python学习day15地图、柱状图

地图

from pyecharts.charts import Map
map=Map()
data=[
    ('北京市',999),
    ('上海市',133),
    ('河南省',123),
    ('西藏自治区',123),
    ('吉林省',12),
]

map.add("地图",data,"china")
map.render()

示例

from pyecharts.charts import Map
from pyecharts.options import VisualMapOpts

map=Map()
data=[
    ('北京市',999),
    ('上海市',133),
    ('河南省',123),
    ('西藏自治区',123),
    ('吉林省',12),
]

map.add("地图",data,"china")


map. set_global_opts(
visualmap_opts=VisualMapOpts(
    is_show=True,
    is_piecewise=True,
    pieces=[
        {"min" : 1,"max": 9, "label": "1-9人","color": "#CCFFFF"},
        { "min": 10,"max" : 99,"label" : "10-99人","color":"#FFFF99"},
        { "min": 100,"max": 499,"label": "99-499人","color" :"#FF9966"},
        {"min": 500,"max": 999,"label": "499-999人","color":"#FF6666"},
        { "min": 1000,"max": 9999,"label": "1000-9999人","color":"#CC3333"},
        { "min" : 10000,"label" : "10000以上","color" :"#990033"}
])
)



map.render()

RGB颜色对照表获取

全国疫情地图

import json
from pyecharts.charts import Map
from pyecharts.options import VisualMapOpts

map=Map()

data1=open("E:/桌面文件/疫情.txt",'r',encoding="UTF-8")
data2=data1.read()
JSON_data=json.loads(data2)

province=JSON_data["areaTree"][0]["children"]
data=[]

for i_data in province:
    province_name=i_data["name"]
    if province_name[-1] != "省":
        province_name = province_name + "省"
    print(province_name)
    province_num=i_data["total"]["confirm"]
    yuan_data=(province_name,province_num)
    data.append(yuan_data)
print(data)
map.add("全国疫情地图",data,"china")
map. set_global_opts(
visualmap_opts=VisualMapOpts(
    is_show=True,#是否显示
    is_piecewise=True,#是否分段
    pieces=[
        {"min" : 1,"max": 9, "label": "1-9人","color": "#CCFFFF"},
        { "min": 10,"max" : 99,"label" : "10-99人","color":"#FFFF99"},
        { "min": 100,"max": 499,"label": "99-499人","color" :"#FF9966"},
        {"min": 500,"max": 999,"label": "499-999人","color":"#FF6666"},
        { "min": 1000,"max": 9999,"label": "1000-9999人","color":"#CC3333"},
        { "min" : 10000,"label" : "10000以上","color" :"#990033"}
])
)



map.render()

河南省疫情地图

import json
from pyecharts.charts import Map
from pyecharts.options import VisualMapOpts

map=Map()

data1=open("E:/桌面文件/疫情.txt",'r',encoding="UTF-8")
data2=data1.read()
JSON_data=json.loads(data2)

province=JSON_data["areaTree"][0]["children"][3]["children"]
data=[]

for i_data in province:
    province_name=i_data["name"]
    province_name = province_name + "市"
    print(province_name)
    province_num=i_data["total"]["confirm"]
    yuan_data=(province_name,province_num)
    data.append(yuan_data)
print(data)
map.add("河南省疫情地图",data,"河南")
map. set_global_opts(
visualmap_opts=VisualMapOpts(
    is_show=True,#是否显示
    is_piecewise=True,#是否分段
    pieces=[
        {"min" : 1,"max": 9, "label": "1-9人","color": "#CCFFFF"},
        { "min": 10,"max" : 99,"label" : "10-99人","color":"#FFFF99"},
        { "min": 100,"max": 499,"label": "99-499人","color" :"#FF9966"},
        {"min": 500,"max": 999,"label": "499-999人","color":"#FF6666"},
        { "min": 1000,"max": 9999,"label": "1000-9999人","color":"#CC3333"},
        { "min" : 10000,"label" : "10000以上","color" :"#990033"}
])
)



map.render()

柱状图

from pyecharts.charts import Bar
from pyecharts.options import *
#构建柱状图对象
bar = Bar()
#添加x轴数据
bar.add_xaxis(["中国","美国","英国"])
#添加y轴数据
bar.add_yaxis ("GDP",[30,20,10])
#绘图
bar.render("基础柱状图.html" )

XY轴反转

bar.reversal_axis()

小结

时间线柱状图

#创建时间线
from pyecharts.charts import Bar,Timeline
from pyecharts.options import *
bar1= Bar()
bar1.add_xaxis(["中国","美国","英国"])
bar1.add_yaxis(" GDP",[30,20,10],label_opts=LabelOpts(position="right"))
bar1.reversal_axis()
bar2=Bar()
bar2.add_xaxis(["中国","美国","英国"])
bar2.add_yaxis("GDP",[50,30,20],label_opts=LabelOpts(position="right"))
bar2.reversal_axis()
#创建时间线对象
timeline = Timeline()#timeline对象添加bar柱状图
timeline.add(bar1,"2021年GDP")
timeline.add(bar2,"2022年GDP")
#通过时间线绘图
timeline.render("基础柱状图-时间线.html")

自动播放

#设置自动播放
timeline.add_schema(
play_interval=1000,
#自动播放的时间间隔，单位毫秒
is_timeline_show=True,
#是否在自动播放的时候，显示时间线
is_auto_play=True,
#是否自动播放
is_loop_play=True,
#是否循环自动播放
)

#创建时间线
from pyecharts.charts import Bar,Timeline
from pyecharts.options import *
from pyecharts.globals import ThemeType
bar1= Bar()
bar1.add_xaxis(["中国","美国","英国"])
bar1.add_yaxis(" GDP",[30,20,10],label_opts=LabelOpts(position="right"))
bar1.reversal_axis()
bar2=Bar()
bar2.add_xaxis(["中国","美国","英国"])
bar2.add_yaxis("GDP",[50,30,20],label_opts=LabelOpts(position="right"))
bar2.reversal_axis()
#创建时间线对象
timeline = Timeline({"theme":ThemeType.LIGHT})#timeline对象添加bar柱状图
timeline.add(bar1,"2021年GDP")
timeline.add(bar2,"2022年GDP")


#设置自动播放
timeline.add_schema(
play_interval=1000,
#自动播放的时间间隔，单位毫秒
is_timeline_show=True,
#是否在自动播放的时候，显示时间线
is_auto_play=True,
#是否自动播放
is_loop_play=True,
#是否循环自动播放
)
#通过时间线绘图
timeline.render("基础柱状图-时间线.html")

小结

动态柱状图

sort排序

my_list=[['a',33],['b',90],['c',12]]


def choose_sort_key(element):
    return element[1]

my_list.sort(key=choose_sort_key,reverse=True)
print(my_list)

练习动态柱状图

from pyecharts.charts import Bar, Timeline
from pyecharts.options import *
from pyecharts.globals import ThemeType

def sort_dta(element):
    return element[1]

f=open("E:/桌面文件/1960-2019全球GDP数据.csv","r",encoding="GB2312")
data=f.readlines()
f.close()
data.pop(0)
data_culi=[]
data_dirc={}
for element in data:
    data_culi.append(element.strip())

for j in data_culi:
    year=int(j.split(",")[0])
    country=j.split(",")[1]
    GDP=float(j.split(",")[2])
    try:
        data_dirc[year].append([country,GDP])
    except KeyError:
        data_dirc[year]=[]
        data_dirc[year].append([country, GDP])
list_year_key=sorted(data_dirc.keys())
timeline = Timeline({"theme": ThemeType.LIGHT})  # timeline对象添加bar柱状图
for element2 in list_year_key:
    data_dirc[element2].sort(key=sort_dta, reverse=True)
    year_data=data_dirc[element2][0:8:1]
    print(year_data)
    x_data = []
    y_data = []
    for  i in year_data:
        x_data.append(i[0])
        y_data.append(i[1]/100000000)
    x_data.reverse()
    y_data.reverse()
    bar = Bar()
    bar.add_xaxis(x_data)
    bar.add_yaxis(" GDP(亿)", y_data, label_opts=LabelOpts(position="right"))
    bar.reversal_axis()
    # 创建时间线对象
    bar.set_global_opts(

        title_opts=TitleOpts(
            title=f"{element2}全球前8GDP数据"
        )

    )

    timeline.add(bar, str(element2))


timeline.add_schema(
play_interval=500,
#自动播放的时间间隔，单位毫秒
is_timeline_show=True,
#是否在自动播放的时候，显示时间线
is_auto_play=True,
#是否自动播放
is_loop_play=True,
#是否循环自动播放
)



#通过时间线绘图
timeline.render("GDP时间线.html")