显示带有数据帧中的值的标签堆叠条形图

如何显示来自数据框的堆积条形图的值？如何将标签放置在每个栏上各自部分的上方并修改字体，以便它显示为灰度图形？

是有关系的对于这个问题 https://stackoverflow.com/questions/30228069/how-to-display-the-value-of-the-bar-on-each-bar-with-pyplot-barh但它有一个值列表，而不是从 pandas 数据框中提取的两个列表。如果它是单个列表，我想我可以从数据框中的单个记录中提取值，但如果有两个列表，我不确定如何将其应用于条形图中的每个条形。

我的数据框：

Delin.  Group1  Group2  Group3  Group4  Group5
Census  0.2829  0.3387  0.2636  0.0795  0.0353
USPS    0.2538  0.3143  0.2901  0.1052  0.0366

My code:

import os
import pandas as pd
import time
#
start_time   = time.time()
#
output_dir   = r"C:\Some\Directory\For\Ouputs"
#
output_fig   = "race_barh2.png"
#
fig_path     = os.path.join(output_dir, output_fig)
#
os.chdir(output_dir)
#
input_csv    = r"C:\Some\Directory\To\My.csv"
#
df           = pd.read_csv(input_csv, delimiter = ",")
#
ax           = df.plot.barh( stacked = True, color = ("#252525", "#636363", "#969696", "#cccccc", "#f7f7f7"), edgecolor = "black", linewidth = 1)
#
ax.set_xlabel("Percentage of Total",  fontsize = 18)
#
ax.set_ylabel("Boundary Delineation", fontsize = 18)
#
ax.set_yticklabels(["Census", "USPS"])
#
ax.set_xticklabels(["0%", "20%", "40%", "60%", "80%", "100%"])
#
horiz_offset = 1.03
#
vert_offset  = 1
#
ax.legend(bbox_to_anchor=(horiz_offset, vert_offset))
#
fig          = ax.get_figure()
#
fig.savefig(fig_path, bbox_inches = "tight", dpi = 600)
#
#
#
end_time     = round( time.time() - start_time, 5 )
#
print "Seconds elapsed: {0}".format(end_time)

您可以通过注释条形来与引用的问题中类似地执行此操作。对于堆叠条形图，您必须稍微调整标签的位置才能将它们放在您想要的位置。你可以玩一下horizontalalignment, verticalalignment并像我一样添加一点余量（+.5）。

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from cycler import cycler

#used gray colormap, you can use your own colors by replacing colormap='gray' with color=colors
colors = ["#252525", "#636363", "#969696", "#cccccc", "#f7f7f7"]
plt.rcParams['axes.prop_cycle'] = cycler(color=colors)

#dummy data
df = pd.DataFrame(np.random.randint(5, 8, (10, 3)), columns=['Group1', 'Group2', 'Group3'])

for col in df.columns.tolist():
    df[col] = df[col].apply(lambda x:x*100 / df[col].sum())

ax = df.T.plot.barh(stacked=True, colormap='gray', edgecolor='black', linewidth=1)

for lbl in ax.patches:
    ax.annotate("{:.0f}%".format(int(lbl.get_width())), (lbl.get_x(), lbl.get_y()+.5), verticalalignment='bottom', horizontalalignment='top', fontsize=8, color='black')

ax.legend(loc='center left', bbox_to_anchor=(1.0, .5))
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['bottom'].set_visible(False)
ax.spines['left'].set_visible(False)

plt.show()