如何为 Pandas/matplotlib 条形图提供自定义颜色 [英] How to give a pandas/matplotlib bar graph custom colors

问题描述

我刚开始使用 pandas/matplotlib 作为 Excel 的替代品来生成堆积条形图.我遇到了一个问题

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

(1) 默认颜色图中只有 5 种颜色，所以如果我有 5 个以上的类别，那么颜色会重复.如何指定更多颜色?理想情况下，具有起始颜色和结束颜色的渐变，以及在两者之间动态生成 n 种颜色的方法?

(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) 颜色不太美观.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.

说明上述两点的示例如下:

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)

输出是这样的:

推荐答案

您可以将 color 选项指定为一个列表，直接用于 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 技术以通过其 RGB 值等定义颜色项.您可以根据需要变得尽可能复杂.

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:

我玩的时间不够长，无法弄清楚如何强制图例选择定义的颜色，但我相信您可以做到.

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.

不过，总的来说，一个重要的建议是直接使用 Matplotlib 中的函数.从 Pandas 调用它们是可以的，但我发现直接从 Matplotlib 调用它们可以获得更好的选择和性能.

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.

这篇关于如何为 Pandas/matplotlib 条形图提供自定义颜色的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！