如何给 pandas /matplotlib条形图自定义颜色 [英] How to give a pandas/matplotlib bar graph custom colors

问题描述

我刚刚开始使用pandas/matplotlib代替Excel来生成堆积的条形图.我遇到了问题

I just started using pandas/matplotlib as a replacement for Excel to generate stacked bar charts. I am running into an issue

(1)在默认的颜色表中只有5种颜色，因此，如果我有5种以上的类别，则颜色会重复.如何指定更多颜色?理想情况下，是具有开始颜色和结束颜色的渐变，以及动态生成介于两者之间的n种颜色的方法吗?

(1) there are only 5 colors in the default colormap, so if I have more than 5 categories then the colors repeat. How can I specify more colors? Ideally, a gradient with a start color and an end color, and a way to dynamically generate n colors in between?

(2)颜色在视觉上不太令人满意.如何指定一组自定义的n种颜色?或者，渐变也可以.

(2) the colors are not very visually pleasing. How do I specify a custom set of n colors? Or, a gradient would also work.

以下示例说明了以上两点:

An example which illustrates both of the above points is below:

  4 from matplotlib import pyplot
  5 from pandas import *
  6 import random
  7 
  8 x = [{i:random.randint(1,5)} for i in range(10)]
  9 df = DataFrame(x)
 10 
 11 df.plot(kind='bar', stacked=True)

输出为:

推荐答案

您可以将color选项作为列表直接指定给plot函数.

You can specify the color option as a list directly to the plot function.

from matplotlib import pyplot as plt
from itertools import cycle, islice
import pandas, numpy as np  # I find np.random.randint to be better

# Make the data
x = [{i:np.random.randint(1,5)} for i in range(10)]
df = pandas.DataFrame(x)

# Make a list by cycling through the colors you care about
# to match the length of your data.
my_colors = list(islice(cycle(['b', 'r', 'g', 'y', 'k']), None, len(df)))

# Specify this list of colors as the `color` option to `plot`.
df.plot(kind='bar', stacked=True, color=my_colors)

要定义您自己的自定义列表，您可以执行以下一些操作，或者只是查找Matplotlib技术以根据其RGB值定义颜色项，等等.这样做可能会变得很复杂. /p>

To define your own custom list, you can do a few of the following, or just look up the Matplotlib techniques for defining a color item by its RGB values, etc. You can get as complicated as you want with this.

my_colors = ['g', 'b']*5 # <-- this concatenates the list to itself 5 times.
my_colors = [(0.5,0.4,0.5), (0.75, 0.75, 0.25)]*5 # <-- make two custom RGBs and repeat/alternate them over all the bar elements.
my_colors = [(x/10.0, x/20.0, 0.75) for x in range(len(df))] # <-- Quick gradient example along the Red/Green dimensions.

最后一个示例为我生成了以下简单的颜色渐变:

The last example yields the follow simple gradient of colors for me:

我玩的时间还不够长，无法弄清楚如何强制图例使用已定义的颜色，但是我敢肯定您可以做到.

I didn't play with it long enough to figure out how to force the legend to pick up the defined colors, but I'm sure you can do it.

但是，通常，很大的建议是直接使用Matplotlib中的函数.从Pandas调用它们是可以的，但是我发现您有更好的选择和性能，直接从Matplotlib调用它们.

In general, though, a big piece of advice is to just use the functions from Matplotlib directly. Calling them from Pandas is OK, but I find you get better options and performance calling them straight from Matplotlib.

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