<jupyter_start><jupyter_text>动态条形图  demo<jupyter_code>from pyecharts import options as opts
from pyecharts.charts import Bar, Timeline
from pyecharts.faker import Faker

tl = Timeline()
for i in range(2015, 2020):
    bar = (
        Bar()
        .add_xaxis(Faker.choose())
        .add_yaxis("商家A", Faker.values(), label_opts=opts.LabelOpts(position="left"))#Y1坐标轴
        .add_yaxis("商家B", Faker.values(), label_opts=opts.LabelOpts(position="right"))#Y2坐标轴
        .reversal_axis()
        .set_global_opts(
            title_opts=opts.TitleOpts("Timeline-Bar-Reversal (时间: {} 年)".format(i))
        )
    )
    tl.add(bar, "{}年".format(i))
tl.render("timeline_bar_reversal_bar.html")
print(Faker.values())
print(Faker.choose())<jupyter_output>[42, 121, 149, 47, 86, 48, 140]
['河马', '蟒蛇', '老虎', '大象', '兔子', '熊猫', '狮子']<jupyter_text>动态条形图-改写   随机生成数据<jupyter_code>import random
import pandas as pd
import math

cats0 = ['驯鹿','飞机','火车','船','汽车']
color0 = ['#D6A5DD','#F7DC73','#EBBDBF','#76CBE8','#A4DFE5']
year0 = list(range(1977,2021))
year = []
for i in year0:
    for j in range(len(cats0)):
        year.append(i)

cats = cats0*len(year0)
color = color0*len(year0)
value = []
for i in year:
    value.append(math.pow(random.randint(0,50), 2))#求平方，拉开数据
df = pd.DataFrame()
df['year'] = year
df['value'] = value
df['cats'] = cats
df['color'] = color
df['csum']=df.groupby(['cats'])['value'].cumsum()
df[df['year']==1999]<jupyter_output><empty_output><jupyter_text>把数据放到代码块中<jupyter_code>from pyecharts import options as opts
from pyecharts.charts import Bar, Timeline

tl = Timeline()
for i in range(1977,2019):
    df_sub = df[df['year']==i].sort_values(by='csum')
    cats_list = list(df_sub['cats'])
    csum_list = list(df_sub['csum'])
    color_list = list(df_sub['color'])

    bar = (
        Bar()
        .add_xaxis(cats_list)
        .add_yaxis("", csum_list,label_opts=opts.LabelOpts(position="right",font_weight="bold"),category_gap=30)
        .reversal_axis()
        .set_global_opts(
            title_opts=opts.TitleOpts("跑得快 (时间: {} 年)".format(i),pos_left=350,padding=[30,20]),
            xaxis_opts=opts.AxisOpts(max_=50000)
        )
    )
    tl.add(bar, "{}年".format(i))
    tl.add_schema(play_interval=300, is_loop_play=True)#播放间隔，是否循环播放
tl.render("timeline_bar_reversal_dynamic_data.html")<jupyter_output><empty_output><jupyter_text>改变柱条颜色<jupyter_code>from pyecharts import options as opts
from pyecharts.charts import Bar, Timeline

tl = Timeline()
for i in range(1977,2019):
    df_sub = df[df['year']==i].sort_values(by='csum')
    cats_list = list(df_sub['cats'])
    csum_list = list(df_sub['csum'])
    color_list = list(df_sub['color'])
    y=[]
    for j in range(5):
        y.append(
            opts.BarItem(
                name=cats_list[j],
                value=csum_list[j],
                itemstyle_opts=opts.ItemStyleOpts(color=color_list[j]),
            
            )
        )

    bar = (
        Bar()
        .add_xaxis(cats_list)
        .add_yaxis("", y,label_opts=opts.LabelOpts(position="right",font_weight="bold"),category_gap=30)
        .reversal_axis()
        .set_global_opts(
            title_opts=opts.TitleOpts("跑得快 (时间: {} 年)".format(i),pos_left=350,padding=[30,20]),
            xaxis_opts=opts.AxisOpts(max_=50000)
        )
    )
    tl.add(bar, "{}年".format(i))
    tl.add_schema(play_interval=300, is_loop_play=True)#播放间隔，是否循环播放
tl.render("timeline_bar_reversal_dynamic_color.html")<jupyter_output><empty_output><jupyter_text>完整图 -添加图像后<jupyter_code>from pyecharts import options as opts
from pyecharts.charts import Bar, Timeline

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'bird':'path://M959.4 236.2v-1.4c-32.6 14.3-67.7 24.1-104.4 28.4 38-22.8 67.3-58.9 81-102-35.6 21.1-75 36.5-117 44.7-33.6-35.8-81.5-58.1-134.5-58.1-101.7 0-184.2 82.5-184.2 184.2 0 14.4 1.6 28.5 4.8 42-153.1-7.7-288.8-81-379.7-192.5-15.8 27.3-24.9 58.9-24.9 92.6 0 63.9 32.5 120.3 81.9 153.3-30.2-1-58.6-9.3-83.4-23v2.3c0 89.2 63.5 163.7 147.7 180.6-15.5 4.2-31.7 6.5-48.5 6.5-11.9 0-23.4-1.2-34.7-3.3C187 663.7 255 717 335.6 718.5c-63 49.4-142.4 78.9-228.8 78.9-14.4 0-28.7-0.8-42.7-2.4v0.7c81.3 51.8 177.6 82 281.1 82 338.8 0 524.1-280.7 524.1-524.1 0-8-0.2-16-0.5-23.8 35.4-25.7 66.1-57.5 90.6-93.6z'
}
tl = Timeline()
for i in range(1977,2019):
    df_sub = df[df['year']==i].sort_values(by='csum')
    cats_list = list(df_sub['cats'])
    csum_list = list(df_sub['csum'])
    color_list = list(df_sub['color'])
    y=[]
    for j in range(5):
        y.append(
            opts.BarItem(
                name=cats_list[j],
                value=csum_list[j],
                itemstyle_opts=opts.ItemStyleOpts(color=color_list[j]),
            
            )
        )
    bar = (
        Bar()
        .add_xaxis(cats_list)
        .add_yaxis("", y,label_opts=opts.LabelOpts(position="top",font_weight="bold"),category_gap=30,
                  markpoint_opts=opts.MarkPointOpts(#每个条形图的分类坐标内容value=cats_list[0], value=cats_list[1], value=cats_list[2], value=cats_list[3], value=cats_list[4]
            data=[opts.MarkPointItem(name="",coord=[csum_list[0], cats_list[0]],symbol=symbols[cats_list[0]],
                                     itemstyle_opts=opts.ItemStyleOpts(color=color_list[0],border_color='grey')),
                   opts.MarkPointItem(name="",coord=[csum_list[1], cats_list[1]],symbol=symbols[cats_list[1]],
                                      itemstyle_opts=opts.ItemStyleOpts(color=color_list[1],border_color='grey')),
                 opts.MarkPointItem(name="",coord=[csum_list[2], cats_list[2]],symbol=symbols[cats_list[2]],
                                    itemstyle_opts=opts.ItemStyleOpts(color=color_list[2],border_color='grey')),
                  opts.MarkPointItem(name="",coord=[csum_list[3], cats_list[3]],symbol=symbols[cats_list[3]],
                                     itemstyle_opts=opts.ItemStyleOpts(color=color_list[3],border_color='grey')),
                  opts.MarkPointItem(name="",coord=[csum_list[4], cats_list[4]],symbol=symbols[cats_list[4]],
                                     itemstyle_opts=opts.ItemStyleOpts(color=color_list[4],border_color='grey'))
                   ]))
            #category_gap=30,
        #.add_yaxis("", csum_list, label_opts=opts.LabelOpts(position="right"))
        .reversal_axis()
        .set_global_opts(
            title_opts=opts.TitleOpts("跑得快 (时间: {} 年)".format(i),pos_left=350,padding=[30,20]),
            xaxis_opts=opts.AxisOpts(max_=50000)
        )
    )
    tl.add(bar, "{}年".format(i))
    tl.add_schema(play_interval=300, is_loop_play=True)#播放间隔，是否循环播放
tl.render("timeline_bar_reversal_dynamic_final.html")<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.24944953065245104, 'fraction_numerical': 0.42484644802410476, 'mean_word_length': 3.1941676792223572, 'pattern_counts': {'":': 0, '<': 20, '<?xml version=': 0, '>': 20, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 5, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '5', 'dir': 'jupyter-structured-clean-dedup', 'id': '98587', 'license': 'MIT', 'n_tokens_mistral': 13464, 'n_tokens_neox': 9925, 'n_words': 458, 'path': 'pyecharts_timeline.ipynb', 'repo_name': 'Yangyehong/python', 'size': '17258'}