基于值的颜色matplotlib条形图 [英] Color matplotlib bar chart based on value

问题描述

是否有一种方法可以根据条形图的颜色为条形图的条形着色.例如:

Is there a way to color the bars of a barchart based on the bar's value. For example:

- values below -0.5: red
- values between -0.5 to 0: green
- values between 0 to 08: blue
- etc

我发现了一些条形着色的基本示例，但没有一个可以满足值范围的颜色，例如上述示例.

I have found some basic examples of bar coloring but nothing which can cater for value ranges, such as the above examples.

更新:

谢谢kikocorreoso的建议.根据您的示例，当两个轴都是数字时，这非常有用.但是对于我来说，我的原始数据结构是pandas数据框.然后，我使用df.stack()并绘制结果.这意味着数据框的行/列成为图的x轴，数据框的单元格为Y轴(条形).

Thank you kikocorreoso for your suggestion. This works great when both axes are numbers as per your example. However in my case my original data structure is a pandas dataframe. I then use df.stack() and plot the result. This means that the dataframes rows/columns become the x axis of the plot and the dataframe cells are the Y axis (bars).

我已经按照您的示例尝试了遮罩，但是当Y轴为数字而X轴为名称时，它似乎不起作用.例如:

I have tried masking as per your example but it doesn't seem to work when the Y axis are numbers and the X axis are names. eg:

     col1    col2   col3   col4
 row1 1       2      3      4
 row2 5       6      7      8
 row3 9       10     11     12
 row4 13      14     15     16

以上数据框需要绘制为条形图，其中行/列组合形成x轴.每个单元格值将是一个条形图.最终，按照原始问题为条形着色.谢谢

The above dataframe needs to be plotted as a barchart with the row/column combinations forming the x-axis. Each cell value will be a bar. And ultimately, coloring the bars as per the original question. Thanks

推荐答案

您可以对数据集使用掩码.一个基本的示例如下:

You could use masks for your datasets. A basic example could be the following:

import numpy as np
import matplotlib.pyplot as plt

x = np.arange(10)
y = np.arange(10) * 0.1

mask1 = y < 0.5
mask2 = y >= 0.5

plt.bar(x[mask1], y[mask1], color = 'red')
plt.bar(x[mask2], y[mask2], color = 'blue')
plt.show()

结果应为:

更新:

在您更新问题时，我也会更新代码.对于您的简单情况，如果我理解正确，则可以进行以下(丑陋的)破解:

As you updated your question I update the code. For your simple case, and if I understood correctly, you could do the following (ugly) hack:

import pandas as pd

df = pd.DataFrame({'col1':[1,2,3], 'col2':[4,5,6]}, 
                  index = ['row1','row2','row3'])

dfstacked = df.stack()

mask = dfstacked <= 3

colors = np.array(['b']*len(dfstacked))
colors[mask.values] = 'r'

dfstacked.plot(kind = 'bar', rot = 45, color = colors)
plt.show()

或者使用更多的 OO解决方案.

代码简要说明:

• 我为我的红色列创建一个蒙版
• 我创建了一个颜色数组
• 更改颜色数组，以便将其他颜色用于蒙版值
• 由于dfstacked数据帧具有MultiIndex，因此刻度没有很好地打印出来，因此我使用rot关键字来旋转它们.如果要使其自动化以获取良好的绘图，可以在plt.show()之前使用plt.tight_layout().

• I create a mask for my red columns
• I create an array of colors
• Change the the array of colors in order to use other color for my masked values
• As the dfstacked dataframe has a MultiIndex the ticks are not well printed so I use the rot keyword to rotate them. If you want to automate it in order to get a nice plot you can use plt.tight_layout() before plt.show().

希望对您有帮助.

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