Pandas+Pyecharts | 2022 Fortune 500 Data Analysis Visualization-Python Tutorial-php.cn

Pandas+Pyecharts | 2022 Fortune 500 Data Analysis Visualization

Release： 2023-08-09 17:19:20

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In this issue, we use Python to analyze the information data of the world's top 500 companies in 2022, take a look:

What countries are the top 500 companies roughly distributed in?
Top 500 companies What are the Chinese companies and their distribution in various cities in the country
Profit and loss situation of the top 500 companies
...

Hope it will be helpful, if you have any questions or need If you want to improve, you can send a private message to the editor.

Libraries involved:

Pandas — Data Processing
Pyecharts — Data Visualization

##Visualization Section:

Pictogram — PictorialBar
Bar chart — Bar
Map — Map
##Geographic coordinate system — Geo
Water Polo Chart — Liquid
Polar Coordinate Chart — Polar
Word Cloud — WordCloud

1. Import module

import pandas as pd 
from pyecharts.charts import Pie
from pyecharts.charts import Bar
from pyecharts.charts import Grid
from pyecharts.charts import Map
from pyecharts.charts import Geo
from pyecharts.charts import WordCloud
from pyecharts.charts import PictorialBar
from pyecharts.charts import Liquid
from pyecharts.charts import Polar
from pyecharts import options as opts
from pyecharts.commons.utils import JsCode

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2. Pandas数据处理

2.1 读取数据

df = pd.read_excel(&#39;2022年世界五百强排行榜.xlsx&#39;)
df.head(10)

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Pandas+Pyecharts | 2022 Fortune 500 Data Analysis Visualization

2.2 查看数据信息

df.info()

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Pandas+Pyecharts | 2022 Fortune 500 Data Analysis Visualization

500条数据没有确缺失，不需要进行其他处理。

3. Pyecharts数据可视化

3.1 各国世界500强企业数量排名柱状图

bar = (
    Bar(init_opts=opts.InitOpts(width=&#39;1000px&#39;, height=&#39;1000px&#39;,bg_color=&#39;#0d0735&#39;))
    .add_xaxis(x_data)
    .add_yaxis("",y_data)
    .set_series_opts(label_opts=opts.LabelOpts(position="right",
                                              font_size=12,
                                              font_weight=&#39;bold&#39;,
                                              formatter=&#39;{c} 家&#39;),
                    )
    .set_global_opts(
                    xaxis_opts=opts.AxisOpts(is_show=False,),
                    yaxis_opts=opts.AxisOpts(
                        axislabel_opts=opts.LabelOpts(font_size=13,color=&#39;#fff200&#39;),
                        axistick_opts=opts.AxisTickOpts(is_show=False),
                        axisline_opts=opts.AxisLineOpts(is_show=False)
                    ),
                    title_opts=opts.TitleOpts(title="各国世界500强企业数量排名",pos_left=&#39;center&#39;,pos_top=&#39;1%&#39;,
                              title_textstyle_opts=opts.TextStyleOpts(font_size=22,color="#38d9a9")),
                    visualmap_opts=opts.VisualMapOpts(is_show=False, 
                                      min_=20,
                                      max_=150,
                                      is_piecewise=False,
                                      dimension=0,
                                      range_color=[&#39;#203fb6&#39;, &#39;#008afb&#39;, &#39;#ffec4a&#39;, &#39;#ff6611&#39;, &#39;#f62336&#39;]
                                                     ),
                    )
    .reversal_axis()
)

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Pandas+Pyecharts | 2022 Fortune 500 Data Analysis Visualization

我国以145家世界500强企业高居榜首
美国128家、日本47家位居二、三位
亚洲方面还有韩国以18家的数量排名第六

3.2 各国世界500强企业数量排名TOP8极坐标图

p = (
    Polar(init_opts=opts.InitOpts(width=&#39;1000px&#39;, height=&#39;800px&#39;, bg_color=&#39;#0d0735&#39;))
    .add_schema(
        radiusaxis_opts=opts.RadiusAxisOpts(data=x_data[-8:], 
                                            type_=&#39;category&#39;),
        angleaxis_opts=opts.AngleAxisOpts(
              is_clockwise=True, 
              is_scale=True,
              max_=150,
              axislabel_opts=opts.LabelOpts(font_size=14, color=&#39;#fff200&#39;),
              axisline_opts=opts.AxisLineOpts(is_show=True,linestyle_opts=opts.LineStyleOpts(
                                                    width=2,type_=&#39;dashed&#39;,color=&#39;#e4e932&#39;)),
              splitline_opts=opts.SplitLineOpts(is_show=True,
                    linestyle_opts=opts.LineStyleOpts(type_=&#39;dashed&#39;, color=&#39;#9FC131&#39;)
                ),
             ),
    )
    .add(&#39;&#39;,y_data[-8:], type_=&#39;bar&#39;)
    .set_global_opts( 
        title_opts=opts.TitleOpts(title=&#39;各国世界500强企业数量排名TOP8&#39;,subtitle=&#39;制图@公众号：Python当打之年&#39;,pos_left=&#39;center&#39;,pos_top=&#39;1%&#39;,
            title_textstyle_opts=opts.TextStyleOpts(color=&#39;#38d9a9&#39;,font_size=20)
        ),
         visualmap_opts=opts.VisualMapOpts(max_=150, is_show = False, is_piecewise=True, split_number = 8, min_ = 10,
                                           range_color=[&#39;#203fb6&#39;, &#39;#008afb&#39;, &#39;#ffec4a&#39;, &#39;#ff6611&#39;, &#39;#f62336&#39;] 
                                          ),
    )
)

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Pandas+Pyecharts | 2022 Fortune 500 Data Analysis Visualization

3.3 各国世界500强企业数量占比饼状图

Pandas+Pyecharts | 2022 Fortune 500 Data Analysis Visualization

我国世界500强企业有145家，占比高达29%，接近总量的1/3
The United States accounts for 24.8 and Japan accounts for 9.4%

##3.4 TOP8 pictograms of the number of Fortune 500 companies in each country

Pandas+Pyecharts | 2022 Fortune 500 Data Analysis Visualization

##3.5 Bar chart of the number of Fortune 500 companies in each Chinese city

Pandas+Pyecharts | 2022 Fortune 500 Data Analysis Visualization Domestic aspects:

my country’s 145 Fortune 500 companies are basically based on first-line Most cities
Beijing ranks first with 54 Fortune 500 companies, followed by Shanghai and Shenzhen with 12 and 10 companies respectively
Beijing, Shanghai, Guangzhou, Shenzhen and Zhongshan,
Guangzhou fell out of the top 5 with 4 companies, ranking 7th

3.6 各国世界500强企业数量地图分布

m1 = (
    Map(init_opts=opts.InitOpts(width=&#39;1000px&#39;, height=&#39;500px&#39;,theme=&#39;dark&#39;,bg_color=&#39;#0d0735&#39;)) 
    .add(&#39;公司数量&#39;, 
         region_data, 
         "world", 
         is_map_symbol_show=False,
         is_roam=False, 
        )
    .set_series_opts(label_opts=opts.LabelOpts(is_show=False))
    .set_global_opts(
        legend_opts=opts.LegendOpts(is_show=False),
        visualmap_opts=opts.VisualMapOpts(is_show=True, 
                                          max_=150,
                                          min_=0,
                                          is_piecewise=True,
                                          split_number=10,
                                          pos_top=&#39;50%&#39;,
                                          pos_left=&#39;10%&#39;,
                                          range_color=[&#39;#9ecae1&#39;,&#39;#6baed6&#39;,&#39;#4292c6&#39;,&#39;#2171b5&#39;,&#39;#08519c&#39;,&#39;#08306b&#39;,&#39;#d4b9da&#39;,&#39;#c994c7&#39;,&#39;#df65b0&#39;,&#39;#e7298a&#39;,&#39;#ce1256&#39;,&#39;#980043&#39;,&#39;#67001f&#39;]
        ), 
    )
)

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Pandas+Pyecharts | 2022 Fortune 500 Data Analysis Visualization

效果2：

3.7 中国世界500强企业数量占比水球图

Pandas+Pyecharts | 2022 Fortune 500 Data Analysis Visualization

3.8 世界500强企业公司名称词云

wd = WordCloud(init_opts=opts.InitOpts(width=&#39;1000px&#39;,height=&#39;600px&#39;,theme=&#39;dark&#39;,bg_color=&#39;#0d0735&#39;))
wd.add(&#39;&#39;, 
       [list(z) for z in zip(x_data, y_data)],
      )
wd.set_global_opts(
        title_opts=opts.TitleOpts(
            title=""),
        tooltip_opts=opts.TooltipOpts(is_show=True),
    )
wd.render_notebook()

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Pandas+Pyecharts | 2022 Fortune 500 Data Analysis Visualization

营收方面：

Walmart ranks first with operating income of US$572,754 million, Amazon ranks second with operating income of US$469,822 million, and State Grid Corporation of my country ranks first with operating income of US$469,822 million. 460616.9 million US dollars, ranking 3rd
A total of 4 companies in my country have entered the top 10 of the Fortune 500 list: State Grid Co., Ltd. ( 3), China National Petroleum Corporation (4), China Petrochemical Corporation (5), China State Construction Engineering Corporation (9)

##4.

Online running address

#Part of the code is not shown due to space reasons, Online running address (including source code) ：

##https://www.heywhale.com/mw/project/6318517d9b96502cad5c5ab0

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