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 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')
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 analysisProvince():
friends_info = get_friends_info()
df = pd.DataFrame(friends_info)
province_count = df.groupby(
'province', as_index=True)['province'].count().sort_values()
temp = list(
map(lambda x: x if x != '' else '未知', list(province_count.index)))
# 画图
page = Page()
style = Style(width=1100, height=600)
style_middle = Style(width=900, height=500)
attr, value = temp, list(province_count)
chart1 = Map('好友分布(中国地图)', **style.init_style)
chart1.add('',
attr,
value,
is_label_show=True,
is_visualmap=True,
visual_text_color='#000')
page.add(chart1)
chart2 = Bar('好友分布柱状图', **style_middle.init_style)
chart2.add('',
attr,
value,
is_stack=True,
is_convert=True,
label_pos='inside',
is_legend_show=True,
is_label_show=True)
page.add(chart2)
page.render('analysisProvince.html')
def analysisCity(province):
friends_info = get_friends_info()
df = pd.DataFrame(friends_info)
temp1 = df.query('province == "%s"' % province)
city_count = temp1.groupby('city',
as_index=True)['city'].count().sort_values()
attr = list(
map(lambda x: '%s市' % x if x != '' else '未知', list(city_count.index)))
value = list(city_count)
# 画图
page = Page()
style = Style(width=1100, height=600)
style_middle = Style(width=900, height=500)
chart1 = Map('%s好友分布' % province, **style.init_style)
chart1.add('',
attr,
value,
maptype='%s' % province,
is_label_show=True,
is_visualmap=True,
visual_text_color='#000')
page.add(chart1)
chart2 = Bar('%s好友分布柱状图' % province, **style_middle.init_style)
chart2.add('',
attr,
value,
is_stack=True,
is_convert=True,
label_pos='inside',
is_label_show=True)
page.add(chart2)
page.render('analysisCity.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._option.get("baseOption").get("series")) == 0
timeline.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 create_charts():
users = get_friends()
page = Page()
style = Style(width=1100, height=600)
style_middle = Style(width=900, height=500)
data = sex_stats(users)
attr, value = data
chart = Pie('微信性别') # title_pos='center'
chart.add('', attr, value, center=[50, 50],
radius=[30, 70], is_label_show=True, legend_orient='horizontal', legend_pos='center',
legend_top='bottom', is_area_show=True)
page.add(chart)
data = prov_stats(users)
attr, value = data
chart = Map('中国地图', **style.init_style)
chart.add('', attr, value, is_label_show=True, is_visualmap=True, visual_text_color='#000')
page.add(chart)
chart = Bar('柱状图', **style_middle.init_style)
chart.add('', attr, value, is_stack=True, is_convert=True, label_pos='inside', is_legend_show=True,
is_label_show=True)
page.add(chart)
data = gd_stats(users)
attr, value = data
chart = Map('河南', **style.init_style)
chart.add('', attr, value, maptype='河南', is_label_show=True, is_visualmap=True, visual_text_color='#000')
page.add(chart)
chart = Bar('柱状图', **style_middle.init_style)
chart.add('', attr, value, is_stack=True, is_convert=True, label_pos='inside', is_label_show=True)
page.add(chart)
page.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")
assert len(timeline.options.get("baseOption").get("series")) == 0
timeline.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 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 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 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 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_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 render_city(cities):
# 对城市数据和坐标文件中的地名进行处理
handle(cities)
data = Counter(cities).most_common() # 使用Counter类统计出现的次数，并转换为元组列表
print(data)
# 定义样式
style = Style(title_color='#fff',
title_pos='center',
width=1200,
height=600,
background_color='#404a59')
# 根据城市数据生成地理坐标图
geo = Geo('《悲伤逆流成河》粉丝位置分布', **style.init_style)
attr, value = geo.cast(data)
geo.add('',
attr,
value,
visual_range=[0, 600],
visual_text_color='#fff',
symbol_size=15,
is_visualmap=True,
is_piecewise=True,
visual_split_number=10)
geo.render(d + '/picture/geo.html')
def create_charts():
page = Page()
style = Style(width=900, height=600, title_pos='center')
w = '雷音'
res = {}
for rt, ds, ffs in os.walk('/Users/fxm/经语料/T_out/'):
for d in ds:
if int(d.replace('T', '')) < 18:
for rr, dd, ff in os.walk(rt + d):
for f in ff:
with open(rr + '/' + f, encoding='utf8') as file:
ss = file.read()
jm = re.search('title:(.*)\s', ss).group(1)
try:
res[jm] += ss.count(w)
except:
res[jm] = ss.count(w)
res = sorted(res.items(), key=lambda x: x[1], reverse=True)[:50]
attr = [x[0] for x in res]
v1 = [x[1] for x in res]
chart = Bar("雷音-經目出現頻次圖", **style.init_style)
# chart.add("", attr, v1, xaxis_interval=0, xaxis_rotate=30,yaxis_rotate=30)
chart.add("",
attr,
v1,
is_label_show=True,
is_datazoom_show=True,
xaxis_rotate=30,
xaxis_interval=0)
page.add(chart)
return page
def create_charts_pie():
#pie
page = Page()
style = Style(width=1100, height=900)
data = pd.read_csv(
'/Users/fxm/PycharmProjects/fo/data/结果/名+标点_class_1213.csv')
ks1, vs1 = [], []
for k, v in countit(data['d'].values).items():
ks1.append(k)
vs1.append(v)
ks2, vs2 = [], []
for k, v in countit(data['e'].values).items():
ks2.append(k)
vs2.append(v)
chart = Pie("类别分布", title_pos='center', **style.init_style)
chart.add("",
ks2,
vs2,
radius=[60, 80],
is_label_show=True,
is_legend_show=False)
chart.add("",
ks1,
vs1,
radius=[0, 50],
is_label_show=True,
is_legend_show=False,
label_pos='inside')
page.add(chart)
return page
def create_line(title, line_data, show_avg=True, attr=None):
# 横竖坐标的大小
style = Style(width=800, height=600)
chart = Line(title, **style.init_style)
if len(line_data) == 0:
return
if attr is None:
attr = []
size = len(line_data[0].dataList)
for i in range(1, size + 1):
cur = u"第 " + str(i) + u" 次"
attr.append(cur)
for data in line_data:
if show_avg is True:
chart.add(data.phone_type,
attr,
data.dataList,
is_label_show=True,
mark_line=["average"])
else:
chart.add(data.phone_type, attr, data.dataList, is_label_show=True)
return chart
def create_charts(data):
# data字典格式(三个表的情况下)：
# {'charcloud':[str:表一的前描述,str:表一的后描述,数据1,数据2,...,数据n],'...':[...]}
html = ''
page = Page()
style = Style(width=900, height=600)
# 本页面包含：1：所有字的词云charcloud(两个数据chars,values)、
# 表一：
# 获取表一的数据
html_before = data['charcloud'][0]
html_after = data['charcloud'][1]
chars = data['charcloud'][2]
values = data['charcloud'][3]
wordcloud = WordCloud("唐诗用字云图", **style.init_style)
wordcloud.add("字云",
chars,
values,
word_size_range=[10, 100],
shape='pentagon')
java_script = wordcloud.render_embed()
html += html_before + java_script + html_after
page.add(wordcloud)
# 表二：
html_before = data['chartop10'][0]
html_after = data['chartop10'][1]
chars = data['chartop10'][2]
values = data['chartop10'][3]
bar = Bar("唐诗高频十字", **style.init_style)
bar.add("柱状图", chars, values)
java_script = bar.render_embed()
html += html_before + java_script + html_after
page.add(bar)
# 表三:
html_before = data['frequency×'][0]
html_after = data['frequency×'][1]
keys = data['frequency×'][2]
values = data['frequency×'][3]
line = Line("唐诗字频-字数", **style.init_style)
line.add("字频--字数",
keys,
values,
is_smooth=True,
is_fill=True,
area_opacity=0.2,
is_datazoom_show=True,
datazoom_type="both",
datazoom_range=[0, 60],
xaxis_interval=1,
yaxis_formatter="字",
xaxis_name="频次",
yaxis_name="字数",
xaxis_name_pos="end",
yaxis_name_pos="end",
is_more_utils=True)
java_script = line.render_embed()
html += html_before + java_script + html_after
page.add(line)
# 最后
script = page.get_js_dependencies()
return html, script
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 ewide2(request):
template = loader.get_template('ewpyecharts.html')
style = Style(
title_top="#fff",
title_pos="center",
width=1200,
height=600,
background_color="#404a59"
)
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("水务地图可视化--点线图", **style.init_style)
geolines.add("从广州出发", data_guangzhou, is_legend_show=False)
context = dict(
myechart=geolines.render_embed(),
host=REMOTE_HOST,
script_list=geolines.get_js_dependencies()
)
return HttpResponse(template.render(context, request))
def getView(self):
db = DBUtils()
sql = 'select city from comment'
city = db.selectallInfo(sql)
print(city)
for i in city:
citys.append(i[0])
data = []
for item in self.all_list(citys):
data.append((item, self.all_list(citys)[item]))
style = Style(title_color="#fff",
title_pos="center",
width=950,
height=650,
background_color="#404a59")
geo = Geo("《西红市首富》粉丝人群地理位置", "刘宏伟", **style.init_style)
attr, value = geo.cast(data)
geo.add("",
attr,
value,
visual_range=[
0,
],
visual_text_color="#fff",
symbol_size=20,
is_visualmap=True,
is_piecewise=True,
visual_split_number=5)
geo.render('../templates/render.html')
def geo_qgtd(attr_v1: List[Tuple[str, int]], chart_name: str,
v1_name: str) -> geo.Geo:
"""
生成全国地图-数据通道图
:param attr_v1: 主要数据
:param chart_name: 图表名
:param v1_name: 数据一名
"""
style = Style(title_color="#fff",
title_pos="center",
width=900,
height=600,
background_color='#404a59')
# chart = Map(chart_name, **style.init_style)
# chart.add(v1_name, attr, value, maptype='china', is_visualmap=True,
# visual_text_color='#000')
chart = Geo(chart_name, "", **style.init_style)
attr, value = chart.cast(attr_v1)
chart.add(v1_name,
attr,
value,
visual_range=[0, 70000],
visual_text_color="#fff",
is_legend_show=False,
symbol_size=15,
is_visualmap=True,
tooltip_formatter='{b}',
label_emphasis_textsize=15,
label_emphasis_pos='right',
type='effectScatter')
return chart
def line_ssdd(attr_v1_v2: List[Tuple[str, int, int]], chart_name: str,
v1_name: str, v2_name: str) -> line.Line:
"""
生成一个折线图-数据堆叠图
:param attr_v1_v2: 包含想要显示的数据列表
:param chart_name: 图表名
:param v1_name: 数据一名
:param v2_name: 数据二名
"""
style = Style(width=WIDTH, height=HEIGHT)
attr = [a[0] for a in attr_v1_v2]
v1 = [v[1] for v in attr_v1_v2]
v2 = [v[2] for v in attr_v1_v2]
# chart = Line(chart_name, **style.init_style)
# chart.add(v1_name, attr, v1, is_label_show=True, is_smooth=True)
# chart.add(v2_name, attr, v2, is_label_show=True, is_smooth=True)
chart = Line(chart_name, **style.init_style)
chart.add(v1_name, attr, v1, mark_point=["average"])
chart.add(v2_name,
attr,
v2,
is_smooth=True,
mark_line=["max", "average"],
is_more_utils=True)
return chart
def visualize(df, name):
# 导入自定义的地点经纬度
geo_cities_coords = {
df.iloc[i]['poi_name']: [df.iloc[i]['lng'], df.iloc[i]['lat']]
for i in range(len(df))
} # 根据文件大小生成字典
attr = list(df['poi_name']) # 字典的每个键值
value = list(df['poi_porb']) # 由于量值的太大，换算以下(散点的颜色就是和这个想关的)
style = Style(title_color="#fff",
title_pos="center",
width=1200,
height=600,
background_color="#404a59")
# 可视化
geo = Geo(name, **style.init_style)
geo.add("",
attr,
value,
visual_range=[0.2, 1],
symbol_size=10,
visual_text_color="#fff",
is_piecewise=True,
is_visualmap=True,
maptype='北京',
visual_split_number=10,
geo_cities_coords=geo_cities_coords)
return geo
def create_geo_charts(data, title):
'''地图'''
page = Page()
# 样式
style = Style(title_color="#fff",
title_pos="center",
width=1200,
height=600,
background_color='#c4ccd3')
# 创建地图模型
chart = Geo(title, "", **style.init_style)
# 数据 ['上海', '北京', '广州', '深圳', '苏州'] [5, 40, 10, 15, 5]
attr, value = chart.cast(data)
# 添加数据
chart.add("",
attr,
value,
maptype='china',
is_visualmap=True,
type="effectScatter",
is_legend_show=False,
geo_emphasis_color='c4ccd3',
visual_text_color='#2f4554')
page.add(chart)
return page
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
#!/usr/bin/env python
# coding=utf-8
from __future__ import unicode_literals
from nose.tools import assert_raises
from pyecharts import GeoLines, Style
from pyecharts.datasets.coordinates import search_coordinates_by_keyword
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",
)
