实现动态条形图——matplotlib

深藏阁楼爱情的钟 2022-12-27 07:46 258阅读 0赞

说明：  
首先保证你导入的数据是这样的：  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ0NzYwOTEy_size_16_color_FFFFFF_t_70_pic_center]  
***数据源：***  
[链接：https://pan.baidu.com/s/13HzYkMspIzKQRGUxndozQg][https_pan.baidu.com_s_13HzYkMspIzKQRGUxndozQg]  
提取码：love

#### 1.导入模块，读取文件 ####

import pandas as pd
    df = pd.read_csv('D:/Python/Mypython/python项目集锦/actor-弹幕数据分析/df_resuluts.csv',engine='python',encoding='utf-8')
    df.head(5)

#### 2.绘制单个图 ####

%matplotlib inline
    import pandas as pd
    import matplotlib.pyplot as plt
    import matplotlib.ticker as ticker
    import matplotlib.animation as animation
    from IPython.display import HTML
    #显示中文（可能还会显示不了，请自行百度解决中文问题）
    plt.rcParams['font.sans-serif']=['SimHei']
    
    df2 = df[['name', '2020-09-28']].sort_values(by='2020-09-28', ascending=False).head(10)#内嵌一个列表实现取两列，温习
    df2.sort_values(by='2020-09-28', ascending=True, inplace=True)
    df2#为了条形图做准备

fig, ax = plt.subplots(figsize=(15, 8))
    ax.barh(df2['name'], df2['2020-09-28'])

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ0NzYwOTEy_size_16_color_FFFFFF_t_70_pic_center 1]

#### 3.为y轴数据随机配色 ####

colors = ['#adb0ff', '#ffb3ff', '#90d595', '#e48381', '#aafbff', '#f7bb5f', '#eafb50', 
             '#adb0ff', '#ffb3ff', '#90d595', '#e48381', '#aafbff', '#f7bb5f', '#eafb50',
             '#adb0ff', '#ffb3ff', '#90d595', '#e48381', '#aafbff', '#f7bb5f', '#eafb50',
             '#adb0ff', '#ffb3ff', '#90d595', '#e48381', '#aafbff', '#f7bb5f', '#eafb50',
             '#adb0ff', '#ffb3ff', '#90d595', '#e48381', '#aafbff', '#f7bb5f', '#eafb50',
              '#adb0ff', '#ffb3ff', '#90d595', '#e48381', '#aafbff', '#f7bb5f', '#eafb50',
              '#adb0ff', '#ffb3ff', '#90d595', '#e48381', '#aafbff']
    
    #给每个国家随机分配颜色
    namecolors = dict()
    names = set(df['name'])
    for color, name in zip(colors, names):#多个序列(列表，元组，集合)同时遍历，使用zip()方法，这里很高级哦！
        namecolors[name] = color
        
    namecolors

#### 4.绘制单个彩色图 ####

fig, ax = plt.subplots(figsize=(15, 8))
    #排名前10的国家
    ax.barh(df2['name'], df2['2020-09-28'], color=[namecolors[c] for c in df2['name']])
    for i, (value, name) in enumerate(zip(df2['2020-09-28'], df2['name'])):
            ax.text(value, i,     name,           size=14, weight=600, ha='right', va='bottom')
            ax.text(value, i,     f'{value:,.0f}',  size=14, ha='left',  va='center')
    ax.text(1, 0.45, '2020-09-28', transform=ax.transAxes, size=46, ha='right')

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ0NzYwOTEy_size_16_color_FFFFFF_t_70_pic_center 2]

#### 5.读取df列名 ####

list(df)

#data = [i for i in df[1:]][1:]#瞎猫碰上死耗子了
    #取出列名的几种方法之一
    data = list(df)[1:] 
    @datadata

#### 6.使用循环遍历，都是一种模板 ####

fig, ax = plt.subplots(figsize=(15, 8))
    
    def draw_barchart(date):
        #整理数据
        date = str(date)
        df2 = df[['name', date]].sort_values(by=date, ascending=False).head(10)
        df2.sort_values(by=date, ascending=True, inplace=True)
        
        #横向条形图
        ax.clear()
        ax.barh(df2['name'], df2[date], color=[namecolors[name] for name in df2['name']])
        dx = df[date].max()/200
        
        for i, (value, name) in enumerate(zip(df2[date], df2['name'])):
            ax.text(value-dx, i,     name,           size=14, weight=600, ha='right', va='bottom')
            ax.text(value+dx, i,     f'{value:,.0f}',  size=14, ha='left',  va='center')
                   
        #细节修饰
        ax.text(1, 0.45, date, transform=ax.transAxes, color='#777777', size=46, ha='right', weight=800)
        ax.text(0, 1.06, 'y轴标题', transform=ax.transAxes, size=12, color='#777777')
        
        ax.xaxis.set_ticks_position('top')
        ax.tick_params(axis='x', colors='#777777', labelsize=12)
        ax.xaxis.set_major_formatter(ticker.StrMethodFormatter('{x:,.0f}'))
        ax.xaxis.set_ticks_position('top')
        ax.tick_params(axis='x', colors='#777777', labelsize=12)
    
        
        ax.margins(0, 0.01)
        ax.grid(which='major', axis='x', linestyle='-')
        ax.set_axisbelow(True)
        ax.text(0.3, 1.05, '总标题',
               transform=ax.transAxes, size=24, weight=600, ha='left')
        
        plt.box(False)
        
    # for i in range(39):
    draw_barchart(data[0])

#### 7.导入动画 ####

import matplotlib.animation as animation
    from IPython.display import HTML
    
    fig, ax = plt.subplots(figsize=(15, 8))
    animator = animation.FuncAnimation(fig, draw_barchart, frames=[data[i] for i in range(39)])
    HTML(animator.to_jshtml())

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ0NzYwOTEy_size_16_color_FFFFFF_t_70_pic_center 3]

#### 8.保存为gif ####

#保存为gif
    #animator.save('resetvalue.gif', writer='imagemagick')
    #animator.save('crap.gif', writer='imagemagick', savefig_kwargs={'facecolor':'white'}, fps=1)

![在这里插入图片描述][20201208230806908.gif_pic_center]

#### 9.保存为视频 ####

# 如何保存为视频
    animator.to_html5_video()
    #animator.save('countryflys1.mp4')

#### 10.导入视频需要下载ffmpeg ####

使用如下方法需要 先安装Anaconda3，直接在网上搜Anaconda镜像下载即可，或者官网。  
cmd中使用该命令采用镜像方式安装

conda-forge是编译的ffmpeg视频编解码库，它可直接对视频读存取

conda install -c https:*//conda.anaconda.org/menpo ffmpeg*

conda install ffmpeg -c conda-forge

安装完后记得重启才会有效果

###### conda安装提速 ######

conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/
    conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
    conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge/
    conda config --set show_channel_urls yes

### 补充： ###

使用pyecharts实现动态图

##### 1.先去pyecharts中文文档找到对应的代码，然后做如下修改 #####

data = [i for i in list(df)]#x
    datay = [df.iloc[:,i] for i in range(1,40)]#y

##### 2.建表 #####

import pyecharts.options as opts
    from pyecharts.charts import Timeline, Bar
    def get(date: int) -> Bar:
        bar = (
            Bar()
            .add_xaxis(xaxis_data=x)
            .add_yaxis(
                series_name="弹幕探讨次数",
                y_axis=datay[date],
                label_opts=opts.LabelOpts(is_show=False),
            )
            .set_global_opts(
                title_opts=opts.TitleOpts(
                    title="{}".format(data[date]), subtitle="人物被提及次数"
                ),
                # datazoom_opts=[opts.DataZoomOpts(), opts.DataZoomOpts(type_="inside"),],
                tooltip_opts=opts.TooltipOpts(
                is_show=True, trigger="axis", axis_pointer_type="shadow"
                ),
            )
        )
        return bar
    # 生成时间轴的图
    timeline = Timeline(init_opts=opts.InitOpts(width="1200px", height="600px"))
    
    for i in range(39):
        timeline.add(get(date = i),time_point=str(data[i]))
    # 1.0.0 版本的 add_schema 暂时没有补上 return self 所以只能这么写着
    timeline.add_schema(is_auto_play=True, play_interval=1000,)
    # timeline.render("wode.html")

最终得到的是一个横向柱形图。

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[https_pan.baidu.com_s_13HzYkMspIzKQRGUxndozQg]: https://pan.baidu.com/s/13HzYkMspIzKQRGUxndozQg
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ0NzYwOTEy_size_16_color_FFFFFF_t_70_pic_center 1]: https://img-blog.csdnimg.cn/20201208230431897.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ0NzYwOTEy,size_16,color_FFFFFF,t_70#pic_center
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ0NzYwOTEy_size_16_color_FFFFFF_t_70_pic_center 2]: https://img-blog.csdnimg.cn/20201208230521194.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ0NzYwOTEy,size_16,color_FFFFFF,t_70#pic_center
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ0NzYwOTEy_size_16_color_FFFFFF_t_70_pic_center 3]: https://img-blog.csdnimg.cn/20201208230726817.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3FxXzQ0NzYwOTEy,size_16,color_FFFFFF,t_70#pic_center
[20201208230806908.gif_pic_center]: https://img-blog.csdnimg.cn/20201208230806908.gif#pic_center