近年来中国及各国GDP变化
一．可视化数据来源
经各方面搜索，最终选择此数据来源
https://www.kylc.com/stats/global/yearly_per_country/g_gdp/chn.html
整理后数据如下
中国GDP 6.09, 7.55, 8.53, 9.57, 10.48, 11.06, 11.23, 12.31, 13.89, 14.28
美国GDP 14.99, 15.544, 16.2, 16.78, 17.53, 18.22, 18.71, 19.52, 20.58, 21.43
日本GDP 5.7, 6.16, 6.2, 5.16, 4.85, 4.39, 4.92, 4.87, 4.95, 5.08
中国GDP在世界占比 9.2, 10.2, 11.3, 12.3, 13.1, 14.7, 14.7, 15.1, 16.0, 16.2
2019年各国GDP占比 中国 16.2， 韩国1.8， 印度3.2， 德国4.4， 日本5.7， 美国24.4，其他44.3
对应关系 "中国", "韩国", "印度", "德国", "日本", "其他国家"
16.2, 1.8, 3.2, 4.4, 5.7, 44.3
二．代码及展示
（1.）生成json的代码如下
import pyecharts.options as opts
from pyecharts.charts import Pie,Bar, Grid, Line,Liquid,Page
from pyecharts.globals import SymbolType
#------------------------------------------------------------------------------------------------------------------
#------------------------------------------------------------------------------------------------------------------
##标题------------------------------------------------------------------------------------------------------------------
title=(Pie(init_opts=opts.InitOpts(bg_color="black"))
.set_global_opts(
title_opts=opts.TitleOpts(title="中国近年人口数量，出生率自然增长率",
pos_top="middle",
pos_left="center",
title_textstyle_opts=opts.TextStyleOpts(color="red", font_size=40),))
)
#------------------------------------------------------------------------------------------------------------------
#------------------------------------------------------------------------------------------------------------------
##饼图------------------------------------------------------------------------------------------------------------------
x_data = ["中国", "韩国", "印度", "德国", "日本", "其他国家"]
y_data = [16.2, 1.8, 3.2, 4.4, 5.7, 44.3]
a=Pie(init_opts=opts.InitOpts(width="1000px", height="900px"),)
a.add(
series_name="访问来源",
data_pair=[list(z) for z in zip(x_data, y_data)],
radius=["30%", "60%"],
# label_opts=opts.LabelOpts(is_show=False, position="center"),
)
a.set_global_opts(title_opts=opts.TitleOpts(title="中国及世界各国GDP占比")
#,legend_opts=opts.LegendOpts(pos_left="legft", orient="vertical")#使标签竖着排列
)
a.set_series_opts(
tooltip_opts=opts.TooltipOpts(
trigger="item", formatter="{a} <br/>{b}: {c} ({d}%)"
),
label_opts=opts.LabelOpts(formatter="{b}: {c}") #引导线及标签
)
#a.render_notebook()
#------------------------------------------------------------------------------------------------------------------
#------------------------------------------------------------------------------------------------------------------
##水仙图------------------------------------------------------------------------------------------------------------------
c = (
Liquid()
.add("2019中国在世界占比", [0.16, 0.83], is_outline_show=False, shape=SymbolType.DIAMOND)
.set_global_opts(title_opts=opts.TitleOpts(title="2019中国在世界占比"))
#.render("水仙图.html")
)
#------------------------------------------------------------------------------------------------------------------
#------------------------------------------------------------------------------------------------------------------
##组合图------------------------------------------------------------------------------------------------------------------
bar = (
Bar()
.add_xaxis(["{}年".format(i) for i in range(2010, 2020)])
.add_yaxis(
"中国GDP",
[6.09, 7.55, 8.53, 9.57, 10.48, 11.06, 11.23, 12.31, 13.89, 14.28],
yaxis_index=0,
color="#d14a61",
)
.add_yaxis(
"美国GDP",
[14.99, 15.544, 16.2, 16.78, 17.53, 18.22, 18.71, 19.52, 20.58, 21.43],
yaxis_index=1,
color="#5793f3",
)
.extend_axis(
yaxis=opts.AxisOpts(
name="中国GDP",
type_="value",
min_=0,
max_=25,
position="right",
axisline_opts=opts.AxisLineOpts(
linestyle_opts=opts.LineStyleOpts(color="#d14a61")
),
axislabel_opts=opts.LabelOpts(formatter="{value} 万亿美元"),
)
)
.extend_axis(
yaxis=opts.AxisOpts(
type_="value",
name="占比",
min_=0,
max_=20,
position="left",
axisline_opts=opts.AxisLineOpts(
linestyle_opts=opts.LineStyleOpts(color="#675bba")
),
axislabel_opts=opts.LabelOpts(formatter="{value} %"),
splitline_opts=opts.SplitLineOpts(
is_show=True, linestyle_opts=opts.LineStyleOpts(opacity=1)
),
)
)
.set_global_opts(
yaxis_opts=opts.AxisOpts(
name="美国GDP",
min_=0,
max_=25,
position="right",
offset=80,
axisline_opts=opts.AxisLineOpts(
linestyle_opts=opts.LineStyleOpts(color="#5793f3")
),
axislabel_opts=opts.LabelOpts(formatter="{value} 万亿美元"),
),
title_opts=opts.TitleOpts(title="中国与美国、日本GDP比较"),
tooltip_opts=opts.TooltipOpts(trigger="axis", axis_pointer_type="cross"),
legend_opts=opts.LegendOpts(pos_left="25%"),
)
)
line = (
Line()
.add_xaxis(["{}年".format(i) for i in range(2010, 2020)])
.add_yaxis(
"中国占比",
[9.2, 10.2, 11.3, 12.3, 13.1, 14.7, 14.7, 15.1, 16.0, 16.2],
yaxis_index=2,
color="#675bba",
label_opts=opts.LabelOpts(is_show=False),
)
)
bar1 = (
Bar()
.add_xaxis(["{}年".format(i) for i in range(2010, 2020)])
.add_yaxis(
"中国GDP 1",
[6.09, 7.55, 8.53, 9.57, 10.48, 11.06, 11.23, 12.31, 13.89, 14.28],
color="#d14a61",
xaxis_index=1,
yaxis_index=3,
)
.add_yaxis(
"日本GDP",
[5.7, 6.16, 6.2, 5.16, 4.85, 4.39, 4.92, 4.87, 4.95, 5.08],
color="#5793f3",
xaxis_index=1,
yaxis_index=3,
)
.extend_axis(
yaxis=opts.AxisOpts(
name="中国GDP",
type_="value",
min_=0,
max_=16,
position="right",
axisline_opts=opts.AxisLineOpts(
linestyle_opts=opts.LineStyleOpts(color="#d14a61")
),
axislabel_opts=opts.LabelOpts(formatter="{value} 万亿美元"),
)
)
.extend_axis(
yaxis=opts.AxisOpts(
type_="value",
name="占比",
min_=0,
max_=20,
position="left",
axisline_opts=opts.AxisLineOpts(
linestyle_opts=opts.LineStyleOpts(color="#675bba")
),
axislabel_opts=opts.LabelOpts(formatter="{value} %"),
splitline_opts=opts.SplitLineOpts(
is_show=True, linestyle_opts=opts.LineStyleOpts(opacity=1)
),
)
)
.set_global_opts(
xaxis_opts=opts.AxisOpts(grid_index=1),
yaxis_opts=opts.AxisOpts(
name="日本GDP",
min_=0,
max_=15,
position="right",
offset=80,
grid_index=1,
axisline_opts=opts.AxisLineOpts(
linestyle_opts=opts.LineStyleOpts(color="#5793f3")
),
axislabel_opts=opts.LabelOpts(formatter="{value} 万亿美元"),
),
tooltip_opts=opts.TooltipOpts(trigger="axis", axis_pointer_type="cross"),
legend_opts=opts.LegendOpts(pos_left="65%"),
)
)
line1 = (
Line()
.add_xaxis(["{}年".format(i) for i in range(2010, 2020)])
.add_yaxis(
"中国占比",
[9.2, 10.2, 11.3, 12.3, 13.1, 14.7, 14.7, 15.1, 16.0, 16.2],
color="#675bba",
label_opts=opts.LabelOpts(is_show=False),
xaxis_index=1,
yaxis_index=5,
)
)
overlap_1 = bar.overlap(line)
overlap_2 = bar1.overlap(line1)
grid = (
Grid(init_opts=opts.InitOpts(width="1200px", height="800px"))
.add(
overlap_1, grid_opts=opts.GridOpts(pos_right="58%"), is_control_axis_index=True
)
.add(overlap_2, grid_opts=opts.GridOpts(pos_left="58%"), is_control_axis_index=True)
# .render("组合图.html")
)
#------------------------------------------------------------------------------------------------------------------
#------------------------------------------------------------------------------------------------------------------
##网页------------------------------------------------------------------------------------------------------------------
page=Page(layout=Page.DraggablePageLayout)
page.add(title,a,c,grid,)
page.render("result.html")
#如果不想保存在默认地址中，可以直接写入想保存的地址，但是文件级别直接不可以写“\”,而应该写"\\"，列如
“C:\\Users\\lenovo\\Desktop\\可视化作业\\result.html”
（2.）将生成的网页打开，结果如下，是一张张自上而下排列的图，并不是理想结果
（3.）调整后结果如下
（4.）保存调整后的json
点击左上角的save
（5.）json转html【重新渲染html】
page.save_resize_html("result.html",cfg_file="C:\\Users\\lenovo\\Desktop\\可视化作业\\chart_config.json",dest="C:\\Users\\lenovo\\Desktop\\可视化作业\\re_result.html")
#cfg_file 后加 生成的json文件地址
#dest 后加 最终生成的网页存放的地址
#json转html---重新渲染html
（6.）此时将生成的网页打开，结果如下
（7.）为什么要保存json重新渲染
如果不这样做，刷新网页后又会恢复调整前的状态，重新渲染后，再次生成的网页打开即为想要的效果
三．可视化分析
根据作图结果分析，中国GDP日益提升，与日本相比较高，但还是没有超出美国，还有提升的空间，随着我国国际地位及经济、政治各方面的变化，我国GDP预测会持续变好！