def locate_on_map(addr, longtitude, latitude):
g = Geo().add_schema(maptype="上海")
g.add_coordinate(addr, longtitude, latitude)
data_pair = [(addr, 1)]
g.add('', data_pair, type_=GeoType.EFFECT_SCATTER, symbol_size=20)
g.set_series_opts(label_opts=options.LabelOpts(is_show=False))
g.set_global_opts(title_opts=options.TitleOpts(title="地图标点测试"))
g.render_notebook()
print("process finished")
def out_data(date_number):
city_list = ('南宁市', '柳州市', '桂林市', '梧州市', '北海市', '防城港市', '钦州市', '贵港市',
'玉林市', '百色市', '贺州市', '河池市', '来宾市', '崇左市')
city_od_list_pro = []
city_od_values_pro = []
for i in city_list:
city = i
workbook = xlrd.open_workbook(f'.\\{path}\\{city}-迁入来源地规模指数.xlsx')
sheet = workbook.sheet_by_index(0)
city_od_list = []
city_od_values = []
a = 0
cols = sheet.col_values(1)[1:]
cols_date = sheet.col_values(date_number + 1)[1:]
for j in cols:
city_od = (city, j)
city_od_v = (j, cols_date[a])
city_od_list.append(city_od)
city_od_values.append(city_od_v)
a += 1
city_od_list_pro.append(city_od_list)
city_od_values_pro.append(city_od_values)
od_list = []
os_values = []
for i in range(14):
for j in range(14):
od_list.append(city_od_list_pro[i][j])
os_values.append(city_od_values_pro[i][j])
# print(od_list)
# print(os_values)
geo = Geo()
# 地图类型，世界地图可换为world
geo.add_schema(maptype="广西")
# 添加数据点
geo.add("%", os_values, type_=ChartType.EFFECT_SCATTER)
# 添加流向，type_设置为LINES，涟漪配置为箭头，提供的标记类型包括 'circle', 'rect', 'roundRect', 'triangle',
# 'diamond', 'pin', 'arrow', 'none'
geo.add("迁出城市",
od_list,
type_=ChartType.LINES,
effect_opts=opts.EffectOpts(symbol=SymbolType.ARROW,
symbol_size=5,
color="yellow"),
linestyle_opts=opts.LineStyleOpts(curve=0.2),
is_large=True)
# 不显示标签
geo.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
# 设置图标标题，visualmap_opts=opts.VisualMapOpts()为左下角的视觉映射配置项
geo.set_global_opts(visualmap_opts=opts.VisualMapOpts(),
title_opts=opts.TitleOpts(title="广西地市迁徙数据"))
# 直接在notebook里显示图表
geo.render_notebook()
# 生成html文件，可传入位置参数
geo.render(f".\\out_od\\广西-2020.10.{date_number}迁出OD图.html")
def in_data(city, date_number):
workbook = xlrd.open_workbook(f'.\\{path}\\{city}-迁入来源地规模指数.xlsx')
sheet = workbook.sheet_by_index(0)
city_od_list = []
city_od_values = []
a = 0
cols = sheet.col_values(1)[1:]
cols_date = sheet.col_values(date_number + 1)[1:]
for j in cols:
city_od = (j, city)
city_od_v = (j, cols_date[a])
city_od_list.append(city_od)
city_od_values.append(city_od_v)
a += 1
geo = Geo()
# 地图类型，世界地图可换为world
geo.add_schema(maptype="广西")
# 添加数据点
geo.add("%", city_od_values, type_=ChartType.EFFECT_SCATTER)
# 添加流向，type_设置为LINES，涟漪配置为箭头，提供的标记类型包括 'circle', 'rect', 'roundRect', 'triangle',
# 'diamond', 'pin', 'arrow', 'none'
geo.add("迁入城市",
city_od_list,
type_=ChartType.LINES,
effect_opts=opts.EffectOpts(symbol=SymbolType.ARROW,
symbol_size=5,
color="yellow"),
linestyle_opts=opts.LineStyleOpts(curve=0.2),
is_large=True)
# 不显示标签
geo.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
# 设置图标标题，visualmap_opts=opts.VisualMapOpts()为左下角的视觉映射配置项
geo.set_global_opts(visualmap_opts=opts.VisualMapOpts(),
title_opts=opts.TitleOpts(title=f"{city}迁入数据"))
# 直接在notebook里显示图表
geo.render_notebook()
# 生成html文件，可传入位置参数
geo.render(f".\\in_od\\{city}-2020.10.{date_number}迁入OD图.html")
("深圳", 1),
("汕头", 1),
("烟台", 1),
("威海", 1),
("芜湖", 1),
("南京", 1),
("温州", 1),
("嘉兴", 1),
],
type_=ChartType.EFFECT_SCATTER)
c.add(
"机场",
[
("北京", 6),
("呼和浩特", 4),
("南昌", 4),
("贵州", 4),
("成都", 4),
("哈尔滨", 2),
("乌鲁木齐", 1),
("郑州", 1),
("沈阳", 2),
("长春", 1),
],
type_=ChartType.EFFECT_SCATTER,
)
c.set_series_opts(label_opts=opts.LabelOpts(is_show=False)).set_global_opts(
title_opts=opts.TitleOpts(title="港口机场分布图"),
visualmap_opts=opts.VisualMapOpts(max_=30))
c.render_notebook()
)
pie.render_notebook()
# 高校分布热力图
geo = Geo()
geo.add_schema(maptype="china")
geo.add("高校分布热力图", [
list(z)
for z in zip(data['name'].values.tolist(), data['counts'].values.tolist())
],
type_=ChartType.HEATMAP)
geo.set_global_opts(
visualmap_opts=opts.VisualMapOpts(),
title_opts=opts.TitleOpts(title="全国高校热力图"),
)
geo.render_notebook()
# 各地区高校数量段位图
geo = Geo()
geo.add_schema(maptype="china")
geo.add("各地区高校数量段位图", [
list(z)
for z in zip(data['name'].values.tolist(), data['counts'].values.tolist())
],
type_=ChartType.EFFECT_SCATTER)
geo.set_global_opts(
visualmap_opts=opts.VisualMapOpts(is_piecewise=True, max_=150),
title_opts=opts.TitleOpts(title="各地区高校数量段位图"),
)
geo.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
geo.render_notebook()
a.add_schema(
maptype="china",
itemstyle_opts=opts.ItemStyleOpts(color="#323c40", border_color="gray"),
is_roam=True,
zoom=1,
)
a.add(
"",
[("广州", 44), ("北京", 66), ("杭州", 77), ("重庆", 88),
("西安", 99)], #后边的数字代表每个城市的数据
type_=ChartType.EFFECT_SCATTER,
color="white",
)
a.add(
"",
[("广州", "上海"), ("广州", "北京"), ("广州", "杭州"), ("广州", "重庆"), ("广州", "西安")],
type_=ChartType.LINES,
effect_opts=opts.EffectOpts(symbol=SymbolType.ARROW,
symbol_size=6,
color="gold"),
linestyle_opts=opts.LineStyleOpts(curve=0.1),
)
a.set_series_opts(label_opts=opts.LabelOpts(is_show=False)).set_global_opts(
title_opts=opts.TitleOpts(title="航线图"))
a.render_notebook()
