在 barh 中更改 colors（堆叠）

Question

I have one table with regions (y axes) and in x values. Each region has two bars. I would like to change colors. I would like that each little bar in barh has a different color. I have this code where colors repeat: For example after pink I would like another color, not red again.It is possible to change the colors scale? using for example "tab10" Furthemore, it is possible to get legend where each color outline one year (2010,2011,2012,2013,2014,2015,2016,2017,2018,2019)

import pandas as pd
import matplotlib.pyplot as plt
import matplotlib

matplotlib.style.use('ggplot')

plotdata = pd.DataFrame({
    "2010_y":[0.63,0.56,0.89,0.94,0.68,0.63,0.34,0.54,0.77,0.77,0.86,0.42,0.49,0.70,1.12,1.10,0.30,0.67,0.30,0.23],
    "2011_y":[1.10,0.54,0.94,0.81,0.80,0.87,0.90,0.99,0.53,0.78,0.98,0.99,0.87,1.09,1.18,0.89,0.89,0.70,1.05,0.86],
    "2012_y":[1.39,0.97,0.98,0.99,0.95,1.10,1.07,1.10,1.02,1.05,0.97,0.92,0.94,0.91,0.85,1.22,1.24,1.08,1.08,1.01],
    "2013_m":[1.86,1.34,1.12,1.25,1.26,1.08,1.31,1.58,1.22,1.26,1.37,1.14,1.23,1.00,1.13,1.49,1.14,1.37,1.25,1.23],
    "2014_m":[1.59,1.04,1.03,1.10,1.44,1.43,1.33,1.81,1.56,1.22,1.08,1.36,1.11,0.87,1.10,0.68,1.31,1.26,1.25,1.61],
    "2015_m":[0.71,1.14,1.18,0.99,0.87,0.74,0.91,0.57,0.79,1.09,1.16,0.89,1.15,0.98,1.24,0.75,0.85,0.83,1.02,0.71],
    "2016_m":[0.67,1.22,1.00,0.96,0.97,0.96,0.95,0.79,1.06,1.04,0.83,1.06,1.07,0.98,0.66,1.06,0.99,1.13,1.03,1.05],
    "2017_m":[0.68,0.84,0.73,0.73,0.79,0.98,0.80,0.54,0.85,0.91,0.55,0.65,0.86,0.71,0.71,0.77,0.95,0.80,0.81,0.87],
    "2018_m":[0.74,1.28,1.21,1.13,0.99,1.00,1.21,0.97,1.07,0.91,1.38,1.34,1.25,1.65,1.28,0.97,1.11,1.09,1.20,1.13],
    "2019_m":[0.63,1.07,0.92,1.10,1.24,1.21,1.18,1.10,1.12,0.97,0.80,1.24,1.04,1.11,0.74,1.06,1.23,1.07,1.01,1.30]
    }, index=["ABR", "BAS", "CAL", "CAM", "EMR","FVG","LAZ","LIG","LOM","MAR","MOL","PIE","PUG","SAR","SIC","TOS","TAA","UMB","VDA","VEN"]
)
plotdata3 = pd.DataFrame({
    "2010_y":[4.12,1.44,5.73,3.91,3.43,0.00,4.26,0.00,1.95,2.65,0.00,4.82,3.61,2.17,3.05,2.66,0.00,2.86,3.00,1.15],
    "2011_y":[0.00,0.39,0.00,0.00,0.00,1.32,0.00,0.00,1.02,0.00,2.72,0.00,0.00,0.00,0.83,0.00,0.00,0.00,0.00,0.00],
    "2012_y":[0.08,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00],
    "2013_m":[0.00,0.00,0.00,0.00,0.45,0.00,0.00,2.58,0.00,0.00,0.00,0.00,0.00,1.90,0.00,0.00,0.00,0.51,0.00,0.00],
    "2014_m":[0.05,0.03,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.40,0.00,0.01,0.00,0.00,0.42,0.00,0.00,0.00,0.00,0.00],
    "2015_m":[1.45,0.16,0.27,0.09,0.64,1.68,0.20,2.42,0.47,0.41,0.28,0.32,0.09,0.93,0.18,0.52,0.00,0.67,0.00,0.00],
    "2016_m":[0.00,0.89,0.00,0.00,1.11,0.00,0.00,0.00,0.00,0.44,0.00,0.03,0.00,0.00,0.00,0.00,0.00,0.22,0.00,0.00],
    "2017_m":[0.00,0.00,0.00,0.00,0.95,0.00,0.00,0.00,0.09,1.85,0.00,0.00,0.11,0.00,0.07,0.35,0.00,1.74,0.00,0.00],
    "2018_m":[0.00,0.00,0.00,0.00,0.06,0.00,0.11,0.00,0.00,0.00,0.00,0.25,0.00,0.00,0.01,0.00,0.00,0.00,0.00,0.00],
    "2019_m":[0.30,3.09,0.00,0.00,0.34,0.00,0.42,0.00,1.48,0.25,0.00,0.58,0.19,0.00,2.44,0.46,0.00,0.00,0.00,0.85]
    }, index=["ABR", "BAS", "CAL", "CAM", "EMR","FVG","LAZ","LIG","LOM","MAR","MOL","PIE","PUG","SAR","SIC","TOS","TAA","UMB","VDA","VEN"]
)
fig, ax = plt.subplots()
#stacked_data = plotdata.apply(lambda x: x*100/sum(x), axis=1)
#stacked_data2 = plotdata2.apply(lambda x: x*100/sum(x), axis=1)
#stacked_data3 = plotdata3.apply(lambda x: x*100/sum(x), axis=1)

stacked_data.plot(kind="barh", stacked=True, width=0.4, 
                  ax=ax, position=0, edgecolor='black')
#stacked_data2.plot(kind="barh", stacked=True, width=0.25, 
                  # ax=ay, position=1, hatch='//',edgecolor='black')

stacked_data3.plot(kind="barh", stacked=True, width=0.4, 
                   ax=ax, position=1,edgecolor='black')
ax.get_legend().remove()
ax.set_ylim(top=len(stacked_data)-0.1)
#ax.set_xlim(right=len(stacked_data)-0.5)
ax.set_facecolor('xkcd:white')
# displaying the title
plt.title("titla")
# set various colors
ax.spines['bottom'].set_color('black')
ax.spines['top'].set_color('black') 
ax.spines['right'].set_color('black')
ax.spines['left'].set_color('black')

Answer 1

You can specify your colormap when plotting. Also use different colormaps for your barplots if you like, for example:

stacked_data3.plot(kind="barh", stacked=True, width=0.4, 
                   ax=ax, position=1,edgecolor='black', cmap='Accent')

A list of available colormaps is available on matplotlib.org