python - 子图中每个标记中变量的数据值

Question

我正在开发以下函数:extract_name_value() 生成一个采用 Python 中 Pandas DataFrame 值的步骤图，现在它工作正常，但我想在每个标记中添加变量 points_axisyvalue 或 values_list 的值:Script Here
我尝试使用以下示例:Data value at each marker , Matplotlib scatter plot with different text at each data point或 How to put individual tags for a matplotlib scatter plot? ，这将是我想要的东西；我什至尝试使用 plt.annotate() ，但是值的数据并没有按照我想要的方式出现，而且我认为它会掩盖图形很多并且不能很好地欣赏。下面我放了我使用 plt.annotate() 的代码:

    # Function to extract the Name and Value attributes
    def extract_name_value(signals_df, rootXML):
        # print(signals_df)
        names_list = [name for name in signals_df['Name'].unique()]
        num_names_list = len(names_list)
        num_axisx = len(signals_df["Name"])
        values_list = [value for pos, value in enumerate(signals_df["Value"])]
        print(values_list)
        points_axisy = signals_df["Value"]
        print(len(points_axisy))

        colors = ['b', 'g', 'r', 'c', 'm', 'y']
    
        # Creation Graphic
        fig, ax = plt.subplots(nrows=num_names_list, figsize=(20, 30), sharex=True)
        plt.suptitle(f'File XML: {rootXML}', fontsize=16,         fontweight='bold', color='SteelBlue', position=(0.75, 0.95))
        plt.xticks(np.arange(-1, num_axisx), color='SteelBlue', fontweight='bold')
        labels = ['value: {0}'.format(j) for j in values_list]
        print(labels)
        i = 1
        for pos, name in enumerate(names_list):
            # get data
            data = signals_df[signals_df["Name"] == name]["Value"]
            print(data)
            # get color
            j = random.randint(0, len(colors) - 1)
            # get plots by index = pos
            x = np.hstack([-1, data.index.values, len(signals_df) - 1])
            y = np.hstack([0, data.values, data.iloc[-1]])
            ax[pos].plot(x, y, drawstyle='steps-post', marker='o', color=colors[j], linewidth=3)
            ax[pos].set_ylabel(name, fontsize=8, fontweight='bold', color='SteelBlue', rotation=30, labelpad=35)
            ax[pos].yaxis.set_major_formatter(ticker.FormatStrFormatter('%0.1f'))
             ax[pos].yaxis.set_tick_params(labelsize=6)
             ax[pos].grid(alpha=0.4)
             i += 1

             for label, x, y in zip(labels, x, y):
             plt.annotate(label, xy=(x, y), xytext=(-20, 20), textcoords='offset points', ha='right', va='bottom', bbox=dict(boxstyle='round,pad=0.5', fc='yellow', alpha=0.5),
                    arrowprops=dict(arrowstyle='->', connectionstyle='arc3,rad=0'))

        plt.show()

我得到的是拼接的和在不同位置的注释。
但是，我的代码需要在每个点显示每个值吗？
我也一直在尝试使用 Matplotlib 引用中的代码，但无法完成:Marker Reference .非常感谢您，任何评论都有帮助。

Answer 1

您可以使用 plt.annotate循环运行以解决您的问题。
我随机生成了一些数据并将其绘制为单个图。你可以在子图中做同样的事情，功能是一样的。

# sample data points for the plot
x=np.arange(1,10)
y=np.linspace(20,40,9)

plt.figure(figsize=[15,5],dpi=200)
plt.plot(x,y,drawstyle='steps-post', marker='o')
# using annotate function to show the changepoints in a loop 
for i in range(len(x)):
    # I rounded the y values as string and used the same x and y coords as the locations
    # next we can give a constant offset points to offset the annotation from each value
    # here I used (-20,20) as the offset values
    plt.annotate(f"{str(round((y[i])))}",(x[i],y[i]),xycoords='data',
                 xytext=(-20,20), textcoords='offset points',color="r",fontsize=12,
                 arrowprops=dict(arrowstyle="->", color='black'))

如果您不想要箭头，可以移除箭头 Prop 。

已编辑
我用了 example1.xml在您的 GitHub 存储库中创建文件并稍微编辑该函数。我所做的只是在您的函数中添加一个循环和一个 if-else 条件。

# Initial part is same as yours
names_list = [name for name in signals_df['Name'].unique()]
num_names_list = len(names_list)
num_axisx = len(signals_df["Name"])
values_list = [value for pos, value in enumerate(signals_df["Value"])]
points_axisy = signals_df["Value"]
colors = ['b', 'g', 'r', 'c', 'm', 'y']
# start new figure
plt.figure(figsize=[20,28],dpi=200)
#start a loop with the subplots
for i in range(len(names_list)):
    # subplot has 14 rows, 1 column and the i+1 represents the i'th plot
    plt.subplot(num_names_list,1,i+1)
    # choose color
    col=np.random.randint(0, len(colors) - 1)
    # get the locations of the values with the similar name in your list
    locs=signals_df['Name']==names_list[i]
    # get the values in those locations
    data=signals_df['Value'][locs]
    # arrange the x and y coordinates
    x = np.hstack([-1, data.index.values, len(signals_df) - 1])
    y = np.hstack([0, data.values, data.iloc[-1]])
    # plot the values as usual
    plt.plot(x, y, drawstyle='steps-post', marker='o', color=colors[col], linewidth=3)
    plt.ylabel(names_list[i], fontsize=8, fontweight='bold', color='SteelBlue', rotation=30, labelpad=35)
    plt.grid(alpha=0.4)
    # this loop is for annotating the values 
    for j in range(len(x)):
        # I found it is better to alternate the position of the annotations 
        # so that they wont overlap for the adjacent values
        if j%2==0:
            # In this condition the xytext position is (-20,20)
            # this posts the annotation box over the plot value
            plt.annotate(f"Val={round((y[j]))}",(x[j],y[j]),xycoords='data',
                         xytext=(-20,20), textcoords='offset points',color="r",fontsize=8,
                         arrowprops=dict(arrowstyle="->", color='black'),
                        bbox=dict(boxstyle='round', pad=0.5, fc='yellow', alpha=0.5))
        else:
            # In this condition the xytext position is (-20,-20)
            # this posts the annotation box under the plot value
            plt.annotate(f"Val={round((y[j]))}",(x[j],y[j]),xycoords='data',
                 xytext=(-20,-20), textcoords='offset points',color="r",fontsize=8,
                 arrowprops=dict(arrowstyle="->", color='black'),
                         bbox=dict(boxstyle='round', pad=0.5, fc='yellow', alpha=0.5))

新函数结果

我希望它有用。