Question

我被困在一些感觉应该相对容易的事情上。我下面的代码是基于我正在研究的更大项目的示例。我没有理由发布所有细节，所以请接受我带来的数据结构。

基本上，我正在创建一个条形图，我只想弄清楚如何在条形图上添加值标签（在条形图的中心，或者在它上面）。一直在寻找网络上的样本，但没有成功实现我自己的代码。我相信解决方案是'text'或'annotate'，但我： a）不知道使用哪一个（一般来说，还没弄清楚何时使用哪个）。 b）无法看到要么呈现价值标签。非常感谢您的帮助，我的代码如下。提前谢谢！

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)

Answer 1

首先freq_series.plot会返回一个轴而不是一个数字，以便让我的回答更加清晰我已经更改了您的给定代码，将其称为ax而不是fig与其他代码示例更加一致。

您可以从ax.patches成员获取图表中生成的条形图列表。然后，您可以使用this matplotlib gallery example中演示的技术使用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')

这会生成标签图，如下所示：

enter image description here

Answer 2

根据this answer to another question中提到的功能，我找到了一种非常普遍适用的解决方案，可以在条形图上放置标签。

遗憾的是，其他解决方案在许多情况下都不起作用，因为标签和条之间的间距为given in absolute units of the bars或scaled by the height of the bar。前者仅适用于较窄范围的值，后者在一个图中给出不一致的间距。两者都不适用于对数轴。

我建议的解决方案独立于比例（即小数字和大数字），甚至可以正确地为负值和对数比例放置标签，因为它使用视觉单位points进行偏移。

我添加了一个负数，以便在这种情况下展示标签的正确位置。

每个条形的高度值用作它的标签。其他标签可以轻松地与Simon's for rect, label in zip(rects, labels) snippet一起使用。

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：我已根据barnhillec的建议在函数中提取了相关功能。

这会产生以下输出：

使用对数刻度（并对输入数据进行一些调整以显示对数缩放），结果如下：

Answer 3

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：


    disabledDate = (current) =>{         
            // Can not select days after today and before start Date
            const start = moment('2020-01-01','YYYY-MM-DD');        
            return  current< start || current>moment();
     }

通过分别指定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]), ha='center', va='bottom') plt.show()和'center'的水平和垂直对齐，可以得到居中的注释。

Answer 4

以上述（很好！）的答案为基础，我们还可以通过一些调整来制作水平条形图：

# 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")

horizontal bar plot with annotations

Answer 5

来自`matplotlib v3.4.2`

使用matplotlib.pyplot.bar_label
- 使用参数 label_type 设置的默认标签位置为 'edge'。要将标签居中置于条形中间，请使用 'center'
有关其他格式选项，请参阅 matplotlib: Bar Label Demo 页面。
使用 pandas v1.2.4 进行测试，它使用 matplotlib 作为绘图引擎。
ax.containers 是 list 的 BarContainer artists
- 对于单级条形图，它是一个 len 1 的列表，因此使用 [0]。
- 对于分组和堆叠条形图，list 中的对象会更多
- 参见 How to annotate each segment of a stacked bar chart 或 Stacked Bar Chart with Centered Labels。
- 有关分组条形示例，请参阅 How to plot and annotate multiple data columns in a seaborn barplot
可以使用 fmt 参数完成简单的标签格式设置，如演示示例和 How to annotate a seaborn barplot with the aggregated value 中所示。
更复杂的标签格式应使用 label 参数，如演示示例和 stack bar plot in matplotlib and add label to each section、How to add multiple annotations to a barplot 或 How to plot a horizontal stacked bar with annotations 所示。

import pandas as pd

# dataframe using frequencies and x_labels from the OP
df = pd.DataFrame({'Frequency': frequencies}, index=x_labels)

# display(df)
          Frequency
108300.0          6
110540.0         16
112780.0         75
115020.0        160
117260.0        244

# plot
ax = df.plot(kind='bar', figsize=(12, 8), title='Amount Frequency',
             xlabel='Amount ($)', ylabel='Frequency', legend=False)

# annotate
ax.bar_label(ax.containers[0], label_type='edge')

# pad the spacing between the number and the edge of the figure
ax.margins(y=0.1)

Answer 6

如果您只想在条形上方添加数据点，则可以轻松地做到这一点：

 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

在matplotlib条形图上添加值标签

6 个答案:

来自`matplotlib v3.4.2`

在matplotlib条形图上添加值标签

6 个答案:

来自matplotlib v3.4.2

来自`matplotlib v3.4.2`