Home > Article > Backend Development > Pandas+Pyecharts | 2022 Fortune 500 Data Analysis Visualization
In this issue, we use Python to analyze the information data of the world's top 500 companies in 2022, take a look:
Libraries involved:
Pandas — Data Processing
##Visualization Section:
Pictogram — PictorialBar
Bar chart — Bar
Map — Map
2.2 查看数据信息 500条数据没有确缺失,不需要进行其他处理。
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% Domestic aspects: Guangzhou fell out of the top 5 with 4 companies, ranking 7th 效果2: 营收方面: #Part of the code is not shown due to space reasons, Online running address (including source code) :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
df = pd.read_excel('2022年世界五百强排行榜.xlsx')
df.head(10)
df.info()
bar = (
Bar(init_opts=opts.InitOpts(width='1000px', height='1000px',bg_color='#0d0735'))
.add_xaxis(x_data)
.add_yaxis("",y_data)
.set_series_opts(label_opts=opts.LabelOpts(position="right",
font_size=12,
font_weight='bold',
formatter='{c} 家'),
)
.set_global_opts(
xaxis_opts=opts.AxisOpts(is_show=False,),
yaxis_opts=opts.AxisOpts(
axislabel_opts=opts.LabelOpts(font_size=13,color='#fff200'),
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='center',pos_top='1%',
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=['#203fb6', '#008afb', '#ffec4a', '#ff6611', '#f62336']
),
)
.reversal_axis()
)
p = (
Polar(init_opts=opts.InitOpts(width='1000px', height='800px', bg_color='#0d0735'))
.add_schema(
radiusaxis_opts=opts.RadiusAxisOpts(data=x_data[-8:],
type_='category'),
angleaxis_opts=opts.AngleAxisOpts(
is_clockwise=True,
is_scale=True,
max_=150,
axislabel_opts=opts.LabelOpts(font_size=14, color='#fff200'),
axisline_opts=opts.AxisLineOpts(is_show=True,linestyle_opts=opts.LineStyleOpts(
width=2,type_='dashed',color='#e4e932')),
splitline_opts=opts.SplitLineOpts(is_show=True,
linestyle_opts=opts.LineStyleOpts(type_='dashed', color='#9FC131')
),
),
)
.add('',y_data[-8:], type_='bar')
.set_global_opts(
title_opts=opts.TitleOpts(title='各国世界500强企业数量排名TOP8',subtitle='制图@公众号:Python当打之年',pos_left='center',pos_top='1%',
title_textstyle_opts=opts.TextStyleOpts(color='#38d9a9',font_size=20)
),
visualmap_opts=opts.VisualMapOpts(max_=150, is_show = False, is_piecewise=True, split_number = 8, min_ = 10,
range_color=['#203fb6', '#008afb', '#ffec4a', '#ff6611', '#f62336']
),
)
)
m1 = (
Map(init_opts=opts.InitOpts(width='1000px', height='500px',theme='dark',bg_color='#0d0735'))
.add('公司数量',
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='50%',
pos_left='10%',
range_color=['#9ecae1','#6baed6','#4292c6','#2171b5','#08519c','#08306b','#d4b9da','#c994c7','#df65b0','#e7298a','#ce1256','#980043','#67001f']
),
)
)
wd = WordCloud(init_opts=opts.InitOpts(width='1000px',height='600px',theme='dark',bg_color='#0d0735'))
wd.add('',
[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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