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import json
import requests # 3rd party
import jsonpath
from pyecharts.charts import Map
from pyecharts import options as opts
from src.covid19_data import nameMap
url = 'https://api.inews.qq.com/newsqa/v1/automation/foreign/country/ranklist'
resp = requests.post(url).text
data = json.loads(resp)
# get contry names and confirmed cases $：outer {}， ..: fuzzy match + key
name = jsonpath.jsonpath(data, "$..name") # ['美国', '巴西', '印度', '俄罗斯', ... ]
confirm = jsonpath.jsonpath(data, "$..confirm")
pairs = list(zip(name, confirm)) # [('美国', 5321520), ('巴西', 3109630), ('印度', 2329638), ...]
# 2. data visualization map plotting - size,title,color,data
map_ = Map(opts.InitOpts(width='1200px', height='600px'))
.add(series_name="Global Covid-19 Confirmed Cases",
data_pair=pairs, # data entry - country : confirmed
maptype="world", # world map
name_map=nameMap, # country name mapping
is_map_symbol_show=False) # 不显示标记点
# set series options
map_.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
map_.set_global_opts(title_opts=opts.TitleOpts(title="Global Covid-19 Pandemic (Chinese)"),
visualmap_opts=opts.VisualMapOpts(max_=6000000, is_piecewise=True))
map_.render('../result/covid19.html')
nameMap = {
'Singapore Rep.': '新加坡',
'Dominican Rep.': '多米尼加',
'Palestine': '巴勒斯坦',
'Bahamas': '巴哈马',
'Timor-Leste': '东帝汶',
'Afghanistan': '阿富汗',
'Guinea-Bissau': '几内亚比绍',
"Côte d'Ivoire": '科特迪瓦',
'Siachen Glacier': '锡亚琴冰川',
"Br. Indian Ocean Ter.": '英属印度洋领土',
'Angola': '安哥拉',
'Albania': '阿尔巴尼亚',
'United Arab Emirates': '阿联酋',
'Argentina': '阿根廷',
'Armenia': '亚美尼亚',
'French Southern and Antarctic Lands': '法属南半球和南极领地',
'Australia': '澳大利亚',
'Austria': '奥地利',
'Azerbaijan': '阿塞拜疆',
'Burundi': '布隆迪',
'Belgium': '比利时',
'Benin': '贝宁',
'Burkina Faso': '布基纳法索',
'Bangladesh': '孟加拉国',
'Bulgaria': '保加利亚',
'The Bahamas': '巴哈马',
'Bosnia and Herz.': '波斯尼亚和黑塞哥维那',
'Belarus': '白俄罗斯',
'Belize': '伯利兹',
'Bermuda': '百慕大',
'Bolivia': '玻利维亚',
'Brazil': '巴西',
'Brunei': '文莱',
'Bhutan': '不丹',
'Botswana': '博茨瓦纳',
'Central African Rep.': '中非共和国',
'Canada': '加拿大',
'Switzerland': '瑞士',
'Chile': '智利',
'China': '中国',
'Ivory Coast': '象牙海岸',
'Cameroon': '喀麦隆',
'Dem. Rep. Congo': '刚果（金）',
'Congo': '刚果（布）',
'Colombia': '哥伦比亚',
'Costa Rica': '哥斯达黎加',
'Cuba': '古巴',
'N. Cyprus': '北塞浦路斯',
'Cyprus': '塞浦路斯',
'Czech Rep.': '捷克',
'Germany': '德国',
'Djibouti': '吉布提',
'Denmark': '丹麦',
'Algeria': '阿尔及利亚',
'Ecuador': '厄瓜多尔',
'Egypt': '埃及',
'Eritrea': '厄立特里亚',
'Spain': '西班牙',
'Estonia': '爱沙尼亚',
'Ethiopia': '埃塞俄比亚',
'Finland': '芬兰',
'Fiji': '斐',
'Falkland Islands': '福克兰群岛',
'France': '法国',
'Gabon': '加蓬',
'United Kingdom': '英国',
'Georgia': '格鲁吉亚',
'Ghana': '加纳',
'Guinea': '几内亚',
'Gambia': '冈比亚',
'Guinea Bissau': '几内亚比绍',
'Eq. Guinea': '赤道几内亚',
'Greece': '希腊',
'Greenland': '格陵兰',
'Guatemala': '危地马拉',
'French Guiana': '法属圭亚那',
'Guyana': '圭亚那',
'Honduras': '洪都拉斯',
'Croatia': '克罗地亚',
'Haiti': '海地',
'Hungary': '匈牙利',
'Indonesia': '印度尼西亚',
'India': '印度',
'Ireland': '爱尔兰',
'Iran': '伊朗',
'Iraq': '伊拉克',
'Iceland': '冰岛',
'Israel': '以色列',
'Italy': '意大利',
'Jamaica': '牙买加',
'Jordan': '约旦',
'Japan': '日本',
'Kazakhstan': '哈萨克斯坦',
'Kenya': '肯尼亚',
'Kyrgyzstan': '吉尔吉斯斯坦',
'Cambodia': '柬埔寨',
'Korea': '韩国',
'Kosovo': '科索沃',
'Kuwait': '科威特',
'Lao PDR': '老挝',
'Lebanon': '黎巴嫩',
'Liberia': '利比里亚',
'Libya': '利比亚',
'Sri Lanka': '斯里兰卡',
'Lesotho': '莱索托',
'Lithuania': '立陶宛',
'Luxembourg': '卢森堡',
'Latvia': '拉脱维亚',
'Morocco': '摩洛哥',
'Moldova': '摩尔多瓦',
'Madagascar': '马达加斯加',
'Mexico': '墨西哥',
'Macedonia': '马其顿',
'Mali': '马里',
'Myanmar': '缅甸',
'Montenegro': '黑山',
'Mongolia': '蒙古',
'Mozambique': '莫桑比克',
'Mauritania': '毛里塔尼亚',
'Malawi': '马拉维',
'Malaysia': '马来西亚',
'Namibia': '纳米比亚',
'New Caledonia': '新喀里多尼亚',
'Niger': '尼日尔',
'Nigeria': '尼日利亚',
'Nicaragua': '尼加拉瓜',
'Netherlands': '荷兰',
'Norway': '挪威',
'Nepal': '尼泊尔',
'New Zealand': '新西兰',
'Oman': '阿曼',
'Pakistan': '巴基斯坦',
'Panama': '巴拿马',
'Peru': '秘鲁',
'Philippines': '菲律宾',
'Papua New Guinea': '巴布亚新几内亚',
'Poland': '波兰',
'Puerto Rico': '波多黎各',
'Dem. Rep. Korea': '朝鲜',
'Portugal': '葡萄牙',
'Paraguay': '巴拉圭',
'Qatar': '卡塔尔',
'Romania': '罗马尼亚',
'Russia': '俄罗斯',
'Rwanda': '卢旺达',
'W. Sahara': '西撒哈拉',
'Saudi Arabia': '沙特阿拉伯',
'Sudan': '苏丹',
'S. Sudan': '南苏丹',
'Senegal': '塞内加尔',
'Solomon Is.': '所罗门群岛',
'Sierra Leone': '塞拉利昂',
'El Salvador': '萨尔瓦多',
'Somaliland': '索马里兰',
'Somalia': '索马里',
'Serbia': '塞尔维亚',
'Suriname': '苏里南',
'Slovakia': '斯洛伐克',
'Slovenia': '斯洛文尼亚',
'Sweden': '瑞典',
'Swaziland': '斯威士兰',
'Syria': '叙利亚',
'Chad': '乍得',
'Togo': '多哥',
'Thailand': '泰国',
'Tajikistan': '塔吉克斯坦',
'Turkmenistan': '土库曼斯坦',
'East Timor': '东帝汶',
'Trinidad and Tobago': '特里尼达和多巴哥',
'Tunisia': '突尼斯',
'Turkey': '土耳其',
'Tanzania': '坦桑尼亚',
'Uganda': '乌干达',
'Ukraine': '乌克兰',
'Uruguay': '乌拉圭',
'United States': '美国',
'Uzbekistan': '乌兹别克斯坦',
'Venezuela': '委内瑞拉',
'Vietnam': '越南',
'Vanuatu': '瓦努阿图',
'West Bank': '西岸',
'Yemen': '也门',
'South Africa': '南非',
'Zambia': '赞比亚',
'Zimbabwe': '津巴布韦'
}
import pandas
from pyecharts.charts import Pie
from pyecharts import options as opts
# data
# source: https://www.canada.ca/en/public-health/services/diseases/2019-novel-coronavirus-infection.html
provinces = ['NL', 'PE', 'NS', 'NB', 'QC', 'ON', 'MB', 'SK', 'AB', 'BC', 'YT', 'NT', 'NU']
num = [268, 41, 1071, 178, 60813, 40289, 578, 1484, 11893, 4196, 15, 5, 0]
color_series = ['#f00', '#f50', '#ea0', '#aa0', '#a50', '#5f0', '#0f0', '#0f5', '#5f7', '#0ff', '#0af', '#07f', '#00f']
# data frame
df = pandas.DataFrame({'provinces': provinces, 'num': num})
# descending order
df.sort_values(by='num', ascending=False, inplace=True)
# data list
v = df['provinces'].values.tolist()
d = df['num'].values.tolist()
# get pie instance
pie = Pie(init_opts=opts.InitOpts(width='1350px', height='750px'))
# set color
pie.set_colors(color_series)
# pie chart settings
pie.add("", [list(z) for z in zip(v, d)],
radius=["50%", "85%"],
center=["35%", "55%"],
rosetype="area"
)
# set global options
pie.set_global_opts(
title_opts=opts.TitleOpts(title='2020-08-12 Covid-19 Canada'),
legend_opts=opts.LegendOpts(is_show=True),
toolbox_opts=opts.ToolboxOpts()
)
# set series options
pie.set_series_opts(
label_opts=opts.LabelOpts(is_show=True, position="inside", font_size=12,
formatter="{b}n{c}", font_style="normal",
font_weight="normal", font_family="Microsoft YaHei"
),
)
# render html
pie.render('./result/nightingalerosediagram.html')
# 先导入Jupyter notebook渲染插件
from pyecharts.globals import CurrentConfig, NotebookType
CurrentConfig.NOTEBOOK_TYPE = NotebookType.JUPYTER_NOTEBOOK
# 注意区分大小写，如果使用Jupyter Lab 则改为如下代码
# CurrentConfig.NOTEBOOK_TYPE = NotebookType.JUPYTER_LAB
# 导入pyecharts，并显示版本
import pyecharts
print(pyecharts.__version__)
# 绘图测试
from pyecharts.charts import Bar
from pyecharts import options as opts
# from pyecharts.render import make_snapshot
bar = (
Bar()
.add_xaxis(["衬衫", "毛衣", "领带", "裤子", "风衣", "高跟鞋", "袜子"])
.add_yaxis("商家A", [114, 55, 27, 101, 125, 27, 105])
.add_yaxis("商家B", [57, 134, 137, 129, 145, 60, 49])
.set_global_opts(title_opts=opts.TitleOpts(title="某商场销售情况"))
)
bar.render_notebook() # 在Notebook中进行渲染图像
bar.render("result/barchart.html") # 在本地生成静态网页
# make_snapshot(snapshot, bar.render(), "result/bar.png")#在本地生成图表截图
# from pyecharts import Line
from pyecharts.charts import Line
x = ['2018-{:0>2d}'.format(s) for s in range(1,13)]
y1 = [5,10,26,30,35,30,20,26,40,46,40,50]
y2 = [8,20,24,36,40,36,40,45,50,53,48,58]
# line = Line(title="月销售总额", width=600, height=420)
line = Line()
line.page_title = "商家折线图"
line.set_colors(['blue', 'green'])
line.add_xaxis(x)
line.add_yaxis("商家A", y1)
line.add_xaxis(x)
line.add_yaxis("商家B", y2)
line.render('../result/linechart.html')
line
from pyecharts.charts import Line3D
import math
_data = []
for t in range(0, 25000):
_t = t / 1000
x = (1 + 0.25 * math.cos(75 * _t)) * math.cos(_t)
y = (1 + 0.25 * math.cos(75 * _t)) * math.sin(_t)
z = _t + 2.0 * math.sin(75 * _t)
_data.append([x, y, z])
range_color = ['#313695', '#4575b4', '#74add1', '#abd9e9', '#e0f3f8', '#ffffbf',
'#fee090', '#fdae61', '#f46d43', '#d73027', '#a50026']
line3D = Line3D()
line3D.page_title = '3D 折线图'
line3D.add("", _data)
line3D.render('../result/3dline.html')
Author: IT Team
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