关于python：在matplotlib条形图上添加值标签


Adding value labels on a matplotlib bar chart

我陷入一种感觉应该相对容易的事情上。 我在下面提供的代码是基于我正在从事的一个较大项目的示例。 我没有理由发布所有详细信息，因此请原样接受我带来的数据结构。

基本上，我正在创建一个条形图，我可以弄清楚如何在条形图上(在条形图的中心或上方)添加值标签。 一直在网上查看示例，但是在我自己的代码上实现没有成功。 我相信解决方案是使用"文本"或"注释"，但是我：
a)不知道使用哪个(通常来说，还没有弄清楚何时使用哪个)。
b)看不到要显示值标签。
感谢您的帮助，下面是我的代码。
提前致谢！

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import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
pd.set_option('display.mpl_style', 'default')
%matplotlib inline

# Bring some raw data.
frequencies = [6, 16, 75, 160, 244, 260, 145, 73, 16, 4, 1]

# In my original code I create a series and run on that,
# so for consistency I create a series from the list.
freq_series = pd.Series.from_array(frequencies)

x_labels = [108300.0, 110540.0, 112780.0, 115020.0, 117260.0, 119500.0,
            121740.0, 123980.0, 126220.0, 128460.0, 130700.0]

# Plot the figure.
plt.figure(figsize=(12, 8))
fig = freq_series.plot(kind='bar')
fig.set_title('Amount Frequency')
fig.set_xlabel('Amount ($)')
fig.set_ylabel('Frequency')
fig.set_xticklabels(x_labels)
相关讨论

首先，freq_series.plot返回的轴不是数字，所以为了使我的回答更加清楚，我将您给定的代码更改为将其称为ax而不是fig，以使其与其他代码示例更加一致。

您可以从ax.patches成员获取在图中生成的条形图的列表。然后，您可以使用matplotlib图库示例中演示的技术，使用ax.text方法添加标签。

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import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

# Bring some raw data.
frequencies = [6, 16, 75, 160, 244, 260, 145, 73, 16, 4, 1]
# In my original code I create a series and run on that,
# so for consistency I create a series from the list.
freq_series = pd.Series.from_array(frequencies)

x_labels = [108300.0, 110540.0, 112780.0, 115020.0, 117260.0, 119500.0,
            121740.0, 123980.0, 126220.0, 128460.0, 130700.0]

# Plot the figure.
plt.figure(figsize=(12, 8))
ax = freq_series.plot(kind='bar')
ax.set_title('Amount Frequency')
ax.set_xlabel('Amount ($)')
ax.set_ylabel('Frequency')
ax.set_xticklabels(x_labels)

rects = ax.patches

# Make some labels.
labels = ["label%d" % i for i in xrange(len(rects))]

for rect, label in zip(rects, labels):
    height = rect.get_height()
    ax.text(rect.get_x() + rect.get_width() / 2, height + 5, label,
            ha='center', va='bottom')

这将产生一个标记的图，如下所示：

enter image description here

相关讨论

基于对另一个问题的回答中提到的功能，我发现了一种非常普遍适用的解决方案，用于在条形图上放置标签。

不幸的是，其他解决方案在很多情况下不起作用，因为标签和条之间的间距要么以条的绝对单位给出，要么由条的高度缩放。前者仅适用于狭窄范围的值，而后者在一个绘图中给出的间距不一致。两者均不能很好地使用对数轴。

我提出的解决方案独立于比例尺(即小数和大数)工作，甚至可以正确放置负值标签和对数比例尺，因为它使用可视单位points进行偏移。

在这种情况下，我添加了一个负数来展示标签的正确位置。

每个条形的高度值都用作其标签。其他标签可轻松与Simon的for rect, label in zip(rects, labels)代码段一起使用。

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import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

# Bring some raw data.
frequencies = [6, -16, 75, 160, 244, 260, 145, 73, 16, 4, 1]

# In my original code I create a series and run on that,
# so for consistency I create a series from the list.
freq_series = pd.Series.from_array(frequencies)

x_labels = [108300.0, 110540.0, 112780.0, 115020.0, 117260.0, 119500.0,
            121740.0, 123980.0, 126220.0, 128460.0, 130700.0]

# Plot the figure.
plt.figure(figsize=(12, 8))
ax = freq_series.plot(kind='bar')
ax.set_title('Amount Frequency')
ax.set_xlabel('Amount ($)')
ax.set_ylabel('Frequency')
ax.set_xticklabels(x_labels)


def add_value_labels(ax, spacing=5):
   """Add labels to the end of each bar in a bar chart.

    Arguments:
        ax (matplotlib.axes.Axes): The matplotlib object containing the axes
            of the plot to annotate.
        spacing (int): The distance between the labels and the bars.
   """

    # For each bar: Place a label
    for rect in ax.patches:
        # Get X and Y placement of label from rect.
        y_value = rect.get_height()
        x_value = rect.get_x() + rect.get_width() / 2

        # Number of points between bar and label. Change to your liking.
        space = spacing
        # Vertical alignment for positive values
        va = 'bottom'

        # If value of bar is negative: Place label below bar
        if y_value < 0:
            # Invert space to place label below
            space *= -1
            # Vertically align label at top
            va = 'top'

        # Use Y value as label and format number with one decimal place
        label ="{:.1f}".format(y_value)

        # Create annotation
        ax.annotate(
            label,                      # Use `label` as label
            (x_value, y_value),         # Place label at end of the bar
            xytext=(0, space),          # Vertically shift label by `space`
            textcoords="offset points", # Interpret `xytext` as offset in points
            ha='center',                # Horizontally center label
            va=va)                      # Vertically align label differently for
                                        # positive and negative values.


# Call the function above. All the magic happens there.
add_value_labels(ax)

plt.savefig("image.png")

编辑：正如barnhillec所建议的，我已经提取了函数中的相关功能。

这将产生以下输出：

Bar chart with automatically placed labels on each bar

使用对数标度(以及对输入数据进行一些调整以展示对数标度)，结果如下：

Bar chart with logarithmic scale with automatically placed labels on each bar

相关讨论

在上述答案(很棒！)的基础上，我们还可以通过一些调整就可以制作出水平条形图：

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# Bring some raw data.
frequencies = [6, -16, 75, 160, 244, 260, 145, 73, 16, 4, 1]

freq_series = pd.Series(frequencies)

y_labels = [108300.0, 110540.0, 112780.0, 115020.0, 117260.0, 119500.0,
            121740.0, 123980.0, 126220.0, 128460.0, 130700.0]

# Plot the figure.
plt.figure(figsize=(12, 8))
ax = freq_series.plot(kind='barh')
ax.set_title('Amount Frequency')
ax.set_xlabel('Frequency')
ax.set_ylabel('Amount ($)')
ax.set_yticklabels(y_labels)
ax.set_xlim(-40, 300) # expand xlim to make labels easier to read

rects = ax.patches

# For each bar: Place a label
for rect in rects:
    # Get X and Y placement of label from rect.
    x_value = rect.get_width()
    y_value = rect.get_y() + rect.get_height() / 2

    # Number of points between bar and label. Change to your liking.
    space = 5
    # Vertical alignment for positive values
    ha = 'left'

    # If value of bar is negative: Place label left of bar
    if x_value < 0:
        # Invert space to place label to the left
        space *= -1
        # Horizontally align label at right
        ha = 'right'

    # Use X value as label and format number with one decimal place
    label ="{:.1f}".format(x_value)

    # Create annotation
    plt.annotate(
        label,                      # Use `label` as label
        (x_value, y_value),         # Place label at end of the bar
        xytext=(space, 0),          # Horizontally shift label by `space`
        textcoords="offset points", # Interpret `xytext` as offset in points
        va='center',                # Vertically center label
        ha=ha)                      # Horizontally align label differently for
                                    # positive and negative values.

plt.savefig("image.png")

horizontal bar plot with annotations

相关讨论

如果只想在条形上方添加数据点，则可以使用以下方法轻松完成此操作：

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 for i in range(len(frequencies)): # your number of bars
    plt.text(x = x_values[i]-0.25, #takes your x values as horizontal positioning argument
    y = y_values[i]+1, #takes your y values as vertical positioning argument
    s = data_labels[i], # the labels you want to add to the data
    size = 9) # font size of datalabels