def plot_geo_station_num(re_dic, to_path):
dw = my_(config.MYSQL_BI_RW_ENV)
muchcols_table = 'data_center.dc_stations_muchcols_enc'
sqls = "select city scale,avg(latitude) avg_lat,avg(longitude) avg_lng,count(*) numbers from %s where name like '%%%s%%' group by city order by numbers desc" % (
muchcols_table, re_dic['name'])
count_station_ = dw.to_dataframe(sqls)
# count_station_['scale'] = count_station_['scale'].apply(lambda x: change_city(x, pro))
coords = {}
for i in range(len(count_station_)):
coords[count_station_.loc[i, 'scale']] = [count_station_.loc[i, 'avg_lng'], count_station_.loc[i, 'avg_lat']]
num_Max = count_station_['numbers'].max()
name_str = "油站名包含'%s':" % re_dic['name'] if re_dic['name'] else ''
page = pyecharts.Page()
style = pyecharts.Style(width=1300, height=860, background_color='#404a66', title_color="#eee", title_pos="center")
geo = pyecharts.Geo(name_str + "油站分布地图", **style.init_style)
geo.add("", count_station_['scale'], count_station_['numbers'], visual_text_color="#eee", is_legend_show=False,
symbol_size=12, is_visualmap=True, visual_range=[0, num_Max],
tooltip_formatter='{b}',
label_emphasis_textsize=15,
label_emphasis_pos='right', geo_cities_coords=coords)
page.add(geo)
chart2 = pyecharts.Bar(name_str + "油站分布柱状图", **style.init_style)
chart2.add("", count_station_['scale'][:25], count_station_['numbers'][:25], visual_range=[0, num_Max],
is_label_show=True,
is_visualmap=True, visual_text_color='#eee')
page.add(chart2)
page.render(to_path)
def aboutMe(request):
gauge = pyecharts.Gauge('', background_color='#f5f5f5')
gauge.add('title',
'Percent',
80.66,
scale_range=[0, 100],
is_more_utils=True)
gauge.show_config()
result = gauge.render_embed()
data = [("海门", 9), ("鄂尔多斯", 10), ("招远", 12), ("舟山", 18), ("齐齐哈尔", 10),
("盐城", 15)]
geo = pyecharts.Geo("全国主要城市空气质量",
"data from pm2.5",
title_color="#000",
title_pos="center",
background_color='#f5f5f5')
attr, value = geo.cast(data)
geo.add("",
attr,
value,
type="effectScatter",
is_random=True,
effect_scale=5,
is_more_utils=True)
geo.show_config()
result1 = geo.render_embed()
attr = ["Jan", "Feb", "Mar", "Apr", "May", "Jun"]
v1 = [20, 33, 133, 124, 24, 313]
v2 = [2.6, 12, 31, 241, 324, 134]
bar = pyecharts.Bar('Bar Sample', background_color='#f5f5f5')
bar.add("A", attr, v1, mark_line=["average"], mark_point=["min", "max"])
bar.add("B",
attr,
v2,
mark_line=["average"],
mark_point=["min", "max"],
is_more_utils=True)
bar_result = bar.render_embed()
pie = pyecharts.Pie('', background_color="#f5f5f5")
pie.add("",
attr,
v1,
is_lable_show=True,
lable_text_color="#156ACF",
is_more_utils=True)
pie.show_config()
pie_result = pie.render_embed()
liquid = pyecharts.Liquid('', background_color="#000")
liquid.add("", [0.66, 0.5], ['diamond'], ['#294D99', '#156ACF'],
is_more_utils=True)
liquid.show_config()
liquid_result = liquid.render_embed()
return render_to_response(
'AboutMe.html', {
'result': result,
'result1': result1,
'bar_result': bar_result,
'pie_result': pie_result,
'liquid_result': liquid_result
})
def t9(pa):
# geo地图有不显示数值的bug加上下面的函数和 add的参数 label_formatter=label_formatter
def label_formatter(params):
return params.value[2]
style = p.Style(title_color="#fff",
title_pos="center",
width=1200,
height=600,
background_color='#404a59')
chart = p.Geo("山东省计算机职位分布",
'数据来自齐鲁人才网，部分地区数据不准确',
**style.init_style,
subtitle_text_size=18)
city = [i.replace('市', '') for i in next(pa)]
# label_formatter=label_formatter防bug maptype去掉就是全国地图
chart.add("",
city,
next(pa),
maptype='山东',
visual_range=[0, 700],
label_formatter=label_formatter,
visual_text_color="#fff",
is_legend_show=True,
symbol_size=15,
is_visualmap=True,
tooltip_formatter='{b}',
label_emphasis_textsize=15,
label_emphasis_pos='right',
is_toolbox_show=False)
return chart
def generateChinaMap():
data = [("海门", 9), ("鄂尔多斯", 12), ("招远", 12), ("舟山", 12), ("齐齐哈尔", 14),
("盐城", 15), ("赤峰", 16), ("青岛", 18), ("乳山", 18), ("金昌", 19),
("泉州", 21), ("莱西", 21), ("日照", 21), ("胶南", 22), ("南通", 23),
("拉萨", 24), ("云浮", 24), ("梅州", 25), ("文登", 25), ("上海", 25),
("攀枝花", 25), ("威海", 25), ("承德", 25), ("厦门", 26), ("汕尾", 26),
("潮州", 26), ("丹东", 27), ("太仓", 27), ("曲靖", 27), ("烟台", 28),
("福州", 29), ("瓦房店", 30), ("即墨", 30), ("抚顺", 31), ("玉溪", 31),
("张家口", 31), ("阳泉", 31), ("莱州", 32), ("湖州", 32), ("汕头", 32),
("昆山", 33), ("宁波", 33), ("湛江", 33), ("揭阳", 34), ("荣成", 34),
("连云港", 35), ("葫芦岛", 35), ("常熟", 36), ("东莞", 36), ("河源", 36),
("淮安", 36), ("泰州", 36), ("南宁", 37), ("营口", 37), ("惠州", 37),
("江阴", 37), ("蓬莱", 37), ("韶关", 38), ("嘉峪关", 38), ("广州", 38),
("延安", 38), ("太原", 39), ("清远", 39), ("中山", 39), ("昆明", 39),
("寿光", 40), ("盘锦", 40), ("长治", 41), ("深圳", 41), ("珠海", 42),
("宿迁", 43), ("咸阳", 43), ("铜川", 44), ("平度", 44), ("佛山", 44),
("海口", 44), ("江门", 45), ("章丘", 45), ("肇庆", 46), ("大连", 47),
("临汾", 47), ("吴江", 47), ("石嘴山", 49), ("沈阳", 50), ("苏州", 50),
("茂名", 50), ("嘉兴", 51), ("长春", 51), ("胶州", 52), ("银川", 52),
("张家港", 52), ("三门峡", 53), ("锦州", 54), ("南昌", 54), ("柳州", 54),
("三亚", 54), ("自贡", 56), ("吉林", 56), ("阳江", 57), ("泸州", 57),
("西宁", 57), ("宜宾", 58), ("呼和浩特", 58), ("成都", 58), ("大同", 58),
("镇江", 59), ("桂林", 59), ("张家界", 59), ("宜兴", 59), ("北海", 60),
("西安", 61), ("金坛", 62), ("东营", 62), ("牡丹江", 63), ("遵义", 63),
("绍兴", 63), ("扬州", 64), ("常州", 64), ("潍坊", 65), ("重庆", 66),
("台州", 67), ("南京", 67), ("滨州", 70), ("贵阳", 71), ("无锡", 71),
("本溪", 71), ("克拉玛依", 72), ("渭南", 72), ("马鞍山", 72), ("宝鸡", 72),
("焦作", 75), ("句容", 75), ("北京", 79), ("徐州", 79), ("衡水", 80),
("包头", 80), ("绵阳", 80), ("乌鲁木齐", 84), ("枣庄", 84), ("杭州", 84),
("淄博", 85), ("鞍山", 86), ("溧阳", 86), ("库尔勒", 86), ("安阳", 90),
("开封", 90), ("济南", 92), ("德阳", 93), ("温州", 95), ("九江", 96),
("邯郸", 98), ("临安", 99), ("兰州", 99), ("沧州", 100), ("临沂", 103),
("南充", 104), ("天津", 105), ("富阳", 106), ("泰安", 112), ("诸暨", 112),
("郑州", 113), ("哈尔滨", 114), ("聊城", 116), ("芜湖", 117), ("唐山", 119),
("平顶山", 119), ("邢台", 119), ("德州", 120), ("济宁", 120), ("荆州", 127),
("宜昌", 130), ("义乌", 132), ("丽水", 133), ("洛阳", 134), ("秦皇岛", 136),
("株洲", 143), ("石家庄", 147), ("莱芜", 148), ("常德", 152), ("保定", 153),
("湘潭", 154), ("金华", 157), ("岳阳", 169), ("长沙", 175), ("衢州", 177),
("廊坊", 193), ("菏泽", 194), ("合肥", 229), ("武汉", 273), ("大庆", 279)]
geo = pyecharts.Geo("全国空气质量检测",
"data from PM2.5",
title_color="#fff",
title_pos="center",
width=1000,
height=600,
background_color='#404a59')
attr, value = geo.cast(data)
geo.add("",
attr,
value,
visual_range=[0, 20],
maptype='china',
visual_text_color='#fff',
symbol_size=10,
is_visualmap=True)
geo.render("全国空气质量检测.html")
geo
def func():
page = pyecharts.Page() # step 1
# 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 = pyecharts.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) # step 2
# 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 = pyecharts.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) # step 2
page.render() # step 3
# scatter_geo
attr = ['11', '22']
data = ['1', '2']
scatter_geo = pyecharts.Geo("地理位置视图", width=1200, height=600)
scatter_geo.add("", attr, data)
page.add(scatter_geo) # step 2
page.render() # step 3
data = [["广州", "北京"], ["广州", "上海"]]
scatter_geo = pyecharts.GeoLines("地理位置视图", width=1200, height=600)
scatter_geo.add("上午航班",
data,
geo_normal_color='#ff00ff',
geo_effect_period=9,
geo_effect_color='#ff0000',
geo_effect_symbol='arrow')
data = [["广州", "南昌"], ["广州", "成都"]]
scatter_geo.add("下午航班",
data,
geo_effect_traillength=1,
geo_emphasis_color='#0000ff')
page.add(scatter_geo) # step 2
page.render() # step 3
def geoData(self, chatroom=None):
path = self.savedir + 'geoData.html'
if chatroom:
cmd = 'geoData %s' % chatroom
myLogging(self.cmdFile, self.nickName, infoType='cmd', other=cmd)
try:
chatroom == self.instance.search_chatrooms(
name=chatroom)[0]['NickName']
except Exception as reason:
self.instance.send('在您的通讯录中没有找到该群[%s]' % chatroom)
myLogging(self.errFile,
self.nickName,
infoType='err',
other=cmd,
info=reason)
return
memberList = self.getChatroomMembers(chatroom)['MemberList']
subtitle = self.nickName + ':' + chatroom
else:
cmd = 'geoData'
myLogging(self.cmdFile, self.nickName, infoType='cmd', other=cmd)
memberList = [each['Signature'] for each in self.frdInfoList]
subtitle = self.nickName
cities = [each['City'] for each in memberList]
with open(
os.path.dirname(os.path.abspath(__file__)) +
'/city_coordinates.json', 'rb') as f:
cityDict = json.load(f)
data = [(each, cities.count(each)) for each in set(cities)
if each in cityDict.keys()]
geo = pyecharts.Geo('微信好友地理分布',
subtitle,
title_color="#fff",
title_pos="center",
background_color='#404a59')
attr, value = geo.cast(data)
geo.add("",
attr,
value,
visual_range=[0, 100],
visual_text_color="#fff",
symbol_size=10,
is_visualmap=True)
geo.render(path)
self.instance.send('@fil@%s' % path)
os.remove(path)
myLogging(self.cmdFile,
self.nickName,
infoType='cmd',
status='success',
other=cmd)
def read_region(q, star_date, end_date):
# q = '11'
keyword = q
q = quote(q, 'utf-8')
request_url = 'http://47.92.145.108:30003/youche/wordsArea.do?keyword=' + q + '&startDate=' + star_date + '&endDate=' + end_date
s = urllib.request.urlopen(request_url).read().decode('utf8')
json_data = json.loads(s)
region_list = json_data['simba_insight_wordsareadata_get_response'][
'word_areadata_list']['insight_words_area_distribute_data_d_t_o']
regions = []
values = []
min_num = 100000000
max_num = 0
for region in region_list:
if 'cityname' in region:
region_name = region['cityname']
if region_name == '内蒙':
region_name = '内蒙古'
if region_name.find('中国其它') > -1 or region_name.find('国外') > -1:
continue
regions.append(region_name)
pv = int(region['impression'])
if pv < min_num:
min_num = pv
if pv > max_num:
max_num = pv
values.append(region['impression'])
# print(region['cityname'])
geo = pyecharts.Geo(keyword + "--全国主要城市访问量",
star_date + "~" + end_date,
title_color="#fff",
title_pos="center",
width=1000,
height=600,
background_color='#404a59')
# attr, value = geo.cast(data)
geo.add("流量",
regions,
values,
visual_range=[min_num, max_num],
maptype='china',
visual_text_color="#fff",
symbol_size=10,
is_visualmap=True)
# map = Map(keyword+"~全国主要城市访问量", star_date+"~"+end_date, width=1200, height=600)
# map.add("", regions, values, visual_range=[min_num, max_num], maptype='china', is_visualmap=True, is_label_show=True,
# visual_text_color='#000')
return geo
def create_Geo():
geo = pyecharts.Geo("最高气温地理坐标系图",
'2018-4-16',
title_color='#fff',
title_pos='center',
width=1200,
height=600,
background_color='#404a95')
geo.add("最高气温",
cities,
highs,
is_visualmap=True,
visual_range=[0, 40],
visual_text_color='#fff',
symbol_size=5,
legend_pos='right',
is_geo_effect_show=True)
# geo.render("Geo-Low.html")
page.add(geo)
def plot_geo_station(re_dic, to_path):
dw = my_(config.MYSQL_BI_RW_ENV)
muchcols_table = 'data_center.dc_stations_muchcols_enc'
sqls = "select name scale,latitude lat,longitude lng from %s where name like '%%%s%%'" % (muchcols_table, re_dic['name'])
count_station_ = dw.to_dataframe(sqls)
count_station_['numbers']=1
coords={}
for i in range(len(count_station_)):
coords[count_station_.loc[i,'scale']]=[count_station_.loc[i,'lng'],count_station_.loc[i,'lat']]
# num_Max = count_station_['numbers'].max()
name_str = "油站名包含'%s':" %re_dic['name'] if re_dic['name'] else ''
page = pyecharts.Page()
style = pyecharts.Style(width=1300, height=860, background_color='#404a49', title_color="#eee", title_pos="center")
geo = pyecharts.Geo(name_str+"油站分布地图",**style.init_style)
geo.add("",count_station_['scale'], count_station_['numbers'], visual_text_color="#eee", is_legend_show=False,
symbol_size=11, is_visualmap=True,
tooltip_formatter='{b}',
label_emphasis_textsize=15,
label_emphasis_pos='right',geo_cities_coords=coords)
page.add(geo)
page.render(to_path)
def plot_city(friends):
friends_city = []
for city in friends[1:]:
friends_city.append(city['City'])
city_loc = collections.Counter(friends_city)
print(city_loc)
values = []
for city in set(friends_city):
if city != '' and city.isalpha() and city[0].isupper() == False:
values.append((city, city_loc[city]))
geo = pc.Geo(u"陈永斌 各省微信好友分布",
'John',
title_color='#fff',
title_pos='center',
width=1200,
height=600,
background_color='#404a59')
attr, value = geo.cast(values)
print(value)
print(attr)
geo.add('',
attr,
value,
visual_range=[0, 200],
visual_text_color='#fff',
symbol_size=15,
is_visualmap=True)
geo.show_config()
geo.render('weixin2.html')
names=['id','city','comments','score','date','fileview','sex']
UniqueComments=pd.read_table('/home/monchu/Data/assignments/aquamanComments.txt','r',names=names,delimiter='\t')
cityCounter=Counter()
UniqueComments['city'].describe()
after=pd.DataFrame()
for index,row in UniqueComments.iterrows():
if row['date']>'2018-12-07 00:00:00':
try:
city=unicode(row['city'],'utf-8')
cityCounter[city]+=1
#after=after.append(row)
except:pass
#after.to_csv('/home/monchu/Data/assignments/Valuable.csv',sep='\t',index=False)
cityDict=dict(cityCounter)
attr,value=pyecharts.Geo.cast(cityDict)
geo= pyecharts.Geo("Distribution of Aquaman film commenters in China (Total comments:{})".format(sum(value)), "Data scraped from MaoYao.com; Before 2018-12-20 11:09:25", title_color="#fff", title_pos="center", width=1200, height=600,background_color='#404a59')
geo.add_coordinate_json('/home/monchu/Data/assignments/city2.json')
flag=True
i=0
geo.add_coordinate(u'伊犁',80.9,91.01)
geo.add_coordinate(u'杨凌',107.59,34.14)
geo.add_coordinate(u'海东',102.12,36.50)
geo.add_coordinate(u'海南州',99,36)
geo.add_coordinate(u'璧山',106.15,29.41)
geo.add_coordinate(u'锡林郭勒',116.23,43.23)
while flag:
try:
geo.add("", attr, value,visual_range=[min(value),max(value)],is_piecewise=True,visual_text_color="#fff",symbol_size=6, is_visualmap=True,visual_split_numer=6)
print "?"
flag=False
except Exception as e:
except:
pass
results = pd.DataFrame(
results, columns=['cityName', 'content', 'gender', 'id', 'startTime'])
print(results[:5])
results.to_csv('movie_duye_comments.txt', sep='\t', index=False)
data = pd.read_csv('movie_duye_comments.txt',
sep='\t',
header=0,
encoding='utf-8')
print(data['content'][:5])
##pic 1 distribution map
geo = pyecharts.Geo(' distribution of duye ', 'data resource: maoyan')
attr, value = geo.cast(list(data['content']))
# print(value)
geo.add('',
attr,
value,
visual_range=[0, 5000],
visual_text_color='#fff',
symbol_size=15,
is_visualmap=True,
is_piecewise=False,
visual_split_number=10)
geo.render('movie_duye_map.html')
##pic 2 city bar
data_top20 = Counter(list(data['cityName'])).most_common(20)
['广州', '杭州']
]
'''
data_gz = [['广州', '上海'], ['广州', '杭州'], ['广州', '南京'], ['广州',
'西安'], ['广州', '北京'],
['广州', '长沙'], ['广州', '重庆'], ['广州', '成都'], ['广州',
'南昌'], ['广州', '贵阳'],
['广州', '昆明'], ['广州', '哈尔滨'],
['广州', '武汉'], ['广州', '兰州'], ['广州', '拉萨'], ['广州', '乌鲁木齐'],
['广州', '呼和浩特'], ['广州', '台北'], ['广州', '天津'], ['广州', '福州'],
['广州', '郑州'], ['广州', '太原'], ['广州', '长春'], ['广州',
'济南'], ['广州', '银川'],
['广州', '南宁'], ['广州', '海口'], ['广州', '合肥'], ['广州',
'石家庄'], ['广州', '沈阳']]
geo = pca.Geo('GeoLines示例', **style.init_style)
geo_lines = pca.GeoLines('GeoLines示例', **style.init_style)
geo_lines.add('从广州出发', data_gz, is_legend_show=False)
geo_lines.render(r'd:\render.html')
from pyecharts import Geo
import pyecharts as pca
style = pca.Style(title_top='#fff',
title_pos='center',
width=1200,
height=600,
background_color='#404a59')
data = [('广州', 45), ('漳州', 35), ('A市', 43)]
geo = Geo("全国主要城市空气质量", "data from pm2.5", **style.init_style)
bar = echarts.Bar("Bar chart", "precipitation and evaporation one year")
bar.add("precipitation",
attr,
v1,
is_label_show=True,
label_formatter=label_formatter)
bar.render(path='tmp/formatter.html')
# Tooltip tooltip_formatter
if __name__ == '__main__':
def geo_formatter(params):
return params.name + ' : ' + params.value[2]
data = [('澄海区', 30), ('南澳县', 40), ('龙湖区', 50), ('金平区', 60)]
geo = echarts.Geo("汕头市地图示例", )
attr, value = geo.cast(data)
geo.add(
"",
attr,
value,
maptype="汕头",
is_visualmap=True,
is_legend_show=False,
tooltip_formatter=geo_formatter, # 重点在这里，将函数直接传递为参数。
label_emphasis_textsize=15,
label_emphasis_pos='right',
)
geo.render(path='tmp/formatter.html')
# Label 示例
def aboutMe(request):
gauge = pyecharts.Gauge('', background_color='#f5f5f5')
gauge.add('title',
'Percent',
80.66,
scale_range=[0, 100],
is_more_utils=True)
gauge.show_config()
result = gauge.render_embed()
data = [("宿迁", 9), ("武汉", 10), ("重庆", 12), ("哈尔滨", 18), ("乌鲁木齐", 10),
("北京", 15), ("南京", 13)]
geo = pyecharts.Geo("中国各城市PM2.5含量示意图",
"data from pm2.5",
title_color="#000",
title_pos="center",
background_color='#f5f5f5')
attr, value = geo.cast(data)
geo.add("",
attr,
value,
type="effectScatter",
is_random=True,
effect_scale=5,
is_more_utils=True)
geo.show_config()
result1 = geo.render_embed()
attr = ["Jan", "Feb", "Mar", "Apr", "May", "Jun"]
v1 = [20, 33, 133, 124, 24, 313]
v2 = [2.6, 12, 31, 241, 324, 134]
bar = pyecharts.Bar('Bar Sample', background_color='#f5f5f5')
bar.add("A", attr, v1, mark_line=["average"], mark_point=["min", "max"])
bar.add("B",
attr,
v2,
mark_line=["average"],
mark_point=["min", "max"],
is_more_utils=True)
bar_result = bar.render_embed()
pie = pyecharts.Pie('', background_color="#f5f5f5")
pie.add("",
attr,
v1,
is_lable_show=True,
lable_text_color="#156ACF",
is_more_utils=True)
pie.show_config()
pie_result = pie.render_embed()
liquid = pyecharts.Liquid('', background_color="#000")
liquid.add("", [0.66, 0.5], ['diamond'], ['#294D99', '#156ACF'],
is_more_utils=True)
liquid.show_config()
liquid_result = liquid.render_embed()
l3d = line3d()
l3d_result = l3d.render_embed()
name = [
'afaaf', 'Tom han', 'ajf oafoa', 'auoj aoudh', 'ad da fa',
'auohdahb da'
]
value = [
10000,
1132,
414,
1313,
3452,
1413,
]
wordcloud = pyecharts.WordCloud(width=800,
height=400,
background_color="#000")
wordcloud.add("", name, value, word_size_range=[20, 100], rotate_step=50)
wordcloud.show_config()
w = wordcloud.render_embed()
REMOTE_HOST = "https://pyecharts.github.io/assets/js"
return render_to_response(
'AboutMe.html', {
'result': result,
'result1': result1,
'bar_result': bar_result,
'pie_result': pie_result,
'liquid_result': liquid_result,
'l3d_result': l3d_result,
'host': REMOTE_HOST,
'script_list': l3d.get_js_dependencies(),
'w': w
})