The interactive dynamic big picture made by Python is really beautiful!

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Today I will share with you a pyecharts interactive dynamic visualization case. Through the first split and then the combination, I will teach you how to achieve it step by step. The specific results are as follows.

 

1. Draw basic graphics

Use pandas to read the data, and use pyecharts to draw the map, histogram, and pie chart by integrating the data format. The specific content is as follows:

1. Draw a map

import pyecharts.options as opts
from pyecharts.globals import ThemeType
from pyecharts.commons.utils import JsCode
from pyecharts.charts import Timeline, Grid, Bar, Map, Pie
import pandas as pd
data = pd.read_excel('全国各省财政收入.xlsx',index_col=0)
years=list(data.keys()) #获取列名
citys=list(data.index)    #获取索引行名
citys=[city.replace('省','').replace('市','').replace('自治区','') for city in citys]
datas=[]
for y in years:
    dict_year={}
    dict_year['time']=y
    data_list=[[i,j] for i,j in zip(citys,list(data[y]))]
    dict_year['data']=sorted(data_list, key=(lambda x: x[1]),reverse=True)
    datas.append(dict_year)
map_data = [i["data"] for i in datas if i["time"]==2010][0]
min_data, max_data = (
        min([d[1] for d in map_data]),
        max([d[1] for d in map_data]),
    )
map_chart = (
        Map(init_opts=opts.InitOpts(theme=ThemeType.DARK))
        .add(
            series_name="",
            data_pair=map_data,
            label_opts=opts.LabelOpts(is_show=False),
            is_map_symbol_show=False,
        )
        .set_global_opts(
            title_opts=opts.TitleOpts(
                title="2000年以来中国各省GDP排名变化情况",
                subtitle="GDP单位:亿元",
                pos_left="center",
                pos_top="top",
                title_textstyle_opts=opts.TextStyleOpts(
                    font_size=25, color="rgba(123,104,238, 0.9)"
                ),
            ),
            visualmap_opts=opts.VisualMapOpts(
                is_calculable=True,
                dimension=0,
                pos_left="10",
                pos_top="center",
                range_text=["High", "Low"],
                range_color=["lightskyblue", "yellow", "orangered"],
                textstyle_opts=opts.TextStyleOpts(color="#ddd"),
                min_=min_data,
                max_=max_data,
            ),
        )
    )
map_chart.render_notebook()

2. Draw a histogram

map_data = [i["data"] for i in datas if i["time"]==y][0]
min_data, max_data = (
    min([d[1] for d in map_data]),
    max([d[1] for d in map_data]),
)
bar_x_data = [x[0] for x in map_data]
bar_y_data = [x[1] for x in map_data]
bar = (
        Bar(init_opts=opts.InitOpts(theme=ThemeType.DARK))
        .add_xaxis(xaxis_data=bar_x_data)
        .add_yaxis(
            series_name="",
            yaxis_data=bar_y_data,
            label_opts=opts.LabelOpts(
                is_show=True, position="right", formatter="{b}: {c}"
            ),
        )
        .reversal_axis()
        .set_global_opts(
            title_opts=opts.TitleOpts(
                title="2000年以来中国各省GDP排名变化情况",
                subtitle="GDP单位:亿元",
                pos_left="center",
                pos_top="top",
                title_textstyle_opts=opts.TextStyleOpts(
                    font_size=25, color="rgba(123,104,238, 0.9)"
                ),
            ),
            xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(is_show=False)),
            yaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(is_show=False)),
            tooltip_opts=opts.TooltipOpts(is_show=False),
            visualmap_opts=opts.VisualMapOpts(
                is_calculable=True,
                dimension=0,
                pos_left="10",
                pos_top="center",
                range_text=["High", "Low"],
                range_color=["lightskyblue", "yellow", "orangered"],
                textstyle_opts=opts.TextStyleOpts(color="#ddd"),
                min_=min_data,
                max_=max_data,
            ),
        )
    )
bar.render_notebook()

3. Draw a pie chart

pie_data = [[x[0], x[1]] for x in map_data]
percent_sum = sum([x[1] for x in map_data])
rest_value = 0
for d in map_data:
    rest_percent = 100.0
    rest_percent = rest_percent - percent_sum
    rest_value = d[1] * (rest_percent / d[1])
pie = (
    Pie(init_opts=opts.InitOpts(theme=ThemeType.DARK))
    .add(
        series_name="",
        data_pair=pie_data,
        radius=["12%", "20%"],
        center=["50%", "50%"],
        itemstyle_opts=opts.ItemStyleOpts(
            border_width=1, border_color="rgba(0,0,0,0.3)"
        ),
    )
    .set_global_opts(
        title_opts=opts.TitleOpts(
                title="2000年以来中国各省GDP排名变化情况",
                subtitle="GDP单位:亿元",
                pos_left="center",
                pos_top="top",
                title_textstyle_opts=opts.TextStyleOpts(
                    font_size=25, color="rgba(123,104,238, 0.9)"
                ),
            ),
        tooltip_opts=opts.TooltipOpts(is_show=True, formatter="{b} {d}%"),
        legend_opts=opts.LegendOpts(is_show=False),
    )
)
pie.render_notebook()

2. Draw animated pictures

On the basis of the basic graphics, the timeline function is introduced to draw the corresponding dynamic graphics:

1. Draw a dynamic map

def get_year_chart(year: int):
    map_data = [i["data"] for i in datas if i["time"]==year][0]
    min_data, max_data = (
            min([d[1] for d in map_data]),
            max([d[1] for d in map_data]),
        )
    map_chart = (
            Map(init_opts=opts.InitOpts(theme=ThemeType.DARK))
            .add(
                series_name="",
                data_pair=map_data,
                label_opts=opts.LabelOpts(is_show=False),
                is_map_symbol_show=False,
            )
            .set_global_opts(
                title_opts=opts.TitleOpts(
                    title="{}年以来中国各省GDP排名情况".format(year),
                    subtitle="GDP单位:亿元",
                    pos_left="center",
                    pos_top="top",
                    title_textstyle_opts=opts.TextStyleOpts(
                        font_size=25, color="rgba(123,104,238, 0.9)"
                    ),
                ),
                visualmap_opts=opts.VisualMapOpts(
                    is_calculable=True,
                    dimension=0,
                    pos_left="10",
                    pos_top="center",
                    range_text=["High", "Low"],
                    range_color=["lightskyblue", "yellow", "orangered"],
                    textstyle_opts=opts.TextStyleOpts(color="#ddd"),
                    min_=min_data,
                    max_=max_data,
                ),
            )
        )
    return map_chart
time_list = list(range(2000,2020))
timeline = Timeline(
    init_opts=opts.InitOpts(width="1000px", height="800px", theme=ThemeType.DARK)
)
for y in time_list:
    g = get_year_chart(year=y)
    timeline.add(g, time_point=str(y))

timeline.add_schema(
    orient="vertical",
    is_auto_play=True,
    is_inverse=True,
    play_interval=500,
    pos_left="null",
    pos_right="5",
    pos_top="20",
    pos_bottom="20",
    width="50",
    label_opts=opts.LabelOpts(is_show=True, color="#fff"),
)
timeline.render_notebook()

2. Draw a dynamic histogram

def get_year_chart(year: int):
    map_data = [i["data"] for i in datas if i["time"]==year][0]
    min_data, max_data = (
        min([d[1] for d in map_data]),
        max([d[1] for d in map_data]),
    )
    bar_x_data = [x[0] for x in map_data]
    bar_y_data = [x[1] for x in map_data]
    bar = (
            Bar(init_opts=opts.InitOpts(theme=ThemeType.DARK))
            .add_xaxis(xaxis_data=bar_x_data)
            .add_yaxis(
                series_name="",
                yaxis_data=bar_y_data,
                label_opts=opts.LabelOpts(
                    is_show=True, position="right", formatter="{b}: {c}"
                ),
            )
            .reversal_axis()
            .set_global_opts(
                title_opts=opts.TitleOpts(
                    title="2000年以来中国各省GDP排名变化情况",
                    subtitle="GDP单位:亿元",
                    pos_left="center",
                    pos_top="top",
                    title_textstyle_opts=opts.TextStyleOpts(
                        font_size=25, color="rgba(123,104,238, 0.9)"
                    ),
                ),
                xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(is_show=False)),
                yaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(is_show=False)),
                tooltip_opts=opts.TooltipOpts(is_show=False),
                visualmap_opts=opts.VisualMapOpts(
                    is_calculable=True,
                    dimension=0,
                    pos_left="10",
                    pos_top="center",
                    range_text=["High", "Low"],
                    range_color=["lightskyblue", "yellow", "orangered"],
                    textstyle_opts=opts.TextStyleOpts(color="#ddd"),
                    min_=min_data,
                    max_=max_data,
                ),
            )
        )
    return bar
time_list = list(range(2000,2020))
timeline = Timeline(
    init_opts=opts.InitOpts(width="1000px", height="800px", theme=ThemeType.DARK)
)
for y in time_list:
    g = get_year_chart(year=y)
    timeline.add(g, time_point=str(y))

timeline.add_schema(
    orient="vertical",
    is_auto_play=True,
    is_inverse=True,
    play_interval=500,
    pos_left="null",
    pos_right="5",
    pos_top="20",
    pos_bottom="20",
    width="50",
    label_opts=opts.LabelOpts(is_show=True, color="#fff"),
)
timeline.render_notebook()

3. Draw a dynamic pie chart

def get_year_chart(year: int):
    map_data = [i["data"] for i in datas if i["time"]==year][0]
    min_data, max_data = (
        min([d[1] for d in map_data]),
        max([d[1] for d in map_data]),
    )
    pie_data = [[x[0], x[1]] for x in map_data]
    percent_sum = sum([x[1] for x in map_data])
    rest_value = 0
    for d in map_data:
        rest_percent = 100.0
        rest_percent = rest_percent - percent_sum
        rest_value = d[1] * (rest_percent / d[1])
    pie = (
        Pie(init_opts=opts.InitOpts(theme=ThemeType.DARK))
        .add(
            series_name="",
            data_pair=pie_data,
            radius=["12%", "20%"],
            center=["50%", "50%"],
            itemstyle_opts=opts.ItemStyleOpts(
                border_width=1, border_color="rgba(0,0,0,0.3)"
            ),
        )
        .set_global_opts(
            title_opts=opts.TitleOpts(
                    title="2000年以来中国各省GDP排名变化情况",
                    subtitle="GDP单位:亿元",
                    pos_left="center",
                    pos_top="top",
                    title_textstyle_opts=opts.TextStyleOpts(
                        font_size=25, color="rgba(123,104,238, 0.9)"
                    ),
                ),
            tooltip_opts=opts.TooltipOpts(is_show=True, formatter="{b} {d}%"),
            legend_opts=opts.LegendOpts(is_show=False),
        )
    )
    return pie
time_list = list(range(2000,2020))
timeline = Timeline(
    init_opts=opts.InitOpts(width="1000px", height="800px", theme=ThemeType.DARK)
)
for y in time_list:
    g = get_year_chart(year=y)
    timeline.add(g, time_point=str(y))

timeline.add_schema(
    orient="vertical",
    is_auto_play=True,
    is_inverse=True,
    play_interval=500,
    pos_left="null",
    pos_right="5",
    pos_top="20",
    pos_bottom="20",
    width="50",
    label_opts=opts.LabelOpts(is_show=True, color="#fff"),
)
timeline.render_notebook()

Three, merge animation

Finally, merge the three graphics together through the grid module:

 

 

The interactive dynamic map is now ready, have you abandoned it?