python数据可视化-使用pyecharts绘制简单的数据动态展示图

最终效果

前言

大家好,我是PYTHON爱好者二狗.今天向各位领导汇报的题目是:使用pyecharts绘制简单的数据动态展示图.

编程环境

1.文中电脑操作系统:win10

2.文中所使用的python模块:

(1).pandas (第三方模块,需要pip安装)

安装命令:pip install -i https://pypi.tuna.tsinghua.edu.cn/simple pandas

官方文档:https://pandas.pydata.org/pandas-docs/stable/

(2).pyecharts (第三方模块,需要pip安装)

安装命令:pip install -i https://pypi.tuna.tsinghua.edu.cn/simple pyecharts

官方文档:https://pyecharts.org/#/zh-cn/intro

3.文中数据源文件:二手车数据.csv(如果需要,请后台私信)

4.pyecharts版本:1.9.1

5.文中所使用的IDE:VSCODE(安装Jupyter插件)

查看pyecharts版本

数据动态展示图及数据结构剖析

数据动态展示图剖析

数据源表格文件

文中绘制的动态图表分为:①时间线轮播图,②柱状图,③饼图,④词云图,⑤树图

接下来,二狗向各位领导汇报绘制过程及注意事项.

代码拆检

import pandas as pd  # 导入pandas模块
df = pd.read_csv('二手车数据.csv',index_col=0) # 读取数据表格
df['car_year'] = df.car_year.agg(lambda x : x.split('-')[0]) 
# 切割表格中的car_year列的所有值 取出年份
df = df[(df.car_city=='昆明') 
          | (df.car_city=='贵阳') 
          |(df.car_city=='南宁') 
          | (df.car_city=='成都') 
          | (df.car_city=='重庆')
          |(df.car_city=='拉萨')] 
# 筛选出表格中car_city列中的昆明,贵阳,南宁,成都,重庆,拉萨的数据
tb = df.pivot_table(values=['car_price(万元)',],index=['car_year','car_city']) 
# 把筛选出的城市数据聚合分类计算出每年每个城市的二手车均值

每年每个城市的二手车均值

注:pivot_table()方法,不指定aggfunc参数时,默认aggfunc="mean"计算均值.

year_list = [i[0] for i in tb.index] # 生成一个装有年份的列表
city_list = [i[1] for i in tb.index]  # 生成一个装有城市名称的列表
price_list = [round(i,ndigits=2) for i in tb['car_price(万元)']]
# 生成一个装有每个城市均值的列表,对列表里的每个元素四舍五入,保留2位小数
time_data = {} #创建一个空字典
for k,v1,v2 in zip(year_list,city_list,price_list):
#遍历 year_list city_list price_list 组装一个数据格式为{年份:{城市:价格...}}的字典
    if k not in time_data:
        time_data[k] = {v1:v2}
    else:
        time_data[k].update({v1:v2})

组装好的字典结构

import pyecharts.options as opt
from pyecharts.commons.utils import JsCode
from pyecharts.charts import Pie, Bar,Timeline,Grid,TreeMap,WordCloud
from pyecharts.globals import ThemeType
#导入绘图模块
tl = Timeline(
    init_opts=opt.InitOpts(
        theme=ThemeType.DARK,
        animation_opts=opt.AnimationOpts(
            animation_duration=3000,
            animation_delay_update = 10,
    )
))# 绘制时间线轮播图
for year,city_price_dict in time_data.items():
#分别遍历字典的键和值
    values_list = list(sorted(city_price_dict.items(), key=lambda value : value[1], reverse=True))
    # 把字典的值 转换为降序排列(从大到小)的列表 [(城市1,价格1),(城市2,价格2)...]
    values_data = (sorted(city_price_dict.items(), key=lambda value : value[1], reverse=False))
    # 把字典的值 转换为升序排列(从小到大)的列表 [(城市1,价格1),(城市2,价格2)...]

values_data结果

values_list结果

import pyecharts.options as opt
from pyecharts.commons.utils import JsCode
from pyecharts.charts import Pie, Bar,Timeline,Grid,TreeMap,WordCloud
from pyecharts.globals import ThemeType
#导入绘图模块
tl = Timeline(
    init_opts=opt.InitOpts(
        theme=ThemeType.DARK,
        animation_opts=opt.AnimationOpts(
            animation_duration=3000,
            animation_delay_update = 10,
    )
))# 绘制时间线轮播图
for year,city_price_dict in time_data.items():
#分别遍历字典的键和值
    values_list = list(sorted(city_price_dict.items(), key=lambda value : value[1], reverse=True))
    # 把字典的值 转换为降序排列(从大到小)的列表 [(城市1,价格1),(城市2,价格2)...]
    values_data = (sorted(city_price_dict.items(), key=lambda value : value[1], reverse=False))
    # 把字典的值 转换为升序排列(从小到大)的列表 [(城市1,价格1),(城市2,价格2)...]
    pie = (#绘制饼图
        Pie()
        .add(
            series_name=' 单位:万元',
            data_pair = values_data,
            radius= ['50%','60%'],
            center = ['70%','50%'],
            rosetype= 'radius'
        )
        .set_global_opts(
            title_opts=opt.TitleOpts(
                title= f'{year}年西南地区二手车均价'
            )
        )
    )
    charts = WordCloud()
    charts.add( #绘制词云图
        series_name = '均价(万元)',
        data_pair= values_data,
        textstyle_opts=opt.TextStyleOpts(font_family="serif"),
        shape = "diamond",
        word_size_range= [10, 50],
        pos_left = '35%',
        pos_top = '12%',
    )
    charts.set_global_opts(
        title_opts = opt.TitleOpts(
        ), 
    )
    bar = (#绘制柱状图
        Bar()
        .add_xaxis([i[0] for i in values_data])
        .add_yaxis(
            "单位万元", 
            [i[1] for i in values_data],
            bar_width=30,
            category_gap=0
        )
        .reversal_axis()
        .set_global_opts(
            legend_opts=opt.LegendOpts(is_show=False),
            yaxis_opts=opt.AxisOpts(is_show=True,),
            xaxis_opts=opt.AxisOpts(is_show=True),
        )
        .set_series_opts(
            label_opts=opt.LabelOpts(position="right"),
             itemstyle_opts={
            "normal": {
                "color": JsCode(
                    """new echarts.graphic.LinearGradient(0, 0, 0, 1, [{offset: 0,color: 'rgba(0, 244, 255, 1)'}, {offset: 1,color: 'rgba(0, 77, 167, 1)'}], false)"""
                ),
                "barBorderRadius": [30, 30, 30, 30],"shadowColor": "rgb(0, 160, 221)",
            }
        }
        )
    )
    tree = ( #绘制树图
        TreeMap()
        .add(
            series_name=year,
            data=[{'value':i[1],'name':i[0]} for i in values_data],
            visual_min=30,
            leaf_depth=1,
            # 标签居中为 position = "inside"
            width=  '12%',
            height= '53%',
            pos_left = '88%',
            pos_top = '47%',
            label_opts=opt.LabelOpts(position="inside"),
            breadcrumb_opts=opt.TreeMapBreadcrumbOpts(
                is_show=False,
                pos_left= 'left',
                height=50,
                ),
            roam=False,
        )
        .set_global_opts(
            legend_opts=opt.LegendOpts(is_show=False),
            title_opts=opt.TitleOpts(
                
            ),
        )
    )
        
    grid_chart =( #把绘制好的图形组合在一起
        Grid()
        .add(
            bar,
            grid_opts=opt.GridOpts(
                width=  300,
                height= 320
           ),
        )
        .add(
            tree,
            grid_opts=opt.GridOpts(
                
           ),
        )
        .add(
           charts,
           grid_opts=opt.GridOpts(
                
           ),
        )
        .add(
           pie,
           grid_opts=opt.GridOpts(
              
           ),
        )
    )
    tl.add( #把组合好的图形,添加进时间线轮播图里
        chart=grid_chart,
        time_point= f'{year}年',
    )
    tl.add_schema(
        is_auto_play= True,
        is_timeline_show=True,
        orient="horizontal",
        pos_left='left',
        symbol_size=[8,5]
    )

tl.render('时间线图.html')#生成绘制好的图形html文件
tl.render_notebook() # 在notebook里渲染出来绘制好的图形

PS:绘图过程就是调整各图形的对应的参数,各位领导请详阅官方文档:https://pyecharts.org/#/zh-cn/intro

完整代码

import pandas as pd
import pyecharts.options as opt
from pyecharts.commons.utils import JsCode
from pyecharts.charts import Pie, Bar,Timeline,Grid,TreeMap,WordCloud
from pyecharts.globals import ThemeType
time_data = {} 
tl = Timeline(
    init_opts=opt.InitOpts(
        theme=ThemeType.DARK,
        animation_opts=opt.AnimationOpts(
            animation_duration=3000,
            animation_delay_update = 10,
    )
))
df = pd.read_csv('二手车数据.csv',index_col=0)
df['car_year'] = df.car_year.agg(lambda x : x.split('-')[0])
df = df[(df.car_city=='昆明') | (df.car_city=='贵阳') |(df.car_city=='南宁') | (df.car_city=='成都') | (df.car_city=='重庆')| (df.car_city=='拉萨')]
tb = df.pivot_table(values=['car_price(万元)',],index=['car_year','car_city'])
year_list = [i[0] for i in tb.index]
city_list = [i[1] for i in tb.index]
price_list = [round(i,ndigits=2) for i in tb['car_price(万元)']]
for k,v1,v2 in zip(year_list,city_list,price_list):
    if k not in time_data:
        time_data[k] = {v1:v2}
    else:
        time_data[k].update({v1:v2})
for year,city_price_dict in time_data.items():
    values_list = list(sorted(city_price_dict.items(), key=lambda value : value[1], reverse=True))
    values_data = (sorted(city_price_dict.items(), key=lambda value : value[1], reverse=False))
    pie = (
        Pie()
        .add(
            series_name=' 单位:万元',
            data_pair = values_data,
            radius= ['50%','60%'],
            center = ['70%','50%'],
            rosetype= 'radius'
        )
        .set_global_opts(
            title_opts=opt.TitleOpts(
                title= f'{year}年西南地区二手车均价'
            )
        )
    )
    charts = WordCloud()
    charts.add(
        series_name = '均价(万元)',
        data_pair= values_data,
        textstyle_opts=opt.TextStyleOpts(font_family="serif"),
        shape = "diamond",
        word_size_range= [10, 50],
        pos_left = '35%',
        pos_top = '12%',
    )
    charts.set_global_opts(
        title_opts = opt.TitleOpts(
        ), 
    )
    bar = (
        Bar()
        .add_xaxis([i[0] for i in values_data])
        .add_yaxis(
            "单位万元", 
            [i[1] for i in values_data],
            bar_width=30,
            category_gap=0
        )
        .reversal_axis()
        .set_global_opts(
            legend_opts=opt.LegendOpts(is_show=False),
            yaxis_opts=opt.AxisOpts(is_show=True,),
            xaxis_opts=opt.AxisOpts(is_show=True),
        )
        .set_series_opts(
            label_opts=opt.LabelOpts(position="right"),
             itemstyle_opts={
            "normal": {
                "color": JsCode(
                    """new echarts.graphic.LinearGradient(0, 0, 0, 1, [{offset: 0,color: 'rgba(0, 244, 255, 1)'}, {offset: 1,color: 'rgba(0, 77, 167, 1)'}], false)"""
                ),
                "barBorderRadius": [30, 30, 30, 30],"shadowColor": "rgb(0, 160, 221)",
            }
        }
        )
    )
    tree = (
        TreeMap()
        .add(
            series_name=year,
            data=[{'value':i[1],'name':i[0]} for i in values_data],
            visual_min=30,
            leaf_depth=1,
            # 标签居中为 position = "inside"
            width=  '12%',
            height= '53%',
            pos_left = '88%',
            pos_top = '47%',
            label_opts=opt.LabelOpts(position="inside"),
            breadcrumb_opts=opt.TreeMapBreadcrumbOpts(
                is_show=False,
                pos_left= 'left',
                height=50,
                ),
            roam=False,
        )
        .set_global_opts(
            legend_opts=opt.LegendOpts(is_show=False),
            title_opts=opt.TitleOpts(
                
            ),
        )
    )
        
    grid_chart =(
        Grid()
        .add(
            bar,
            grid_opts=opt.GridOpts(
                width=  300,
                height= 320
           ),
        )
        .add(
            tree,
            grid_opts=opt.GridOpts(
                
           ),
        )
        .add(
           charts,
           grid_opts=opt.GridOpts(
                
           ),
        )
        .add(
           pie,
           grid_opts=opt.GridOpts(
              
           ),
        )
    )
    tl.add(
        chart=grid_chart,
        time_point= f'{year}年',
    )
    tl.add_schema(
        is_auto_play= True,
        is_timeline_show=True,
        orient="horizontal",
        pos_left='left',
        symbol_size=[8,5]
    )

tl.render('时间线图.html')
tl.render_notebook()