def test_style():
style = Style(title_pos="center")
s1 = style.add(is_random=True, label_pos="top")
assert style.init_style["title_pos"] == "center"
assert style.init_style.get("title", None) is None
assert s1["is_random"] is True
assert s1["label_pos"] == "top"
def ewide5(request):
template = loader.get_template('ewpyecharts.html')
style = Style(title_top="#fff",
title_pos="center",
width=1200,
height=600,
background_color="#404a59")
style_geo = style.add(
is_label_show=True,
line_curve=0.2,
line_opacity=0.6,
legend_text_color="#eee",
legend_pos="right",
geo_effect_symbol="plane",
geo_effect_symbolsize=15,
label_color=['#a6c84c', '#ffa022', '#46bee9'],
label_pos="right",
label_formatter="{b}",
label_text_color="#eee",
)
data_guangzhou = [["广州", "上海"], ["广州", "北京"], ["广州", "南京"], ["广州", "重庆"],
["广州", "兰州"], ["广州", "杭州"]]
data_beijing = [["北京", "上海"], ["北京", "广州"], ["北京", "南京"], ["北京", "重庆"],
["北京", "兰州"], ["北京", "杭州"]]
geolines1 = GeoLines("GeoLines 示例", **style.init_style)
geolines1.add("从广州出发", data_guangzhou, **style_geo)
geolines1.add("从北京出发", data_beijing, **style_geo)
# geo.show_config()
context = dict(myechart=geolines1.render_embed(),
host=REMOTE_HOST,
script_list=geolines1.get_js_dependencies())
return HttpResponse(template.render(context, request))
def test_timeline_pie():
style = Style()
pie_style = style.add(
is_label_show=True,
radius=[30, 55],
rosetype="radius"
)
pie_1 = Pie("2012 年销量比例", "数据纯属虚构")
pie_1.add("秋季", CLOTHES, [randint(10, 100) for _ in range(6)], **pie_style)
pie_2 = Pie("2013 年销量比例", "数据纯属虚构")
pie_2.add("秋季", CLOTHES, [randint(10, 100) for _ in range(6)], **pie_style)
pie_3 = Pie("2014 年销量比例", "数据纯属虚构")
pie_3.add("秋季", CLOTHES, [randint(10, 100) for _ in range(6)], **pie_style)
pie_4 = Pie("2015 年销量比例", "数据纯属虚构")
pie_4.add("秋季", CLOTHES, [randint(10, 100) for _ in range(6)], **pie_style)
pie_5 = Pie("2016 年销量比例", "数据纯属虚构")
pie_5.add("秋季", CLOTHES, [randint(10, 100) for _ in range(6)], **pie_style)
timeline = Timeline(is_auto_play=True, timeline_bottom=0,
width=1200, height=600)
timeline.add(pie_1, '2012 年')
timeline.add(pie_2, '2013 年')
timeline.add(pie_3, '2014 年')
timeline.add(pie_4, '2015 年')
timeline.add(pie_5, '2016 年')
timeline.render()
def Pie():
from pyecharts import Pie,Style
def cut(value):
if '中国' in value:
return '中国'
else:
value = value.split(',')[0]
return value
file['areas'] = file['areas'].apply(cut)
attr = file['areas'].value_counts().index.tolist()
valu = file['areas'].value_counts().tolist()
style = Style(
title_pos = 'center',
title_top = 'bottom',
width = 900,
height = 500,
background_color = 'white')
pie_style = style.add(
legend_pos = 'center',
#radius=[40, 75],
label_color = [],
label_text_color ='',
is_label_show=True,#显示图例 数据
)
pie = Pie("areas:","",**style.init_style)
pie.add("",attr,valu,**pie_style)
pie.render('pie.html')
def Bar():
from pyecharts import Bar,Style
def cut(value):
if '中国' in value:
return '中国'
else:
value = value.split(',')[0]
return value
file['areas'] = file['areas'].apply(cut)
attr = file['areas'].value_counts().index.tolist()
valu = file['areas'].value_counts().tolist()
style = Style(
title_pos = 'center',
width = 900,
height = 500,
background_color = 'white')
bar_style = style.add(
legend_pos = 'bottom',
label_color = ['yellow'],
label_text_color ='blue',
is_label_show=None,#显示图例 数据
mark_point=['max'],
mark_line=['average'])
bar = Bar("地区分布:","",**style.init_style)#标题和副标题
bar.add("",attr,valu,**bar_style)
#is_convert = True 换x y轴
bar.render('bar.html')
def plot_geolines(plotting_data, geo_cities_coords):
# 设置画布的格式
style = Style(title_pos="center", width=1000, height=800)
# 部分地理轨迹图的格式
style_geolines = style.add(
is_label_show=True,
line_curve=0.3, # 轨迹线的弯曲度，0-1
line_opacity=0.6, # 轨迹线的透明度，0-1
geo_effect_symbol='plane', # 特效的图形，有circle,plane,pin等等
geo_effect_symbolsize=10, # 特效图形的大小
geo_effect_color='#7FFFD4', # 特效的颜色
geo_effect_traillength=0.1, # 特效图形的拖尾效果，0-1
label_color=['#FFA500', '#FFF68F'], # 轨迹线的颜色，标签点的颜色，
border_color='#97FFFF', # 边界的颜色
geo_normal_color='#36648B', # 地图的颜色
label_formatter='{b}', # 标签格式
legend_pos='left')
# 作图
geolines = GeoLines('出行轨迹图', **style.init_style)
geolines.add(
'从北京出发',
plotting_data,
maptype='china', # 地图的类型，可以是省的地方，如'广东',也可以是地市，如'东莞'等等
geo_cities_coords=geo_cities_coords,
**style_geolines)
# 发布，得到图形的html文件
geolines.render()
def escape(self):
echart_unsupported_city = [
"菏泽市", "襄阳市", "恩施州", "湘西州","阿坝州", "延边州",
"甘孜州", "凉山州", "黔西南州", "黔东南州", "黔南州", "普洱市", "楚雄州", "红河州",
"文山州", "西双版纳州", "大理州", "德宏州", "怒江州", "迪庆州", "昌都市", "山南市",
"林芝市", "临夏州", "甘南州", "海北州", "黄南州", "海南州", "果洛州", "玉树州", "海西州",
"昌吉州", "博州", "克州", "伊犁哈萨克州"]
data = []
for index, row in df_aqi.iterrows():
city = row['city']
aqi = row['aqi']
if city=='长沙市':
print(city)
localAQI=aqi
if city in echart_unsupported_city:
continue
for index, row in df_aqi.iterrows():
city = row['city']
aqi = row['aqi']
if city in echart_unsupported_city:
continue
if aqi < localAQI and aqi<20 :
data.append( ['长沙',city] )
global lastcity
lastcity=city
style = Style(
title_top="#fff",
title_pos = "center",
title_color="#fff",
width=425,
height=730,
background_color="#404a59"
)
style_geo = style.add(
is_label_show=True,
line_curve=0.2,#线条曲度
line_opacity=0.6,
legend_text_color="#fff",#图例文字颜色
legend_pos="right",#图例位置
geo_effect_symbol="plane",#特效形状
geo_effect_symbolsize=15,#特效大小
label_color=['#a6c84c', '#ffa022', '#46bee9'],
label_pos="right",
label_formatter="{b}",#//标签内容格式器
label_text_color="#fff",
)
print(data)
print(lastcity)
geolines = GeoLines("逃离路线", **style.init_style)
geolines.add("出发", data, **style_geo)
geolines.render('aqi.html')
self.webView.load(QUrl("file:///D:/源代码/aqi.html"))
#self.webView.reload()
self.webView.repaint()
self.webView.update()
def test_timeline_pie():
style = Style()
pie_style = style.add(is_label_show=True,
radius=[30, 55],
rosetype="radius")
pie_1 = Pie("2012 年销量比例", "数据纯属虚构")
pie_1.add("秋季", CLOTHES, [randint(10, 100) for _ in range(6)], **pie_style)
pie_2 = Pie("2013 年销量比例", "数据纯属虚构")
pie_2.add("秋季", CLOTHES, [randint(10, 100) for _ in range(6)], **pie_style)
pie_3 = Pie("2014 年销量比例", "数据纯属虚构")
pie_3.add("秋季", CLOTHES, [randint(10, 100) for _ in range(6)], **pie_style)
pie_4 = Pie("2015 年销量比例", "数据纯属虚构")
pie_4.add("秋季", CLOTHES, [randint(10, 100) for _ in range(6)], **pie_style)
pie_5 = Pie("2016 年销量比例", "数据纯属虚构")
pie_5.add("秋季", CLOTHES, [randint(10, 100) for _ in range(6)], **pie_style)
timeline = Timeline(is_auto_play=True,
timeline_bottom=0,
width=1200,
height=600)
timeline.add(pie_1, "2012 年")
timeline.add(pie_2, "2013 年")
timeline.add(pie_3, "2014 年")
timeline.add(pie_4, "2015 年")
timeline.add(pie_5, "2016 年")
assert len(timeline._option.get("baseOption").get("series")) == 0
timeline.render()
def test_timeline_pie():
style = Style()
pie_style = style.add(
is_label_show=True,
radius=[30, 55],
rosetype="radius"
)
pie_1 = Pie("2012 年销量比例", "数据纯属虚构")
pie_1.add("秋季", CLOTHES, [randint(10, 100) for _ in range(6)], **pie_style)
pie_2 = Pie("2013 年销量比例", "数据纯属虚构")
pie_2.add("秋季", CLOTHES, [randint(10, 100) for _ in range(6)], **pie_style)
pie_3 = Pie("2014 年销量比例", "数据纯属虚构")
pie_3.add("秋季", CLOTHES, [randint(10, 100) for _ in range(6)], **pie_style)
pie_4 = Pie("2015 年销量比例", "数据纯属虚构")
pie_4.add("秋季", CLOTHES, [randint(10, 100) for _ in range(6)], **pie_style)
pie_5 = Pie("2016 年销量比例", "数据纯属虚构")
pie_5.add("秋季", CLOTHES, [randint(10, 100) for _ in range(6)], **pie_style)
timeline = Timeline(is_auto_play=True, timeline_bottom=0,
width=1200, height=600)
timeline.add(pie_1, '2012 年')
timeline.add(pie_2, '2013 年')
timeline.add(pie_3, '2014 年')
timeline.add(pie_4, '2015 年')
timeline.add(pie_5, '2016 年')
def plot_upstream(self,outputname):
self.init_dict_trans_isvisit()
style = Style(
title_color="#fff",
title_pos="center",
width=1510,
height=840,
background_color="#404a59" # #404a59"
)
style_geo = style.add(
maptype="china",
is_label_show=False,
line_curve=0.1,
line_opacity=0.6,
legend_text_color="#eee",
legend_pos="right",
geo_effect_symbol="arrow",
symbol_size=5,
geo_effect_symbolsize=5,
label_color=['#a6c84c', '#46bee9','red'],
label_pos="right",
label_formatter="{b}",
label_text_color="#eee",
)
geolines = GeoLines(outputname, **style.init_style)
geolines.add(name = "轻度",data = self.prop_df[self.prop_df['class']=='轻度'][['Source','Target']].values.tolist(),
is_legend_show=False,**style_geo)
geolines.add(name = "中度",data = self.prop_df[self.prop_df['class']=='中度'][['Source','Target']].values.tolist(),
is_legend_show=True,**style_geo)
geolines.add(name = "重度",data = self.prop_df[self.prop_df['class']=='重度'][['Source','Target']].values.tolist(),
is_legend_show=True,**style_geo)
geolines.render(outputname+'.html')
def test_timeline_pie():
style = Style()
pie_style = style.add(
is_label_show=True, radius=[30, 55], rosetype="radius"
)
pie_1 = Pie("2012 年销量比例", "数据纯属虚构")
pie_1.add("秋季", CLOTHES, [randint(10, 100) for _ in range(6)], **pie_style)
pie_2 = Pie("2013 年销量比例", "数据纯属虚构")
pie_2.add("秋季", CLOTHES, [randint(10, 100) for _ in range(6)], **pie_style)
pie_3 = Pie("2014 年销量比例", "数据纯属虚构")
pie_3.add("秋季", CLOTHES, [randint(10, 100) for _ in range(6)], **pie_style)
pie_4 = Pie("2015 年销量比例", "数据纯属虚构")
pie_4.add("秋季", CLOTHES, [randint(10, 100) for _ in range(6)], **pie_style)
pie_5 = Pie("2016 年销量比例", "数据纯属虚构")
pie_5.add("秋季", CLOTHES, [randint(10, 100) for _ in range(6)], **pie_style)
timeline = Timeline(
is_auto_play=True, timeline_bottom=0, width=1200, height=600
)
timeline.add(pie_1, "2012 年")
timeline.add(pie_2, "2013 年")
timeline.add(pie_3, "2014 年")
timeline.add(pie_4, "2015 年")
timeline.add(pie_5, "2016 年")
assert len(timeline.options.get("baseOption").get("series")) == 0
timeline.render()
def my_Geolines():
style = Style(title_top="#fff",
title_pos="center",
width=1200,
height=600,
background_color="#404a59")
style_geo = style.add(
is_label_show=True,
line_curve=0.2,
line_opacity=0.6,
legend_text_color="#eee",
legend_pos="right",
geo_effect_symbol="plane",
geo_effect_symbolsize=15,
label_color=['#a6c84c', '#ffa022', '#46bee9'],
label_pos="right",
label_formatter="{b}",
label_text_color="#eee",
)
data_guangzhou = [["珠海", "番禺区", 55], ["番禺区", "天河区", 6], ["天河区", "南昌", 259]]
geolines = GeoLines("GeoLines 示例", **style.init_style)
geolines.add("从广州出发",
data_guangzhou,
tooltip_formatter="{a} : {c}",
**style_geo)
geolines.render()
def test_pie_multiple_movie():
pie = Pie('各类电影中"好片"所占的比例', "数据来着豆瓣", title_pos='center')
style = Style()
pie_style = style.add(
label_pos="center",
is_label_show=True,
label_text_color=None
)
pie.add("", ["剧情", ""], [25, 75], center=[10, 30],
radius=[18, 24], **pie_style)
pie.add("", ["奇幻", ""], [24, 76], center=[30, 30],
radius=[18, 24], **pie_style)
pie.add("", ["爱情", ""], [14, 86], center=[50, 30],
radius=[18, 24], **pie_style)
pie.add("", ["惊悚", ""], [11, 89], center=[70, 30],
radius=[18, 24], **pie_style)
pie.add("", ["冒险", ""], [27, 73], center=[90, 30],
radius=[18, 24], **pie_style)
pie.add("", ["动作", ""], [15, 85], center=[10, 70],
radius=[18, 24], **pie_style)
pie.add("", ["喜剧", ""], [54, 46], center=[30, 70],
radius=[18, 24], **pie_style)
pie.add("", ["科幻", ""], [26, 74], center=[50, 70],
radius=[18, 24], **pie_style)
pie.add("", ["悬疑", ""], [25, 75], center=[70, 70],
radius=[18, 24], **pie_style)
pie.add("", ["犯罪", ""], [28, 72], center=[90, 70],
radius=[18, 24], legend_top="center", **pie_style)
pie.render()
def generate_3d_bar_chart():
data = pd.read_excel(input_file_path + '每日销量.xlsx', sheet_name=0)
print(data.head())
x_axis = data['week'].tolist()
data['week'] = data['week'].str.replace('week', '').map(int) - 1
data = data.set_index('week')
y_axis = data.columns.tolist()
data.columns = range(0, 7)
data = data.stack().reset_index()
data.columns = ['week', 'day', 'amount']
print(data.head())
style = Style(
title_color='#A52A2A',
title_pos='center',
width=900,
height=1100,
background_color='#ABABAB'
)
style_3d = style.add(
is_visualmap=True,
visual_range=[0, 120],
visual_range_color=['#313695', '#4575b4', '#74add1', '#abd9e9', '#e0f3f8', '#ffffbf',
'#fee090', '#fdae61', '#f46d43', '#d73027', '#a50026'],
grid3d_width=200,
grid3d_depth=80,
xaxis_label_textcolor='#fff',
is_grid3d_rotate=True,
legend_pos='right'
)
bar3d = Bar3D('全年产量情况', **style.init_style)
bar3d.add('每日产量', x_axis, y_axis, data.values.tolist(), **style_3d)
bar3d.render(output_file_path + 'htmls/全年产量情况3D柱状图.html')
def test_style():
style = Style(title_pos="center")
s1 = style.add(is_random=True, label_pos="top")
assert style.init_style['title_pos'] == "center"
assert style.init_style.get('title', None) is None
assert s1['is_random'] is True
assert s1['label_pos'] == "top"
def data_visualization(login_success_value=0,
login_failure_value=0,
shiming_success_value=0,
shiming_failure_value=0,
fangyuan_success_value=0,
fangyuan_failure_value=0,
mensuo_success_value=0,
mensuo_failure_value=0):
'''
数据可视化,连环拼图
:param login_success_value:
:param login_failure_value:
:param shiming_success_value:
:param shiming_failure_value:
:param fangyuan_success_value:
:param fangyuan_failure_value:
:param mensuo_success_value:
:param mensuo_failure_value:
:return:
'''
pie = Pie('Results of each interface test',
'Data to Jenkins',
title_pos='center')
style = Style()
pie_style = style.add(label_pos="center",
is_label_show=True,
label_text_color='#6E6E6E')
pie.add('', ['Login Success', 'Login Failure'],
[login_success_value, login_failure_value],
center=[10, 30],
radius=[20, 30],
**pie_style)
pie.add('', ['ShiMing Success', 'ShiMing Failure'],
[shiming_success_value, shiming_failure_value],
center=[10, 80],
radius=[20, 30],
**pie_style)
pie.add('', ['FangYuan Suceess', 'FangYuan Failure'],
[fangyuan_success_value, fangyuan_failure_value],
center=[40, 30],
radius=[20, 30],
**pie_style)
pie.add('', ['MenSuo Success', 'MenSuo Failure'],
[mensuo_success_value, mensuo_failure_value],
center=[40, 80],
radius=[20, 30],
legend_top="center",
**pie_style)
pie.show_config()
pie.render(filename)
def draw_dif_faculty_sex_pie_chart(self, df: pd.DataFrame):
"""
各学院男女借书比例
:param df:
:return:
"""
male = df['Male'].tolist()
female = df['Female'].tolist()
faculty_list = df['Faculty'].tolist()
faculty_sex_list = list(zip(male, female, faculty_list))
pie = Pie(title='广商各学院借书男女人数比', subtitle="男女人数比", title_pos='center', **self.style.init_style)
style = Style()
pie_style = style.add(
label_pos="center",
is_label_show=True,
label_text_color="#698B69",
label_emphasis_textcolor="#9dccfb",
label_emphasis_pos="center",
legend_top="center",
label_color=['#4876FF', '#EE3B3B']
)
label_list = ["男", "女"]
pie.add("", label_list, list(faculty_sex_list[0][:-1]),
center=[10, 30], radius=[18, 24],
label_formatter=faculty_sex_list[0][-1] + "\n{b}: {d}%\n", **pie_style)
pie.add("", label_list, list(faculty_sex_list[1][:-1]),
center=[30, 30], radius=[18, 24],
label_formatter=faculty_sex_list[1][-1] + "\n{b}: {d}%\n", **pie_style)
pie.add("", label_list, list(faculty_sex_list[2][:-1]),
center=[50, 30], radius=[18, 24],
label_formatter=faculty_sex_list[2][-1] + "\n{b}: {d}%\n", **pie_style)
pie.add("", label_list, list(faculty_sex_list[3][:-1]),
center=[70, 30], radius=[18, 24],
label_formatter=faculty_sex_list[3][-1] + "\n{b}: {d}%\n", **pie_style)
pie.add("", label_list, list(faculty_sex_list[4][:-1]),
center=[90, 30], radius=[18, 24],
label_formatter=faculty_sex_list[4][-1] + "\n{b}: {d}%\n", **pie_style)
pie.add("", label_list, list(faculty_sex_list[5][:-1]),
center=[10, 70], radius=[18, 24],
label_formatter=faculty_sex_list[5][-1] + "\n{b}: {d}%\n", **pie_style)
pie.add("", label_list, list(faculty_sex_list[6][:-1]),
center=[30, 70], radius=[18, 24],
label_formatter=faculty_sex_list[6][-1] + "\n{b}: {d}%\n", **pie_style)
pie.add("", label_list, list(faculty_sex_list[7][:-1]),
center=[50, 70], radius=[18, 24],
label_formatter=faculty_sex_list[7][-1] + "\n{b}: {d}%\n", **pie_style)
pie.add("", label_list, list(faculty_sex_list[8][:-1]),
center=[70, 70], radius=[18, 24],
label_formatter=faculty_sex_list[8][-1] + "\n{b}: {d}%\n", **pie_style)
if self._json_mode:
return pie.options
else:
self._public_page_render(chart=pie, filename="广商各学院借书男女人数比")
def dashboard():
'''仪表盘'''
gauge = Gauge('Results of each interface test')
style = Style()
gauge_style = style.add(label_pos='center',
is_label_show=True,
label_text_color=None)
gauge.add('Login Interface Test', 'Rate of passing', 70, **gauge_style)
#gauge.add('FangYuan Interface Test','Rate of passing',60,**gauge_style)
gauge.show_config()
gauge.render(filename)
def GuanJianCi(self, data_name="None", num=20, text=None):
page = Page()
if text == None:
text = "SimHash是一种局部敏感hash，它也是Google公司进行海量网页去重使用的主要算法。传统的Hash算法只负责将原始内容尽量均匀随机地映射为一个签名值，原理上仅相当于伪随机数产生算法。传统的hash算法产生的两个签名，如果原始内容在一定概率下是相等的；如果不相等，除了说明原始内容不相等外，不再提供任何信息，因为即使原始内容只相差一个字节，所产生的签名也很可能差别很大。所以传统的Hash是无法在签名的维度上来衡量原内容的相似度，而SimHash本身属于一种局部敏感哈希算法，它产生的hash签名在一定程度上可以表征原内容的相似度。我们主要解决的是文本相似度计算，要比较的是两个文章是否相似，当然我们降维生成了hash签名也用于这个目的。看到这里估计大家就明白了，我们使用的simhash就算把文章中的字符串变成 01 串也还是可以用于计算相似度的，而传统的hash却不行。"
tags = jieba.analyse.extract_tags(text,
topK=num,
withWeight=True,
withFlag=True)
name = []
value = []
for tag in tags:
name.append(tag[0])
value.append(tag[1])
print(value)
wordCloud = WordCloud(data_name)
wordCloud.add("", name, value)
pie = Pie('前十个词汇占重', "", title_pos='center')
style = Style()
pie_style = style.add(label_pos="center",
is_label_show=True,
label_text_color=None)
hight = 10
width = 30
sum_Wight = sum(value)
for index, (n, v) in enumerate(zip(name, value)):
if index == 5:
hight = 10
width = width + 40
if index < 10:
pie.add("", [n, ""], [v / sum_Wight, 1 - v / sum_Wight],
center=[hight, width],
radius=[18, 24],
**pie_style)
hight = hight + 20
print(hight, width)
print index
page.add(pie)
page.add(wordCloud)
save_helper.save_tu_helper(page, data_name)
def single_chart_common(**kwargs):
"""
:param kwargs: 该类支持
Line(折线图),
Bar(柱状图),
Gauge(仪表盘), 主要看当个指标的完成率等
Pie(饼图),
Scatter(散点图) 相关性分析，聚类分析
WordCloud(词云图) 热点词分析
Map(地图)
Funnel(漏斗图): 展示数据变化的一个逻辑流程转化
EffectScatter(涟漪特效动画散点图)：利用动画特效可以将某些想要突出的数据进行视觉突出
:return:
"""
n_fields, column_conf = field_get(**kwargs)
charts_conf = kwargs.get("echarts", {})
style = Style(**charts_conf.get("init_style"))
title = charts_conf.get("title")
x_conf = column_conf.pop("x")
x_value = x_conf.get('value')
for field in column_conf.keys():
y_conf = column_conf.get(field)
y_value = y_conf.pop('value')
max_value = heapq.nlargest(1, y_value)[0]
min_value = heapq.nsmallest(1, y_value)[0]
chart_type = y_conf.pop('chart_type')
field_nm = y_conf.pop('name')
data_chart = getattr(pyecharts, chart_type)(title=title,
**style.init_style)
if chart_type == 'Map':
y_conf["visual_range"] = [min_value, max_value]
if len(y_value) == 1:
y_value = y_value[0]
data_chart.add(field_nm, x_value, y_value, **style.add(**y_conf))
return data_chart
def gen_render_html(
nodes_path,
edges_path,
output_path=r'../results/energy/figure/2015-2017-finished/city_coop.html'
):
# 读取节点和边
nodes = pd.read_csv(nodes_path, delimiter=';')
edges = pd.read_csv(edges_path, delimiter=';')
# 设置生成echarts地理流向图的配置
geocode = {
nodes.iloc[i]['name']:
[nodes.iloc[i]['Longitude'], nodes.iloc[i]['Latitude']]
for i in range(len(nodes))
}
style = Style(title_color="#fff",
title_pos="center",
width=2400,
height=1200,
background_color="white")
edge_data = [[
edges.iloc[i]['source'], edges.iloc[i]['target'],
edges.iloc[i]['weight']
] for i in range(len(edges))]
style_geo = style.add(line_opacity=0.2, line_color='#2980b9')
# 渲染
geolines = GeoLines('城市合作网络', **style.init_style)
geolines.add("",
edge_data,
maptype='world',
geo_cities_coords=geocode,
is_geo_effect_show=False,
is_roam=False,
symbol_size=0,
geo_normal_color='#dcdcdc',
border_color='black',
**style_geo)
os.makedirs(os.path.dirname(output_path), exist_ok=True)
geolines.render(output_path)
return
def geolines():
"""地理坐标系线图"""
data_beijing = [["北京", "上海"], ["北京", "广州"], ["北京", "南京"], ["北京", "重庆"],
["北京", "兰州"], ["北京", "杭州"]]
data_guangzhou = [
["广州", "上海", 10],
["广州", "北京", 20],
["广州", "南京", 30],
["广州", "重庆", 40],
["广州", "兰州", 50],
["广州", "杭州", 60],
]
data_shanghai = [
["上海", "广州", 10],
["上海", "北京", 20],
["上海", "南京", 30],
["上海", "重庆", 40],
["上海", "兰州", 50],
["上海", "杭州", 60],
]
style = Style(title_top="#fff",
title_pos="center",
width=1200,
height=800,
background_color="#404a59")
style_geo = style.add(
is_label_show=True,
line_curve=0.2,
line_opacity=0.6,
legend_text_color="#eee",
legend_pos="right",
geo_effect_symbol="plane",
geo_effect_symbolsize=15,
label_color=['#a6c84c', '#ffa022', '#46bee9'],
label_pos="right",
label_formatter="{b}",
label_text_color="#eee",
)
geolines = GeoLines("地理坐标系线图", **style.init_style)
geolines.add("从广州出发", data_guangzhou, **style_geo)
geolines.add("从北京出发", data_beijing, **style_geo)
geolines.add("从上海出发", data_shanghai, **style_geo)
geolines.render("地理坐标系线图.html")
def geolines():
data_beijing = [["北京", "上海"], ["北京", "广州"], ["北京", "南京"], ["北京", "重庆"],
["北京", "兰州"], ["北京", "杭州"]]
data_guangzhou = [
["广州", "上海", 10],
["广州", "北京", 20],
["广州", "南京", 30],
["广州", "重庆", 40],
["广州", "兰州", 50],
["广州", "杭州", 60],
]
style = Style(title_top="#fff",
title_pos="center",
width=1200,
height=600,
background_color="#404a59")
style_geo = style.add(
is_label_show=True,
line_curve=0.2,
line_opacity=0.6,
legend_text_color="#eee",
legend_pos="right",
geo_effect_symbol="plane",
geo_effect_symbolsize=15,
label_color=['#a6c84c', '#ffa022', '#46bee9'],
label_pos="right",
label_formatter="{b}",
label_text_color="#eee",
)
geolines = GeoLines("GeoLines", **style.init_style)
geolines.add("从广州出发", data_guangzhou, **style_geo)
geolines.add("从北京出发", data_beijing, **style_geo)
# geolines.render()
return render_template(
'geolines.html',
geolines=geolines.render_embed(),
host=REMOTE_HOST,
script_list=geolines.get_js_dependencies(),
)
def Pies_1():
attr = file.types.value_counts().index.tolist()[0:9]
valu = file.types.value_counts().tolist()[0:9]
style = Style(title_pos='center',
title_top='bottom',
width=900,
height=500,
background_color='white')
pie_style = style.add(
legend_pos='center',
#radius=[40, 75], #饼图还是环形兔
label_color=[],
label_text_color='',
#legend_orient="vertical",
is_label_show=True, #显示图例 数据
)
pie = Pie("", "", **style.init_style)
pie.add("", attr, valu, **pie_style)
pie.render('./Echarts/pie.html')
def Bars():
attr = file.areas.value_counts().index.tolist()[0:7]
valu = file.areas.value_counts().tolist()[0:7]
style = Style(
title_pos='left',
width=1200,
height=500,
background_color='white',
)
bar_style = style.add(
legend_pos='bottom',
label_color=['yellow'],
label_text_color='blue',
is_label_show=None, #显示图例 数据
mark_point=['max', 'min'],
mark_line=['average'])
bar = Bar("地区分布:", "", **style.init_style) #标题和副标题
bar.add("", attr, valu, **bar_style)
#is_convert = True 换x y轴
bar.render('./Echarts/bar.html')
def generate_kfc_dks_distribute_bar_chart():
"""
生成肯德基、德克士分布图
:return:
"""
# 读取数据
data = pd.read_excel(input_file_path + '省会城市KFC_MC_德克士.xlsx', sheet_name=0)
print(data.head())
city = data['城市'].tolist()
mc_num = data['麦当劳店面数量'].tolist()
kfc_num = data['KFC店面数量'].tolist()
dks_num = data['德克士店面数量'].tolist()
# 设置样式
style = Style(title_pos='center', width=1000, height=500, background_color='white')
bar_style = style.add(legend_top='bottom', # 图例位置
yaxis_rotate=45, # Y轴标签旋转角度
label_color=[' #FFB90F', '#FFF68F', '#1E90FF']) # 柱状图颜色
bar = Bar('省会城市快餐店数量', **style.init_style)
bar.add('麦当劳', city, mc_num, is_stack=True, is_convert=False, **bar_style) # 是否堆积，是否反转
bar.add('肯德基', city, kfc_num, is_stack=True, is_convert=False, **bar_style) # 是否堆积，是否反转
bar.add('德克士', city, dks_num, is_stack=True, is_convert=False, **bar_style) # 是否堆积，是否反转
bar.render(output_file_path + 'htmls/省会城市快餐店数量堆积柱状图.html')
def plot_bfs(self, outputname, source_city='上海市', k=5, minimum=300):
import json
dict_nn = self.bfs(source_city, k, minimum=minimum)
jsonstr = json.dumps(dict_nn)
filename = open(outputname+'.json', 'w') # dict转josn
filename.write(jsonstr)
style = Style(
title_color="#fff",
title_pos="center",
width=1510,
height=840,
background_color="#404a59" # #404a59"
)
style_geo = style.add(
maptype="china",
is_label_show=False,
line_curve=0.1,
line_opacity=0.6,
legend_text_color="#eee",
legend_pos="right",
geo_effect_symbol="arrow",
symbol_size=5,
geo_effect_symbolsize=5,
label_color=['#a6c84c', '#46bee9', 'red', '#ffa022','green'],#'#a6c84c'
label_pos="right",
label_formatter="{b}",
label_text_color="#eee",
# geo_cities_coords=airports_geo
)
geolines = GeoLines(outputname, **style.init_style)
for i in range(1,k+1):
geolines.add(name=str(i)+"阶", data=dict_nn[i],
is_legend_show=True, **style_geo)
geolines.render(outputname+'近邻城市.html')
return dict_nn
def Bar_x_y():
attr_1 = file.areas.value_counts().index.tolist()[0:7]
attr_2 = file.types.value_counts().index.tolist()[0:3]
datas = file[(file.areas.isin(attr_1)) & (file.types.isin(attr_2))]
data = datas.groupby(['areas', 'types']).agg({'score': 'mean'})
data.score = data.score.round(decimals=1)
list_1 = []
list_2 = []
list_3 = []
attr = attr_1
#print(city)
#print(data.score.tolist())
for i in range(0, 7):
list_1.append(data.score.tolist()[0 + 3 * i])
list_2.append(data.score.tolist()[1 + 3 * i])
list_3.append(data.score.tolist()[2 + 3 * i])
style = Style(
title_pos='center',
width=800,
height=500,
background_color='white',
)
bar_style = style.add(
legend_top='bottom',
yaxis_rotate=45,
is_label_show=None,
label_color=['#FFB90F', '#FFF68F', '#1E90FF'],
)
#print(city)
print(list_1)
bar = Bar('', **style.init_style)
bar.add('剧情', attr, list_1, is_stack=True, **bar_style) #is_stack=True堆叠
bar.add('喜剧', attr, list_2, is_stack=True, **bar_style)
bar.add('动作', attr, list_3, is_stack=True, **bar_style)
bar.render('Echarts/bar_x_y.html')
def test3():
style = Style(title_top="#fff",
title_pos="center",
width=1200,
height=600,
background_color="404a59")
style_geo = style.add(
is_label_show=True,
line_curve=0.2,
line_opacity=0.6,
legend_text_color="#eee",
legend_pos="right",
geo_effect_symbol="plane",
geo_effect_symbolsize=15,
label_color=['#a6c84c', '#ffa022', '#46bee9'],
label_pos="right",
label_formatter="{b}",
label_text_color="#eee",
)
data_guangzhou = [["广州", "上海"], ["广州", "北京"], ["广州", "南京"], ["广州", "重庆"],
["广州", "兰州"], ["广州", "杭州"]]
geolines = GeoLines("GeoLines 示例", **style.init_style)
geolines.add("从广州出发", data_guangzhou, **style_geo)
geolines.render("coordinate.html")
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
from pyecharts import GeoLines, Style
style = Style(title_top='#fff',
title_pos='center',
width=1200,
height=600,
background_color='#404a59')
style_geo = style.add(
is_label_show=True,
line_curve=0.2,
line_opacity=0.6,
lengend_text_color='#eee',
lengend_pos='right',
geo_effect_symbol='plane',
geo_effect_symbolsize=15,
label_color=['#a6c84c', '#ffa022', '#46bee9'],
label_pos='right',
label_formatter="{b}",
label_text_color="#eee",
legend_selectedmode="single",
)
data_guangzhou = [["广州", "上海"], ["广州", "北京"], ["广州", "南京"], ["广州", "重庆"],
["广州", "兰州"], ["广州", "杭州"]]
data_beijing = [["北京", "上海"], ["北京", "广州"], ["北京", "南京"], ["北京", "重庆"],
["北京", "兰州"], ["北京", "杭州"]]
geolines = GeoLines("GeoLines 示例", **style.init_style)
geolines.add("从广州出发",
data_guangzhou,
**style_geo,
from pyecharts import Geo, Style
style = Style(title_top="#fff",
title_pos="left",
width=1000,
height=800,
background_color="#404a59")
data = [['北京', '阿拉善左旗'], ['北京', '阿克苏'], ['北京', '安顺'], ['北京', '鞍山'],
['北京', '包头'], ['北京', '白城'], ['北京', '毕节'], ['北京', '保山'], ['北京', '巴彦淖尔'],
['北京', '松原'], ['北京', '深圳'], ['北京', '三亚'], ['北京', '上海'], ['北京', '十堰']]
style_geo = style.add(
is_label_show=True,
line_curve=0.2, #曲线的弯曲度
line_opacity=0.5, #航线的透明度
legend_text_color="#eee",
legend_pos="right", #示例的位置
geo_effect_symbol="plane",
geo_effect_symbolsize=10, #飞机大小
label_color=['#ffa022', '#ffa022', '#46bee9'],
label_pos="right",
label_formatter="{b}", #地方标签的格式
label_text_color="#eee",
)
geolines = Geo("GeoLines 示例", **style.init_style) #相当于设置背景
geolines.add("从北京出发", data, tooltip_formatter="{a} : {c}", **style_geo)
geolines.render("F:/Python-study-diary/pyechartsss/airport1.html")
title_top="#fff",
title_pos = "center",
width=1200,
height=600,
background_color="#404a59"
)
style_geo = style.add(
is_label_show=False,
symbol=['arrow', 'arrow'],
symbol_size=1,
line_width=3,
line_curve=0.2,
line_opacity=0.6,
# legend_text_color="#eee",
legend_pos="center",
geo_effect_symbol="arrow",
geo_effect_symbolsize=5,
label_color=['#B9D3EE', '#C5C1AA', '#DB7093', '#B4EEB4', '#CD8162', '#FFEC8B', '#CD96CD'],
label_pos="right",
label_formatter="{b}",
label_text_color="#00CDCD",
item_color='#CD5C5C',
legend_text_color='#CD5C5C'
)
def create_charts(data):
style = Style(width=900, height=900)
page = Page()
html=''
charts = GeoLines("丝绸之路", **style.init_style)
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)
for item in kwargs.items():
if 'color' == item[0]:
color_map = {'r': '#CD0000',
'g': '#008B00',
'b': '#0000EE',
'c':'#40E0D0',
'm': '#CD00CD',
'y': '#EE9A00',
'k': '#000000',
'w': '#FFFFFF'
}
result['line_color'] = color_map[item[1]] if item[1] in color_map else color_map['r']
elif 'linestyle' == item[0]:
line_map = {'-' : 'solid',
'--': 'dashed',
':' : 'dotted'}
result['line_type'] = line_map[item[1]] if item[1] in line_map else line_map['-']
else:
result[item[0]] = item[1]
return result
style = Style(
title_top="#fff",
title_pos="center",
width=1200,
height=600,
background_color="#404a59",
)
style_geo = style.add(
is_label_show=True,
line_curve=0.2,
line_opacity=0.6,
legend_text_color="#eee",
legend_pos="right",
geo_effect_symbol="plane",
geo_effect_symbolsize=15,
label_color=["#a6c84c", "#ffa022", "#46bee9"],
label_pos="right",
label_formatter="{b}",
label_text_color="#eee",
legend_selectedmode="single",
)
def test_geolines():
data_guangzhou = [
["广州", "上海"],
["广州", "北京"],
["广州", "南京"],
["广州", "重庆"],
["广州", "兰州"],
