在matplotlib条形图上添加值标签

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，并且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，但在我自己的代码上实现未成功。我认为解决方案是使用“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！

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)

首先freq_series.plot返回一个轴而不是一个数字，以便使我的回答更加清楚。我已更改了给定的代码以使其引用，ax而不是fig与其他代码示例更加一致。

您可以从该ax.patches成员处获得该图中所产生的钢筋的列表。然后，您可以使用此matplotlib库示例中演示的技术来使用ax.text方法添加标签。

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：

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。

，其他解决方案不幸的是没有工作，在很多情况下是因为标签栏之间的间距或者在酒吧的绝对单位给出或由条的高度成比例。前者仅适用于较小范围的值，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。

我提出的解决方案与比例无关（即，无论大小），甚至可以正确地为负值和对数比例放置标签，因为它使用了可视单位points作为偏移量。

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。其他标签可以轻松地与 Simon的for rect, label in zip(rects, labels)代码段。

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：

使用对数标度（以及对输入数据进行一些调整以显示对数标度），结果如下：

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：

# 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")

如果只想标记条形上方的数据点，则可以使用plt.annotate（）

我的代码：

import numpy as np
import matplotlib.pyplot as plt

n = [1,2,3,4,5,]
s = [i**2 for i in n]
line = plt.bar(n,s)
plt.xlabel('Number')
plt.ylabel("Square")

for i in range(len(s)):
plt.annotate(str(s[i]), xy=(n[i],s[i]))

plt.show()

好吧，带有多个字符的文本可能会稍微偏离中心显示。但这可以通过根据文本的大小略微减小xy参数中的x坐标来克服

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：

 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