Changing color scale in seaborn bar plot

Question

I would like to use seaborn bar plot for my data with a color scale according to the values in the Y-axis. For example, from this image, color changes from left to right according to a color palette:

But what I actually wanted is this same color scheme but in "vertical" instead of "horizontal". Is this possible? I've searched and tried to set the hue parameter to the Y-axis but it doesn't seem to work, how can I do it?

Thanks in advance.

Answer 1

Here a solution:

import numpy as np, matplotlib.pyplot as plt, seaborn as sns sns.set(style="whitegrid", color_codes=True)  titanic = sns.load_dataset("titanic") data = titanic.groupby("deck").size()   # data underlying bar plot in question  pal = sns.color_palette("Greens_d", len(data)) rank = data.argsort().argsort()   # http://stackoverflow.com/a/6266510/1628638 sns.barplot(x=data.index, y=data, palette=np.array(pal[::-1])[rank])  plt.show() 

Here the output:

Note: the code currently assigns different (adjacent) colors to bars with identical height. (Not a problem in the sample plot.) While it would be nicer to use the same color for identical-height bars, the resulting code would likely make the basic idea less clear.

Answer 2

This solution uses the values as indices into the color palette; so that similar values get similar colors:

import seaborn as sns import numpy as np   def colors_from_values(values, palette_name):     # normalize the values to range [0, 1]     normalized = (values - min(values)) / (max(values) - min(values))     # convert to indices     indices = np.round(normalized * (len(values) - 1)).astype(np.int32)     # use the indices to get the colors     palette = sns.color_palette(palette_name, len(values))     return np.array(palette).take(indices, axis=0)   x = np.arange(10) y = np.random.random(10) sns.barplot(x, y, palette=colors_from_values(y, "YlOrRd")) 

Resulting in: