Python精美地理可視化繪制——以中國歷年GDP數(shù)據(jù)為例
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專欄作者：zch，經(jīng)管專業(yè)研一在讀，Python數(shù)據(jù)分析及可視化愛好者。公眾號后臺回復(fù)入群，拉你進(jìn)技術(shù)群與大佬們近距離交流。
01
關(guān)于繪圖數(shù)據(jù)
02
地理可視化
import pandas as pd
from pyecharts.charts import Map
import pyecharts.options as opts
frame = pd.read_csv('C:\\Users\\dell\\Desktop\\分省年度數(shù)據(jù)2.csv',encoding='GBK')
map = Map()
map.add("我國地區(qū)的GDP",frame[['地區(qū)','2019年']].values.tolist(),"china")
map.set_global_opts(visualmap_opts=opts.VisualMapOpts(min_=500,max_=12000))
map.render("2019年全國各地區(qū)GDP.html")
geo.set_global_opts(visualmap_opts=opts.VisualMapOpts(
is_piecewise=True,
pieces=[
{"min":0,"max":10000,"label":"1~10000","color":"cyan"},
{"min":10001,"max":20000,"label":"10001~20000","color":"yellow"},
{"min":20001,"max":50000,"label":"20001~50000","color":"orange"},
{"min":50001,"max":80000,"label":"50001~80000","color":"coral"},
{"min":80001,"max":120000,"label":"80001~120000","color":"red"},
]
))
import pandas as pd
from pyecharts import options as opts
from pyecharts.charts import Map, Timeline
frame = pd.read_csv('C:\\Users\\dell\\Desktop\\分省年度數(shù)據(jù)2.csv',encoding='GBK')
tl = Timeline()
for i in range(2010, 2020):
map0 = (
Map()
.add("省份",frame[['地區(qū)',str(i)+'年']].values.tolist(), "china")
.set_global_opts(
title_opts=opts.TitleOpts(title="Map-{}年GDP（億元）".format(i)),
visualmap_opts=opts.VisualMapOpts(
is_piecewise=True,
pieces=[
{"min":0,"max":10000,"label":"1~10000","color":"cyan"},
{"min":10001,"max":20000,"label":"10001~20000","color":"yellow"},
{"min":20001,"max":50000,"label":"20001~50000","color":"orange"},
{"min":50001,"max":80000,"label":"50001~80000","color":"coral"},
{"min":80001,"max":120000,"label":"80001~12000","color":"red"},
] ),))
tl.add(map0, "{}年".format(i))
tl.render("2010~2019年全國各地區(qū)GDP.html")
03
小結(jié)
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