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main.py
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main.py
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import pandas as pd
import csv
from pyecharts import options as opts
from pyecharts.charts import Map, Tab, Line, Grid
province = ['河北', '山西', '辽宁', '吉林', '黑龙江', '江苏', '浙江', '安徽', '福建', '江西', '山东', '河南', '湖北', '湖南', '广东', '海南', '四川', '贵州', '云南', '陕西', '甘肃', '青海', '台湾',
'内蒙古', '广西', '西藏', '宁夏', '新疆',
'北京', '天津', '上海', '重庆',
'香港', '澳门']
# '日期', '省份', '城市', '新增确诊', '新增出院', '新增死亡', '消息来源'
def input():
data = open('Updates_NC.csv', 'r')
city_list = list(csv.reader(data))
city_list = city_list[1:]
for row in city_list:
"""
纠正地级市名称
"""
if row[2]=="恩施州":
row[2] = "恩施土家族苗族自治州"
elif row[2]=="湘西州":
row[2] = "湘西土家族苗族自治州"
elif row[2] == "阿坝州":
row[2] = "阿坝藏族羌族自治州"
elif row[2] == "甘孜州":
row[2] = "甘孜藏族自治州"
elif row[2] == "凉山州":
row[2] = "凉山彝族自治州"
elif row[2] == "黔西南州":
row[2] = "黔西南布依族苗族自治州"
elif row[2] == "黔东南州":
row[2] = "黔东南苗族侗族自治州"
elif row[2] == "黔南州":
row[2] = "黔南布依族苗族自治州"
elif row[2] == "楚雄州":
row[2] = "楚雄彝族自治州"
elif row[2] == "红河州":
row[2] = "红河哈尼族彝族自治州"
elif row[2] == "文山州":
row[2] = "文山壮族苗族自治州"
elif row[2] == "西双版纳州":
row[2] = "西双版纳傣族自治州"
elif row[2] == "大理州":
row[2] = "大理白族自治州"
elif row[2] == "德宏州":
row[2] = "德宏傣族景颇族自治州"
elif row[2] == "怒江州":
row[2] = "怒江傈僳族自治州"
elif row[2] == "迪庆州":
row[2] = "迪庆藏族自治州"
elif row[2] == "临夏州":
row[2] = "临夏回族自治州"
elif row[2] == "甘南州":
row[2] = "甘南藏族自治州"
elif row[2] == "海北州":
row[2] = "海北藏族自治州"
elif row[2] == "黄南州":
row[2] = "黄南藏族自治州"
elif row[2] == "海南州":
row[2] = "海南藏族自治州"
elif row[2] == "果洛州":
row[2] = "果洛藏族自治州"
elif row[2] == "玉树州":
row[2] = "玉树藏族自治州"
elif row[2] == "海西州":
row[2] = "海西蒙古族藏族自治州"
elif row[2] == "昌吉州":
row[2] = "昌吉回族自治州"
elif row[2] == "博尔塔拉蒙古州":
row[2] = "博尔塔拉蒙古自治州"
elif row[2] == "巴音郭楞蒙古州":
row[2] = "巴音郭楞蒙古自治州"
elif row[2] == "克孜勒苏柯尔克孜州":
row[2] = "克孜勒苏柯尔克孜自治州"
elif row[2] == "伊犁州":
row[2] = "伊犁哈萨克自治州"
"""
改为整数形式
"""
row[3] = to_int(row[3])
row[4] = to_int(row[4])
row[5] = to_int(row[5])
"""
处理日期
"""
str = row[0][:-1].split('月')
row[0] = str[0].zfill(2) + '/' + str[1].zfill(2)
# print(row[0])
return city_list
def to_int(x):
if x:
return int(x)
return 0
"""
导出全国新冠肺炎累计确诊人数、现在确诊人数、累计治愈人数、死亡人数
"""
def china_total(city_list):
china_dict = {}
# print(city_list)
for name in province:
china_dict.update({name: [0, 0, 0]})
for row in city_list:
name = row[1]
if name in province:
day = china_dict[name]
china_dict[name] = [day[0]+row[3], day[1]+row[4], day[2]+row[5]]
print(china_dict)
confirm = [(k, v[0]) for k, v in china_dict.items()]
heal = [(k, v[1]) for k, v in china_dict.items()]
dead = [(k, v[2]) for k, v in china_dict.items()]
current_confirm = [(k, v[0]-v[1]-v[2]) for k, v in china_dict.items()]
tab = Tab()
_map = (
Map()
.add('确诊人数', confirm, "china")
.set_series_opts(label_opts=opts.LabelOpts(is_show=True))
.set_global_opts(
title_opts=opts.TitleOpts(title="新型冠状病毒全国疫情地图",
subtitle="更新时间：{}".format(city_list[-1][0])),
legend_opts=opts.LegendOpts(is_show=True),
visualmap_opts=opts.VisualMapOpts(is_show=True, max_=1000,
is_piecewise=True,
pieces=[
# 数据范围
{"min": 10000, "label": ">=10000", "color": "#80707"},
{"max": 9999, "min": 1000, "label": "1000 - 9999 人", "color": "#8B0000"},
{"max": 999, "min": 500, "label": "500 - 999 人", "color": "#CB0000"},
{"max": 499, "min": 100, "label": "100 - 499 人", "color": "#DD5C5C"},
{"max": 99, "min": 10, "label": "10 - 99 人", "color": "#FFA07A"},
{"max": 9, "min": 1, "label": "1 - 9 人", "color": "#FFFF00"},
]
#range_color=['#FFFFE0', '#FFA07A', '#CD5C5C', '#8B0000'])
)
)
# .render("全国确诊.html")
)
tab.add(_map, "累计确诊")
_map = (
Map()
.add('当前确诊人数', current_confirm, "china")
.set_series_opts(label_opts=opts.LabelOpts(is_show=True))
.set_global_opts(
title_opts=opts.TitleOpts(title="新型冠状病毒全国疫情地图",
subtitle="更新时间：{}".format(city_list[-1][0])),
legend_opts=opts.LegendOpts(is_show=True),
visualmap_opts=opts.VisualMapOpts(is_show=True, max_=30,
is_piecewise=True,
range_color=['#FFFFE0', '#FFA07A', '#CD5C5C', '#8B0000'])
)
# .render("全国确诊.html")
)
tab.add(_map, "当前确诊")
_map = (
Map()
.add('当前治愈人数', heal, "china")
.set_series_opts(label_opts=opts.LabelOpts(is_show=True))
.set_global_opts(
title_opts=opts.TitleOpts(title="新型冠状病毒全国疫情地图",
subtitle="更新时间：{}".format(city_list[-1][0])),
legend_opts=opts.LegendOpts(is_show=True),
visualmap_opts=opts.VisualMapOpts(is_show=True, max_=1500,
is_piecewise=True,
pieces=[
# 数据范围
{"min": 10000, "label": ">=10000", "color": "#143601"},
{"max": 9999, "min": 1000, "label": "1000 - 9999 人",
"color": "#1A4301"},
{"max": 999, "min": 500, "label": "500 - 999 人", "color": "#245501"},
{"max": 499, "min": 300, "label": "300 - 499 人", "color": "#538D22"},
{"max": 299, "min": 100, "label": "100 - 299 人", "color": "#73A942"},
{"max": 99, "min": 0, "label": "1 - 99 人", "color": "#AAD576"},
]
)
)
# .render("全国确诊.html")
)
tab.add(_map, "累计治愈")
_map = (
Map()
.add('当前死亡人数', dead, "china")
.set_series_opts(label_opts=opts.LabelOpts(is_show=True))
.set_global_opts(
title_opts=opts.TitleOpts(title="新型冠状病毒全国疫情地图",
subtitle="更新时间：{}".format(city_list[-1][0])),
legend_opts=opts.LegendOpts(is_show=True),
visualmap_opts=opts.VisualMapOpts(is_show=True, max_=50,
is_piecewise=True,
range_color=['#FFFFE0', '#FFA07A', '#CD5C5C', '#8B0000'])
)
# .render("全国确诊.html")
)
tab.add(_map, "累计死亡")
tab.render(path="各省确诊人数.html")
def generate_city(city_list):
input()
china_province = {}
for _province in province:
china_province.update({_province:{}})
for x in city_list:
if x[1] in province:
china_province[x[1]].update({x[2]:[0, 0, 0]})
for item in city_list:
name = item[1]
if name in province:
day = china_province[name][item[2]]
# if name == '北京' or name == '上海' or name == '天津' or name == '重庆':
# item[2] = item[2] + "区"
# elif "自治" in name:
# continue
# else:
# item[2] = item[2] + '市'
china_province[name].update({item[2]: [day[0]+item[3], day[1]+item[4], day[2]+item[5]]})
tab = Tab()
for x in province:
dict_province = china_province[x]
confirm = [(k, v[0]) for k, v in dict_province.items()]
if x =="湖北":
_map = (
Map()
.add('确诊人数', confirm, x)
.set_series_opts(label_opts=opts.LabelOpts(is_show=True))
.set_global_opts(
title_opts=opts.TitleOpts(title="新型冠状病毒 {} 疫情地图".format(x),
subtitle="更新时间：{}".format(city_list[-1][0])),
legend_opts=opts.LegendOpts(is_show=True),
visualmap_opts=opts.VisualMapOpts(is_show=True, max_=5000,
is_piecewise=True,
pieces=[
# 数据范围
{"min": 5000, "label": ">=5000", "color": "#807070"},
{"max": 4999, "min": 2000, "label": "2000 - 4999 人",
"color": "#8B0000"},
{"max": 1999, "min": 1500, "label": "1500 - 1999 人",
"color": "#CB0000"},
{"max": 1499, "min": 500, "label": "500 - 1499 人",
"color": "#DD5C5C"},
{"max": 499, "min": 200, "label": "200 - 499 人", "color": "#FFA07A"},
{"max": 199, "min": 1, "label": "1 - 199 人", "color": "#FFFF00"},
]
# range_color=['#FFFFE0', '#FFA07A', '#CD5C5C', '#8B0000'])
)
)
# .render("全国确诊.html")
)
else:
_map = (
Map()
.add('确诊人数', confirm, x)
.set_series_opts(label_opts=opts.LabelOpts(is_show=True))
.set_global_opts(
title_opts=opts.TitleOpts(title="新型冠状病毒 {} 疫情地图".format(x),
subtitle="更新时间：{}".format(city_list[-1][0])),
legend_opts=opts.LegendOpts(is_show=False),
visualmap_opts=opts.VisualMapOpts(is_show=True, max_=int(max([x[1] for x in confirm])),
is_piecewise=True,
range_color=['#FFFFE0', '#FFA07A', '#CD5C5C', '#8B0000'])
)
# .render("全国确诊.html")
)
tab.add(_map, x)
# page.add(tab)
tab.render(path="新型冠状病毒全国疫情地图.html")
def quanguo_wuhan_compare(city_list):
time = set()
for item in city_list:
time.add(item[0])
TIME = {}
for x in time:
TIME.update({x: (0, 0)})
for item in city_list:
if item[1] in province:
if item[1] != "湖北":
TIME.update({item[0]: (TIME[item[0]][0]+item[3], TIME[item[0]][1])})
else:
TIME.update({item[0]: (TIME[item[0]][0], TIME[item[0]][1] + item[3])})
time_others_wuhan = []
for k, v in TIME.items():
time_others_wuhan.append([k, v[0], v[1]])
time_others_wuhan.sort()
L1 = (
Line()
.add_xaxis(xaxis_data=[x[0] for x in time_others_wuhan])
.add_yaxis(
series_name="全国其他地区",
y_axis=[x[1] for x in time_others_wuhan],
symbol_size=8,
is_hover_animation=False,
label_opts=opts.LabelOpts(is_show=False),
linestyle_opts=opts.LineStyleOpts(width=1.5),
is_smooth=True,
)
.set_global_opts(
title_opts=opts.TitleOpts(
title="湖北地区和全国其他地区确诊人数对比图", subtitle="截止至2020年5月21日", pos_left="center"
),
tooltip_opts=opts.TooltipOpts(trigger="axis"),
axispointer_opts=opts.AxisPointerOpts(
is_show=True, link=[{"xAxisIndex": "all"}]
),
datazoom_opts=[
opts.DataZoomOpts(
is_show=True,
is_realtime=True,
start_value=30,
end_value=70,
xaxis_index=[0, 1],
)
],
xaxis_opts=opts.AxisOpts(
type_="category",
boundary_gap=False,
axisline_opts=opts.AxisLineOpts(is_on_zero=True),
),
yaxis_opts=opts.AxisOpts(is_inverse=False, name="人数"),
legend_opts=opts.LegendOpts(pos_left="left"),
toolbox_opts=opts.ToolboxOpts(
is_show=True,
feature={
"dataZoom": {"yAxisIndex": "none"},
"restore": {},
"saveAsImage": {},
},
),
)
)
L2 = (
Line()
.add_xaxis(xaxis_data=[x[0] for x in time_others_wuhan])
.add_yaxis(
series_name="湖北地区",
y_axis=[x[2] for x in time_others_wuhan],
xaxis_index=1,
yaxis_index=1,
symbol_size=8,
is_hover_animation=False,
label_opts=opts.LabelOpts(is_show=False),
linestyle_opts=opts.LineStyleOpts(width=1.5),
is_smooth=True,
)
.set_global_opts(
axispointer_opts=opts.AxisPointerOpts(
is_show=True, link=[{"xAxisIndex": "all"}]
),
tooltip_opts=opts.TooltipOpts(trigger="axis"),
xaxis_opts=opts.AxisOpts(
grid_index=1,
type_="category",
boundary_gap=False,
axisline_opts=opts.AxisLineOpts(is_on_zero=True),
position="top",
),
datazoom_opts=[
opts.DataZoomOpts(
is_realtime=True,
type_="inside",
start_value=30,
end_value=70,
xaxis_index=[0, 1],
)
],
yaxis_opts=opts.AxisOpts(is_inverse=True, name="确诊人数"),
legend_opts=opts.LegendOpts(pos_left="15%"),
)
)
(
Grid(init_opts=opts.InitOpts(width="1024px", height="768px"))
.add(chart=L1, grid_opts=opts.GridOpts(pos_left=50, pos_right=50, height="35%"))
.add(
chart=L2, grid_opts=opts.GridOpts(pos_left=50, pos_right=50, pos_top="55%", height="35%"),
)
.render(path="compare.html")
)
if __name__ == '__main__':
# page = Page()
city_list = input()
china_total(city_list)
generate_city(city_list)
quanguo_wuhan_compare(city_list)
# page.render("疫情可视化分析.html")
# print(data)