inplace=True) # 按日期升序排列df，便于找最早date和最晚data，方便后面插值
#print(info_new)
for index, row in info_new.iterrows(): # 第二种遍历df的方法
score_list.append([row['date'], row['votes'], row['score']])
tr = ThemeRiver()
tr.add(['力荐', '推荐', '还行', '较差', '很差'], score_list, is_label_show=True, is_more_utils=True)
page.add_chart(tr)
attr, v1, v2, v3, v4, v5 = [], [], [], [], [], []
attr = list(sorted(set(info_new['date'])))
bar = Bar()
for i in attr:
v1.append(int(info_new[(info_new['date']==i)&(info_new['score']=="力荐")]['votes']))
v2.append(int(info_new[(info_new['date']==i)&(info_new['score']=="推荐")]['votes']))
v3.append(int(info_new[(info_new['date']==i)&(info_new['score']=="还行")]['votes']))
v4.append(int(info_new[(info_new['date']==i)&(info_new['score']=="较差")]['votes']))
v5.append(int(info_new[(info_new['date']==i)&(info_new['score']=="很差")]['votes']))
bar.add("力荐", attr, v1, is_stack=True)
bar.add("推荐", attr, v2, is_stack=True)
bar.add("还行", attr, v3, is_stack=True)
bar.add("较差", attr, v4, is_stack=True)
bar.add("很差", attr, v5, is_stack=True, is_convert=True, mark_line=["average"], is_more_utils=True)
page.add_chart(bar)
line = Line()
line.add("力荐", attr, v1, is_stack=True)
line.add("推荐", attr, v2, is_stack=True)
line.add("还行", attr, v3, is_stack=True)
line.add("较差", attr, v4, is_stack=True)
line.add("很差", attr, v5, is_stack=True, is_convert=False, mark_line=["average"], is_more_utils=True)
page.add_chart(line)
page.render(csv_file[:-4] + "_日投票量分析汇总.html")
def test_more():
page = Page()
# line
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"],
)
# pie
v1 = [11, 12, 13, 10, 10, 10]
pie = Pie("饼图-圆环图示例", title_pos="center")
pie.add(
"",
CLOTHES,
v1,
radius=[40, 75],
label_text_color=None,
is_label_show=True,
legend_orient="vertical",
legend_pos="left",
)
page.add([line, pie])
# kline
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")
kline.add(
"日K",
["2017/7/{}".format(i + 1) for i in range(31)],
v1,
is_datazoom_show=True,
)
page.add(kline)
# radar
schema = [
("销售", 6500),
("管理", 16000),
("信息技术", 30000),
("客服", 38000),
("研发", 52000),
("市场", 25000),
]
v1 = [[4300, 10000, 28000, 35000, 50000, 19000]]
v2 = [[5000, 14000, 28000, 31000, 42000, 21000]]
radar = Radar("雷达图示例")
radar.config(schema)
radar.add("预算分配", v1, is_splitline=True, is_axisline_show=True)
radar.add(
"实际开销",
v2,
label_color=["#4e79a7"],
is_area_show=False,
legend_selectedmode="single",
)
page.add(radar)
# scatter3d
import random
data = [
[
random.randint(0, 100),
random.randint(0, 100),
random.randint(0, 100),
]
for _ in range(80)
]
scatter3D = Scatter3D("3D 散点图示例", width=1200, height=600)
scatter3D.add("", data, is_visualmap=True, visual_range_color=RANGE_COLOR)
page.add(scatter3D)
# wordcloud
name = [
"Sam S Club",
"Macys",
"Amy Schumer",
"Jurassic World",
"Charter Communications",
"Chick Fil A",
"Planet Fitness",
"Pitch Perfect",
"Express",
"Home",
"Johnny Depp",
"Lena Dunham",
"Lewis Hamilton",
"KXAN",
"Mary Ellen Mark",
"Farrah Abraham",
"Rita Ora",
"Serena Williams",
"NCAA baseball tournament",
"Point Break",
]
value = [
10000,
6181,
4386,
4055,
2467,
2244,
1898,
1484,
1112,
965,
847,
582,
555,
550,
462,
366,
360,
282,
273,
265,
]
wordcloud = WordCloud(width=1300, height=620)
wordcloud.add("", name, value, word_size_range=[30, 100], rotate_step=66)
page.add(wordcloud)
# liquid
liquid = Liquid("水球图示例")
liquid.add("Liquid", [0.6])
page.add(liquid)
assert len(page) == 7
assert isinstance(page[0], Line)
assert (
("echarts" in page.js_dependencies)
or ("echarts.min" in page.js_dependencies)
)
page.render()
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()
def draw_citys_pic(csv_file):
page = Page(csv_file+":评论城市分析")
info = count_city(csv_file)
geo = Geo("","Ctipsy原创",title_pos="center", width=1200,height=600, background_color='#404a59', title_color="#fff")
while True: # 二次筛选，和pyecharts支持的城市库进行匹配，如果报错则删除该城市对应的统计
try:
attr, val = geo.cast(info)
geo.add("", attr, val, visual_range=[0, 300], visual_text_color="#fff", is_geo_effect_show=False,
is_piecewise=True, visual_split_number=6, symbol_size=15, is_visualmap=True)
except ValueError as e:
e = str(e)
e = e.split("No coordinate is specified for ")[1] # 获取不支持的城市名称
info.pop(e)
else:
break
info = sorted(info.items(), key=lambda x: x[1], reverse=False) # list排序
# print(info)
info = dict(info) #list转dict
# print(info)
attr, val = [], []
for key in info:
attr.append(key)
val.append(info[key])
geo1 = Geo("", "评论城市分布", title_pos="center", width=1200, height=600,
background_color='#404a59', title_color="#fff")
geo1.add("", attr, val, visual_range=[0, 300], visual_text_color="#fff", is_geo_effect_show=False,
is_piecewise=True, visual_split_number=10, symbol_size=15, is_visualmap=True, is_more_utils=True)
#geo1.render(csv_file + "_城市dotmap.html")
page.add_chart(geo1)
geo2 = Geo("", "评论来源热力图",title_pos="center", width=1200,height=600, background_color='#404a59', title_color="#fff",)
geo2.add("", attr, val, type="heatmap", is_visualmap=True, visual_range=[0, 50],visual_text_color='#fff', is_more_utils=True)
#geo2.render(csv_file+"_城市heatmap.html") # 取CSV文件名的前8位数
page.add_chart(geo2)
bar = Bar("", "评论来源排行", title_pos="center", width=1200, height=600 )
bar.add("", attr, val, is_visualmap=True, visual_range=[0, 100], visual_text_color='#fff',mark_point=["average"],mark_line=["average"],
is_more_utils=True, is_label_show=True, is_datazoom_show=True, xaxis_rotate=45)
#bar.render(csv_file+"_城市评论bar.html") # 取CSV文件名的前8位数
page.add_chart(bar)
pie = Pie("", "评论来源饼图", title_pos="right", width=1200, height=600)
pie.add("", attr, val, radius=[20, 50], label_text_color=None, is_label_show=True, legend_orient='vertical', is_more_utils=True, legend_pos='left')
#pie.render(csv_file + "_城市评论Pie.html") # 取CSV文件名的前8位数
page.add_chart(pie)
page.render(csv_file + "_城市评论分析汇总.html")
import datetime
url = "http://www.86pm25.com/paiming.htm"
head = {
'Referer': 'http://www.86pm25.com/city/Dazhou.html',
'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/69.0.3497.100 Safari/537.36'
}
html = requests.get(url, headers=head)
html.encoding = 'utf-8'
soup = BeautifulSoup(html.text, "lxml")
data1 = soup.find(id="goodtable").find_all(name='a')
data2 = str(soup.find(id='goodtable').find_all(name='td'))
data = re.findall(r'<td>(\d{1,3}.)</td>', data2)
with open("城市.txt", 'r') as f:
CityList = f.read()
city = []
for i in range(0, 367):
if str(data1[i].string) in CityList:
citytuple = (data1[i].string, int(data[i]))
city.append(citytuple)
geo = Geo("全国主要城市空气质量实时监控", "实时：" + str(datetime.datetime.now()), title_color="#fff",
title_pos="center", width='100%',
height=790, background_color='#404a59')
attr, value = geo.cast(city)
geo.add("", attr, value, visual_range=[0, 150], maptype='china', visual_text_color="#fff",
symbol_size=13, is_visualmap=True)
page = Page()
page.add(geo)
page.render("全国主要城市空气质量实时监控.html")
webbrowser.open("全国主要城市空气质量实时监控.html", new=0, autoraise=True)
def graphpage(items,startdate,enddate,option,width1, height1): #labels:复权ork线or分笔 option:hfq, qfq or 15, 30, D, etc
page = Page()
for i in items:#generate numbers of graphs according to numbers of queries in treewidget
j = re.split("-",i)
if len(j)==3:
a = generateline(j[1],j[2],startdate,enddate,option)#stock number, Type, startdate, enddate, 30 or 15 or days
if a is None:
continue
time = [d[0] for d in a]#get time from returned dictionary
if j[2]!="Kline":
if len(a[0])==4 and a[0][2]=="bar": #for 分笔data
overlap = Overlap()
form = [e[1] for e in a]
bar = Bar(j[0] + "-" + j[2], width=width1 * 10 / 11, height=(height1 * 10 / 11) / len(items))
bar.add(j[0] + "-" + j[2], time, form, yaxis_min = "dataMin",yaxis_max = "dataMax",is_datazoom_show = True, datazoom_type = "slider")
overlap.add(bar)
line = Line(j[0] + "price", width=width1 * 10 / 11, height=(height1 * 10 / 11) / len(items))
price = [e[3] for e in a]
line.add(j[0] + "price", time, price, yaxis_min = "dataMin",yaxis_max = "dataMax", is_datazoom_show = True, datazoom_type = "slider",
yaxis_type="value")
overlap.add(line,yaxis_index=1, is_add_yaxis=True)
page.add(overlap)
if len(a[0])==5 and a[0][3]=="pie":
overlap = Overlap()
timeline = Timeline(is_auto_play=False, timeline_bottom=0) #zip(namearray,valuearray,quarter,flag,num)
namearray = [c[0] for c in a]
valuearray = [d[1] for d in a]
quarter = [e[2] for e in a]
num = a[0][4]
for x in range(0, num / 10):
list1 = valuearray[x]
names = namearray[x]
quarters = quarter[x][0]
for idx, val in enumerate(list1):
list1[idx] = float(val)
pie = Pie(j[0]+"-"+"前十股东".decode("utf-8"),width=width1 * 10 / 11, height=(height1 * 10 / 11))
pie.add(j[0]+"-"+"前十股东".decode("utf-8"), names, list1, radius=[30, 55], is_legend_show=False,
is_label_show=True, label_formatter = "{b}: {c}\n{d}%")
# print list
# print names
# print quarterarray
timeline.add(pie, quarters)
# namearray = [y for y in namearray[x]]
timeline.render()
return
#need more statement
else:
form = [e[1] for e in a]#for not分笔 data
line = Line(j[0] + "-" + j[2], width=width1*10/11, height=(height1*10/11)/len(items))
line.add(j[0] + "-" + j[2], time, form, is_datazoom_show=True, datazoom_type="slider",yaxis_min="dataMin",yaxis_max="dataMax")
page.add(line)
else:
overlap = Overlap()#for k线
close = zip(*a)[2]
candle = [[x[1], x[2], x[3], x[4]] for x in a]
candlestick = Kline(j[0] + "-" + j[2], width=width1*10/11, height = (height1*10/11) / len(items))
candlestick.add(j[0], time, candle, is_datazoom_show=True, datazoom_type="slider",yaxis_interval = 1)
overlap.add(candlestick)
if len(close)>10:
ma10 = calculateMa(close, 10)
line1 = Line(title_color="#C0C0C0")
line1.add(j[0] + "-" + "MA10", time, ma10)
overlap.add(line1)
if len(close)>20:
ma20 = calculateMa(close, 20)
line2 = Line(title_color="#C0C0C0")
line2.add(j[0] + "-" + "MA20", time, ma20)
overlap.add(line2)
if len(close)>30:
ma30 = calculateMa(close, 30)
line3 = Line(title_color="#C0C0C0")
line3.add(j[0] + "-" + "MA30", time, ma30)
overlap.add(line3)
page.add(overlap)
else:
for k in range(1, len(j)/3):#if graphs are combined
j[3*k-1] = re.sub("\n&","",j[3*k-1])
sizearray=[]
#if j[1] != "Candlestick"
layout = Overlap()
for i in xrange(0, len(j),3):
array = j[i:i +3]
b = generateline(array[1],array[2],startdate,enddate,option)
if b is None:
continue
btime = [d[0] for d in b]
if array[2] != "Kline":
if len(b[0])==4 and b[0][2]=="bar":
form = [e[1] for e in b]
bar = Bar(array[0] + "-" + array[2], width=width1 * 10 / 11, height=(height1 * 10 / 11) / len(items))
bar.add(array[0] + "-" + array[2], btime, form, is_datazoom_show=True, datazoom_type="slider",
yaxis_min="dataMin", yaxis_max="dataMax")
layout.add(bar)
line = Line(array[0] + "price", width=width1 * 10 / 11, height=(height1 * 10 / 11) / len(items))
price = [e[3] for e in b]
line.add(array[0] + "price", btime, price, is_datazoom_show=True, datazoom_type="slider",
yaxis_min="dataMin", yaxis_type="value")
layout.add(line, yaxis_index=1, is_add_yaxis=True)
else:
line = Line(array[0] + "-" + array[2],width=width1*10/11, height=(height1*10/11) / len(items))
line.add(array[0]+"-"+array[2], btime, b, is_datazoom_show=True, yaxis_max = "dataMax", yaxis_min = "dataMin",datazoom_type="slider")
layout.add(line)
else:
candle = [[x[1], x[2], x[3], x[4]] for x in b]
candlestick = Kline(array[0] + "-" + array[1], width=width1*10/11,
height=(height1*10/11) / len(items))
candlestick.add(array[0], btime, candle, is_datazoom_show=True, datazoom_type=["slider"])
#if i == 0:
close = zip(*b)[2]
if len(close)>10:
ma10 = calculateMa(close, 10)
line4 = Line(title_color="#C0C0C0")
line4.add(array[0] + "-" + "MA10", btime, ma10)
layout.add(line4)
if len(close)>20:
ma20 = calculateMa(close, 20)
line5 = Line(title_color="#C0C0C0")
line5.add(array[0] + "-" + "MA20", btime, ma20)
layout.add(line5)
if len(close)>30:
ma30 = calculateMa(close, 30)
line6 = Line(title_color="#C0C0C0")
line6.add(array[0] + "-" + "MA30", btime, ma30)
layout.add(line6)
layout.add(candlestick)
page.add(layout)
page.render()
def graphpage(labels,mode_combo,startdate,enddate,optInterval,width1, height1):
#optInterval='D/W/M' labels
startdate = startdate.replace("/","-")#convert to tushare readable date
enddate = enddate.replace("/","-")
page = Page()
for label in labels: # generate numbers of graphs according to numbers of queries in treewidget
label1 = re.split("-", label)
overlap = Overlap()
if label1[2]!="分笔" and label1[2]!="季度饼图": #"K线" "复权" "历史分钟"
if mode_combo == "复权":
#if optInterval == "qfq" or optInterval == "hfq":#复权
array = ts.get_h_data(label1[1], start=startdate, end=enddate, autype="qfq")
array = array.sort_index()
time = array.index.format() # 日期正是index
elif mode_combo == "K线":
#elif optInterval.isalnum() :#历史K线
array = ts.get_k_data(label1[1], start=startdate, end=enddate, ktype=optInterval)
time = array['date'].tolist() # array.date
elif mode_combo == "历史分钟":
array_bfr = ts.get_tick_data(label1[1], date=startdate)
array_bfr.sort_values("time")
a = startdate + " " + array_bfr["time"]
array_bfr["time"] = a
array_bfr["time"] = pd.to_datetime(a)
array_bfr = array_bfr.set_index("time")
if label1[2] != "Volume" and label1[2] != "Amount":
price_df = array_bfr["price"].resample(optInterval).ohlc() # resample重新取样,选出ohlc=open/high/low，提取除价格之外另外4列.close,tushare是ohcl
price_df = price_df.dropna()
array = price_df
time = price_df.index.format()
elif label1[2] == "Volume":
vols = array_bfr["volume"].resample(optInterval).sum() #resample重新取样，累加间隔内数值 relevant data processing algorithm taken from Jimmy, Creator of Tushare
vols = vols.dropna()
vol_df = pd.DataFrame(vols, columns=["volume"])
array = vol_df
time = vol_df.index.format()
else:
amounts = array_bfr["amount"].resample(optInterval).sum()
amounts = amounts.dropna()
amount_df = pd.DataFrame(amounts, columns=["amount"])
array = amount_df
time = amount_df.index.format()
#绘图方法
if label1[2] == 'Kline':
re_array = array[['open', 'close', 'high', 'low']]
data_li = list(row.tolist() for index, row in re_array.iterrows()) # data_list = list(re_array.as_matrix())
close = array['close'].tolist()
kline = Kline(label1[0] + "-" + optInterval, width=width1*10/11, height = (height1*10/11) / len(labels))
kline.add(label1[0], time, data_li, is_datazoom_show=True, datazoom_type="slider", yaxis_interval=1)
overlap.add(kline)
if len(close) > 10:
ma10 = calculateMa(close, 10)
line1 = Line(title_color="#C0C0C0")
line1.add(label1[0] + "-" + "MA10", time, ma10)
overlap.add(line1)
if len(close) > 20:
ma20 = calculateMa(close, 20)
line2 = Line(title_color="#C0C0C0")
line2.add(label1[0] + "-" + "MA20", time, ma20)
overlap.add(line2)
if len(close) > 30:
ma30 = calculateMa(close, 30)
line3 = Line(title_color="#C0C0C0")
line3.add(label1[0] + "-" + "MA30", time, ma30)
overlap.add(line3)
page.add(overlap)
else:#When label1[2]==open/close/volume
if label1[2] == 'Open':
list_aft = array['open'].tolist()
elif label1[2] == 'Close':
list_aft = close
elif label1[2] == 'High':
list_aft = array['high'].tolist()
elif label1[2] == 'Low':
list_aft = array['low'].tolist()
elif label1[2] == 'Volume':#volume
list_aft = array['volume'].tolist()
else:#amount
list_aft = array['amount'].tolist()
line = Line(label1[0] + "-" + label1[2], width=width1 * 10 / 11, height=(height1 * 10 / 11) / len(labels))
line.add(label1[0] + "-" + label1[2], time, list_aft, is_datazoom_show=True, yaxis_max="dataMax",
yaxis_min="dataMin", datazoom_type="slider")
overlap.add(line)
page.add(overlap)
elif label1[2]=="分笔":
array = ts.get_tick_data(label1[1], date=startdate)
array = array.sort_values("time")
date = array["time"].tolist()
amount = array["amount"].tolist()
atype = array["type"].tolist()
price = array["price"].tolist()
flag = ["bar" for i in date]
for idx, val in enumerate(atype):
if val == "卖盘":
amount[idx] = -amount[idx]
if val == "中性盘":
amount[idx] = 0
returnarray = list(zip(date, amount, flag, price))
form = [e[1] for e in returnarray]
time = [d[0] for d in returnarray]
bar = Bar(label1[0] + "-" + label1[2], width=width1 * 10 / 11, height=(height1 * 10 / 11) / len(labels))
bar.add(label1[0] + "-" + label1[2], time, form, is_datazoom_show=True, datazoom_type="slider", yaxis_min="dataMin", yaxis_max="dataMax")
overlap.add(bar)
line = Line(label1[0] + "price", width=width1 * 10 / 11, height=(height1 * 10 / 11) / len(labels))
price = [e[3] for e in returnarray]
line.add(label1[0] + "price", time, price, yaxis_min="dataMin", yaxis_max="dataMax", is_datazoom_show=True,
datazoom_type="slider",
yaxis_type="value")
overlap.add(line, yaxis_index=1, is_add_yaxis=True)
page.add(overlap)
elif label1[2]=="季度饼图":
datestr = startdate.split("-")
thisyear = datestr[0]
df2 = ts.top10_holders(code=label1[1], gdtype="1")
test = df2[1]["quarter"].tolist()
df_ready = df2[1]
idxlist = []
for idx, val in enumerate(test):
a = val.split("-")
if a[0] == thisyear:
# print a[0],idx
idxlist.append(idx)
thing = df_ready.loc[idxlist]
thing = thing.sort_values(["quarter", "name"])
# print a[0],id
name = thing["name"].tolist()
value = thing["hold"].tolist()
quarter = thing["quarter"].tolist()
namearray = [name[i:i + 10] for i in range(0, len(name), 10)]
valuearray = [value[j:j + 10] for j in range(0, len(value), 10)]
quarterarray = [quarter[k:k + 10] for k in range(0, len(quarter), 10)]
flag = ["pie" for i in namearray]
num = [len(value) for k in namearray]
returnarray = list(zip(namearray, valuearray, quarterarray, flag, num))
timeline = Timeline(is_auto_play=False, timeline_bottom=0) # zip(namearray,valuearray,quarter,flag,num)
namearray = [c[0] for c in returnarray]
valuearray = [d[1] for d in returnarray]
quarter = [e[2] for e in returnarray]
num = returnarray[0][4]
for x in range(0, int(num / 10)):
list1 = valuearray[x]
names = namearray[x]
quarters = quarter[x][0]
for idx, val in enumerate(list1):
list1[idx] = float(val)
pie = Pie(label1[0] + "-" + "前十股东", width=width1 * 10 / 11, height=(height1 * 10 / 11))
pie.add(label1[0] + "-" + "前十股东", names, list1, radius=[30, 55], is_legend_show=False,
is_label_show=True, label_formatter="{b}: {c}\n{d}%")
timeline.add(pie, quarters)
# namearray = [y for y in namearray[x]]
timeline.render()
page.render()
