def echarts_cate_draw(adcodes,
labels,
file_path,
title="地域分布图",
subtitle="location distribute",
point_size=7):
"""
依据分类生成地域分布的echarts散点图的html文件.
:param adcodes: 地址集
:param labels: 长度必须和locations相等, 代表每个样本所属的分类.
:param file_path: 生成的html文件路径.
:param title: 图表的标题
:param subtitle: 图表的子标题
:param point_size: 每个散点的大小
"""
if len(adcodes) != len(labels):
from .exceptions import CPCAException
raise CPCAException("locations的长度与labels长度必须相等")
# 过滤 None
# 过滤掉缺乏经纬度数据的地点
coordinates = {}
tuples = []
for adcode, label in filter(lambda t: t[0] is not None,
zip(adcodes, labels)):
addr = ad2addr(adcode)
if not addr.longitude or not addr.latitude:
continue
coordinates[adcode] = (float(addr.longitude), float(addr.latitude))
tuples.append((adcode, label))
from pyecharts import Geo
geo = Geo(title,
subtitle,
title_color="#000000",
title_pos="center",
width=1200,
height=600,
background_color='#fff')
geo._coordinates = coordinates
for label, sub_tuples in itertools.groupby(tuples, operator.itemgetter(1)):
sub_adcodes_list = list(map(operator.itemgetter(0), sub_tuples))
value = [1] * len(sub_adcodes_list)
geo.add(label,
sub_adcodes_list,
value,
symbol_size=point_size,
legend_pos="left",
legend_top="bottom",
geo_normal_color="#fff",
geo_emphasis_color=" #f0f0f5")
geo.render(file_path)
def echarts_draw(adcodes,
file_path,
title="地域分布图",
subtitle="location distribute"):
"""
生成地域分布的echarts热力图的html文件.
:param adcodes: 地址集
:param file_path: 生成的html文件路径.
:param title: 图表的标题
:param subtitle: 图表的子标题
"""
from pyecharts import Geo
# 过滤 None
# 过滤掉缺乏经纬度数据的地点
coordinates = {}
counter = defaultdict(int)
for adcode in filter(None, adcodes):
addr = ad2addr(adcode)
if not addr.longitude or not addr.latitude:
continue
counter[adcode] = counter[adcode] + 1
coordinates[adcode] = (float(addr.longitude), float(addr.latitude))
geo = Geo(title,
subtitle,
title_color="#fff",
title_pos="center",
width=1200,
height=600,
background_color='#404a59')
geo._coordinates = coordinates
attr, value = geo.cast(counter)
geo.add("",
attr,
value,
type="heatmap",
is_visualmap=True,
visual_text_color='#fff',
is_piecewise=True,
visual_split_number=10)
geo.render(file_path)
