如何在条形图上添加多个注释

问题描述

除了计数之外，我想将百分比值添加到我的熊猫程序中.但是，我无法这样做.我的代码如下所示，到目前为止，我可以显示计数值.有人可以帮我在每个条形显示的计数值旁边/下方添加相对百分比值吗?

  import matplotlib导入matplotlib.pyplot作为plt%matplotlib 内联plt.style.use('ggplot')将 seaborn 作为 sns 导入sns.set_style(白色")无花果= plt.figure()fig.set_figheight(5)fig.set_figwidth(10)ax = fig.add_subplot(111)计数 = [29227, 102492, 53269, 504028, 802994]y_ax =('A'，'B'，'C'，'D'，'E')y_tick = np.arange(len(y_ax))ax.barh(range(len(counts)), counts, align = "center", color = "tab:blue")ax.set_yticks(y_tick)ax.set_yticklabels(y_ax，size = 8)#用值注释条形图对于我在ax.patches中:ax.text(i.get_width()+.09, i.get_y()+.3, str(round((i.get_width()), 1)), fontsize=8)sns.despine()plt.show();

我的代码的输出如下所示.如何在显示的每个计数值旁边添加 % 值?

解决方案

使用 pandas

• 使用 pandas v1.2.4 进行测试

导入和加载数据

 将熊猫作为pd导入导入matplotlib.pyplot作为plt# 从 OP 中的值创建数据框计数= [29227、102492、53269、504028、802994]df = pd.DataFrame(data=counts, columns=['counts'], index=['A','B','C','D','E'])# 添加百分比列df ['％'] = df.counts.div(df.counts.sum()).mul(100).round(2)# 显示(df)计数 %一个29227 1.96乙 102492 6.87C 53269 3.57D 504028 33.78E 802994 53.82

使用 3.4.2 版中的 matplotlib 绘图

• 使用

  注释资源 - 来自 matplotlib v3.4.2

  • I would like to add percent values - in addition to counts - to my pandas barplot. However, I am not able to do so. My code is shown below and thus far I can get count values to display. Can somebody please help me add relative % values next to/below the count values displayed for each bar?

    import matplotlib
    import matplotlib.pyplot as plt
    %matplotlib inline
    plt.style.use('ggplot')
    
    import seaborn as sns
    sns.set_style("white")
    
    fig = plt.figure()
    fig.set_figheight(5)
    fig.set_figwidth(10)
    
    ax = fig.add_subplot(111)
    
    counts = [29227, 102492,  53269, 504028, 802994]
    
    y_ax = ('A','B','C','D','E')
    y_tick = np.arange(len(y_ax))
    
    ax.barh(range(len(counts)), counts, align = "center", color = "tab:blue")
    ax.set_yticks(y_tick)
    ax.set_yticklabels(y_ax, size = 8)
    
    #annotate bar plot with values
    for i in ax.patches:
        ax.text(i.get_width()+.09, i.get_y()+.3, str(round((i.get_width()), 1)), fontsize=8)
    
    sns.despine()
    plt.show();
    

    The output of my code is shown below. How can one add % values next to each count value displayed?

    解决方案

    With pandas

    • Tested with pandas v1.2.4

    Imports and Load Data

    import pandas as pd
    import matplotlib.pyplot as plt
    
    # create the dataframe from values in the OP
    counts = [29227, 102492,  53269, 504028, 802994]
    df = pd.DataFrame(data=counts, columns=['counts'], index=['A','B','C','D','E'])
    
    # add a percent column
    df['%'] = df.counts.div(df.counts.sum()).mul(100).round(2)
    
    # display(df)
       counts      %
    A   29227   1.96
    B  102492   6.87
    C   53269   3.57
    D  504028  33.78
    E  802994  53.82
    

    Plot use matplotlib from version 3.4.2

    • Use matplotlib.pyplot.bar_label
    • See the matplotlib: Bar Label Demo page for additional formatting options.
    • Tested with pandas v1.2.4, which is using matplotlib as the plot engine.
    • Some formatting can be done with the fmt parameter, but more sophisticated formatting should be done with the labels parameter.

    ax = df.plot(kind='barh', y='counts', figsize=(10, 5), legend=False, width=.75,
                 title='This is the plot generated by all code examples in this answer')
    
    # customize the label to include the percent
    labels = [f' {v.get_width()}\n {df.iloc[i, 1]}%' for i, v in enumerate(ax.containers[0])]
    
    # set the bar label
    ax.bar_label(ax.containers[0], labels=labels, label_type='edge', size=13)
    
    ax.spines['right'].set_visible(False)
    ax.spines['top'].set_visible(False)
    plt.show()
    

    Annotation Resources - from matplotlib v3.4.2

    • Adding value labels on a matplotlib bar chart
    • How to annotate each segment of a stacked bar chart
    • Stacked Bar Chart with Centered Labels
    • How to plot and annotate multiple data columns in a seaborn barplot
    • How to annotate a seaborn barplot with the aggregated value
    • stack bar plot in matplotlib and add label to each section
    • How to plot and annotate a grouped bar chart

    Plot use matplotlib before version 3.4.2

    # plot the dataframe
    ax = df.plot(kind='barh', y='counts', figsize=(10, 5), legend=False, width=.75)
    for i, y in enumerate(ax.patches):
    
        # get the percent label
        label_per = df.iloc[i, 1]
    
        # add the value label
        ax.text(y.get_width()+.09, y.get_y()+.3, str(round((y.get_width()), 1)), fontsize=10)
    
        # add the percent label here
        ax.text(y.get_width()+.09, y.get_y()+.1, str(f'{round((label_per), 2)}%'), fontsize=10)
    
    ax.spines['right'].set_visible(False)
    ax.spines['top'].set_visible(False)
    plt.show()
    

    Original Answer without pandas

    • Tested with matplotlib v3.3.4

    import matplotlib.pyplot as plt
    
    fig, ax = plt.subplots(figsize=(10, 5))
    
    counts = [29227, 102492,  53269, 504028, 802994]
    
    # calculate percents
    percents = [100*x/sum(counts) for x in counts]
    
    y_ax = ('A','B','C','D','E')
    y_tick = np.arange(len(y_ax))
    
    ax.barh(range(len(counts)), counts, align = "center", color = "tab:blue")
    ax.set_yticks(y_tick)
    ax.set_yticklabels(y_ax, size = 8)
    
    #annotate bar plot with values
    for i, y in enumerate(ax.patches):
        label_per = percents[i]
        ax.text(y.get_width()+.09, y.get_y()+.3, str(round((y.get_width()), 1)), fontsize=10)
        # add the percent label here
        # ax.text(y.get_width()+.09, y.get_y()+.3, str(round((label_per), 2)), ha='right', va='center', fontsize=10)
        ax.text(y.get_width()+.09, y.get_y()+.1, str(f'{round((label_per), 2)}%'), fontsize=10)
    
    ax.spines['right'].set_visible(False)
    ax.spines['top'].set_visible(False)
    plt.show()
    

    • You can play with the positioning.
    • Other formatting options mentioned by JohanC
    • Print both parts of the text in one string with a \n in between to get a "natural" line spacing:
    • str(f'{round((y.get_width()), 1)}\n{round((label_per), 2)}%')
    • ax.text(..., va='center') to vertically center and be able to use a slightly larger font.
    • ax.set_xlim(0, max(counts) * 1.18) to get a bit more space for the text.
    • Start each line of text with a space to get a natural "horizontal" padding.
    • str(f' {round((label_per), 2)}%'), note the space before {.
    • y.get_width()+.09 is extremely close to y.get_width() when these values are in the tens of thousands.

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