How to give a pandas/matplotlib bar graph custom colors

Question

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

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

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)

And the output is this:

enter image description here

ely · Accepted Answer · 2012-12-20 13:17:50Z

162

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)

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.

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

enter image description here

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.

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.

edited Dec 20, 2012 at 13:17

answered Aug 13, 2012 at 3:39

ely

77.8k36 gold badges158 silver badges234 bronze badges

Sign up to request clarification or add additional context in comments.

11 Comments

vkontori Over a year ago

Minor bug: my_colors = [cycle(['b', 'r', 'g', 'y', 'k']).next() for i in range(len(df))] will give 'b' every time in python 2.7. You should use list(islice(cycle(['b', 'r', 'g', 'y', 'k']), None, len(df))) instead.

ely Over a year ago

Thanks, I probably wouldn't have caught that. Another option is to create the cycle first, then just call its next function inside the comprehension.

vkontori Over a year ago

Yup. it = cycle(['b', 'r', 'g', 'y', 'k']); my_colors=[next(it) for i in xrange(len(df))] would cut it as well...

kakyo Over a year ago

With pandas and matplotlib installed today, the code above generates nothing for me, although it runs.

lys Over a year ago

Last gradient cmd yields a ValueError (out of range) ValueError: RGBA values should be within 0-1 range need to adjust it for other data

|

Alexandre · Accepted Answer · 2016-08-01 22:50:51Z

64

I found the easiest way is to use the colormap parameter in .plot() with one of the preset color gradients:

df.plot(kind='bar', stacked=True, colormap='Paired')

You can find a large list of preset colormaps here.

answered Aug 1, 2016 at 22:50

Alexandre

2,1314 gold badges21 silver badges24 bronze badges

2 Comments

tsando Over a year ago

in my case this only yields one color across all the bars

qpaycm Over a year ago

I found these colormaps lists useful matplotlib.org/examples/color/colormaps_reference.html gallantlab.github.io/colormaps.html

cmaher · Accepted Answer · 2020-02-07 02:25:31Z

24

For a more detailed answer on creating your own colormaps, I highly suggest visiting this page

If that answer is too much work, you can quickly make your own list of colors and pass them to the color parameter. All the colormaps are in the cm matplotlib module. Let's get a list of 30 RGB (plus alpha) color values from the reversed inferno colormap. To do so, first get the colormap and then pass it a sequence of values between 0 and 1. Here, we use np.linspace to create 30 equally-spaced values between .4 and .8 that represent that portion of the colormap.

from matplotlib import cm
color = cm.inferno_r(np.linspace(.4, .8, 30))
color

array([[ 0.865006,  0.316822,  0.226055,  1.      ],
       [ 0.851384,  0.30226 ,  0.239636,  1.      ],
       [ 0.832299,  0.283913,  0.257383,  1.      ],
       [ 0.817341,  0.270954,  0.27039 ,  1.      ],
       [ 0.796607,  0.254728,  0.287264,  1.      ],
       [ 0.775059,  0.239667,  0.303526,  1.      ],
       [ 0.758422,  0.229097,  0.315266,  1.      ],
       [ 0.735683,  0.215906,  0.330245,  1.      ],
       .....

Then we can use this to plot, using the data from the original post:

import random
x = [{i: random.randint(1, 5)} for i in range(30)]
df = pd.DataFrame(x)
df.plot(kind='bar', stacked=True, color=color, legend=False, figsize=(12, 4))

edited Feb 7, 2020 at 2:25

cmaher

5,2641 gold badge24 silver badges34 bronze badges

answered Nov 6, 2017 at 22:30

Ted Petrou

62.4k19 gold badges139 silver badges139 bronze badges

2 Comments

tsando Over a year ago

Here's the documentation to other color maps apart from inferno_r: matplotlib.org/examples/color/colormaps_reference.html

FaCoffee Over a year ago

I followed this snippet but my color array always has the same values.

Collectives™ on Stack Overflow

How to give a pandas/matplotlib bar graph custom colors

3 Answers 3

11 Comments

2 Comments

2 Comments

Your Answer

Linked

Hot Network Questions

Collectives™ on Stack Overflow

3 Answers 3

11 Comments

2 Comments

2 Comments

Your Answer

Sign up or log in

Post as a guest

Linked

Related