在matplotlib条形图上添加值标签 [英] Adding value labels on a matplotlib bar chart

问题描述

我被困在一种感觉上应该相对容易的东西上.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.我认为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.

I got stuck on something that feels like should be relatively easy. The code I bring below is a sample based on a larger project I'm working on. I saw no reason to post all the details, so please accept the data structures I bring as is.

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未成功.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. 预先感谢！

Basically, I'm creating a bar chart, and I just can figure out how to add value labels on the bars (in the center of the bar, or just above it). Been looking at samples around the web but with no success implementing on my own code. I believe the solution is either with 'text' or 'annotate', but I: a) don't know which one to use (and generally speaking, haven't figured out when to use which). b) can't see to get either to present the value labels. Would appreciate your help, my code below. Thanks in advance!

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)

推荐答案

首先freq_series.plot返回一个轴 not 一个数字，以便使我的答案更加清楚，我已更改了给定的代码将其称为ax而不是fig，以便与其他代码示例更加一致.

Firstly freq_series.plot returns an axis not a figure so to make my answer a little more clear I've changed your given code to refer to it as ax rather than fig to be more consistent with other code examples.

您可以从ax.patches成员那里获得图中绘制的钢筋的列表.然后，您可以使用此matplotlib图库示例中演示的技术来添加标签，方法是 ax.text 方法.

You can get the list of the bars produced in the plot from the ax.patches member. Then you can use the technique demonstrated in this matplotlib gallery example to add the labels using the ax.text method.

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')

这将产生一个带有标签的图，如下所示:

This produces a labeled plot that looks like:

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